Vysoká škola báňská – Technická univerzita Ostrava

VŠB – Technical University of Ostrava Faculty of Economics

Proceedings of the 11th International Scientific Conference

PUBLIC ECONOMICS AND ADMINISTRATION 2015

Ostrava, 8th – 9th September 2015 Czech Republic

Proceedings of the 11th International Scientific Conference

PUBLIC ECONOMICS AND ADMINISTRATION 2015 Ostrava, 8th – 9th September 2015

VŠB – Technical University of Ostrava Faculty of Economics Department of Public Economics

Ostrava, 2015

Proceedings of the 11th International Scientific Conference Public Economics and Administration 2015 Programme Committee prof. Gianluca Colombo, University of Lugano, Switzerland prof. Olena Dymchenko, DSc., O. M. Beketov National University of Urban Economy in Kharkiv, Ukraine Patrizia Gazzola, Ph.D., University of Insubria, Varese, Italy prof. Ing. et Ing. Dušan Halásek, CSc., VŠB – Technical University of Ostrava, Czech Republic prof. Ing. Vojtěch Krebs, CSc., University of Economics, Prague, Czech Republic doc. JUDr. Ivan Malý, CSc., Masaryk University, Brno, Czech Republic doc. JUDr. Pavel Mates, CSc., University of Finance and Administration, Prague, Czech Republic prof. Ing. Juraj Nemec, CSc., Masaryk University, Brno, Czech Republic prof. PhDr. František Ochrana, DrSc., Charles University in Prague, Czech Republic Olena Panova, O. M. Beketov National University of Urban Economy in Kharkiv, Ukraine Ing. Lucie Sedmihradská, Ph.D., University of Economics, Prague, Czech Republic doc. Mgr. Katarína Staroňová, PhD., Comenius University in Bratislava, Slovak Republic doc. Mgr. Jiří Špalek, Ph.D., Masaryk University, Brno, Czech Republic prof. Ing. Rudolf Urban, CSc., University of Defence, Brno, Czech Republic prof. Ing. Elena Žárska, CSc., University of Economics in Bratislava, Slovak Republic Conference Guarantee doc. Ing. Petr Tománek, CSc., VŠB – Technical University of Ostrava, Czech Republic Head of Organizing Committee Ing. Ivana Vaňková, Ph.D., VŠB – Technical University of Ostrava, Czech Republic Editor and Technical Editor Ing. Ivana Vaňková, Ph.D., VŠB – Technical University of Ostrava, Czech Republic Suggested citation AUTHOR, A. Title of paper. In: VAŇKOVÁ, I. (ed.) Proceedings of the 11th International Scientific Conference Public Economics and Administration 2015. Ostrava: VŠB – Technical University of Ostrava, 2015. pp. xx-xx. ISBN 978-80248-3839-7.

This publication has not been linguistically corrected. The authors are responsible for substance, professional level and linguistic accuracy of papers. All papers passed a double-blind review process. © Authors of papers ISBN 978-80-248-3839-7 ISSN 1805-9104

Reviewers Ing. Bc. Jiří Bečica, Ph.D., VŠB - Technical University of Ostrava, Czech Republic Mgr. Ing. Tomáš Černěnko, Ph.D., University of Economics in Bratislava, Slovak Republic doc. Ing. Martina Halásková, Ph.D., VŠB - Technical University of Ostrava, Czech Republic Ing. Marie Hladká, Ph.D., Masaryk University, Brno, Czech Republic Mgr. Tomáš Jacko, PhD., University of Economics in Bratislava, Slovak Republic doc. Ing. Robert Jahoda, Ph.D., Masaryk University, Brno, Czech Republic Ing. Hana Janáčková, Ph.D., VŠB - Technical University of Ostrava, Czech Republic prof. PhDr. Karel Lacina, DrSc., University of Finance and Administration, Prague, Czech Republic Ing. Jan Mertl, Ph.D., University of Finance and Administration, Prague, Czech Republic doc. Ing. Romana Provazníková, Ph.D., University of Pardubice, Czech Republic doc. Ing. Ladislav Průša, CSc., University of Finance and Administration, Prague, Czech Republic Ing. David Slavata, Ph.D., VŠB - Technical University of Ostrava, Czech Republic doc. Ing. Petr Tománek, CSc., VŠB - Technical University of Ostrava, Czech Republic doc. Ing. Petr, Toth, Ph.D., University of Economics, Prague, Czech Republic prof. Ing. Jaroslav Vostatek, CSc., University of Finance and Administration, Prague, Czech Republic Ing. Iveta Vrabková, Ph.D., VŠB - Technical University of Ostrava, Czech Republic Ing. Mirka Wildmannová, Ph.D., Masaryk University, Brno, Czech Republic

CONTENTS Prologue

1

Petr Tománek1

Usage of Multi-criteria Evaluation Methods of Alternatives in E-government Evaluation

2

Eva Ardielli2

Evaluation of Information Availability about Decision-making on Selected Czech Municipal Websites

9

Eva Ardielli, Roman Vavrek9

Poverty in Public Policy Discourse

16

Vladimír Barák16

Property of Self-governing Regions in the Czech Republic

22

Jiří Bečica22

Infrastructure Development through Public-private Partnership: Opportunities and Challenges for Ukraine

27

Olena Dymchenko, Olena Panova, Olena Slavuta27

Volunteers Engagement in Italian Non Profit Organizations

34

Patrizia Gazzola, Gianluca Colombo34

Research and Development (R&D) in the EU Countries: Comparison of Selected Indicators

41

Martina Halásková, Pavel Bednář41

Incentives to Our Generosity

49

Marie Hladká49

Dependency of Pension Insurance Contributions on the Number of Raised Children

56

Martin Holub56

Does the Information Age Free Consumers from Asymmetric Information or Enslave Them in Attention Poverty? 63 Petr Houdek, Petr Koblovský, Daniel Šťastný, Marek Vranka63

Using Implicit Rental Cost as a Measure of Poverty

70

Robert Jahoda, Jiří Špalek70

Consequences of the Czech Housing Market Deformation

76

Hana Janáčková76

Cooperative Educational Model Reflecting Graduate Employability on Labour Market as an Indicator of Structural Relevance and the Quality of Educational System 83 Anna Juřicová, Karel Plunder83

Efficiency of Public Expenditure on Education in the European Union States

88

Grażyna Kozuń-Cieślak88

Knowledge Management Processes in Polish Public Hospitals - Mapping of the Current Situation

95

Agnieszka Krawczyk-Sołtys95

Support of Families with Children through the Pension System

101

Vojtěch Krebs, Marcela Marešová101

Application of Specific Management Approaches in Selected Western European and Scandinavian Countries105 Karel Lacina105

Systemic Corruption in Public Procurement (Two Cases from the Czech Republic)

112

Ivan Langr, František Ochrana112

Analysis of Some Impacts of Regulation eIDAS on Public Bodies in the Czech Republic

118

Tomáš Lechner118

Social and Economic Characteristics of Social Services

125

Jan Mertl125

Assessing the Assumptions of Public Administration Performance from the Perspective of Complex Quality Management in State and Local Government Organisations in the Vysočina Region and USK Banská Bystrica131 Libuše Měrtlová, Zdeňka Dostálová, Martin Prokop, Radoslav Kožiak131

Types of Communication between Authorities of Public Administration (Case of the Czech Republic)

139

Pavel Mička, Milan Jan Půček, František Ochrana139

Ministerial Staff of the Czech Republic František Ochrana, Michal Plaček, Milan Křápek146

146

Municipality Indebtedness Evaluation Model based on System Approach

152

Pavel Petr, Romana Provazníková, Jiří Křupka152

Importance of Public Funding in the Revenue Structure of Non-profit Institutions in the Czech Republic

160

Zuzana Prouzová, Jiří Špalek160

Is the Pension System in the Czech Republic Sustainable in the Long Run?

166

Ladislav Průša166

Multi-year Budget Outlook in Czech Towns

172

Lucie Sedmihradská172

The Ownership Structure of Housing Market and Unemployment in Czech Republic

177

David Slavata177

The Present and the Future of the Institution of Widow’s and Widower’s Pensions

183

Milan Šlapák183

Influence of Criteria of the Employees Number in the Municipality to the Tax Revenues of Municipalities

189

Petr Tománek189

Review of the Czech State Pensions and Their Indexation

195

Jaroslav Vostatek195

The Productivity of Beds of Basic Medical Branches according to the Regions in the Czech Republic

202

Iveta Vrabková, Ivana Vaňková202

New Trends in Employment Policy: Social Entrepreneurship

209

Mirka Wildmannová209

The Influence of Factors of Urban Environment on Creative Individuals Decision Making Elena Žárska215

215

Prologue From 8 to 9 September 2015, the Department of Public Economics at the Faculty of Economics of the VŠB - Technical University of Ostrava held the 11th Annual International Scientific Conference “Public Economics and Administration 2015”. The individual years of the conference have taken place every two years since 1995. The conference creates a space for the presentation of new findings in the field of public economics and management from the research by scientists, academics, and practitioners. Thematically, the conference was divided into six sections that focused on: pension system, public finance, non-profit organizations, public sector, social policy, and public administration. These proceedings summarize the contributions, which are aimed at presenting the results of research on issues of public economics and administration, addressed mainly at universities. The international character of the proceedings is due to the representation of the contributions of experts from Italy, Poland, Ukraine, Slovakia, and the Czech Republic. The papers registered at the conference were subjected to peer review and the proceedings of the conference include 34 peer-reviewed contributions. Peer review of the contributions focused on the scientific benefits, application of appropriate research methods, evaluation of the conclusions, etc. The reviews were carried out by the members of the Scientific Committee of the conference and other experts. The issue of the public economics and administration is going through a series of changes within the changing economic conditions of the current period, changes in connection with computerization, etc., which places demands on relevant research. The proceedings bring new knowledge on this issue that have both application importance and significance for the development of theoretical knowledge. The importance of the proceedings is due to the fact that they represent a broad spectrum of new knowledge of the functioning of public economics and administration, which is intended for the further development of public economics and administration, and it is already applicable in practice, but it may also serve for further development of scientific knowledge, for teaching, or focusing of students’ theses as well as exchange of scientific knowledge at international level.

doc. Ing. Petr Tománek, CSc. Faculty of Economics VŠB – Technical University of Ostrava

1

Usage of Multi-criteria Evaluation Methods of Alternatives in E-government Evaluation Eva Ardielli Abstract E-government is a significant trend of public administration modernization and one of the important targets of European Information Policy. It is also significantly promoted by the strategic documents and practice of European member countries, as well the Czech Republic (CR). The article deals with the evaluation of the state of e-government in the European Union (EU) countries. Evaluation of the state of e-government is necessary for the future implementation of actions and measures in this field across EU countries. The paper focuses on the usage of methods of multi-criteria evaluation of alternatives – TOPSIS (The Technique for Order Preference by Similarity to Ideal Solution) and WSA (Weighted Sum Approach). TOPSIS and WSA methods were used to the comparison of current state of e-government in the EU countries and to the evaluation of the position of the CR. Methods of multi-criteria evaluation of alternatives are the multi-criteria decision methods used in operations research. The purpose of these methods is to provide the complete ranking of the alternatives starting from the best towards the worst one. In this research, there was selected the final list of alternatives (monitored countries EU-28) and criteria (9 indicators of e-government). The research was based on data set across multiple data sources. These were mainly study of 2014 “eGovernment Benchmark”, data processed by Eurostat and data managed by the UN from 2013. The evaluated data described in this paper and outputs of the research show the state of e-government in EU countries in the year 2013. The purpose of this paper is the determination of the state of e-government in the Czech Republic in an international comparison and the proposal of appropriate actions to improve the situation, based on experiences in other EU countries. Keywords: Evaluation, E-government, EU Countries, Methods of multi-criteria evaluation of alternatives JEL Classification: H11, H83 1 Introduction Multi-criteria evaluation of alternatives according to Jablonský (1998) belongs among the basic decision problems of multi-criteria decision making with large possibilities of real applications. As discussed by Dincer (2011) it is both an approach and a set of techniques, with the aim of providing an overall ordering of options, from the most preferred to the least preferred option. Generally provides the multi-criteria evaluation of alternatives a systematic procedure, which help decision makers to choose the most desirable and satisfactory alternative under uncertain situation (Yoon and Hwang, 1995). The aim of this paper is the evaluation of the current state of e-government in the EU countries using methods of multicriteria evaluation of alternatives. The state of e-government is evaluated in the EU-28 countries in the year 2013 based on the indicators of e-government monitored by international institutions. The results of the empirical research evaluate then the state of e-government in the CR and in the EU countries by selected criteria, using TOPSIS and WSA method. These methods were used, because they represent a suitable tool for the selection and creation of the ranking of the larger number of alternatives as stated for example in Vavrek, Kotulič and Adamišin (2014). The application part of this paper was created using the software application for multi-criteria evaluation of alternatives SANNA (System for ANalysis of Alternatives), see more in Jablonský (2009). In the paper, there are verified the research question whether the state of e-government in the CR corresponds to the EU average (or is above average eventually below average). In practice the evaluation of the state of e-government is important matter to selection of appropriate measures for further progress in this field and to propose recommendations for the development of e-government in the country. 1.1 E-government evaluation on international level E-government is one of important current trends of public administration modernization and it is also the subject of international comparisons, as discussed by Khosrow-Pour (2005), West (2004) or Bannister (2007). Interpretation of the term “e-government” is quite broad and divergent. The general definition describes e-government as the use of information and communication technologies (ICT) in a way of government transformation in order to increase the availability, effectiveness and accountability. E-government has been monitored as a part of the activities of many organizations. Approaches to monitoring of e-government differ considerably across organizations, for example Eurostat (2013) processes and evaluates data from the area of e-government in the form of measuring the interaction of citizens and businesses with public administration. The OECD has been involved in monitoring of the usage of ICT indicators in EU member countries, but e-government as a specific area is not measured here. European Commission's approach to evaluation of e-government is based on an evaluation of the effectiveness of European Information Policy (European Commission, 2014). This activity is based on the obligations of the European institutions. The United Nations (UNPACS, 2014) deals with the evaluation of e-government on the basis of the annual evaluation of the composite index of e-government and index of e-participation. Most approaches aimed at assessing the overall and general state of e-government, and therefore assess performance of government at all levels of the country: federal, regional and local. Only some approaches focus solely on the regional 2

or local level. However, e-government data of assessing organizations are not consistent with each other, as they have been monitoring different time periods using different methodology of data collecting and data processing and they have been focusing on description of different sub-areas of e-government services, which are defined based on specifically needs and purpose of the organizations. The paper focuses on the synthesis of these approaches. The synthesis output allows achieving comprehensive information on the state of e-government in the EU countries on the basis of selected e-government indicators. 1.2 Problem description In this paper all EU countries were analysed according to nine e-government indicators by using TOPSIS and WSA methods. Both TOPSIS and WSA method are operations research methods. TOPSIS method is based on the usage of the principle of minimizing the distance from the ideal option. It arranges the alternatives according to the indicator of relative distance from baseline (hypothetically worst) alternative (Chen and Hwang, 1992). This method determines in the result the overall order of alternatives. WSA method is based on the principle of utility maximization. It arranges the alternatives in the order according to the total utility, which is taking into account all represented criteria (Fiala 2008). The comparison of these two methods is presented on evaluation of e-government in the European Union countries. The summarization of monitored e-government indicators and their characteristics are shown in table 1. Table 1 – Monitored indicators of e-government Indicator Organization Characteristic User Centric Government European Commission Extent to which is the service provided on-line. Transparent Government European Commission Extent to which governments are transparent. Citizen Mobility European Commission Possibilities of usage on-line services abroad by EU citizens. Business Mobility European Commission Possibilities of usage on-line services abroad by businesses. Key Enablers European Commission Availability of on-line technical requirements. Online Service Index United Nations Range and quality of on-line services on national governmental websites. E-Participation Index United Nations On-line services and information provided by governments to citizens. Internet Use – Individuals Eurostat Percentage of individuals using the Internet in relation to public administration. Enterprises Using Internet Eurostat Percentage of enterprises using the Internet in relation to public administration. Source: European Commission (2014), UNPACS (2014) and Eurostat (2013), own processing.

Table 2 shows the matrix of alternatives and criteria for the year 2013 in EU countries. In the research, there was selected the final list of alternatives (EU-28 countries) and criteria (9 e-government indicators of various international organizations.) The research was based on data set across multiple data sources; see European Commission (2014), UNPACS (2014) and Eurostat (2013).

Country Austria Belgium Bulgaria Cyprus Czech Republic Germany Denmark Estonia Greece Spain Finland France Croatia Hungary Ireland Italy Latvia Luxembourg Lithuania Malta Netherlands Poland Portugal Romania

UCG 82 72 60 60 57 65 80 84 50 87 83 75 54 45 84 75 73 62 73 94 81 72 90 45

Table 2 – The Matrix of Alternatives and Criteria (2013) TG CM BM KE EPI 68 35 59 82 0,62745 51 37 44 58 0,62745 38 24 52 23 0,25480 36 48 75 46 0,31372 29 33 48 25 0,25490 30 29 66 49 0,70588 59 47 67 72 0,54901 75 79 70 87 0,76470 23 16 18 11 0,80392 66 12 59 77 0,78431 63 81 76 60 0,70588 64 38 31 69 0,96078 40 31 38 7 0,33333 23 13 27 30 0,45098 48 68 76 18 0,64705 49 30 37 42 0,78431 67 26 57 63 0,64705 36 39 68 41 0,54901 61 65 54 74 0,70588 96 87 89 95 0,47058 51 42 76 36 1,00000 37 23 40 62 0,49019 71 32 73 83 0,64705 17 20 17 12 0,47058

OSI 0,74803 0,67716 0,23622 0,47244 0,37007 0,66929 0,66141 0,77165 0,60629 0,94488 0,77165 1,00000 0,46456 0,55905 0,67716 0,74803 0,75590 0,62204 0,70078 0,40157 0,92913 0,54330 0,63779 0,44094

EUI 92 89 83 85 94 83 95 95 84 82 97 96 93 84 95 85 99 90 93 88 90 90 92 65

IUI 54 50 23 30 29 49 85 48 36 44 69 60 25 37 45 21 34 56 35 32 79 23 38 5

3

Sweden 81 59 64 61 64 0,60784 0,70078 95 Slovenia 70 53 48 36 46 0,39215 0,42519 93 Slovakia 44 17 22 54 8 0,62745 0,48818 92 United Kingdom 70 38 49 85 27 0,96078 0,89763 91 Source: European Commission (2014), UNPACS (2014) and Eurostat (2013), own processing.

78 52 33 41

2 Material and Methods The above mentioned input data were processed using the TOPSIS and WSA method. The results were processed in the software SANNA. E-government was evaluated based on the extent of on-line services (UCG), according to government transparency (TG), the possibility of online services usage abroad by citizens and businessman (CM and BM), according to availability of online technical assumptions (KE), in terms of services quality on governmental websites (OSI) and the e-participation (EPI) and according to representation of individuals and businessman which use the internet in relation to public administration (EUI and IUI). The results indicate the state of e-government in the EU28. All 9 criteria were equal weight. The methods TOPSIS and WSA provide the complete ranking of the alternatives starting from the best towards the worst one. TOPSIS method is based on the selection of alternative that is closest to the ideal solution and furthest from baseline solution. Application of TOPSIS method is as follows: 

Creation of normalized criterial matrix R according to following formula (1): (1)

√∑

where rij is R, where i = 1,2, … m; j = 1,2, … r; 

Calculation of weighted criterion matrix W by following equation (2): (2) in such a manner that each column of the matrix R will be multiplied by the corresponding weight criterion vi;



Determination of the ideal and basal variant relative to the matrix values W, see following formulas (3) and (4): (3) (4) for j = 1,2, … k;



Distance calculation of variants from the ideal variant, respectively basal variant, see formula (5) and (6): √∑

(

)

√∑

(5)

(6)

for all i = 1, 2, … m; 

Calculation of the relative distance indicator of variants from baseline variant by formula (7): (7) where i = 1,2, … m;



Arrangement of variants by non-growing values of ci.

WSA method is based on linear utility function. The method provides complete ranking of alternatives according to their total utilities. Application of WSA consists of the following steps: 

Normalization of input data using following equation (8): (8) where rij are the normalized values for i alternative and j criterion, yij is original value of alternatives according to the criterion j, Dj are the values of the basal alternative and Hj are values of the ideal alternative.



Calculation of the total utility according to the following formula (9): (9) 4

where u(ai) is the total utitlity of the alternative ai,, rij are normalized values from the previous step, vj is the weight of j-th criteria and k is the n umber of criteria. 

Order of alternatives according to the utilities.

3 Results and Discussion In this part of the paper there are presented the application results of TOPSIS and WSA methods. On the basis of the TOPSIS method there was performed distance calculation from ideal and basal variant. The coefficient of total distance of variant i from the ideal variant di+ was calculated from formula (5). Coefficient of total distance of variant i from basal variant di- was calculated according to formula (6). Subsequently there was calculated the total relative indicator of distance from basal variant ci. The relative distance of variant i from the basal variant is given by formula (7). Values of individual alternatives are summarized in appendix. The values of the calculated index range between 1 and 0. Value 0 corresponds to the basal variant; value 1 corresponds to the ideal variant. Based on the result, it is possible to determine the order of the EU countries in terms of the e-government functioning, from the best to the worst, as shown in figure 1. Assessment of the state of e-government in the EU countries in 2013 according to TOPSIS method showed that on the best place are Estonia and the Nordic countries - Finland and Sweden, while the worst e-government state is in Croatia, Bulgaria and Romania. Figure 1 – Evaluation of e-government state in the EU by TOPSIS method (2013). Source: European Commission (2014), UNPACS (2014) and Eurostat (2013), own calculations in software SANNA.

WSA application was processed in three steps. The values of the criterion were normalized using formula (8) and it was calculated the total utility of each alternative using the equation (9). Then the total utility of alternatives was ordered from the highest to the lowest. The ranking of EU countries is represented in figure 2. Figure 2 – Evaluation of e-government state in the EU by WSA method (2013). Source: European Commission (2014), UNPACS (2014) and Eurostat (2013), own calculations in software SANNA.

Evaluation of the e-government state according to WSA method in EU for 2013 presented that on the best place was also Estonia and then Finland and Malta. On the worst place was also Romania. Other countries with the worst state of e-government were Greece, Bulgaria and Hungary. 5

The figures 1 and 2 also capture EU-countries averages, based on which it can be deduced about the difference in egovernment between original EU-15 countries and the accessing countries EU-10 in 2004. Based on comparison of egovernment state in EU countries is possible to conclude that on average significantly better results have the EU-15 countries while the EU-10 countries are lagging behind. Here is possible to note the exceptional status of Estonia, which, though also belongs among the countries of the eastern EU enlargement in 2004, showed the best state of the egovernment across the whole EU-28. Both methods TOPSIS and WSA carried out the ranking process successfully and gave very close result to each other. The results obtained by using TOPSIS and WSA method is also in parallel with other researches of international organizations as World Economic Forum (2013) or European Commission (2014) as well as academic researchers, for example Kuncová and Doucek (2013). Based on the use of methods of multi-criteria evaluation of alternatives was found highly unsatisfactory position of the Czech Republic in the field of e-government. The Czech Republic ranked on the 24. place of EU-28 when using TOPSIS method and on the 22. position when using WSA method. Results of this own research dealing with evaluation of the state of e-government in the Czech Republic reflect to a considerable extent the current results obtained on the basis of international benchmarking activities of major international institutions such as UNPACS (2014) or European Commission (2015). According to UN assessment of e-government based on an index EGDI in 2013 the Czech Republic ranked only on the 25. position out of 28 EU countries. Also as stated by index DESI monitored by European Commission aimed on evaluation of ICT in public administration the Czech Republic ranked on the 25. position. The cause of the inadequacy of the e-government state in the Czech Republic is mainly lack of the basic concept and long-term lack of interest by the Czech government. The e-government activities in the Czech Republic have focused primarily on building large systems in recent years, which became the basis for the functioning of e-government. There were implemented projects such as basic registers, data boxes or the Czech POINTs. However, these systems were built with considerable delay, and therefore it was not possible to put them into operation as quickly as originally expected. The possibilities, how to improve the current situation in the digitization of public services, is the active promoting of eolutions by the state and searching of ways to maximize the usage of them, e.g. on-line dealing of everyday situations, such as the exchange of driving licenses and so on. Services should be accessible to as many platforms as possible (smartphones, tablets) and for the greatest number of users and by the simplest way. It should also be published the greatest amount of information, which government can provide (i.e. Open Data). It is also important to strengthen citizens' confidence in e-government. As an example in e-government field for the Czech Republic could be for example the Baltic States, which are in the field of digital services on top of the European Union. A good example for the Czech Republic can be British server gov.uk, which acts as an integrated, user friendly portal to access to all the services of the public administration. The improvement of the situation in the Czech Republic is currently supported by recent political development and by the approval of the Strategic Framework for the development of public administration, see MVČR (2014) and the restoration of the Government Council for the Information Society. The Ministry of Interior, which is responsible for e-government also intensified its activities and communication with the public. 4 Conclusion The results of the evaluation of the countries EU-28 in terms of the state of e-government by TOPSIS method and WSA method in the 2013 acknowledged, that the best ranking in this area obtained Estonia, then the Scandinavian countries Finland, Sweden and Malta by usage of TOPSIS method and Netherlands by usage of WSA method as well. The worst state of e-government was reported in Romania, Bulgaria and Croatia (TOPSIS) and also Hungary (WAS). Based on the ranking of EU countries by the monitored criteria (quality and range of on-line services and the use of ICT in relation to public administration) from the best result to the worst was showed that in the average the countries EU-10 are in the eovernment significantly lagging behind in comparison with countries EU-15. One part of the research was also the answer of research question dealing with the evaluation of e-government in the CR in comparison with other EU countries. Based on the evaluation of the e-government state in the EU-28 countries in 2013 it was found highly unsatisfactory position of the Czech Republic in the field of e-government. The Czech Republic ranked under average of EU-28 countries among the worst countries in the EU. In the country there are serious shortcomings, particularly on the side of public digital services providers. Changing the attitude of government officials in this area is therefore required because e-government is a useful tool for reducing the cost of public administration and it is also the benefit for the residents in the form of time savings. This area remains for the Czech Republic the main challenge for the future. When evaluating the applicability and relevance of used methods (TOPSIS and WSA), it is for the purpose of eovernment evaluation more objective and therefore more suitable TOPSIS method, which reflects the variability, for example the range of values among other countries. The WSA method then always exalts the extreme values before the average values, so through this procedure, get better evaluation those countries which have maximum values in some of the monitored criteria. Acknowledgements This paper was created within the financial support of the student grant on EKF, Technical University of Ostrava in the project No. SP2012/163 "Specification of capitalization rate for calculation of the yield value of the property." 6

References [1] BANNISTER, F. (2007). The curse of the benchmark: an assessment of the validity and value of e-government comparisons. In International Review of Administrative Sciences. Vol. 73, pp. 171–188. [2] DINCER, S. E. (2011). Multi-criteria Analysis of Economic Activity for European Union Member States and Candidate Countries: TOPSIS and WSA Applications. European Journal of Social Sciences. Vol. 21, pp. 563-572. [3] EUROPEAN COMMISSION. (2014). E-Government Benchmark: Insight report. Publications Office of the European Union. [online]. [cit. 2015-02-20]. Available: https://ec.europa.eu/digital-agenda/en/news/euegovernment-report-2014-shows-usability-online-public-services-improving-not-fast. [4] EUROPEAN COMMISSION (2015). Digital Agenda Scoreboard. [online]. [cit.2015-02-25]. Available from http://ec.europa.eu/digital-agenda/en/digital-agenda-scoreboard>. [5] EUROSTAT. (2013). Statistical database. [online]. [cit.2015-02-20]. Available from http://epp.eurostat.ec.europa.eu/portal/page/portal/information_society/introduction>. [6] FIALA, P. (2008). Modely a metody rozhodování. Praha: Oeconomica. [7] CHEN, S. J., and HWANG, C. L. (1992). Fuzzy Multiple Attribute Decision Making: Methods and Applications. Berlin: Springer. [8] JABLONSKÝ, J. and URBAN, P. (1998). MS Excel based system for multicriteria evaluation of alternatives. [online]. [cit. 2015-05-17]. Available: http://www.fhi.sk/files/katedry/kove/ssov/VKOX/Jablonsky.pdf [9] JABLONSKÝ, J. (2009). Software Support for Multiple Criteria Decision Making Problems. Management Information Systems. Vol. 4, pp. 29–34. [10] KHOSROW-POUR, M. (2005). Practicing E-Government: A Global Perspective. Hershey: Idea Group Publishing. [11] KUNCOVA, M. and DOUCEK, P. (2013). Využívání ICT v České republice ve srovnání s evropskými zeměmi. Regionální studia. Vol. 3, pp. 67-81. [12] MVČR. (2014). Strategický rámec rozvoje veřejné správy České republiky pro období 2014 – 2020. [online]. [cit. 2015-07-16]. Available: http://www.mvcr.cz/clanek/strategicky-ramec-rozvoje.aspx [13] YOON, K. P. and HWANG, CH. (1995). Multiple Attribute Decision Making: An Introduciton. California: Sage. [14] VAVREK, R., KOTULIČ, R. and P. ADAMIŠIN. (2014). TOPSIS Method and Its Application to the Local SelfGovernment of the Slovak Republic. Journal of Applied Economic Sciences. Vol. 3, pp. 504-512. [15] WEST, D. M. (2004). E-Government and the Transformation of Service Delivery and Citizen Attitudes. Public Administration Review. Vol. 64, pp. 15-27. [16] WORLD ECONOMIC FORUM. (2013). Global competitiveness report 2013. [online]. [cit. 2015-03-3]. Available: http://www.weforum.org/reports/global-competitiveness-report-2013-2014. [17] UNPACS. (2014). Data Center - Government Development Index. [online]. [cit. 2014-08-02]. Available from http://unpan3.un.org/egovkb/en-us/Data-Center>. Appendix – Values of distance coefficients of variants and of total relative indicator Country di+ dici Austria 0,03755 0,05317 0,58607 Belgium 0,04600 0,04067 0,46923 Bulgaria 0,06917 0,02068 0,23020 Croatia 0,06846 0,02001 0,22614 Cyprus 0,05405 0,03736 0,40871 Czech Republic 0,06683 0,02133 0,24195 Denmark 0,03642 0,05266 0,59116 Estonia 0,02037 0,06739 0,76787 Finland 0,02637 0,06221 0,70235 France 0,04007 0,05556 0,58097 Germany 0,05197 0,03886 0,42785 Greece 0,07189 0,02578 0,26392 Hungary 0,07086 0,01936 0,21456 Ireland 0,04574 0,04869 0,51562 Italy 0,05218 0,03769 0,41941 Latvia 0,04454 0,04591 0,50760 Lithuania 0,03309 0,05389 0,61959 Luxembourg 0,05080 0,03765 0,42562 Malta 0,03175 0,07397 0,69970 Netherlands 0,04065 0,05526 0,57616 Poland 0,05755 0,03262 0,36173 Portugal 0,03855 0,05468 0,58648 Romania 0,07772 0,01173 0,13110 Slovakia 0,07041 0,02404 0,25453

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Slovenia 0,05223 0,03532 0,40343 Spain 0,04571 0,05464 0,54449 Sweden 0,03266 0,05420 0,62400 United Kingdom 0,04611 0,05168 0,52848 Source: European Commission (2014), UNPACS (2014) and Eurostat (2013), own calculations in SANNA.

Contact information Ing. Eva Ardielli, Ph.D. VŠB – Technical University of Ostrava Sokolská třída 33, 701 21 Ostrava Czech Republic [email protected]

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Evaluation of Information Availability about Decision-making on Selected Czech Municipal Websites Eva Ardielli, Roman Vavrek Abstract Public information availability respectively the disclosure of public information by state administration is regarded as the expression of the fulfillment of the principle of transparency and openness in the public administration. These principles play nowadays significant role in the modernization trends of public administration. They belong to principles of Good Governance, which were first defined in 1999, by SIGMA organization and gradually became the basis of efficient public administration in democratic states. Another important trend of contemporary public administration modernization is the development of citizen participation. This is the development of innovative tools that allow citizens to involve actively in decision-making processes of government. Transparency, openness and participation in public administration are currently significantly supported by the entry of modern technologies (Information and Communication Technologies) to this sector. One suitable means which allows better public access to information, greater transparency and citizen participation in decision-making is the development of e-government. This paper focuses on the e-government of local level, especially the disclosure of information on municipal websites. The research was done in the selected Czech municipal websites, where was evaluated the information availability rate about decision-making in the municipalities with extended competences and the availability of participation tools. There were analysed selected information available on the municipal websites in Moravian-Silesian region. The results of the research pointed out the shortcomings in publishing of information on municipal websites. There was also stressed the low level of citizen participation on local level of government in the monitored area. Keywords: evaluation, information availability, municipal websites JEL Classification: H11, H70, H83 1 Introduction The aim of the paper is the evaluation of information availability rate about decision-making in selected Czech municipalities situated in Moravian-Silesian region provided by official municipal websites. The evaluation of the public administration websites is discussed by many authors as Ancarani (2005), Carrizales (2008) or Špaček and Malý (2010). Evaluation by monitoring of information availability on the websites is not only the domain of national states as described for example by Khosrow-Pour (2005) or Bannister (2007) and annually performed in the international dimension by various international organizations as United Nations (see UNPACS, 2014) or European Union (EC, 2014). It is possible and desirable to be performed at the level of local bodies, as analysed for example on the local government websites in the EU countries, see more Pina, Torres, Royo (2009) or as implemented in the municipal websites in Slovak Republic in 2010, 2012 and 2014, see more in TIS (2014). In the Czech Republic there were analysed the websites at the level of higher local government units (FOM, 2012) and selected municipal websites (OS, 2014) As significant approaches to the evaluation of the content of municipal websites are considered for example the Website Attribute Evaluation System (WAES), the approach of the organization Transparency International of Slovakia or Rutgers-SKKU Municipal E-Governance methodology. WAES methodology is aimed for assessment of the content of websites. WAES is the binary tool. It analyses the content of the website in the context of specific detailed criteria (types of information, services, and web tools). The component in the content either exists or is absent. As a result, a score of either “y” or “n” is assigned to the specific criterion (Porebski, 2011). The methodology of Transparency International of Slovakia is aimed at assessing of municipalities from the perspective of openness of public administration. The openness is evaluated in 11 areas: access to information, public participation, provision of public services, selling and renting of property, budget, subsidies and grants, flats and social facilities, personnel policy, ethics and conflict of interest, spatial planning and municipal enterprises and investment. For more detailed description of the methodology see on TIS (2012). Rutgers-SKKU Municipal E-Governance methodology is based on Rutgers-SKKU E-Governance Performance Index. This is the instrument used to evaluation of municipal web portals with respect to delivery of public service and citizen participation in governance. The instrument is composed of five components: security and privacy, usability, content, services and citizen participation, see more in Holzer and Kim (2006). The method is based on 100 measurements. Each component includes 20 measurements. Almost half of measurements is coded on a dichotomy of two-points (no, yes) representing un/availability of requested parameter on websites. Other measurements can be evaluated on a scale of 0-2 or 0-3 points. Despite the above mentioned approaches and the researches done the local level still attracts much less attention than national level. However, local and regional level seems to be necessary because it is the closest level to the citizen. Most services are provided through local governments; as well participation in public life should be higher at local level

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than at the national level. Therefore, it is necessary to provide citizen with transparent information on public decisionmaking as comfortable as possible. 2 Material and Methods The research sample included the total number (all 22) of municipalities with extended competences in the MoravianSilesian Region in the Czech Republic. The analysis of web portals of municipalities with extended competences was realized on basis of publicly available data obtained through remote access from municipal web portals. This data were collected in the period from the beginning of September to the end of October 2014. The research sample of municipalities and their numbers of inhabitants are summarized in Tab. 1. Table 1 – Research sample of municipalities Number of Municipality Municipality inhabitants Bílovec 7558 Frýdlant nad Ostravicí Bohumín 21663 Jablunkov Frýdek-Místek 57135 Kopřivnice Havířov 76109 Krnov Hlučín 14042 Odry Karviná 56848 Rýmařov Kravaře 6737 Orlová Nový Jičín 23676 Vítkov Opava 57931 Bruntál Ostrava 295563 Český Těšín Třinec 36077 Frenštát pod Radhoštěm Source: Own processing according to RIS (2014).

Number of inhabitants 9773 5727 22597 24315 7361 8492 30345 5912 16913 25000 10878

To meet the defined objectives, there were monitored for all selected municipalities a total of 20 indicators related to the information availability on the websites (Tab. 2). There were visited the municipal websites and searched monitored information (indicators). Within the found information were done no detailed analysis of the accuracy and comprehensiveness of the information, such as whether the annual accounts are complete or whether the minutes of the meeting contain the expected data. Their simple occurrence was considered to meet the existence of the monitored indicator. The search was carried out in accordance with the logical breakdown of websites within 20 minutes of acceptable term for a web page; see Chen (2009) or Ziemba, Papaj and Descours (2014). In case that the desired information was not found within the expected logical location in the menus and submenus of websites and even within the usage of search function in a sustainable time, so the information was considered as unavailable. As archives there were considered two years old data or more.

Indicator P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14 P15 P16 P17 P18 P19 P20

Table 2 – Monitored indicators of municipal websites Characteristic of monitored indicator Electronic board and its archive Materials for the meeting of the council (publication before the meeting starts) and archives Minutes of the council and archives The audio / video recordings of council meetings and archive The procurement notice and archive The commission for evaluation of procurement and archive The results of procurement decisions and their archives Public tender for sale and rental of real property - offer, minutes of process and outcome, archives Annual final accounting and their archives The current budget and archive Supplier invoices Subsidies and grants – applications evaluation and allocation decisions and their archives Land use plan Publication of e-mail addresses of employees Generally binding regulations and city decrees on-line Free access to public information (no registration or passwords) Discussion on decision-making or message board with answers of representatives On-line voting and decision-making and its interim and final results Search tool Disclosure of information requests and archive Source: Own processing according to TIS (2010) and Holzer and Kim (2006).

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Monitored indicators P1 to P20 were in case of availability on the concrete website of municipality marked by "y", otherwise "n". Almost all of the monitored indicators are multi-valued (e.g., occurrence of current information and nooccurrence of archive - the indicator value is then “y, n”). For multi-valued indicators could be only part of the information available for that category. Availability of information in this situation was determined proportionally (50 %). The output of the paper was also the characteristic of results using selected torque characteristics. As the characteristics of the basic file were used selected torque characteristics that Markechová, Stehlíková and Tirpáková (2011) divided into 3 groups: a) Degree position (mode, median, average), b) the degree of variability (standard deviation), c) the degree of asymmetry (skewness coefficient, kurtosis coefficient). These results are tested by Shapiro-Wilk test to identify normal distribution of results and population monitored municipalities: ∑ ∑

∑

(1) ̅

where ui is constant, xi is value of i-statistical unit and ̅ is average value of a variable. In the case of confirmation of normal distribution of both sets (by Shapiro-Wilk test) the relationship between population (number of inhabitants in the municipality) and reached results is tested by Pearson correlation coefficient: ̅̅̅̅

∑

̅̅ √

∑ ̅

̅̅ ∑

̅

(2)

where n is number of observations, sx is standard deviation of first variable, sy is standard deviation of second variable, xi is value of i-statistical unit of first variable, yi is value of i-statistical unit of second variable, ̅ is average value of first variable and ̅ is average value of second variable. In the case of rejection (normal distribution) of one of monitored variables the relationship between variables is tested by Kendall's coefficient of concordance: (3) where n is number of observations, nc is number of concordant pairs and nd is number of discordant pairs. Analysis and outputs are processed in MS Office, Statgraphics and Statistica 12. 3 Results and Discussion The graph in Fig. 1 shows the availability of the monitored indicators. 100 % availability of information for all monitored municipal websites were traced with seven parameters, which are Minutes of council meetings and their archives, Current budget and archive, published Land use plan, publication of e-mail addresses of employees, publication of generally binding regulations and city decrees on-line, free access to public information and Search Tool. On the contrary, none of the monitored websites disclosed supplier invoices. Very low were also information about committee’s members that evaluate public procurement. Figure 1 – The absolute frequency of monitored indicators. Source: Own processing.

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On average the municipality had available on its website 12 parameters from monitored 20 parameters ( ̅ = 12.068). Results of municipalities Orlová (8.5 points) and Nový Jičín (14.95 points) were identified by box plot as outliers (Fig. 2). Figure 2 – Number of points obtained in individual municipalities. Source: Own processing.

We conclude relatively higher range of variation of results (R = 6.7) and low variability (VR = 14.47 %). Up to 75% of municipalities had on its website published at least 55 % of parameters (Q1 = 11.2). Normal distribution of first variable (population - Fig. 3) was rejected by Shapiro-Wilk test (SW = 0.491, p = 0). Figure 3 –The structure of municipalities by population. Source: Own processing.

Despite the normal distribution of results (SW = 0.972, p = 0.748) we used Kendall's coefficient of concordance to identify correlation between variables. This coefficient confirmed the statistical significance of this correlation (r K = 0.306, p = 0.048). Availability of indicators on the municipal websites, which is closer statistically described above, is shown in Fig. 4. The map shows the spatial distribution of results of all 22 municipalities with extended competences in MoravianSilesian Region for the year 2014.

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Figure 4 – Spatial distribution of the results. Source: Own processing.

Based on this survey it was evaluated the rate of information availability in monitored area and the municipal websites were ranked according to the availability of information. It was found, that the top rated municipalities offered 65 - 76 % of the monitored indicators. Most web sites (75 %) showed the availability of indicators greater than 56 %. The best rated municipalities in the Moravian-Silesian Region were Kopřivnice, Nový Jičín and Frýdek-Místek. The worst rated were the municipalities Orlová, Kravaře and Hlučín. In the Czech Republic, there were also evaluated the municipal websites within the initiative Infoliga, see more in OS (2014). This initiative focused on the selected aspects of the praxis of the transparency principle. There were assessed the municipalities according to the content of the municipal websites. The evaluation watched for example publication of municipal budgets, municipal board and the public procurement announcements. The best rated municipalities in the Moravian-Silesian Region in the last evaluated year 2012 were the municipalities Kopřivnice and Nový Jičín, what confirm the results of own research (Fig. 4). Through the remote access there were in the own research at least accessible information about the materials for council meetings, audio and video recordings of the council meetings and the commission for evaluation of procurement. None of the municipalities disclose the supplier's invoice and generally it was found very low participation of citizens in decision-making through electronic access (Fig. 1). Some municipal websites were very confusing and it was very difficult to find required information. For this reason, it would be appropriate to introduce some kind of standardization of municipal web pages, so that the important data are easily obtainable. The area of e-participation has not been in the Czech research sufficiently analyzed yet, but the actual results of web sites evaluation in the Czech Republic (FOM, 2012 and OS, 2014) point out the low level of citizen participation in the decision-making process. As well as this mentioned researches and researches done on the local level of government in the Slovakia (TIS, 2014) or Poland (Porebski, 2012 or Ziemba, Papaj and Descours, 2014), the own research on the second level of government in the Czech Republic, Moravian-Silesian region, identified low participation of citizens in decision-making process. For example Porebski (2012) described in the year 2009 only 13.7 % availability of discussion forums on the polish municipal websites. In the own research the availability of online discussion forums on the monitored websites was 14 %. Also TIS (2014) in Slovakia evaluated the state of transparency at municipal websites in the year 2010, 2012 and 2014. The level of citizen participation was evaluated very low. The shortcomings were found in the area of publication of Council meetings and insufficient tools for decision-making participation, similar as was found in own research on selected Czech municipalities in Moravian-Silesian region. Despite the fact, communication with citizens and citizen involvement in various discussions and decision-making should be one of the main roles of the city website. Participation of citizens should be therefore encouraged by implementation of on-line discussion and thematic forums. Leaders of municipalities should participate in these discussions and citizens should be involved in decision-making through electronic elections or surveys. The results of these surveys should be also published online. This approach can effectively improve the management of public affairs in municipalities. 4 Conclusion Availability of information is a topical issue concerning the subjects of the private and also public sector. The paper focuses on the availability of data about decision-making on the websites of selected municipalities in the MoravianSilesian Region in the year 2014. Based on the realized own survey can be concluded: a) Heterogeneous representation of the monitored indicators (the incidence rate varies from availability of all indicators to their complete absence), 13

b) low availability of data about decision-making in selected municipalities (max 75 %), while this value was also identified in a box plot as outlier, c) statistically proven positive relationship between population (number of inhabitants in municipality) and number of indicators available on the website of the municipality. Based on the incidence rate of monitored indicators in selected municipalities was found that municipalities have different approach to information disclosure. While some information are published by all, or almost all municipalities, others are published only rarely or as invention of a single municipality that have than an inspirational character for others. However, certain standardization measures for the public administration presentations are given by the Law, by Act No. 106/1999 on Free Access to Information. Information provided in this Act shall be published in every case which also corresponded to the reality on the researched websites. Other disclosure of information is fully in the competence of municipality, which corresponds to the outputs of the research connected with the low availability of monitored indicators on the municipal websites. Czech municipalities prefer for various reasons the option to publish only the minimum information beyond the scope given by law. There are only lower number of municipalities that actively disclose information in accordance with the principle of openness and transparency in public administration. This approach is usually applied if is desired to become more visible or to engage in a prize for innovation. The results of the research show also that the quality of the municipal website from the perspective of information disclosure is dependent on the size of the municipality. From this fact it can be assumed that smaller municipalities do not have sufficient financial or human capacity, and this is reflected in the level of web portals of municipalities. The main recommendations resulting from the research are directed to increase of citizens' access to information on decision-making in the municipality. The possibility of watching decision-making processes of the elected representatives in real time is one of the basic examples of e-participation. Direct supervision over the negotiations of municipal councils using ICT is not common in Czech municipalities according to the own research. This problem is not so much the lack of technology or finance, but also unwillingness of representatives to publish the audio-visual records. The most effective ways to ensure the publication of that information online is the establishing the requirement by law. Acknowledgements This paper was created within the project GAMA/15/2 and within the financial support of the project No. SP2012/163 "Specification of capitalization rate for calculation of the yield value of the property." References: [1] ANCARANI, A. (2005). Towards quality e-service in the public sector: The evolution of web sites in local publice service sector. Managing Service Quality. Vol. 15, pp. 6-26. [2] BANNISTER, F. (2007). The curse of the benchmark: an assessment of the validity and value of e-government comparisons. International Review of Administrative Sciences. Vol. 73, pp. 171-188. [3] CARRIZALES, T. (2008). Functions of E-Government: A Study of Municipal Practices. State and Local Government Review. Vol. 40, pp. 12-26. [4] EUROPEAN COMMISSION. (2014). E-Government Benchmark: Insight report [online]. [cit. 2015-02-20]. Available: https://ec.europa.eu/digital-agenda/en/news/eu-egovernment-report-2014-shows-usability-onlinepublic-services-improving-not-fast [5] FOM - Fond Otakara Motejla (2012). Hodnocení krajů. [online]. [cit. 2015-05-03]. Available from http://www.hodnocenikraju.cz/cz/sets/kraje-2012/about> [6] HOLZER, M., KIM, S. T. (2006). Digital Governance in Municipalities Worldwide (2005): A Longitudinal Assessment of Municipal Websites Throughout the World. United States of America: National Center for Public Productivity. [7] CHEN, S. et al. (2009). Take Your Time First, Time Your Search Later: How College Students Perceive Time in Web Searching. American Society for Information Science and Technology. 2009. pp 19. [8] KHOSROW-POUR, M. (2005). Practicing E-Government: A Global Perspective. Hershey: Idea Group Publishing. [9] MARKECHOVÁ, D., STEHLÍKOVÁ, B., TIRPÁKOVÁ, A. (2011). Štatistické metódy a aplikácie. Nitra: Univerzita Konštantína filozofa v Nitre. [10] OS – Otevřená společnost (2014). Infoliga. Projekt otevřené společnosti. [online]. [cit. 2014-04-04]. Available from http://www.infoliga.cz/ >. [11] PINA, V., TORRES, L., ROYO, S. (2009). E-government evolution in EU local governments: a comparative perspective. Online Information Review. 2009. Vol. 33, pp. 1137-1168. [12] POREBSKI, L. (2011). Evaluating the Development of eGovernment Systems: The Case of Polish Local Government Websites. In Proceedings of the 11th european conference on e-government. pp. 475-481. [13] RIS - Regionální informační servis (2014). Správní členění kraje. [online]. [cit. 2015-03-01]. Available from http://www.risy.cz/cs/krajske-ris/moravskoslezsky-kraj/verejna-sprava/spravni-cleneni>. [14] ŠPAČEK, D., MALÝ, I. (2010). E-Government evaluation and its practice in the Czech Republic: challenges of synergies. Journal of Public Administration and Policy. 2010. Vol. 3, pp. 93-124. 14

[1] TIS - Transparency International Slovensko (2014). Otvorená samospráva 2014. [online]. [cit. 2015-05-04]. Available from http://samosprava.transparency.sk/sk/>. [2] UNPACS (2014). Data Center - Government Development Index. [online]. [cit. 2014-08-02]. Available from http://unpan3.un.org/egovkb/en-us/Data-Center>. [3] ZIEMBA, E., PAPAJ, T., DESCOURS, D. (2014). Assessing the quality of e-government portals – the Polish experience. In Proceedings of the 2014 Federated Conference on Computer Science and Information Systems. pp. 1259–1267.

Contact information Ing. Eva Ardielli, Ph.D. VŠB – Technical University of Ostrava Sokolská třída 33, 701 21 Ostrava Czech Republic [email protected] PhDr. Roman Vavrek, Ph.D. University of Prešov 17. Novembra 15, 080 01 Prešov Slovak Republic [email protected]

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Poverty in Public Policy Discourse Vladimír Barák Abstract The paper discusses the problems of poverty in the Czech public policy discourse in recent years. It describes in detail how the phenomenon of poverty evolved over time from a simple synonym misery after multivariate, multidimensional problem, as it is generally understood today. As poverty is vaguely definable, also becomes very prone to abuses in favor of political goals constructors policy. Often, then regardless of the outcome, which would hopefully contribute to a truly better quality of life of citizens. The paper presents the statement of policy makers in order to highlight the fact how much poverty is the common (wild card) issue to justify their political decisions which do not lead to solving the problem of poverty, but clearly lower targets - such as the re-election. Keywords: poverty, public policy, social risks, society JEL Classification: I30, I39, P45, L38 1 Introduction Poverty is a phenomenon that has accompanied mankind since its beginning. Because of this we can find in the literature of last decades a wide variety of definitions of poverty, often very varied and more or less concrete. "Poor people are below the poverty line, and that constitutes… the revenue that has been insufficient to meet basic living needs of the individual." (Rowntree, 1908) "It is the inability of individuals to ensure a basic standard of living." (World Bank, 1990) "Poverty can be defined as a human condition characterized by sustained or chronic deprivation of the resources and capabilities, choices, security and power, which are necessary for it to be allowed to enjoy a decent standard of living and other civil, cultural, economic, political and social rights. "(UN Committee on Economic, social and Cultural Rights, 2001) As can be seen, the definition of poverty is far from straightforward and we can say that it is always indebted to the fact that time and which subject was used. "For the success of the fight against poverty is crucial that society perceive it as an absolute evil that must be eradicated." These words were elected by Advisors of Czech Prime Minister Bohuslav Sobotka, Vladimír Špidla at the press conference at Salvation Army Czech Republic (2014, Prague, Czech republic). Did not fail to mention that poverty threshold is defined as an annual income of 116,000 crowns, which is about 9500 crowns a month. "It's not a random definition, but it means that if you live below this threshold and because of low incomes have been pushed out of mainstream society into subculture. You simply are not a citizen anymore" said the politician. Quote only illustrates how the phenomenon of poverty is nowadays is part of the agenda of virtually all political and social actors in the Czech Republic and how political entities use poverty in their intentions and attitudes in the political spectrum. Each of the actors, whether they are the foundation of political or civil forms, emphasizes the very different aspects and types of poverty. It's no wonder then that there is a similar approach and activities of scientists and academics who publish various analyzes, the results of research and investigations relating to poverty, but not only did not supplement, they are often even contradictory. This is proof that there is still no consensus in the debate on how poverty conceptually grasp and how to solve it. The phenomenon of poverty is multilayered the overall picture is unclear if anyone imagines something a little different. Poverty clearly has its economic dimension. If we accept the thesis of the present crisis of the welfare state, and responds to the failure of the dominant institutions of modern society. Transferring the consequences of global economic competition in the labor market encounters on mechanisms of adaptation of the labor markets and lack of adaptation to the requirements of flexibility, including the inability to solve problems employability. (Kolibová, 2011). Poverty has a social dimension as well. As for specific individuals affected by poverty as well as for society as a whole. Poverty is closely related with the threat of social exclusion. In connection with the fact that modern society creates its own forms of exclusion and exclusion from one system at the same time, the exclusion of individuals from a variety of other systems: for example, if we do not have money, it’s hard to get education and without education is difficult to obtain a job (Luhman 1986). Poverty is directly related to social exclusion, then there is the inability of excluded to effectively participate in the economic, political, cultural and social life of the community. It is not only their personal risk, but also a risk to society. From this perspective, the issue of poverty can be seen as a so-called. "New social risk" (Keller, 2011). Increasingly, poverty is mentioned as a problem with the legal dimension, human-legal, ethical and moral, when mankind and society forgets the natural solidarity and responsibility towards other people. In the Czech Republic poverty threatens over one and a half million people - probably about 15 percent of the population. The European average is significantly higher - up about a quarter of the population. Czech Republic, therefore, not in the statistics relating to people at risk of social exclusion among the most affected countries. Neither we can ignore the issue of poverty. Stating that the problem is not with us would pay perhaps in the distant past autarkic oriented regions with have full sovereignty and not in terms of a globalizing world. In the Czech Republic, as in other countries, there is a widening gap between wealth and poverty, displacing the middle class and deepening the 16

differentiation between people enshrined inside and outside the society. There is Absolute failure to address this position of executive or legislative, civil initiatives and other subjects in the Czech Republic, this could accelerate this status greatly. How to deal with poverty? From the above definitions we can be see in which direction there was change in last hundred years and Its perception. From earlier development emphasis on meeting the basic human needs only measures of simply income, poverty got to the stage where it is seen as a multidimensional, multi-dimensional problem. As is unclearly defined, also it becomes very prone to be abuses in favor of political goals of designer’s policy. Often, then regardless to the outcome, which would hopefully contribute to a truly better quality of life of citizens. It’s necessary to say, like in the case of poverty, there were also changes in perception and the content of social policy that it has to solve. "In the last century led dispute between reputable economists and social scientists about whether man its nature homo economicus or homo socialis. Only in the twentieth century it is generally recognized that the essence of man is not an economic activity. Economic activities are the only instrument for human life and development. This created space for new conception of the function of state social policy" (Tomeš, 1996). 2 The development of perception of poverty For the overall context, it is necessary to look into the past and thus show how the view of poverty that has changed over time and that poverty today is not what it once was. Currently we mean by poverty only negative concept, while in the middle Ages or in the period of early capitalism, poverty was defined by a substantially positive - the word actually meant a worker. Poverty thus coincided with a certain social status as a natural attribute of the particular role (Leibfried, 1990). An important change in the understanding of poverty occurred in the late 19th century, when poverty ceased to be perceived as a poor dependence on revenue from support and in particular charity, but began to be perceived as insufficient income, however, regardless of income source. In the early 20th century, the poverty research focused determining the amount of the minimum objective of family budgets with respect to estimates of the amounts spent on each category of expenditure, such as food, housing and clothing (Kotýnková, 2007). In 1919, apart from the poverty of minimum family income, William F. Ogburn, who set the following three levels:  1st level of poverty - surviving through state aid.  2nd level of the minimum family budget - an objective means of physical nature that is necessary for survival.  3rd level of minimum comfort of recipient. Number of authors followed and extended this scale. Generally, the lowest rung of the people were entirely dependent on public support, followed by people that avoid to work, then people on the level of basic subsistence minimum. With such a division is easier to distinguish between the two layers of people affected by poverty, where it was examined whether the working people with low incomes or with non-working support. The difference between the income of the working and non-working should ensure motivation to actively seek work (Kotýnková, 1997). In the 19th and the first half of the 20th century were typical concepts of poverty, which was based on an absolute concept, the poverty line is based on a minimum expenditure of families. It fundamentally changed in 1958, when JK Galbraight publishes that there are social mechanisms that would guarantee even assuming a healthy economic growth and poverty reduction. Thus defined poverty as not just a state of absolute income, but the difference in incomes of the individual and the average income in a given part of society. If it also detects great a difference, we can talk about poverty. Current concepts of poverty are then formed from the beginning of the 21st century, when it can no longer be narrowly understood as a problem of poverty, but in a much broader sense, as the problem of inequality and inaccessibility of social goods, which causes social exclusion. While in developing countries is still observe a large extent the incidence of absolute poverty, according to standardized, traditional criteria, the most widely used classification of poverty created by the World Bank, the boundaries of daily income per capita (as a condition of extreme poverty called living on less than $ 1 per day) in most industrialized countries we are talking about relative poverty. We follow many more dimensions of the problem of poverty, such as no access to employment, education, housing and opportunities to participate in society. We are talking about social exclusion. This is a result of structural changes that accompany the socio-economic development of society. They include the changes in the labor market, technological changes in society, changes in the structure of households and demographic changes. States are also facing with the phenomenon of globalization. Its impact on poverty is considerable.  Global markets reward more countries and individuals that have usually most productive assets  Negative externalities in the global economy, increase costs and create new costs for vulnerable groups  Rules of the global economy tend to favor the countryside and individuals who already have the economic strength because the rich man has stronger influence on the creation of these rules towards his own advantage (Birdsall, 2006).

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Table 1 – Main methodological systems of poverty measuring Direct access

The main methods for determining poverty

Indirect access

Combined access

1) The unmet basic needs 2) Human development index 1) Calorie Consumption 2) The price of basic needs 3) Relative method 4) Subjective method 1) The holistic method of measuring poverty 2) Two-dimensional method

Source: RODRIGUEZ RAMIREZ, H. (b.d.). Propuesta Metodológica para la Medición de la Pobreza en Nuevo León [online]. [cit. 2015-06-05]. Available: http://www.mty.itesm.mx/egap/centros/caep/imagenes/PobrezaNuevoLeon.pdf

As is apparent from the above, poverty has undergone is still is undergoing major changes. Old poverty can be particularly associated with the life cycle impact on the ability or inability to work, typically in case of old people ill or lonely single parents. Then the new position of individuals social groups in the labor market (the unemployed, singleparent families, disadvantaged groups in the labor market), and appears in the complex long-term unemployment. New poverty can be seen as extremely serious. In quantitative terms, it is characterized by a higher number of vulnerable persons, as occurs across all age groups, different social and economic classes in case of people from different ethnicities and on a wide spatial distribution. The qualitative aspect is then typical that people with stable jobs are also affected by poverty. (Kolibová, 2011). As the Czech society is changing, pockets of poverty are changing too. They Relate to:  Members of households where is only employed parent, because the other is absent (Typically about single mothers with below-average earnings, which themselves are caring for two or more children).  Poverty of heavily indebted families that pays its liabilities from non-banking companies, energy companies, transport companies, etc.  Long-term unemployed, typically due to lack of work or medical disability (Keller, 2010). Threatened are for example all people who receive minimum wage, which applies to approximately one hundred thousand Czechs. This is crucial - at risk of poverty are people who have no health handicap, do not avoid jobs and fully participate in the labor market because they have a full-time job, pays taxes fulfills its fundamental role in society. With other groups at risk of poverty is one and a half million citizens of the Czech Republic. This number of people can not be ignored is naturally monitored by politicians. But mostly for their own profit not for good of citizens. The theme of poverty is then very easily abused in political struggles. 3 Poverty as a political issue Social Security is in the Czech Republic the main instrument of social policy, serving to fulfill its objectives. We understand it as a set of institutions, facilities and measures which help to prevent, mitigate and eliminate the consequences of the social events that are exposed to citizens. Market trends is to make the rich richer, and the poor even poorer. This is counterbalanced by policies of states, which take part of rich of the capital and give certain part the poor. It is thus one of the ways to alleviate the problem of poverty. Czech social system can be compared with other European Union countries perceived as moderately generous, however, in terms of state highly expensive. On a few examples will show how political representation can perform differently on certain matters relating to poverty and combating it. Figure 1 – Social security system expenditure (mill. CZK). Source: VÚPSV, personal adaptation.

As we can see in Figure 1 state spending on social security continues to grow with few exceptions since 1990. In 2014 amounted to 512 billion crowns a year. As well as increasing spending on security alone grew also expenditures for system administration. In the framework of the state budget it is therefore an increasingly important item which is of course closely watched not only experts but also by policy makers. 18

"It is a lie that social conscience is the prerogative only of the left. However, we can distinguish between irresponsible populism, which under the guise of building a so-called welfare state leads to disruption of state finances on the one hand effective solidarity of responsible citizens... We will never take part in the race bribing voters by promising economically unsustainable social security. On the contrary, we have the courage to tell the citizens of the Czech Republic - the social security system must be in accordance with the economic possibilities of the state“ said in 2010 the former ODS deputy chairman Petr Necas. The leftist Social Democrats, however, coined a different approach: "The CSSD will strive to maintain and further develop the ongoing public social insurance systems which represent the only long experience proven development of a universal system." From the above quotations we can infer that social system itself (including the amount of expenditure incurred) has become one of the themes of political struggle. While the right-wing parties elect investigation where the social system is described as a bloated and overly generous left-wing parties do not develop a tendency to change it in terms of volume but rather a fight for their higher efficiency. It is obvious why politicians have chosen a different rhetoric - trying to please their voters. Voters of left parties generally more often agree that political parties should increase their pensions and social benefits and solve the unemployment problem. While more right-wing voters are calling for the need to reform the system and achieve a balanced economy. Figure 2 – Minimum Pensions Ratio (of individuals, in % of gross earnings). Source: VÚPSV, personal adaptation.

Figure 2, shows changes in the proportion between the minimum pension and the average gross wage. In this case, therefore, we only focus on revenue type of measured poverty. We can conclude that the lower the share, the more inequality there is in this sense among people already receiving an average wage and people already receiving a pension. The worst situation was in 2007 in 2014 compared to the previous share there was slight decrease. Overall, we observed a significant change. As mentioned in the previous chapter, people of pension age belonging to those groups are significantly threatened by poverty status. What can we do with it? Even in this case, the political representatives don’t agree. As an example, let us mention much discussed valorization of pensions. It returned in 2015 to the rules in force until 2012 when under the Act increased inflation of a third of real wage growth. It abolished temporary restrictions which were pushed for three years by the previous government of the ODS, TOP 09 and the LIDÉ which beginning in January 2013 when it was determined that pensions rose only one-third of inflation third of the growth in real wages. In this case, the current rather left-oriented government abolished the previous government measures, by one full year earlier than it should come to an end. This corresponds to a situation where we are increasingly witnessing practices which at that given moment, the opposition party threatens to repeal the measures by currently ruling parties once they come to power. The current government coalition of Social Democrats ANO and the Christian Democrats went even further this year. Income did not increased directly, but prepared bonus for retirees - at the end of the year every single senior will receives a state bonus of 600 crowns. This is unsystematic step to help pensioners only momentarily and in terms of combating poverty is very insignificant. Even here, yet government politicians mention the social aspects of the whole thing: "an Increasing income for me is not a political issue but human and social matter" said the one-time Minister of Labor and Social Affairs of the Czech Republic, Michaela Marksová (CSSD). "For CSSD is not just a question of how psychologically deal with seniors. We also have another election next year,“ commented opposition parliament member Markéta Adamová (TOP 09). These steps of political representation prove that there is high non-conceptual immaturity and lack of culture.

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Figure 3 – Minimum Wages Ratio (in % of gross av. earnings). Source: VÚPSV, personal adaptation.

Another group of the population at risk of poverty are people working for minimum wage. And this topic is a significant political issue. On Figure 3, we see the ratio of the minimum wage to the average gross wage. Also in this case, we can conclude that the lower this percentage, the greater the inequality prevails among people already receiving an average wage and people already receiving the minimum wage. Among the policy (but also among economists and other experts in various disciplines) is prevailing issue of the minimum wage has different views. Some would cancel it completely, while others would want to reduce it or continual increase. Whether any of them is right them the Institute of minimum wage is important in the fight against poverty because it directly affects the income of people at risk of poverty. "Increasing the minimum wage is very antisocial action. In the Czech Republic there are relatively large regional disparities in employment and the average salary - in Prague, such an increase may not indicate a problem but in the Karlovy Vary region, for example, the minimum wage is already at 40 percent of average wages and such increase will be for entrepreneurs most vulnerable social groups devastating. ODS will continue to oppose the minimum wage, as it indeed holds the vast majority of economists, will also continue to defend the weakest in the labor market“ said on the issue of increasing the minimum wage Jan Skopeček right-wing ODS economic expert. "Within the European Union when we measure the ratio of the minimum wage to the average wage we are still at the end of the tail. And I think that we are relatively rich country we have a low proportion of people with poverty so certainly we can handle it. It must be effective to work and not be dependent on welfare. And in this the minimum wage also plays a very important role“ opposes the Minister of Labor and Social Affairs Michaela Marksová of CSSD. In this case, it is not surprising that the rhetoric is different between left and right but rather that both parts of the political spectrum operate in terms of poverty and "the most vulnerable social groups. "It's a evidence to how very sensitive issue (poverty) may be used in the context of the economic measures of the state (minimum wage) which is a logical purely political decision. 4 Conclusions The above examples show how political representation is able and willing to exploit the issue of poverty to promote their own political goals regardless of the actual solution to the problem of poverty. The theme of poverty is not the policy of repeatedly mentioned as the main problem to solve but as an excuse to enforce certain political goals. It is important to answer the question whether and to what extent it is necessary to tackle poverty. "Bipolarity poverty and wealth is one of the driving forces of human motivation and development of the society at the same time, however, it is a permanent risk of social development. Under certain circumstances, lead to political radicalization of totalitarian ideology and social destruction." (Tomes, 1996). The risks are enormous and therefore poverty and must be the subject of permanent interest policy. But we can say that each of the cited political parties and representatives of political parties emphasizes the very different aspects and types of poverty. This revenue outweighs perspective although poverty is currently a problem that is more likely to define not only the material and economic but as a multidimensional problem multidimensional. Political leaders in their submissions are unable (or unwilling) to think comprehensively and poverty is their only terms that they are willing to use within their political goals or party. Exploitability of poverty is high. The phenomenon of poverty has undergone significant development as its present form the one about which older literature talks about. The problem becomes more difficult to understand and also to solve. Poverty is undergoing gradual evolution. Each of its developmental stages is then useful for another part of the political spectrum. Specific politicians, then uses poverty not for objectives that would tackle poverty but especially to provide him with positive points with voters and media. Alpha and Omega is becoming one - instant popularity (in the case of populists) or the specter of re-election (by career politicians). We can expect that on the way tackle poverty new trends will not help in Czech politics (and indeed the world) where they are gradually emerging. Due to the large public mistrust in politics, in polls and elections on top there are parties and movements with protest character. In them they are often cumulative populists aimed not usually to solve problems but on the contrary escalate and then obtain their radical expressions of other political points. 20

Then salvation can’t be seen neither in oligarchs in politics. If the big businessmen - billionaires are buying up the media are more involved in public space and then even actively enter politics then it is logical fear that they are doing so for their own commercial interests and the concentration of power in their hands that can greatly help them in the fight with competitors and increases in their property. And there will be the topic of poverty only popular topic as how to justify some actions but without poverty being really systematically solved. It must follow the selected social doctrine and according to the doctrine long-term systematically deal with it. It is necessary to choose such instruments to solve the very existence of poverty and the consequences, as well as the level of resources that are the purpose for reassigning. In the European area, which we are part of it can be based for example, on historical determination, especially religious, which has a strong tradition of the old continent and build on the solidarity of the rich with the poor. How will be such solidarity pursued, It is another subject itself. Acknowledgements This paper was created within the project of Internal development competition VŠE v Praze “Nový předmět: Úvod do sociální práce”. Project registration number F5/5/2015. References [1] KELLER, J. (2011). Nová sociální rizika a proč se jim nevyhneme. Praha: Sociologické nakladatelství. [2] KELLER, J. (2010). Tři sociální světy. Praha: Sociologické nakladatelství. [3] KOLIBOVÁ, H. (2011). Sociální systém. Solidarita jako základ sociálně politických aktivit společnosti. Karviná: Slezská univerzita v Opavě. [4] KOTÝNKOVÁ, M. (2007). Sociální ochrana chudých v České republice. Praha: Oeconomica. [5] LEIBFRIEND, S. (1992). Towards a European welfare state? On integrating Poverty Regimes into the European Community, in Z. Ferge and J. E. Kolberg (Eds) Social Policy in a Changing Europe. Frankfurt: Campus Verlag. [6] ROWNTREE, B. S. (1908). Poverty a study of town life. London: Macmillan. [7] TOMEŠ, I. (1996). Sociální politika, teorie a mezinárodní zkušenost. Praha: Socioklub. [8] WORLD BANK (1990). World Development Report 1990. Poverty, Oxford University Press, New York. [9] RODRIGUEZ RAMIREZ, H. (b. d.). Propuesta Metodológica para la Medición de la Pobreza en Nuevo León [online]. [cit.2015-06-05]. Available: http://www.mty.itesm.mx/egap/centros/caep/imagenes/PobrezaNuevoLeon.pdf [10] WORLD HEALTH ORGANIZATION (2008). Human Rights, Health and Poverty Reduction Strategies [online]. [cit.2015-06-15]. Available: http://www.who.int/hdp/publications/human_rights.pdf [11] CSSD (2010). Oranžová kniha - Sociální politika [online]. [cit.2015-06-15]. Available: http://www.cssd.cz/kestazeni/volebni-programy/oranzove-knihy-cssd-pro-volby-2010/socialni-politika/ [12] CT24. (2015). Marksová: Vyšší minimální mzda má motivovat lidi k práci [online]. [cit.2015-06-15]. Available: http://www.ceskatelevize.cz/ct24/ekonomika/296923-marksova-vyssi-minimalni-mzda-ma-motivovat-lidi-k-praci/ [13] DENIK.CZ (2014). Špidla si přeje, aby společnost vnímala chudobu jako absolutní zlo [online]. [cit.2015-06-10]. Available: http://www.denik.cz/z_domova/spidla-si-preje-aby-spolecnost-vnimala-chudobu-jako-absolutni-zlo20141014.html [14] NECAS, P. (2010). Moderní sociální systém [online]. [cit.2015-06-10]. Available: http://www.vize2020.cz/vystoupeni/moderni-socialni-system [15] ODS (2014). Zvýšení minimální mzdy ohrozí tisíce zaměstnanců [online]. [cit.2015-06-06]. Available: http://www.ods.cz/os.domazlice/clanek/7646-zvyseni-minimalni-mzdy-ohrozi-tisice-zamestnancu?tisk=1 [16] UDALOSTI, KOMENTARE (2015). Do důchodu s obavami? [online]. [cit.2015-06-10]. Available: http://www.ceskatelevize.cz/porady/1096898594-udalosti-komentare/215411000370615/ [17] VÚPSV (2015). Ekonomické a sociální ukazatele ČR [online]. [cit.2015-06-06]. Available: http://www.vupsv.cz/index.php?p=economic_social_indicators&site=default

Contact information Mgr. Vladimír Barák University of Economics, Prague W. Churchilla 4 sq., 130 67 Prague 3 Czech Republic [email protected]

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Property of Self-governing Regions in the Czech Republic Jiří Bečica Abstract The territorial self-government is an important part of public administration in the Czech Republic. After 1990 there was a gradual restoration of the elected members of the self-government, first at the municipal level and subsequently at the regional level. One of the prerequisites for the functioning of the territorial self-government is the ownership of property and the ability to manage it. The paper is therefore devoted to analyzing the state of property at the higher territorial self-government units in the Czech Republic (regions), with the exception of the capital, Prague. In short, the ownership of property is justified by the territorial self-government, the legislative entrenchment of ownership and types of property. Subsequently, in several tables and graphs the assets of the self-governing regions are compared according to the balance sheets at the end of 2013. From the conducted analysis of the state of property follows that the amount of the assets and the structure in each region is different in terms of the total volume as well as in comparison with per capita in the region. The largest volumes of the assets in the regions are allocated in long-term tangible fixed assets, specifically in buildings, land and long-term tangible assets. Keywords: Financial assets, Intangible assets, Property, Regions, Tangible fixed assets JEL Classification: H 76, M 41, R 53 1 Introduction The territorial self-government is an important part of public administration in the Czech Republic. After 1990 there was a gradual restoration of the elected members of the self-government, first at the municipal level and subsequently at the level of artificially created regions that originated on the basis of Constitutional Act no. 347/1997 Coll., On Establishment of Higher Territorial Units. Regions finally came into existence on January 1, 2000, self-governing competencies were acquired by them pursuant to Act no. 129/2000 Coll., on Regions (regional government), on 12 November 2000, when the first elections were held to the newly established local authorities. As stated by Peková (2011) and Kadeřábková (2012) or Bland and Rubin (1997) the ownership of property in accordance with the property right and the right to manage it independently of the state is a significant authority and one of the essential economic preconditions for the proper functioning of the territorial self-government. The right to own and manage property is guaranteed to the self-government in Chapter Seven, Art. 101 Sec. 3 of the Constitution of the Czech Republic, which says: "Territorial self government units are public corporations which may own property and manage it according to their own budget." One of the assumptions for the functioning of the territorial self-government is, therefore, the ownership of property and the ability to manage it. In the context of this paper the analysis of the assets of higher territorial self-governing units by the end of 2013 with the exception of the assets of the capital Prague is conducted. The comparison is carried out according to the individual components of the assets as this is commonly distinguished in professional literature, i.e. tangible assets, intangible assets, financial assets, receivables and current assets. The aim of this paper is to compare and evaluate the amount of the assets in each region, per capita. Attention is focused on the largest component of the assets of the regions, which are the long-term tangible fixed assets. The output of the paper are comparative tables and graphs showing the amount and the structure of the assets of the regions in total, and the amount of the assets per capita. The comparison of per capita was chosen deliberately as each region in the Czech Republic is incomparable given the population, as well as the area of the region. 2 Materials and Methods Property is referred to as equity. For a set of property one can also use the term assets. Property is closely related to the concept of ownership or wealth. What follows from the above stated is that property is a very general term (Schneiderová, 2010). According to professional literature the most general form of property stands for a set of things, rights and obligations pertaining to an entity or assets are classified as the sum of property values, i.e. things, receivables and other rights and money valuables (Peková, 2008). Property can be distinguished as private and public property, which include "administrative property" which public entities manage and administer proprietary, in connection with the performance of their operation (Rektořík, Šelešovský, 2002). When considering the long-term aspect, according to Havlan (2013), most assets are divided into fixed and current (assets), investment assets (assets held for further use, evaluation). Given the physical substance one then distinguishes between tangible and intangible assets or financial assets (Drozen, Ryska, Vacek, 1997). The analysis of property further down uses publicly available data from the websites of the individual regions and the data of the Czech Statistical Office of Population Census and Housing from 2011. The data concerning the assets are taken from the balance sheets of the individual regions at 31.12. 2013. For the purposes of the paper the data for all regions are analyzed with the exception of the capital, Prague, which is a municipality and a region at the same time, and for this reason the comparison of the property of Prague would not be objective. The data on the population of each 22

region is based on the data from the Czech Statistical Office and are used for the comparison of the amount of the assets per capita of a respective region. Subsequently, by deduction, an evaluation of the state of the assets in each region and the data are interpreted. 3 The volume and structure of the property of the regions Regions acquired their property through the transition of property from the state based on the adoption of the so-called "delimitation" acts, where we rank the adoption of Act no. 157/2000 Coll., On the Transfer of Certain Things, Rights and Liabilities from the property of the Czech Republic to the regions and the adoption of Law no. 290 / 2002 Sb., On the Transfer of Certain other Things, Rights and Obligations of the Czech Republic to the regions and municipalities, civic associations involved in physical education and sport and related changes. Property management is the responsibility of the elected members of the local authority of the region, as they can make their decisions on renting, selling, gifting, lending, and putting property into established legal entities. The property of the region may also be entrusted to the established subsidized organizations, which are usually set up on a non-profit basis to carry out tasks in the public interest in the field of education, culture, social services, health and transport (Ochrana, 2014). Property entrusted to the care of the region established through legal entities and subsidized organizations in the region is not studied in this paper. Property is a condition of the self-government and a necessary instrument for carrying out certain tasks, which include the performance of public administration, the provision of public goods and the overall development of the region. As a result of the mixed system of territorial public administration, the property of the regions is important for the state administration (Hrabalová, 2004). The following figure no. 1 shows the volume of the assets in the individual regions by the end of 2013. The total volume of the assets of all regions without the capital Prague at the same date amounts to 139.8 bn. CZK. Figure 1 - The amount of the assets in the individual regions, at 31.12. 2013 bn. CZK. Source: Own elaboration based on the data available from the balance sheets of the individual regions in 2013. 19,5 20 18 16 14 12 10 8 6 4 2 0

15,5 15,0

14,0 11,8

11,5

9,8

8,3

7,7 5,8

8,9 6,9

5,3

As can be seen from the graph no. 1, the volume of the assets in the individual regions is very different. Obviously, what applies here is that the larger regions, measured by population or area of its territory, possess more assets than smaller regions. As for the population among the big regions the following can be ranked: the Central Bohemian Region, the Moravian-Silesian Region, the South Moravian Region (over 1 mil. inhabitants) and the Ústí Region. As for the area, then the South Bohemian Region is large. If we take the above-stated size of the regions into account, the Pardubice Region does not meet that size criterion, which according to the balance sheet shows the largest volume of its assets - about 19.5 bn. CZK. If we consider the structure of the assets in the individual regions, then we can observe that even this will vary among the regions. Figure no. 2 shows the structure of the assets categorized as long-term intangible fixed assets (LIFA), long-term tangible assets (LTA), long-term financial assets (FM), long-term receivables and current assets for the individual regions in % expressions.

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Figure 2 - The structure of the assets in the individual regions at 31. 12. 2013 in %. Source: Own elaboration based on the data available from the balance sheets of the individual regions in 2013. 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

LIFA

LTA

FM

long-term receivables

current assets

Given the determined goal of the paper the following part is devoted to a comparison of the assets of the regions per capita. Firstly, the size and the structure of all components of the assets of the regions are shown, and then tangible fixed assets of the regions are discussed, as these make up the largest part of the assets in almost all regions, as can be seen from figure no. 2. 4 Results and discussion Table no. 1 shows the values of the assets of the regions per capita according to the number of permanent residents in the relevant region in line with the logic of the above-mentioned classification of the assets. The table shows a different volume of the assets per capita of the region, the South Moravian Region shows the least assets per capita with just five thousand CZK, as far as the area and population is concerned the Pardubice Region and the Carlsbad Region demonstrate the most assets, which with their average per capita of about 15 thousand CZK exceed two and a half and reach a value of about 38.5 thousand CZK per capita. The below-average volume of the assets can be found in addition to the already mentioned South Moravian Region also in the Moravian-Silesian Region, the Olomouc Region, the Pilsen Region, the Central Bohemian Region and the Hradec Kralove Region. Table 1 - The structure of the assets of the regions per capita in CZK Long-term Current Total receivables assets assets 198 3 932 865 1 205 3 068 9 267 Moravian-Silesian 141 6 044 2 020 145 3 709 12 059 The Olomouc 266 7 989 5 546 1 443 1 271 16 516 Zlín 137 1 443 89 546 2 729 4 944 South Moravian 184 36 739 9 7 1 630 38 568 The Pardubice 103 9 128 2 170 378 3 193 14 971 Hradec Králové 516 4 365 3 620 437 6 676 15 613 Liberec 318 4 945 3 441 1 111 2 354 12 170 Central Bohemian 195 5 051 12 663 733 4 812 23 453 South Bohemian 299 5 491 1 799 1 1 567 9 157 Pilsen 583 27 270 2 346 2 040 5 873 38 112 Carlsbad 265 5 142 8 544 124 2 736 16 812 The Ústí 250 13 546 0 1 638 1 942 17 375 The Vysočina 244 7 874 3 219 748 2 986 15 069 Average Source: Own elaboration based on the data available from the balance sheets of the individual regions in 2013. Region

LIFA

LTA

FM

With respect to the structure of the assets, intangible assets are negligible in all regions, which are in the regions most represented in the form of software, minor long-term intangible assets and long-term intangible assets, or other item of long-term intangible assets. The largest part of the assets falls in most regions on long-term tangible fixed assets, except for the South Bohemian Region and the Usti nad Labem Region, where the largest volume of the assets lies in the category of long-term financial assets and the Liberec Region, where current assets are predominant. The structure of long-term tangible fixed assets broken down into land, buildings, cultural objects, separate movable items, small tangible assets, tangible assets and prepayments for long-term tangible fixed assets per capita is shown in Table no. 2.

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Table 2 - The structure of long-term tangible assets in CZK per capita prepayme nts for Cultural Tangible Region Land Buildings long-term objects assets tangible fixed assets 166 0 1 542 840 132 1 250 1 Moravian-Silesian 97 2 4 369 201 125 1 246 4 The Olomouc 1 090 2 6 167 392 116 221 0 Zlín 23 0 1 120 175 94 30 0 South Moravian 3 271 5 28 001 3 404 2 000 58 0 The Pardubice 195 1 7 736 459 118 619 0 Hradec Králové 42 1 1 367 399 152 2 403 0 Liberec 219 1 1 088 143 98 3 395 1 Central Bohemian 147 1 3 608 164 129 1 001 0 South Bohemian 135 0 4 761 396 121 76 2 Pilsen 3 579 94 12 506 836 211 10 043 0 Carlsbad 310 0 4 826 0 3 3 0 The Ústí 11 330 0 0 495 0 1 720 1 The Vysočina 1 115 4 4 637 515 206 1 396 1 Average Source: Own elaboration based on the data available from the balance sheets of the individual regions in 2013. separate movable items

Small tangible assets

Total tangible assets 3 932 6 044 7 989 1 443 36 739 9 128 4 365 4 945 5 051 5 491 27 270 5 142 13 546 7 874

Buildings have the largest share in the structure of long-term tangible fixed assets in total and per capita in all regions, with the exception of the Liberec Region and the Central Bohemian Region. The average per capita accounts for 4.6 thousand CZK, the largest amount of 28 thousand CZK per capita was recorded in the Pardubice Region and the Carlsbad Region (12.5 thousand CZK). The second largest item per capita then is made up by long-term tangible assets where the average per capita amounts to 1.4 thousand CZK and extraordinary items were recorded in the Carlsbad Region (10.4 thousand CZK) and in the Vysočina Region, the Central Bohemia Region and the Liberec Region. Lands are then the third most common item of long-term tangible fixed assets and account for about 1.1 thousand CZK per capita. The highest amount for the land was in the Vysočina Region, where the amount per capita accounts for 11.3 thousand CZK. The above-average value was then determined in the Carlsbad Region (3.5 thousand CZK) and the Pardubice Region (3.2 thousand CZK) per capita. There is almost no value of the land per capita in the South Moravian Region (23 CZK) the Liberec Region (42 CZK) and the Olomouc Region (97 CZK). 5 Conclusions The property of territorial self-governing units is a very important socio-economic area which is dynamic, constantly develops and shapes. There is currently no existing list of the regions’ property in the existing legal adjustment, and therefore we can start from the assumption that the regions cannot be denied the right to the property of any kind. Each region should posses at least as much property, and in such quality, in order to properly and effectively carry out the functions and tasks that are entrusted to them by a variety of applicable laws. This is particularly the issues related to the daily life of citizens in the areas of education, protection and development of health and welfare, social services, culture and transport, which involves owning the property to a certain degree, as well as looking after it as a good administrator. Regions are required by law to take care of their property and use it for the overall development and welfare, along with the obligation to protect it, maintain it and repair it. However, all cannot do without a considerable amount of funds (Tománek, 2013), which are necessary not only to maintain the operating state of property, but also to its renewal and expansion. Regions do not always obtain sufficient funds to such an extent so that they were capable of performing the above mentioned activities the way they would imagine. Acknowledgements The paper is output of project no. 0231/2014/RRC, which was approved by the Moravian-Silesian Region council in the program: Support of science and research in the Moravian-Silesian Region called: „Exploiting of the potential for regional development of settlements in Moravian-Silesian Region “ References [1] BLAND, R. L., RUBIN, I. Budgeting: A guide for local governments. Washington, DC, 1997: International City/County Management Association. [2] CAAMAŇO-ALEGRE, J. et al. Budget Transparency in Local Governments: An Empirical Analysis. International Center for Public Policy, 2011. Working Paper 11-02. Available at http://ideas.repec.org/p/ays/ispwps/paper1102.html [3] Czech Republic. Act no. 129/2000 coll. The date 12 th of April 2000 by regions. In: Sbírka zákonů České republiky. 2000, amount 38/2000. Available from: http://www.zakonyprolidi.cz/cs/2000-129. 25

[4] Czech Republic. Act no. 157/2000 coll. The date 18 th of May 2000 on the transfer of certain assets, rights and liabilities from the Czech Republic to the Regions. In: Sbírka zákonů České republiky. 2000, amount 49/2000. Available from: http://www.zakonyprolidi.cz/cs/2000-157 [5] Czech Republic. Act no. 290/2002 coll. The date 13 th of June 2002 on the transition of certain other assets, rights and obligations of the Czech Republic to regions and municipalities, civic associations involved in physical education and sport and related changes. In: Sbírka zákonů České republiky. 2002, amount 106/2002. Available from: http://www.zakonyprolidi.cz/cs/2002-290 [6] Czech Statistical Office: Public Database. Czso.cz [online]. [cit. 2015-06-15]. Available from: http://www.scitani.cz/sldb2011/ [7] DROZEN, František, Jaromír RYSKA and Alexandr VACEK. Oceňování majetku. Prague: VŠE, 1994. 177 p. ISBN 80-7079-856-4. [8] HAVLAN, Petr and Jan JANEČEK. Majetek zemních samosprávných celků v teorii a pra i. Prague: Linde, 2013, 343 p. ISBN 80-720-1899-X. [9] HRABALOVÁ, Simona. Teorie a pra e rozvoje měst a obcí. Brno: MU, 2004. 99 p. ISBN 80-210-3356-8. [10] KADEŘÁBKOVÁ, Jaroslava and Jitka PEKOVÁ. Územní samospráva - udržitelný rozvoj a finance. Prague: Wolters Kluwer ČR, 2012, 297 p. ISBN 978-80-7357-910-4. [11] OCHRANA, František et al. Decentralization vs Economies of Scale: Expenditure on Maintenance of Municipal Property In: Theoretical and Practical Aspects of Public Finance 2014. Prague: Wolters Kluwer ČR, 2014, p. 228236. ISBN 978-80-7478-534-4. [12] PEKOVÁ, Jitka, Jaroslav PILNÝ and Marek JETMAR: Veřejná správa a finance veřejného sektoru. 3. aktualiz. a rozš. vyd. Prague: ASPI, 2008. 712 p. ISBN 978-80-7357-351-5. [13] PEKOVÁ, Jitka. Finance zemní samosprávy: teorie a pra e v ČR. Prague: Wolters Kluwer ČR, 2011, 587 p. ISBN 978-807-3576-141 [14] REKTOŘÍK, Jaroslav, ŠELEŠOVSKÝ, Jan et al. Finance, rozpočty, četnictví, veřejná kontrola – rukověť zemní samosprávy, Díl II., Jak řídit kraj, město a obec, Prague: Institut pro místní správu, 2002, p. 81. [15] SEDMIHRADSKÁ, Lucie. Yardstick Competition in case of the Czech Property Tax. Národohospodářský obzor, 2013, vol. 13, no. 02, pp. 77-91. [16] SEDMIHRADSKÁ, Lucie. Budget transparency in the Czech local government. 2013, Available from: https://www.researchgate.net/publication/256294349_Budget_transparency_in_Czech_local_government> [17] SCHNEIDEROVÁ, Ivana. Majetek krajů, měst, obcí, DSO a příspěvkových organizací. Prague: Acha obec účtuje, 2010, 258 p. ISBN 978-802-5456-095. [18] The Czech Constitution: Charter of Fundamental Rights and Freedoms; Parliament, ministries; Ombudsman; Antidiscrimination Act: Ostrava: Sagit, 2014, 13 p. ISBN 978-80-7488-031-5. [19] TOMÁNEK, Petr: Postavení zemních rozpočtů v rámci rozpočtové soustavy ČR. Ekonomická revue – Central European Review of Economic Issues. VŠB-Technical University Ostrava, Faculty of Economics, 2013. Vol. 11, No. 1. 27-38 p. [20] TOMÁNEK, Petr. Aspects of Spatial Distribution of Tax Revenues in Terms of its Usage in Regional Budgets In: Theoretical and Practical Aspects of Public Finance 2015. Prague: Oeconomica, 2015, p. 267-272, ISBN 978-80245-2094-0. [21] ŽEHROVÁ, Jana and Daniela PFEIFEROVÁ. Finance municipalit. 2. vyd. Prague: ČZU, 2010, 168 p. ISBN 97880-213-2024-6.

Contact information Ing. Bc. Jiří Bečica, Ph.D. VŠB – Technical University of Ostrava Sokolská třída 33, 701 21 Ostrava Czech Republic [email protected]

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Infrastructure Development through Public-private Partnership: Opportunities and Challenges for Ukraine Olena Dymchenko, Olena Panova, Olena Slavuta Abstract The paper represents an analytical research of the infrastructure development opportunities based on the adoption of public-private partnership (PPP) in Ukraine, which would contribute to modernization of the state and municipal infrastructure through private funds, improvement of the quality of goods and services provided to the public, creation of new jobs, revenue growth of budgets of different levels. The paper provides the theoretical basis of New Public Management as the core concept embedded in public-private partnership approach. In the course of adoption of the European PPP best practice in Ukraine, the European Union PPP experience serves as an example of PPP practices along with identified benefits and drawbacks. The concluding special emphasis is made on the analysis of Ukraine’s legislation regulating PPP with consequential identification of barriers of PPP practical implementation in Ukraine. Keywords: economic growth, infrastructure development, new public management, public-private partnership JEL Classification: E22, H12, H54, O18, R10-5 1 Introduction Ukraine is facing substantial political, economic and social issues hindering economic development in the conditions, under which neither the state nor local authorities are capable of independent financing and taking the required measures to restore, modernize and develop the necessary infrastructure to meet the contemporary public needs. The expanding infrastructure gap addresses the issue of the lack of investment to pursue the vector of economic stabilization and successive growth. When it comes to infrastructure, the following elements are taken into account: transportation, communication, utilities, education, health care, recreation, social security, culture, ecology as the most important systems for economic development at macro- and meso levels. Infrastructure is the key to economic growth because its existence is connected with the condition of productive forces and the territorial division of labor as well as with efficient functioning of material production. On the one hand, infrastructure improvement of the economy depends on the pace of modernization, and on the other hand, it serves as a catalyst of economic growth. In developing countries, accumulation of the infrastructure stock and improvement of the service quality affect positively long-term economic growth [2]. In transition economies, the impact of infrastructure development has demonstrated significant positive effects through higher productive efficiency, and it is estimated to be high in the cause of practical implementation of institutional reforms [10]. However, the limitations of state and local budgets, increasing social responsibilities of public authorities result in low economic growth, and in most cases reduction of spending on infrastructure needs. The main factors hindering infrastructure development in Ukraine include:  low efficiency of enterprises in production and social domains which is primarily related to significant depreciation of fixed assets;  insufficient funding for infrastructure creation, development and support on the behalf of state and local budgets;  low attractiveness of infrastructure objects for private and institutional investors;  absence of the adequate competitive market of transport, information, educational, scientific and technical, social and utility service market;  slow development of service quality in compliance with the increasing infrastructure needs. The public sector represents a significant share of the national economy in Ukraine (37 per cent of gross domestic product) and plays an important role in the real sector. By the evaluation of the Ministry of Economic Development and Trade of Ukraine, about 60 percent of public sector objects demonstrate inefficient operation and management [13]. Even though the satisfaction of public needs has always been relied on the public domain, the evident inefficiency of public institutions in Ukraine highlight the need of private sector involvement. Public-private partnership (PPP) serves an efficient mechanism for infrastructure development projects taking into account the inability of privatization of some infrastructure objects due to their strategic economic and social significance. The economic effect of PPPs is exercised in better quality products and a higher level of services along with cost reduction on their production.Therefore, the priority is to be shifted to the principles of New Public Management (NPM) based on private sector managerialism and aimed at the reduction of public expenditure on the provision of public services. In this context, PPP becomes a tool for economic and social development since private companies’ financial resources and know-how accompanied with keeping the government’s control over the required specifications will allow for the provision of public services and infrastructure of better quality at lower costs.

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The goal of the paper is to analyze the European practice of PPP application in infrastructure development and identify the prospects of PPP adoption in Ukraine’s realities in the course of the European integration processes based on the principles of NPM philosophy pursued in the public management reform. 2 Material and Methods Research methods used in the presented research involve scientific literature analysis, statistical data analysis, Ukraine’s PPP legislation analytical analysis. First, New Public Management principles are conceptualized in terms of PPP implementation policy. Second, the analysis of statistical data collection on PPP practices in the EU is presented. Third, the framework of the PPP legislation in Ukraine is analysed in the scope of opportunities of PPP implementation In Ukraine. Finally, the paper is summarized by the conclusions. 2.1 Conceptualization of New Public Management principles in public-private partnership The New Public Management (NPM) or as often defined the “new managerialism” has evolved public sector reform in the global arena since 1980s in order to transform the traditional public administration by developing a more efficient, more adaptive and consequently more effective public governance [5]. D. Kettl defines NPM as "…a collection of tactics and strategies to overcome the inefficiencies inherent in the traditional model of the public sector ..." [6]. In terms of the NPM approach, governance is no longer perceived as the sole responsibility of the state, and it is represented in terms of an interaction between the government, markets and the civil society [4]. NPM also highlights the importance of organizing and managing public services in a relational compliance with stakeholders’ interests [14]. NPM involves a policy that is meant to adapt successful business management practices to management technologies in the public sector. This new line of thinking envisages application of such NPM principles as the use of competition in public service delivery, providing general management but not actual public service provision, taking on marketoriented decision making, adoption of the customer-orientated approach, providing the customer with an opportunity of choice, implementation of planning and management methods with the objective of delivering better public services at lower costs [9]. NPM philosophy is based on trilateral cooperation in which the three parties – the state, business and civil society – are partners that jointly develop and implement socially significant projects and create new public values. In this context, in a number of economies a special quality of interaction between the state, business and society has been formed, commonly referred to as a partnership, imbedded in the PPP mechanism. The NPM principles encouraged the establishment of PPPs as a new management tool. The goal of PPP is embedded in the execution of strengths of public and private sectors for the public benefit [4]. The variety of types, forms and applications of PPP’s make it a universal mechanism for the solution of a number of longterm issues ranging from the creation and development of infrastructure to the development and adaptation of new advanced technologies. As the major dimension of NPM rationale, PPP serves as an efficient mechanism for the creation of drivers of local and regional development by overcoming budget and capacity constraints in public service delivery and infrastructure development. 2.2 Public-private partnership: EU practice of infrastructure development The term "public-private partnership" (PPP) has been used since the beginning of the 90s in the XX century. In the variety of PPP definitions, we base our research on the World Bank PPP definition as a long-term contractual arrangement between public and private partners on providing a public asset or service, in which the private party bears significant risk and management responsibility [11]. Any PPP aims to improve the quality, efficiency and user access to essential public services and infrastructure, regardless of whether it is households, businesses, government agencies or any other economic operator, thus pending to contribute to the improvement of quality of life in the local community. Specifically PPP advantages involve improved management efficiency, investment attraction, introduction of innovative solutions, technology transfer, distribution of business and investment risks between partners [15]. PPP as an efficient and promising tool for economic and social development at the regional and local level is a means of raising funds in projects where the state and local authorities keep control over the assets and establish cooperation with investors. In such cooperation, better technical and economic results are achieved, public resources and municipal property are used in a more efficient way. In terms of this cooperation the private sector provides for capital, technology, and expertise to finance, develop, and manage public-sector infrastructure projects. However, it is important to emphasize that the fact that the private sector is able to work more efficiently does not mean that it will be unconditionally more efficient. The assumption that a private company provides services better than a public or communal enterprise is to be proved by developing thorough feasibility studies, conducting open competitive tenders and making clear agreement binding provisions [15]. Risk allocation is a crucial success factor for a PPP project. Risk management within PPPs involves the development of measures of its optimal distribution and allocation to the party that can manage it best. Risk allocation methodology involves the following steps: 1) identification of potential risks for all parties PPP project; 2) qualitative and quantitative 28

assessment of the effects of risks for participants PPPs; 3) limitation of risks and taking steps to neutralize them; 4) fair risk sharing between partners. To ensure the participation of the private sector in the implementation of socially important infrastructure projects, the public party should create the acceptable balance of risks and benefits to both parties. The public sector shifts risks related to lack of demand and revenue, design and construction, operations and maintenance, finance, and force majeure. The private sector typically takes on commercial risks related to financing, developing, and managing a project. In transition economies, where civil society institutions are not developed enough, the state or local government usually initiates PPP. In such circumstances, PPP reflects the leading role of the state. The private party’s interests must be fairly balanced with public affordability, safety, access and quality requirements. If partnership parties pursue exclusively financial goals, a PPP project might fail. The socio-economic component is the basis for such partnership creation as the project that will be financed primarily with income from its operation, must be designed to provide for a better service at the best price that would satisfy the widest range of users of services provided, thus ensuring better quality of life in a community. PPPs free the competent authorities from the issues of investment provision and focus their activities on monitoring the service quality. In its turn, the private party is to seek ways to optimize their funding for provide for the required level of service quality. As the service consumer becomes a client, the private party will have to steadily improve the quality of services provided. The EU represents the biggest region in the world in terms of PPP deals: despite the recent decline of PPP projects in Europe due to the general decrease of infrastructure investment in terms of the global financial crisis, in 2014 the aggregate value of PPP transactions which reached financial close in the European market totalled 18.7 billion, a 15% increase over 2013 (EUR 16.3 billion) (Figure 1). Figure 1 – European PPP Market 2005-2014 by Value and Number of Projects. Source: EPEC. [8]

With EUR 11.8 billion worth of transactions and the largest number of deals, the transport sector remains the most active in PPP sectoral applications in the EU. The healthcare sector is featured by the upward trend. It is the second largest sector for PPP application both in number of projects and value: 15 health transactions reached financial close worth an aggregate value of EUR 2.2 billion (Figure 2). Figure 2 – Sector Breakdown by Value and Number of PPP Transactions in the EU in 2014. Source: EPEC. [8]

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The UK remains the leader of PPP deals in Europe in terms of both value and number of projects: in 2014, 24 transactions were closed (compared to 31 in 2013) with a value of about EUR 6.6 billion (EUR 6 billion in 2012) (Figure 3). Figure 3 – Country Breakdown by Value and Number of PPP Transactions in the EU in 2014. Source: EPEC. [8]

In today’s EU context, PPPs manifest themselves as essential schemes for cooperation between the public and the private sector. Governments are motivated to take part in PPPs for budgetary reasons, as project risks are transferred to the private sector and infrastructure assets provided through PPP are not classified as government assets and do not fall for deficit calculation by the Maastricht criteria [8]. Public services benefit from improved operational efficiency resulting from technology and innovation introduced by the private sector [11]. The acquired PPP beneficial aspects also involve long-term investment opportunities, enabling private actors to maximize revenues by increasing asset capacity or by setting and segmenting user prices. However, PPP drawbacks include high dependence on the political and financial commitments of the government, lack of transparency in the procurement procedure and on the returns made by equity investors, unexpected delays and extra costs during the construction phase [8]. Even though PPP infrastructure developments are not evenly distributed in the EU they have demonstrated overall positive effects as to infrastructure improvement by adding to the quality of services provided and decrease of the financial burden on the public sector. 2.3 Public-private partnership: opportunities for Ukraine In Ukraine, only in recent years the interest to PPP has been intensified as to a mechanism to attract private investment capital and expertise to efficiently manage infrastructure maintenance and construction, provision of services that have traditionally been provided by state and municipal enterprises. In 2010, Ukraine adopted the Law "On State-Private Partnership", however, the national experts and public managers have not developed the common understanding of the PPP mechanism [15]. According to the World Bank database, infrastructure investment projects with the private participation in Ukraine from 1992 to 2014 amounted to USD 14.3 billion, of which the telecommunications sector accounted approximately 82% by value (Table 1).

Number of projects

Investment, USD mln

Number of projects

Investment, USD mln

Number of projects

Investment, USD mln

Number of projects

Investment, USD mln

1992 1993 1994 1995 1996 1997 1998

Investment, USD mln

Year

Total

Number of projects

Table 1 – Infrastructure investment projects with private participation in Ukraine, 1992–2014 Infrastructure Sector Energy Telecom Transport Water and Sewage

0 0 0 0 0 0 6

0 0 0 0 0 0 0

1 1 0 0 3 2 1

11 72 10 18 317 187 331

0 0 0 0 0 0 0

0 0 0 0 0 0 0

0 0 0 0 0 0 0

0 0 0 0 0 0 0

1 1 0 0 3 2 7

11 72 10 18 317 187 331

30

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total

0 0 6 1 0 0 0 1 1 1 0 4 5 16 0 0 41

0 0 160 20 0 0 0 4 83 100 121 89 998 725 0 0 2,299

0 1 3 0 0 0 0 1 0 0 0 0 1 0 0 0 14

242 0 0 206 0 0 255 0 0 186 0 0 370 0 0 738 0 0 1,407 0 0 865 0 0 1,346 0 0 1,364 0 0 934 1 130 413 0 0 1,819 0 0 440 0 0 185 0 0 0 0 0 11,714 1 130 Source: The World Bank Group. [12]

0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 2

0 0 0 0 0 0 100 0 0 102 0 0 0 0 0 0 202

0 1 9 1 1 0 0 2 1 2 1 4 6 16 0 0 58

242 206 415 206 370 738 1,507 869 1,429 1,566 1,185 501 2,816 1,164 185 0 14,346

Investments in infrastructure in Ukraine are estimated to be above 2% of GDP in the period of economic growth, but it was considerably hit by the recession in the recent years (Figure 4). Figure 4 – Total infrastructure finance by type of finance in Ukraine, % of GDP. Source: EIB. [7]

However, infrastructure investment projects with private participation in Ukraine can be identified as “quasi PPPs” [3] and they have been implemented as concession, divesture, greenfield, management and lease projects (Table 2).

Total

Greenfield project

0 31 10 0 2 12 0 0 1 1 0 0 1 33 23 Source: The World Bank Group. [12]

Management and lease contract

Energy Telecom Transport Water and sewerage Total

Divestiture

Infrastructure Sector

Concession

Table 2 – Total investment in infrastructure investment projects by type in Ukraine, USD mln

0 0 0 1 1

41 14 1 2 58

The main factor hindering the implementation of PPP principles in Ukraine is the general lack of legal regulation, which would meet the contemporary economic realities. One of the signals of low efficiency of the PPP legal model Ukraine adopted in the Law of Ukraine “On State-Private Partnership” is the absence of successfully implemented PPP projects 31

in accordance to its mechanism but not to its separate types such as concession which is regulated by the special legislation in Ukraine. 3 Results and Discussion In 2011, the EBRD report determined that the legal framework regulating PPP in Ukraine corresponds to PPP international best practice [11]. Since then a significant number of changes has been made in the Ukrainian legislation on PPP that have complicated rules, created several layers of legal/institutional PPP’s while creating the controversy. The whole variety of legislature related to PPP regulation in Ukraine includes the Economic Code of Ukraine, Civil Code of Ukraine, Budget Code of Ukraine, the Law of Ukraine “On Leasing State and Communal Property”, Law of Ukraine “On Concession”, Law of Ukraine “On Concession for the Construction and Operation of Motor Roads”, Law of Ukraine “On the Administration of State and Communal Property”, Law of Ukraine “On Financial Leasing”, Law of Ukraine “On peculiarities of lease or concession facilities of centralized water-supply and sanitation that are municipally owned”, Law of Ukraine “On peculiarities of lease or concession of state-owned fuel and energy complex”, Law of Ukraine “On Local Government” etc. The provisions of the Law of Ukraine "On State-Private Partnership" and other legislation on PPP is characterized by several shortcomings that hinder PPP development in Ukraine:  there is no clear distinction between projects implemented under PPP and projects implemented not under PPP;  failure of the regulation of relations in terms of land use for PPP implementation, which actually blocks implementation of PPP projects;  an efficient mechanism of state financial and other participation for PPP project implementation has not been developed;  it is not clearly defined which public authorities are authorized to analyze PPP project efficiency and to sign PPP contracts;  the private partner is not provided with real guarantees in case of approval of tariffs for goods (works, services) that are not economically substantiated;  there are contradictions between the Law of Ukraine "On State-Private Partnership" and the laws administering the procedure of concluding individual contracts within PPP: even though the Law of Ukraine "On StatePrivate Partnership" is the primary piece of legislation that applies to all forms of PPP including concession agreements, cooperation agreements, production sharing agreements and other contracts, each of these types of contracts are regulated by a separate law which makes partners to analyze numerous contradictory pieces of legislation while choosing a specific form of PPP to implement a project. As such, the major directions on PPP development in Ukraine involve systemic improvement of the legal PPP regulation, development of the unified PPP concept in the long term prospect, institutional provision at the national and regional levels on initiating and managing PPP projects, staff training in public and private sector on PPP project development, public information on the potential of PPP influence on the social and economic development. 4 Conclusion Considering the diversity of forms and areas of PPP application makes it a universal mechanism to address a number of long-term issues in Ukraine there is an urgent need of PPP practical implementation in terms of the current transformational reform processes. Although the practical introduction of PPP projects in Ukraine is at the fairly early stage of development, Ukraine has gained the experience of public procurement, state property lease, management of cooperative rights of the state entities, participation in investment joint projects and activities on the basis of appropriate agreements. Based on the accomplished research, we can formulate the following areas of fostering PPP development in Ukraine: 1. Improvement of the legal framework to eliminate its controversy in order to form a unified approach to the formation of the institutional mechanism of PPP development, to clearly identify public entities that have the right to serve as public partners in a PPP contract, to clarify the division of responsibilities of executive bodies in the system of public administration as to PPP development to avoid their duplication. 2. Development of the commonly accepted PPP concept for a long-term period by ensuring conditions for the trustworthy, transparent and equitable cooperation between public and private parties preconditioned by investment climate improvement, protection of investors’ property rights, elaboration of the mechanism of state support by providing state guarantees, simplification of conciliation and administrative procedures, creation of favorable conditions for land use for PPP implementation, improvement of the mechanism of commercial dispute resolution. 3. Conducting information and education work on PPP concept promotion at regional and local levels to eliminate an important practical obstacle to launching PPP projects, which is the lack of appropriate PPP methodological staff training provision for public units responsible for investment activity as they are primarily aimed at redistribution of budget funds allocated for investment and not to create favorable conditions for private capital attraction into the real economy. 4. Establishment of "centers of competence" by initiating institutional PPP project management at regional level to maintain the framework of competent and trusted advisors, both public and private, to assist with structuring, screening, and procuring PPP projects. 32

5. Enabling active involvement of civil society organizations in PPP project initiation, assessment and monitoring to build an efficient constructive dialogue with communities to maintain citizens’ trust to public authorities and private actors as well as to provide for the sufficient level of awareness of PPP advantages and risks. References [1] BARZELAY, M. (2001). The New Public Management. Improving Research and Policy Dialogue. University of California Press, Berkeley. [2] CALDERON, C., SERVEN, L. (2010). Infrastructure in Latin America, World Bank, Policy Research Working Paper 5317, 2010. [online]. [cit.2015-04-20]. Available from https://openknowledge.worldbank.org/bitstream/handle/10986/3801/WPS5317.pdf?sequence=1 [3] CHEREVYKOV, IEVGEN (2013). Institutional environment for public-private partnership in Ukraine: Do institutions really matter? MPRA Paper No. 62110, 2013. [online]. [cit.2015-04-25]. Available from http://mpra.ub.uni-muenchen.de/62110/ [4] HODGE, G.A. and GREVE, C., (2007). Public-Private Partnerships: An International Performance Review, Public Administration Review, Vol. pp. 545-559. [5] HOOD, C. (1991). A public management for all seasons? Public Administration, Vol. 69., No. 1., pp. 3-19. [6] KETTL D. (2000). The Global Public Management Revolution: A Report on the Transformation of Governance. Washington. [7] KRAVETS, O. (2013). Infrastructure Investments in Eastern Neighbours and Central Asia (ENCA). EIB Working Papers. 2013. [online]. [cit.2015-04-20]. Available from http://www.eib.org/infocentre/publications/all/economics-working-paper-2013-01.htm [8] EPEC (2014). Review of the European PPP Market in 2014. www.eib.org/epec/epec_market_update_2014_en.pdf [9] OSBORNE, S. (2000). Public-private partnerships: theory and practice in international perspective, Routledge advances in management and business studies, Routledge, London. [10] SUGOLOV, P., DODONOV, B., VON HIRSCHHAUSEN, C. (2003). Infrastructure Policies and Economic Development in East European Transition Countries: First Evidence, Institute for Economic Research (IER). 2003. [online]. [cit.2015-04-18]. Available from http://tudresden.de/die_tu_dresden/fakultaeten/fakultaet_wirtschaftswissenschaften/bwl/ee2/lehrstuhlseiten/ordner _publikationen/publications/wp_psm_02_sogulov_dodonov_hirschhausen_infrastructure_growth_transition.pdf [11] The EBRD (2011). Assessment of the quality of the PPP legislation and of the effectiveness of its implementation. 2011 [online]. [cit.2015-04-25]. Available from www.ebrd.com/downloads/legal/concessions/moldova.pdf [12] THE WORLD BANK GROUP (2014). A World Bank Resource for PPPs in Infrastructure. [online]. [cit.2015-0417]. Available from http://ppp.worldbank.org/public-private-partnership/ [13] THE WORLD BANK GROUP (2015). Private Participation in Infrastructure Projects Database. Ukraine. 2015. [online]. [cit.2015-04-18]. Available from http://ppi.worldbank.org/explore/ppi_exploreCountry.aspx?countryID=97 [14] THE MINISTRY OF ECONOMIC DEVELOPMENT AND TRADE OF UKRAINE. [online]. [cit.2015-04-17]. Available from http://www.me.gov.ua/?lang=uk-UA [15] WETTENHALL, R., (2003). „The Rhetoric and Reality of Public-Private Partnerships”, Public Organization Review: A Global Journal, Vol. 3, pp. 77-107. [16] АСОЦІАЦІЯ МІСТ УКРАЇНИ (2013). Досвід залучення бізнесу до надання комунальних послуг та модернізації об’єктів інфраструктури, кращі практики місцевого самоврядування, збірка 26, Київ, 2013. [online]. [cit.2015-04-17]. Available from http://www.auc.org.ua/sites/default/files/files/Praktyky_26_small.pdf Contact information prof. Olena Dymchenko, DSc Department of Enterprise Economics, Business Administration and Regional Development O.M. Beketov National University of Urban Economy in Kharkiv 12, Revolutsii St., Kharkiv 61002, Ukraine [email protected] Olena Panova, Senior Lecturer Department of Enterprise Economics, Business Administration and Regional Development O.M. Beketov National University of Urban Economy in Kharkiv 12, Revolutsii St., Kharkiv 61002, Ukraine [email protected] Olena Slavuta, Senior Lecturer Department of Enterprise Economics, Business Administration and Regional Development O.M. Beketov National University of Urban Economy in Kharkiv 12, Revolutsii St., Kharkiv 61002, Ukraine [email protected] 33

Volunteers Engagement in Italian Non Profit Organizations Patrizia Gazzola, Gianluca Colombo Abstract The aim of the paper is to analyze the involvement of the volunteers in the non profit organizations in Italy. The human resources of a non profit organization are composed by workers and volunteers. Volunteering is a crucial renewable resource for social and environmental problem-solving the world over. Volunteers are workers who voluntarily choose to provide services to a non profit, without any expectation of compensation. Volunteers satisfaction and retention are crucial for the success of a non profit organization, which are known for attracting highly committed volunteers who are motivated by mission. Effective volunteer engagement is critical to the success of a non profit. The time, talent and treasure provided by volunteers help an organization maximize results in working toward its mission. The work in the first part is theoretical. In the second part predominantly employs the quantitative methods; authors present an empirical analysis based on observed and measured phenomena and derives knowledge from actual experience rather than from theory or belief. It describes and synthesizes, with the use of statistical data, the outcomes of the first survey on voluntary made by the National Institute of Statistics (ISTAT). Keywords: motivation, non profit, volunteers JEL Classification: J24, J28, O15 1 Introduction Non-profit organizations are an indivisible part of the structure of today’s economy, some of them draw a big amount of money. Non profit sector in Italy play a crucial role in providing social services and contributing to achieving social policy goals (Bryson, 1988; Cornforth, 2003; Morganti, 2004). The non profit organization are a vital component of the world economy and of many national economies (Pomper, 2002; Powell, Steinberg, 2006). One of the most distinctive features of the non profit organizations is its voluntary nature. Volunteers have become a valuable set of human resources in many sectors of society. Non profit organizations do not coerce people to work within the organization nor do they can oblige people to use of their services (Frumkin, 2002). For non profit organizations, “free choice is the coin of the realm. Donors give because they choose to do so. Volunteers work of their own volition” (Frumkin, 2002, p.3). Volunteering is a crucial renewable resource for social and environmental problem-solving the world. Non profit organizations provide important opportunities for people to combine their energy, talents and values for community improvement and enrichment (Minnesota Council of Nonprofits, 2010). They have the role of entities that engage and inspire individuals and communities for public benefit (Gazzola, Ratti, 2014; Carroll, 1991). The skills and talents of volunteers help the non profit organizations to pursue their mission (Emerson, Twersky, 1996). In the research we highlight the importance, for the Italian non profit organizations, of the volunteers. human resources (Glaeser, Shleifer 2001) and the role of the volunteers engagement. Approximately one out of eight Italians does unpaid activities to benefit others or the community. In Italy the number of volunteers is estimated at 6.63 millions people (Istat, 2013). 2 Material and Methods 2.1 Literature review According to Salamon and Anheier (1997), the term "non profit organization", utilized in the research, expresses that the organization does not aim primarily to make a profit, in reality, profits are often achieved (Drucker, 1989). However, these profits are not distributed to the shareholders, but are usually used to realize the organization's purpose or are retained. The definition is integrated by Badelt (1999) that considers, among the number of different viewpoints, there is only one common denominator namely to try to consciously distance oneself from the for-profit world of the private sector. The importance of volunteerism has been highlighted by many scholars (e.g., Chelladurai, Madella, 2006; Clary et als, 2009; Cravens, 2006; Cuskelly, Boag, 2001; Twynam, Farrell, Johnston, 2002/). Cuskelly, McIntyre, and Boag (1998) indicated that volunteers tend to more thoroughly commit themselves to organizations in a strong, positive manner given that the services from volunteers are more value-based and less tangible than those of paid employees. The traditional definition considers volunteer as non salaried service. The term volunteer originated in the military (Christiansen-Ruffman, 1990). The term was used for civilians mobilized for military service in times of emergency. Military volunteers were not payed for the their services. (Cnaan, Handy, Wadsworth, 1996). Van Til (1980) defined volunteering like a person who “may be identified as a helping action of an individual that is valued by him or her and yet is not aimed directly at material gain or mandated or coerced by others. For a large number of non profit organizations the number of employees isn’t important, but volunteers represent important part of the human resources and often smaller organizations sometimes has only volunteer work (Jäger, Schmidt, Beyes, 2007). We consider the definition of volunteers as the individuals that provide services without any expectation of compensation (Shin, Kleiner, 2003), and without any coercion or intimidation, non-employees (U. S. Federal law, 1938). The European Commission defined volunteering i. e. encompassing all forms of non-remunerated work (European Union (EU), 2009). The definition of volunteering in Italy was established in 1991 with law 266/91, Framework law on 34

volunteering‟ and explicitly states that a volunteering activity must be: spontaneous, gratuitous, without intended remunerative aims and should be undertaken exclusively for solidarity purposes. To this effect, the Italian definition of a volunteer is “a person, who, having carried out the duties of every citizen, places her/his own capacity at the disposal of others, for the community or for all humanity. She/he operates in a free and gratuitous manner promoting creative and effective responses to the needs of beneficiaries of her/his own action and contributing to the realization of common goods”. Since this definition excludes any activity that is not undertaken for solidarity purposes (Ferreira, Proenca, Proenca, 2010) The term “volunteerism‟ in Italy refers to all types of activities, whether formal or informal, full-time or part-time, at home or abroad. It is undertaken of a person's own free-will, choice and motivation, and is without concern for financial gain. It benefits the individual volunteer, communities and society as a whole. It is also a vehicle for individuals and associations to address human, social or environmental needs and concerns. Formal voluntary activities add value, but do not replace professional, paid employees. Volunteers are fundamental for non profit organizations (Weisbrod, 1975). According to Wilson and Pimm (1996) some non profit organizations do not need to make a big effort to attract volunteers, although this process is difficult for the majority. Organizations with some prestige only need to issue an invitation to quickly get volunteers (Wilson, Pimm 1996). Other groups where recruitment represents no difficulty are those where there is a definitive measurable benefit such as music concerts. However, the communication task that the organization needs to develop in order to attract and retain volunteers must consider the variety of factors that influence individuals and make them donate their time to voluntarism programs (Dolnicar, Randle, 2007). Volunteers provide their time and efforts for a wide variety of reasons. One historical way of understanding volunteer motivations has been based on theories of altruism and selflessness (Phillips, 1982; Rehberg, 2005), in that the primary motivation is that volunteers want to help others. However, other motives should not be excluded in understanding volunteers. Contemporary notions of volunteering often involve more project oriented and specific expectations in terms of form, time, and content of volunteer involvement (Rehberg, 2005). In this regard, numerous volunteer studies on social services have found different motivations such as altruism, social contact, personal interests, and emotional needs (Yeung, 2004). 2.2 Methods This study is focused on volunteers, in Italian non profit organizations. The research design in the first part is theoretical. In the second part predominantly employs the quantitative methods; authors present an empirical analysis based on observed and measured phenomena and derives knowledge from actual experience rather than from theory or belief (Brant, Borges-Andrade, 2014). It describes and synthesizes, with the use of statistical data, the dynamics and the evolution of the volunteers resources in non profit organizations. The research questions are:  Are Italian non profit organizations a volunteer creation engine?  Which is the composition of volunteering in the Italian non profit organizations? Statistical data provided in this report is based on the main sources Istat census conducted in 2011 and compared with the Istat census conducted in 2001. The survey on non profit organizations is part of the 9 th General Census of industry and services conducted by Istat. Data collection was completed 20 th December 2012 and they were released during 2013. As Istat says, the survey is a magnifying glass on the world of non profit, a crucial sector for companies and Western economies. The purpose of the investigation is to meet the information needs of policy maker, scholars and sector practitioners but also to answer the demands of the international organizations on the placement of non profit sector in the context of Italian social policies and on economic measurement on volunteer work. The International Labour Organization (ILO) approved on 23 March 2011 the first-ever official ‘Manual on the Measurement of Volunteer Work’ (ILO, 2011), which establishes a common procedure for national statistical agencies to use when regularly measuring the amount and economic value of volunteering. The recipients of the survey are legal and economic units with or without legal personality, of private nature, that produce goods and services for market or not and that, on the basis of the existing laws or to its own laws, does not have the right to distribute, even indirectly, profits or other gains different from the remuneration for work done to the subject that have established or to the members. The individual reality involved in the survey has been identified by complying with the international definition of the System of National Accounts (SNA), which considers mainly the criterion of "ban on distribution of profits or other gains different from the remuneration for work done to the subject that have established or members". Italy is among the few countries in Europe to assess periodically the world of the non-profit sector. In this edition of the census 474.765 organizations are involved, nearly twice the 235.000 of the previous edition, held in 1999. In the paper also the outcomes of the first survey on voluntary work are included; the survey is a result of the agreement between Istat, CSVnet (National Coordination of Volunteer Support Centres) and the Volontariato e Partecipazione Foundation are used (ISTAT, 2014). In the research are analyzed: the number of volunteers in 2011 compared with the volunteers in 2001; the number of volunteers divided in classes; the volunteers by gender and by education; the division between volunteers retired and employed; the volunteers divided for sector of activity comparing 2011 with 1999. The main contribution of this line of research is the analysis of the volunteers resources involved in non profit organizations in Italy. The research shows the importance of the stakeholder engagement and a model of motivation for the volunteers. 35

3 Results and Discussion In Italy the number of volunteers was estimated in 4.758 millions people in the findings of the 2011 Italian census on non profit organizations. The answer to the first question: “Are Italian non profit organizations a volunteer creation engine?” is in Table 1 and Figure 1. In 10 years the increase of the numbers of volunteers is of 28% Table 1 - Number of volunteers Istat 2011 compared with Istat 2001 2011 2001 Var % 2011/2001 Non profit organizations 301.191 235.232 28,0 Non profit with volunteers 243.482 220.084 10,6 Volunteers 4.758.622 3.315.327 43,5 Source: Istat 2011 and 2001.

The second question is: “What’s the composition of volunteering in the Italian non profit organizations?” isin the following dates. The Volunteer work is more widespread in the North of the Italy. The highest volunteering rate was recorded in the North-East (16%), while the South area is characterized by a noticeably lower participation rate (8.6%). Men were more active than women (13.3% against 11.9%), due to greater male participation in organization-based volunteering. Volunteers belong mainly to the 55-64 age group (15.9%) (Table 2). The contribution of the young and the old in terms of active involvement is, instead, lower than the national average. The share of those performing voluntary activities grows with educational level. 22.1% of university graduates experienced volunteering against 6.1% of those who only completed primary schooling (Table 2). Considering the occupational level, those in employment (14.8%) and students (12.9%) were the most active. Participation is, moreover, at the highest among the members of more affluent families (23.4%) and at the lowest among members of families with entirely insufficient means (9.7%). The majority of volunteer are employed (55%) and the retired are 28% (Table 3). Table 2 - Volunteers by gender and by education

Source: Istat. Table 3 - Volunteers by employed and by retired

Source: Istat. Figure 1 - Non profit organizations volunteers (in classes). Source: Istat 2011.

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The average volunteer engagement was 19 hours in four weeks. The greatest hourly contribution in direct voluntary activities was the one of women and senior citizens. People in an excellent financial situation and people aged 55 – 74 devote an above average number of hours to voluntary activities. Organization-based voluntary activities are more diversified and qualified than direct voluntary activities. Approximately a volunteer out of six is involved in more than one organization (16.2%). Organization-based volunteering is a consolidated practice: 76.9% of people has been involved in the same activity for three or more years and 37.7% for over ten years. Conversely, 48.9% of those performing direct volunteering has been doing it for less than two years. 62.1% of organization-based volunteers performed their activities because they believed “in the cause promoted by the group/organization”. 49.6% of those volunteering stated they felt better about themselves. 59,1% of volunteers is active in, in cultural, sport and recreational organizations, 7,1% in the health sector, 12,6% in social services and emergency intervention, education and research 3,7% (Figure 2). In Figure 2 the International Classification of Non-profit Organizations, is used, the activities are divided into 12 major sectors. Figure 2 - Volunteers divided for sector of activities 1999 and 2011. Source: Istat 2011 and 1999.

The new data of volunteers in Italy calculated according to the definition of ILO, in 2013 confirmed the date of the Census and found that 12.6 percent of the population, or about 1 in 8 Italians, engage in volunteering. Moreover, these data allow us to see how Italians volunteer in more detail – about 4.414 millions citizens did their activity through a group or an organization (organization-based volunteering rate equal to 7.9%) and three millions were directly involved (direct volunteering rate equal to 5.8%). This exceeds the total 6.63 million individuals reporting volunteer work in the time frame covered by the survey, showing that many volunteers work both directly and indirectly. 4 Conclusion The evolution of volunteering in the Italian non profit organizations was supported by two main reasons: the development of the volunteers engagement and the legislation. The large number of volunteers is encouraging for the continued understanding of volunteer motivations. The ability of a non profit organization to create strategies for a meaningful experience, the ability to make volunteers feel responsible for outcomes, and providing volunteers with positive feedback may result in increasing volunteer motivation and satisfaction while at the same time encouraging individuals to volunteer in the future. From a managerial perspective, the role of the organization seems to be exceedingly important in managing volunteers. Event managers must understand what motivates people to volunteer and how to help each volunteer achieve a sense of personal satisfaction through the identification of various motivations. Johnston et al. (1999/2000) suggest that identifying volunteer motivations should be substantial, by specifically matching with the characteristics of organizations or events, rather than a simple motivation of helping others. If the motivations of individual volunteer are identified successfully, event managers would be able to more accurately assign appropriate tasks to volunteers. Moreover, when managers place volunteers, giving them constant support and guidance would be required to enhance volunteers’ satisfaction and positive feeling of the organization (Figure 3).

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Figure 3 – The motivational model. Source:author’s elaboration.

Volunteer Engagement is a strategy that builds organizational capacity through employee and volunteer collaboration and the development of high-impact, meaningful volunteer opportunities that create greater influence and outcome for the organization. Volunteer engagement is focused on matching the needs of the organization to the skills and talents that volunteers want to share (Hall et als. 2006). We can summarize the benefits of volunteer engagement: staff can accomplish more with volunteers than they can do on their own; more people choose the organization as the place to volunteer; increased ability to provide valuable services to the organization, community, and clients you serve; increased community awareness and support for programs and events; increased donations from volunteers. Also legislation in Italy play and important role in developing activities of voluteering Starting, then, since 1991, the legislator began the process of regulation of the non profit sector by, first of all, defining the activity of volunteering and voluntary organisations; after that it also established: the regional registries, with the formalities for voluntary organisations to receive their funds; the National Observatory for Volunteering and its functions; the Special Fund that is financed by Bank Foundations and distributed to each Volunteering Service Centre on the territory. After that, in 1997, the legislator enacted the law 460/97, also known as the “Onlus law”; it concerns voluntary organisations which, through the registration in the regional registries, are automatically recognised as non-profit organisations with social utility (Onlus). This system enables Onlus to benefit from tax incentives, such as the possibility given to donators to deduct 19% of their taxes, for an amount not superior to €2000, in aid of non lucrative organisations with social utility. The last step was the approval of the law 328/2000, also known as the “framework law for assistance reform”, in order to reaffirm the positive contribution of voluntary organisations to meeting social policy objectives. More specifically, it drew a legislative framework within which voluntary organisations are called to cooperate with public authorities in the designing and implementation of social assistance projects. It is also important to note that, Italian regions have, since 2001, administrative and legislative powers, also in the sector of volunteering. More specifically, regions have the power to create their own legislative framework in addition to the national framework. Government have an important role to play in supporting volunteering. They represent citizen action and endorsement. Without volunteers, its difficult for any non profit organizations to express truthful credibility. Government should be actively encouraging and supporting volunteer involvement in non profit organizations. They should be providing a legislation that encourages and supports volunteers, and looking to organizations that involve volunteers for guidance on a variety of domestic issues. References [1] BADELT, C. (Hrsg.), BACHSTEIN, W. (1999). Handbuch der Nonprofit Organisation, Strukturen und Management. Stuttgart: Schäffer-Poeschel. [2] BRANT, S. R. C., BORGES-ANDRADE, J. E. (2014). Crenças no contexto do trabalho: características da pesquisa nacional e estrangeira. Revista Psicologia. Vol 14, n. 3, pp. 292-302. [3] BRYSON, J. M. (1988). A strategic planning process for public and non-profit organizations. Long range planning. . Vol. 21, n.1, pp. 73-81. [4] CARROLL, A. B. (1991). The Pyramid of Corporate Social Responsibility: Toward the Moral Management of Organizational Stakeholders. Business Horizons. Vol. 34, pp 39-48. [5] CHELLADURAI, P., MADELLA, A. (2006). Human Resource Management of Olympic Sport Organisations: Memos Manual. Champaign, IL: Human Kinetics Publishers. [6] CHRISTIANSEN-RUFFMAN, L. (1990). Women and volunteers: Contradictions and conceptual challenges Symposium conducted at the meeting of the Annual Meeting of the Association of Voluntary Action Scholars. London. 38

[7] CLARY, G. E., SNYDER, M., WORTH, K.A., STUKAS, A.A. (2009). The matching of motivations to affordances in the volunteer environment: An index for assessing the impact of multiple matches on volunteer outcomes. Nonprofit and Voluntary Sector Quarterly.  Vol. 38, n. 1, pp. 5-28. [8] CNAAN, R. A., HANDY, F., WADSWORTH, M. (1996). Defining who is a volunteer: Conceptual and empirical considerations. Nonprofit and Voluntary Sector Quarterly. Vol. 25, n. 3, pp. 364-383. [9] CORNFORTH, C. (Ed.). (2003). The governance of public and non-profit organizations. Oxford, UK: Routledge. [10] CRAVENS, J. (2006). Involving international online volunteers: Factors for success, organizational benefits, and new views of community. The International Journal of Volunteer Administration,. Vol. 24, n. 1, pp. 15-23. [11] CUSKELLY, G., BOAG, A. (2001). Organizational commitment as a predictor of committee member turnover amongst volunteer sport administrators: Results of a time-lagged study. Sport Management Review. Vol. 4, n. 1, pp. 65-86. [12] TWYNAM, G.D., FARRELL, J.M., JOHNSTON, M.E. (2002). Leisure and volunteer motivation at a special sporting event. Leisure/Loisir, Vol. 27, n. 3/4, pp. 363-377. [13] CUSKELLY, G., MCINTYRE, M., BOAG, A. (1998). A longitudinal study of the development of organizational commitment amongst volunteer sport administrators. Journal of Sport Management, Vol. 12, n. 3, pp. 181-202. [14] DOLNICAR, S., RANDLE, M. (2007). What Moves Which Volunteers to Donate Their Time? An Investigation of Psychographic Heterogeneity Among Volunteers in Australia. International Journal of Voluntary and Nonprofit Organisations. Vol. 18, n. 2, pp. 135-155. [15] DRUCKER, P. F. (1989). What Business Can Learn from Nonprofits, Harvard Business Review. Vol. 67, n. 4, pp. 88-93. [16] EMERSON, J., TWERSKY, F. (1996). New social entrepreneurs: The success, challenge and lessons of nonprofit enterprise creation. San Francisco: San Francisco, The Roberts Foundation, Homeless Economic Development Fund [17] EUROPEAN UNION (2009). Study on Volunteering in the European Union Country Report Italy. [online]. [cit.2015-03-4]. Available http://ec.europa.eu/citizenship/pdf/national_report_it_en.pdf [18] FERREIRA, M., PROENCA, J. F. AND PROENCA, T. (2012). Motivations Which Influence Volunteers’ Satisfaction. Proceedings of the 10th International Conference of the International Society for Third Sector Research, Siena, Italy, published in Conference Working Papers Series, Vol. VIII, Siena, Italy. [19] FRUMKIN, P. (2002). On being nonprofit: A conceptual and policy primer. Cambridge, Mass.: Harvard University Press. [20] GAZZOLA, P., RATTI, M. (2014). Transparency in Italian non profit organizations, The Annals of the University of Oradea. Economics Sciences Tom XXIII 1st Issue / July 2014, pp. 123-133. [21] GLAESER, E. L., SHLEIFER, A. (2001). Not-for-profit entrepreneurs. Journal of public economics. Vol. 81, n. 1, pp. 99-115. [22] HALL, M., LASBY, D., GUMMULKA, G., TYRON, C. (2006). Caring Canadians, involved Canadians: Highlights from the 2004 Canada Survey of Giving, Volunteering and Participating. Ottawa, ON: Minister of Industry (Statistics Canada). [23] ILO (2011). Manual on the Measurement of Volunteer Work. [online]. [cit.2015-03-12]. Available http://www.ilo.org/stat/Publications/WCMS_162119/lang--en/index.htm [24] ISTAT (2001). 8th General Census of industry and services 2001. [online]. [cit.2015-03-15]. Available http://dwcis.istat.it/cis/index.htm [25] ISTAT (2014). Unpaid activities to benefit others. [online]. [cit.2015-03-10]. Available http://www.istat.it/en/archive/129122 [26] ISTAT, (2011). 9th General Census of industry and services. [online]. [cit.2015-03-10]. Available http://www.istat.it/en/archive/133905 [27] JÄGER, U., SCHMIDT, K., AND BEYES, T. (2007). Leading Without Formal Power. Paper presented at the 6th Workshop on the Challenges of Managing the Third Sector, Venice. [28] MINNESOTA COUNCIL OF NONPROFITS (MCN) (2010). Principles and Practices for Nonprofit Excellence. A guide for nonprofit board members, managers and staff. MCN. [29] MORGANTI, M. (2004). Non profit: produttività e benessere. Come coniugare efficienza e solidarietà nelle organizzazioni del terzo settore (Vol. 191). Milano: FrancoAngeli. [30] PHILLIPS, M. (1982). Motivation and expectation in successful volunteerism. Journal of Voluntary Action Research, 11 (1/2), 118-125. [31] POMPER, F. (2002). Handbuch der Nonprofit Organisation: Strukturen und Management. Stuttgart: SchäfferPoeschel. [32] POWELL, W. W., STEINBERG, R. (Eds.). (2006). The nonprofit sector: A research handbook. Yale: University Press. [33] REHBERG, W. (2005). Altruistic individualists: Motivations for international volunteering among young adults in Switzerland. Voluntas: International Journal of Voluntary and Nonprofit Organizations. Vol. 16, n. 2, pp. 109122. [34] SALAMON, L. M., ANHEIER, H. K. (1997). Defining the nonprofit sector: a crossnational analysis. Manchester: Manchester University Press. 39

[35] SHIN, S., KLEINER, B. H. (2003). How to Manage Unpaid Volunteers in Organisations. Management Research News. Vol. 26, n. 2/3/4, pp. 63-71. [36] U.S. FEDERAL LAW (1938). Under the federal Fair Labor Standards Act. FLSA. [37] VAN TIL, J. (1988). Mapping the third sector: Voluntarism in a changing social economy. New York: The Foundation Center. [38] WEISBROD, B. A. (1975). Toward a Theory of the Voluntary Nonprofit Sector in a Three-Sector Economy,” in PHELPS E., ed., Altruism, Morality, and Economic Theory. New York: Russell Sage Foundation, pp. 171-95. [39] WILSON, A., PIMM, G. (1996). The tyranny of the Volunteer: the care and feeding of voluntary workforce. MCB University Press, Vol. 34, n. 4, pp. 24-40. [40] YEUNG, A. B. (2004). The octagon model of volunteer motivation: Results of a phenomenological analysis. Voluntas: International Journal of Voluntary and Nonprofit Organizations. Vol. 15, n. 1, pp. 21-46.

Contact information assoc. prof. Patrizia Gazzola Insubria University Via Montegeneroso, 71 – Varese Italy [email protected] prof. Gianluca Colombo University of Lugano Institute of Management (IMA) Via Buffi, 13 – Lugano Switzerland [email protected]

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Research and Development (R&D) in the EU Countries: Comparison of Selected Indicators Martina Halásková, Pavel Bednář Abstract This paper deals with the position of Research & Development (R&D) in the EU countries. In greater detail, attention is paid to selected R&D indicators, with focus on financial R&D indicators. Results of the research show a comparison of the total expenditure on R&D in % of GDP (R&D intensity), expenditure according to R&D sector (business enterprise sector, government sector, higher-education sector, and private non-profit sector) in the EU countries, and a comparison of government budget appropriations or outlays for R&D as % of total general government expenditure as a mean value of the years 2009–2013. By means of hierarchical cluster analysis, selected financial R&D indicators are compared, with focus on public expenditure (R&D indicators in the higher-education sector, R&D expenditure in the government sector, and government budget appropriations or outlays for R&D as % of total general government expenditure) as average of the years 2009–2013, and similarities and differences are evaluated in the individual countries. Cluster analysis enabled dividing the EU countries into three clusters, with the most significant differences observed in all clusters of the EU countries in government budget appropriations or outlays for R&D as % of total general government expenditure; by contrast, the least marked differences were observed in R&D expenditure in the government sector. Keywords: comparison, financial indicators, development, research, EU Countries JEL Classification: H59, O39 1 Introduction Research and development (R&D) play a key role in creating new knowledge, products and technological processes, which are a necessary prerequisite for a stable and sustainable economic growth within a society. The level and intensity of research, development and innovations is closely connected with economic development, dynamics of economic development, and the structure of generating added value and employment. Science, research, development and innovations are some of the numerous sources of economic growth and social welfare. From the viewpoint of macro-economy, the areas of research and development belong to the category of intensive (qualitative) sources of economic growth, i.e. they enable the increase in and improvement of the productivity based on the factors of production (Appelt, S. et. al.; Bojnec, Ferto, 2014). Currently, what mainly dominates the development of economies and societies is knowledge connected with research and development outputs. Significant economic indicators, such as economic growth, unemployment rate, or competitiveness, are, according to European Commission (2014); Majerová (2014); OECD (2013); Šoltés, Gavurová (2014); UNESCO-UIS (2014), actually dependent, to a marked extent, upon the outcomes of research and development. Research and development involves a host of activities that can be divided on the basis of several criteria or purposes. Among the most frequent criteria are who carries out the research, who the recipient of the outcome is and who provides the financing. Research and development have a definition in the OECD methodology. It is divided into basic research, applied research and experimental development. Basic research involves experimental or theoretical work that is primarily focused on gaining new knowledge about fundamental causes of phenomena and observable facts, without dealing with application of this knowledge. Applied research can be characterized as experimental and theoretical work to gain new knowledge, solely focused on specific, pre-defined objectives for further use. Experimental development is a systematic, creative work that leads to broadening knowledge, including knowledge about an individual, culture and society, and its application so as to discover new possibilites of using this knowledge. However, the OECD statistics fails to discern individual types of R&D in its data and indicators (e.g. finances, staff). The most recognized is R&D statistics by OECD, which evaluates R&D in member states with more than 100 defined indicators (OECD, 2014, 2015). This mainly concerns indicators of HR, outcome, innovations, international cooperation and R&D financing. Indicators related to R&D financing include, for instance Gross domestic expenditure on research and development (GERD), expenditure in the business enterprise sector (BERD), expenditure in the government sector (GOVERD), the higher education sector (HERD), and the private non-profit sector. One of the EU financial indicators is Government budget appropriations or outlays for R&D (GBAORD). It is another valuable indicator that measures government support for R&D using data from budgets. This essentially involves identifying all the budget items involving R&D and measuring or estimating their R&D content in terms of funding. These estimates are less accurate than performancebased data but as they are derived from the budget, they can be linked to policy through classification by objectives. Trends in R&D, and relations between R&D expenditure and other indicators in EU countries are supplied by research and studies already carried out (Bojnec, Ferto, 2014; OECD, 2015; UNESCO-UIS, 2014). Total expenditure on R&D (GERD) in % of GDP includes all investment- and non-investment expenditure allocated to R&D in the area of a given country over the observed period, regardless of the source of financing. International comparison mostly measures total expenditure on R&D (GERD) towards GDP. This financial relation is called “research and development intensity” and belongs to the group of elementary structural indicators evaluating the progress of Lisbon-treaty objective-fulfilments in individual EU countries (European Commission, 2010, 2014; Halásková, Halásková, 2015; OECD, 2013). Gross domestic expenditure on research and development (GERD) includes all R&D activities performed within the territory, whatever the origin of funding. This sector presents various 41

indicators that provide information on GERD as a whole, GERD performance structure and GERD financing structure. The total expenditure on R&D (GERD) includes expenditure on doing research and development in four sectors according to UNESCO-UIS (2014), namely: 1) The Government sector – Government intramural expenditures on research and development (GOVERD) include all government R&D activities by R&D performance structure and financing structure. The Government sector includes expenditures on the workplace of the Academy of Science, research facilities, libraries, archives, museums, and other institutions. 2) The Higher-education sector – Higher education expenditures on research and development (HERD) include R&D activities performed by the higher education sector. This sector includes public and state universities, teaching hospitals, and private universities, and expenditures on research and development associated with these institutions. 3) The Business-enterprise sector – Business enterprise expenditures on research and development (BERD) includes all R&D activities performed in Québec by enterprises. This sector provides information on R&D performance, R&D financing structure, distribution of enterprises conducting R&D, R&D activities in the information and communication technology (ICT) sector, industrial R&D tax support, R&D personnel and R&D activities by administrative region. 4) In addition, another sector involved is the Private non-profit sector, which comprises but a small part of conducted R&D and associated expenditure. To implement the strategy Europe 2020 in the field of R&D, areas to focus on are better conditions for financing research, development and innovations, where financial capabilities of the EU countries are an important prerequisite. In R&D, member states should begin investing 3% of their GDP (1% public resources, 2% resources from the private sector) by no later than 2020, which should generate 3.7 million new jobs and contribute to an annual increase of GDP by approximately 800 billion Euros by 2025 (European Commission, 2010; 2013). Based on a theoretical-empirical approach, this paper aims to evaluate the position of R&D in the EU countries and to compare selected R&D indicators. More closely, it deals with comparing R&D intensity, expenditure according to sectors of R&D application, and Government budget appropriations or outlays for R&D as % of total general government expenditure over the period 2009–2013. Selected financial R&D indicators (HERD, GOVERD, GBAORD as % of total general government expenditure) in EU countries are then compared by means of cluster analysis. The purpose of the performed analysis is to closer evaluate and highlight the differences in trends and approaches of national policies of the research and development (R&D) in various countries on the basis of selected financial indicators. 2 Material and Methods Analytical methods have been applied in compiling this paper, which are used in literature, in statistical data and in EU documents focused on R&D indicators. Comparative analysis and cluster analysis were used in the comparison of selected R&D indicators in EU countries. For the purposes of this paper, Eurostat data from the period 2009–2013 was used. The selected cluster comprises 28 EU countries, which were selected deliberately: (BE-Belgium, BG-Bulgaria, CZ-Czech Republic, DK-Denmark, DE-Germany, EE-Estonia, IE-Ireland, EL-Greece, ES-Spain, FR-France, HRCroatia, IT-Italy, CY-Cyprus, LV-Latvia, LT-Lithuania, LU-Luxembourg, HU-Hungary, MT-Malta, NL-Netherlands, AT-Austria, PL-Poland, PT-Portugal, RO-Romania, SI-Slovenia, SK-Slovakia, FI-Finland, SE-Sweden, UK-United Kingdom). In the EU countries, R&D indicators in financing are compared, i.e. total expenditure on R&D (GERD), and according to the sectors of R&D implementation (HERD, GOVERD, BERD, non-private profit sector) as % of total R&D expenditure and Government budget appropriations or outlays for R&D (GBAORD) as % of total general government expenditure as average of 2009–2013. 2.1 Model and Data For the sake of comparison of key R&D indicators in financing, R&D expenditure by the HERD sector as percentage of GDP (‘HERD’), expenditure R&D by the GOVERD sector as percentage of GDP (‘GOVERD’) and GBAORD as percentage of total general government expenditure (‘GBAORD’) have been selected in the member states. The comparison was carried out on the basis of average values over the period 2009–2013. These selected indicators are provided in Table 1.

EU member state

Expenditure R&D by HERD sector (% GDP)

Expenditure R&D by GOVERD sector (% GDP)

GBAORD as % of total expenditure

EU member state

Expenditure R&D by HERD sector (% GDP)

Expenditure R&D by GOVERD sector (% GDP)

GBAORD as % of total expenditure

Table 1 – Selected R&D financial indicators in EU member states as the mean value for 2009–2013

BE BG CZ DK DE EE IE EL

0.48 0.06 0.38 0.91 0.50 0.65 0.39 0.28

0.18 0.21 0.32 0.06 0.41 0.17 0.08 0.18

1.23 0.72 1.48 1.73 1.98 1.95 1.04 0.65

LT LU HU MT NL AT PL PT

0.47 0.17 0.23 0.24 0.65 0.70 0.27 0.54

0.18 0.28 0.20 0.05 0.21 0.14 0.25 0.10

1.06 1.40 0.84 0.57 1.60 1.55 0.81 2.02

42

ES FR HR IT CY LV

0.37 0.46 0.22 0.35 0.24 0.27

0.25 1.50 RO 0.10 0.31 1.44 SI 0.28 0.21 1.56 SK 0.21 0.17 1.16 FI 0.73 0.08 0.94 SE 0.87 0.15 0.40 UK 0.45 Source: Own calculation based on Eurostat (2015).

0.18 0.36 0.18 0,32 0.15 0.14

0.66 1.20 1.02 1.94 1.66 1.25

For the sake of finding similarities between the EU member states from this perspective, cluster analysis was used, as it represents a multi-dimensional statistical method used for classification of objects. It enables dividing observed units (EU28 countries in this case) into groups of similar units with other groups differing to the largest extent. For the purposes of this case study, the method of hierarchical cluster analysis was used, due to the low number of cases. Its advantage is graphic depiction of the process of clustering (see Garson, 2014), i.e. EU member states according to R&D indicators. Thus, hierarchical tree diagram (i.e. dendrogram) is widely applied for depiction of final distances between objects. The horizontal line of the dendrogram expresses distance between clusters. Clusters unite based on the shortest distance, measured either with the Euclidean distance, or another, using any method of counting distance, such as average linkage, single linkage and complete linkage. The vertical line can determine the required extent of object clustering. As Ward’s method was implemented to perform hierarchical cluster analysis, it was supposed to employ squared Euclidean distances as the initial distance between objects (Garson, 2014), i.e. the EU member states in this case. The advantage of Ward’s method is its tendency to create clusters of small size to minimize building of clusters with one object only (ibid). Box plot was employed as a method of graphical visualization of differences in the variance of R&D indicators by groups of the EU member states. Box plot, as one type of a diagram, divides continuous variables into quartiles, when 25% of elements have values below the lower quartile Q0,25 and 75% of elements have values lower than the upper quartile Q0,75. The middle "box" part of the diagram borders the 3rd quartile from the top, 1st quartile from the bottom, and between those is a line delimiting the mean. Size of the box is represented by the interquartile range. The lower whisker represents the values below the box, within the distance not exceeding 1.5-fold height of the box. End of the whisker corresponds with the lowest value of the cluster. Similarly, upper whisker corresponds with the highest value of the cluster. Besides whiskers (below and above them), points that correspond to outlays are depicted. However, graphic presentation (i.e. box plot) of differences among the indicators according to clusters does not provide reliable and comprehensive results to verify in subsequent research. Therefore, one factorial ANOVA was performed. Thus, analysis of variance – ANOVA – through the F-test, enables verifying differences of group mean values, which tests the hypothesis whether group mean values vary to an extent higher than accidental fluctuations. Generally, the Ftest in dispersion-analysis has the form of:

F

dispersion between group  averages . dispersion among units of the same group

To conduct ANOVA, all variables were split into two parts. Thus, the indicators were considered as dependent variables and clusters as independent variables. Several tests of assumptions were conducted before one factorial ANOVA was performed, according to Field (2005). Firstly, dependent variables in clusters were assessed for outlier by inspection of a boxplot for values greater than 1.5 box-lengths from the edge of the box. Although some outliers were revealed in the Cluster 1 within variables HERD and GOVERD (see Figure 5), it was resolved that violence of ANOVA assumptions was not materially affected considering the graphical presentation of variance of these variables. The second assumption was checked for the reason whether dependent variables are approximately normally distributed for each group of the independent variable, i.e. for clusters. Therefore, the Shapiro-Wilk W test (p > 005) was exploited as it is recommended for smaller sample sizes, i.e. 4 ≤ n ≤ 2000 (De Muth, 2014). The deviation from normality was not revealed except for the R&D expenditure by HERD sector as a percentage of GDP in the Cluster 1 due to presence of the two outliers. The third assumption concerning on homogeneity of variances (i.e., the variance is equal in each group of independent variable) was measured by Levene's test of equality of variances (p > 0.05). The homogeneity of variances was proved within all three dependent variables (p = 0.295, 0.241, 0.890). Furthermore, it could be concluded that sensitivity of ANOVA to different size of groups (i.e. 8, 9 and 11) was not violated regarding the third assumption as these differences among the clusters were relatively small. Using the groups formed by categories of the independent variable, i.e. clusters, unbalanced ANOVA design had to be applied as this design does not provide equal group sizes. Moreover, any specific hypotheses had not been set previously based on the results of hierarchical cluster analysis. Hence, post hoc comparison to evaluate pairwise differences between group means were conducted as it is noted in Field (2005). As a method for these comparisons the least-significant difference (LSD) post hoc test was selected. It provides the best results for three groups in case of unbalanced ANOVA design according to De Muth (2014) although it does not check the Type I error and as Field (2005, p. 340) states it is equivalent to performing multiple T-tests.

43

3 Results and Discussion 3.1 Comparison of selected R&D indicators in EU countries Total expenditure on R&D in % of GDP (R&D intensity) is about 2% of GDP in EU28 countries in the period 2009– 2013 on average. The highest R&D intensity is observed in Scandinavian countries (Finland 3.57%, Sweden 3.27% and Denmark 3%). In the EU, high R&D intensity, more than 2.5% of GDP, is reached in Germany (2.81%) and Austria (2.73%). The Czech Republic is found below the EU28 average, where R&D intensity reaches 1.58%, which is comparable to Ireland (1.59%). Comparison with EU member states shows that the Czech Republic shows not only the highest R&D intensity (GERD as % of GDP) among the new member states (except for Estonia and Slovenia), but also when compared to all south-European countries, such as Spain, Italy, Portugal or Greece. The lowest R&D intensity as % of GDP was found in Romania and Cyprus (0.45%) over the observed period. For more information about R&D intensity in the EU, see Figure 1. Figure 1 – Comparison of R&D-Intensity in EU member states (GERD) as the average value from the period 2009–2013 (% of GDP). Source: Authors calculation according Eurostat (2015). 4 3,5

3

3

1,58

1,5 1 0,5

2,81

2,73 2,3

2,21

2,5 2,14 2

3,57 3,27

0,58

1,84 1,59

1,98 1,68

1,85 1,31

0,67

1,4 1,23 0,87 0,78 0,72 0,6 0,45 1,23

1,46 0,78 0,45

0,68

BE BG CZ DK DE EE IE EL ES FR HR IT CY LV LT LU HU MT NL AT PL PT RO SI SK FI SE UK EU (28)

0

As numerous studies prove, apart from R&D intensity, which is influenced by a different volume and growth of GDP in each country, total expenditure on R&D in purchasing power parity (PPP) per capita is also used for international comparison (European Commission, 2014; UNESCO-UIS, 2014). When using this indicator in evaluation, Scandinavian countries (Finland and Sweden) have a dominating position again, along with countries outside the EU (Switzerland and the USA), with total R&D expenditure exceeding USD 1,300 PPP per capita. Despite the fact that expenditure in the Czech Republic on R&D per capita is 2 times higher than in Hungary, and 3 times higher than in Poland, it is approximately 2.5 times smaller than in Austria in Germany, and as much as 3 times small than in Denmark, Finland or Sweden, or countries outside the EU (Switzerland, the USA, Israel) when recalculated to PPP. For the results of the comparison of R&D expenditure in EU countries according to sectors over the period 2009–2013, see Figure 2. The comparison showed that in the majority of countries, expenditure on R&D is most significantly represented in the business-enterprise sector, and least significantly in the private non-profit sector in all countries. In the EU, it is difficult to define precisely what sort of research were the financial resources expended on. Resources which universities obtain from thematically defined R&D programs are registered in specific socio-economic areas. What most probably conforms to general research at universities in the Czech Republic is research financed from institutional university resources and programs aimed solely at universities. In analyses devoted to comparison of R&D some R&D areas form larger groups. Majority of R&D activities realized in both the government and the highereducation sector belong, from the viewpoint of R&D type, to basic research (Aristovnik, 2012; Cohen et al, 2002; Gulbrandsen, Kyvik, 2014; OECD, 2013). Based on R&D analyses and international comparisons, it is possible to say that the role and importance of public research institutions differs in most countries, not only within the EU but also the OECD (OECD, 2013, 2014, 2015).

44

Figure 2 – R&D expenditure comparison in EU countries by sector performance 2009–2013 (% of total expenditure). Source: Authors’ calculation according to Eurostat 2015).

35 68

52 55

67 67

54

52 70

16

45

30 26

64

39 35 28 21 28 28 25 30 18 24 22 10

33 53 67 64 60 69

54

53 45 54 13 19

38 47

43 70 69 62 63

72

33 35 26 35 37 22

31

21 27 27 23

12

BE BG CZ DK DE EE IE EL ES FR HR IT CY LV LT LU HU MT NL AT PL PT RO SI SK FI SE UK EU (28)

100 90 80 70 60 50 40 30 20 10 0

HERD

GOVERD

BERD

Private non- profit

Next R&D financial indicator compared in the EU countries in the period 2009–2013 was GBAORD as % of total general government expenditure. Results show quite marked differences in the individual countries. GBAORD in the EU28 is approximately 1.47% of total general government expenditure on R&D. The highest national budgetary expenditure and subsidies on R&D over the observed period as % of total general government expenditure on R&D is found in Portugal, Germany, Estonia and Finland. GBAORD of the Czech Republic, France and Spain is found around the EU28 mean value. For a more specific comparison of Government budget appropriations or outlays for R&D (GBAORD) in EU countries, see Figure 3. Figure 3 – GBAORD comparison in the EU Countries (as % of total general government expenditure) average, years 2009–2013. Source: Authors’ calculation according to Eurostat (2015). 2,5 2,02

1,981,95 1,73 1,48

2

1,5 1,441,56

1,5 1,23 1,04 1 0,5

0,72

1,4

1,16 0,94

1,66 1,47 1,25

1,2

1,06

1,02 0,84

0,65

1,94

1,6 1,55

0,57

0,81

0,66

0,4

BE BG CZ DK DE EE IE EL ES FR HR IT CY LV LT LU HU MT NL AT PL PT RO SI SK FI SE UK EU (28)

0

3.2 Comparison of R&D indicators in EU countries with the use of cluster analysis Results of the hierarchical cluster analysis divided the EU member states into three clusters based on their internal similarity. The decisive factor determining the number of clusters from the dendrogram was the value of five on the horizontal line, i.e. rescaled distance cluster combined (see Figure 4). Figure 4 – Dendrogram of R&D financial indicators of EU member states (2009–2013). Source: Own elaboration based on Eurostat (2015).

45

For the sake of clarity of the cluster-analysis results, followed by exploration of box plot and one-factorial ANOVA, the three clusters have been ordered by their mean value in HERD and GBAORD variables, as stated in Table 2. It shows that 28 EU member states were unevenly distributed into clusters of 9, 11 and 8 members in the first, second and third cluster, respectively. Table 2 – Clusters of EU member states by R&D financial indicators (2009–2013) Cluster 1 Cluster 2 Cluster 3 Belgium, Croatia, Czech Republic, Bulgaria, Cyprus, Greece, Latvia, Austria, Denmark, Estonia, France, Ireland, Italy, Lithuania, Malta, Hungary, Poland, Romania, Finland, Germany, Netherlands, Luxembourg, Slovenia, Spain, Slovakia Portugal, Sweden. United Kingdom Source: Own elaboration based on Eurostat (2015).

Results of the cluster analysis in EU member states are further graphically visualised by means of a box plot (see Figure 5). The figure shows the most apparent differences in mean values in the EU countries are in GBAORD (first cluster 0.70, second cluster 1.20 and third cluster 1.80). In the first cluster, the largest share of national budget expenditures and subsidies on R&D is found in Croatia (1.56%) and the lowest in Ireland (1.04%); in the second cluster the largest share is found in Slovakia (1.02%) and the lowest in Latvia (0.40%); in the third cluster, the highest GBAORD value is found in Portugal (2.02%) and the lowest in Austria (1.55%). By contrast, the least marked differences between the individual clusters of EU countries is found in mean values of R&D expenditures in the government sector (GOVERD), i.e. 0.20%. In the first cluster, outlays in R&D expenditure in the higher-education sector (HERD) of Bulgaria (0.06%) and Romania (0.10%) were found. Another outlaying value in the first cluster is found in Malta in R&D expenditure in the government sector (0.10%). Figure 5 – Box plot of R&D financial indicators by clusters of EU member states (2009–2013). Source: Own elaboration based on Eurostat (2015).

The explanation of EU-member-states division into the above-mentioned groups reflects on their GDP per capita, focus on their national R&D policies, their extent of expenditures on and investments in R&D and the impact of the financial crisis after 2008. In this respect, the first cluster, more precisely the first group of countries, comprises countries with the lowest GDP levels per capita in the EU, i.e. Bulgaria and Romania. There are also represented countries struck significantly by the crisis, namely Cyprus and Greece, which is reflected on in expenditure on and investments in R&D. Some countries lack national metropolises whose long-term activity would create a suitable background for R&D development, i.e. Cyprus and Malta. In other countries, science-research activities are influenced by an outflow of qualified workers abroad due to higher salaries. The second group of EU member states comprises Belgium, Croatia, Czech Republic, France, Ireland, Italy, Lithuania, Luxembourg, Slovenia, Spain and United Kingdom. These are countries with quite high budgetary expenditures and subsidies on R&D. Most of these countries show high expenditure on R&D in the higher-education sector (HERD) and low expenditure on R&D in the government sector (GOVERD). The exception are Croatia, Luxembourg and Slovenia, where the share of expenditure on R&D in the government and the higher-education sector is reverse, which is also corroborated by other analyses and studies (Halásková, Halásková, 2015; Lee, 2009). The last group is composed mainly by the EU member states that have been investing considerably in R&D for a long time, in particular with respect to the quality of education and advanced technologies, employment in technology industry and R&D innovations. Due to its linguistic and spatial closeness to Finland, Estonia can serve as an example of diffusion of innovations in IT. Surprisingly, Portugal shows the highest rate of budgetary expenditure and subsidies on R&D from total expenditure in this cluster. The last part of the evaluation of EU member-state-groups based on R&D indicators is discovery of significant differences among the individual clusters (Table 3). 46

Table 3 – Post hoc LSD test for R&D financial indicators by clusters of EU member states (2009–2013) 95% Confidence interval Mean Dependent variable Cluster (I) Cluster (J) Sig. difference (I-J) Lower bound Upper bound 1 2 –0.154 0.004 –0.256 –0.053 R&D expenditure by HERD 1 3 –0.482 0.000 –0.592 –0.372 sector (% GDP) 2 3 –0.328 0.000 –0.433 –0.223 1 2 –0.567 0.000 –0.741 –0.394 GBAORD as a % of total 1 3 –1.069 0.000 –1.256 –0.882 expenditure 2 3 –0.502 0.000 –0.681 –0.323 Source: Own elaboration based on Eurostat (2015).

F-test, used in one-factorial ANOVA, revealed the following differences in HERD variables (F = 42.447; p < 0.01) and GBAORD (F = 69.656; p 0.05). As a result, it is possible to claim that insufficient details were found about the mean differences between groups of the EU member states. Analysed values thus failed to support the disproof of the null hypotheses about the concordance of averages. It can be deduced that GOVERD levels are similar in the member states, despite different economic and social conditions and the impact of the financial crisis. A more detailed view on the differences between the mean values in HERD and GBOARD indicators through the posthoc LSD test shows significant differences between all groups of the EU member states (p < 0.01) (see table 3). Differences in R&D expenditures are thus seen in the higher education sector, when countries, especially from the third cluster, make use of their emphasis on education, regarded as the key aspect of further development. On aggregate, subsidies and budgetary expenditures on R&D (GBAORD) show the most marked differences in mean values of groups of the EU countries. In this context, it is possible to confirm disparities among the individual members, which reflect on not only their innovative performance but also their competitiveness. These differences may also result in a delay of convergence targets of the EU cohesion policy. 4 Conclusion Total expenditure on research and development is one indicator evaluating economic competitiveness. The most recognized is R&D statistics by the OECD, which evaluates R&D in the EU member states with defined indicators. The comparison of selected financial R&D indicators showed that R&D intensity in EU28 is approximately 2% of GDP in the period 2009–2013. The highest R&D intensity is observed in Scandinavian countries (Finland, Sweden and Denmark). Based on the comparison of total R&D expenditure according to sectors of application, it was ascertained that in the majority of EU countries, the business-enterprise sector expends the most resources on R&D, as opposed to the private non-profit sector, which expends the least. Also, the highest budgetary expenditures and subsidies on research (GBAORD as % of total general government expenditure) over the period 2009–2013 in the EU Countries (28) was observed in Portugal, Germany, Estonia and Finland. Different position of R&D in EU countries was also confirmed with the method of hierarchical cluster analysis, and dispersion analysis. The results enabled dividing EU countries according to financial R&D indicators into three clusters based on internal similarity, which showed the largest differences in all clusters of EU countries in government budget appropriations or outlays for R&D (GBAORD); the smallest differences were ascertained in R&D expenditures in the government sector. The results of the comparison of R&D financial indicators in various countries has shown that many EU countries still do not meet the requirements established for the research and development under the „Strategy Europe 2020“. Acknowledgements This paper was supported within Operational Programme Education for Competitiveness (Project No. CZ.1.07/2.3.00/20.0296). References [1] APPELT, S. et al. (2015). Which Factors Influence the International Mobility of Research Scientists? OECD Science, Technology and Industry. Working Papers No 2015/02. Paris: OECD Publishing. [2] ARISTOVNIK, A. (2012). The relative efficiency of education and R&D expenditures in the new EU member states. Journal of Business Economics and Management, Vol. 13, No. 5, pp. 832–848. [3] BOJNEC, Š. and FERTO, I. (2014). Research and development spending and Export performance by the Technological Intensity of Products. Ekonomický časopis / Journal of Economic, Vol. 62, No. 10, pp. 1065–1080. [4] COHEN, W. M., NELSON, R. R. and WALSH, J. P. (2002). Links and Impacts: The Influence of Public Research on Industrial R&D. Management Science. Vol. 48, No. 1, pp. 1–23. [5] DE MUTH, J. E. (2014). Basic Statistics and Pharmaceutical Statistical Applications. Boca Raton, FL: CRC Press. [6] European Commission (2010). Europe 2020. European strategy for smart, sustainable and inclusive growth. [online]. [cit.2015-05-25]. Available from 47

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http://ec.europa.eu/eu2020/pdf/COMPLET%20EN%20BARROSO%20%20%20007%20%20Europe%202020%20-%20EN%20version.pdf European Commission (2013). The Effect of Innovative SMEs' Growth to the Structural Renewal of the EU Economy. A projection to the year 2020. Luxembourg: Office of the European Union. European Commission (2014). Innovation Union report 2013 Competitiveness. Luxembourg: Publications Office of the European Union. Eurostat (2015). Statistic database. Total intramural R&D Expenditure (GERD) by sectors of performance. [online]. [cit.2015-04-23]. Available from http://ec.europa.eu/eurostat/tgm/table.do?tab=table&init=1&language=en&pcode=tsc00001&plugin=1 FIELD, A. P. (2005). Discovering Statistics using SPSS. London: Sage Publications. GARSON, D. G. (2014). Cluster Analysis. Asheboro, NC: Statistical Associates Publishers. GULBRANDSEN, M. and KYVIK, S. (2010). Are the concepts basic research, applied research and experimental development still useful? An empirical investigation among Norwegian academics. Science and Public Policy. Vol. 37, No. 5, pp 343–353. HALÁSKOVÁ, M. and HALÁSKOVÁ, R. (2015). Research and Development Expenditure Assessment based on Selected Indicators in the EU Countries. In Proceedings of the 7th International Scientific Conference Finance and the Performance of Firms in Science, Education and Practice. pp. 342–357. LEE, H. Y., PARK, Y. T. and CHOI, H. (2009). Comparative evaluation of performance of national R&D programs with heterogeneous objectives: A DEA approach. European Journal of Operational Research. Vol. 196, No. 3, pp. 847–855. MAJEROVÁ, I. (2014). Export Performance and Transformational Performance as Measurable Indicators of Macroeconomic Competitiveness Regarding Selected EU Countries and Switzerland. In Proceedings of the 2th International Conference on European Integration 2014. pp. 439–447. OECD (2013). OECD Science, Technology and Industry Scoreboard 2013. OECD: OECD Publishing. [online]. [cit.2015-05-25]. Available from: http://dx.doi.org/10.1787/sti_scoreboard-2013-en OECD (2014). Research and Development Statistics: R-D Expenditure by Sector of Performance and Type of RD, OECD Science, Technology and R&D Statistics (database). [online]. [cit.2015-05-31]. Available from http://dx.doi.org/10.1787/data-00193-en OECD (2015). Main Science and Technology Indicators. [online]. [cit.2015-05-31]. Available from http://stats.oecd.org/Index.aspx?DataSetCode=MSTI_PUB ŠOLTÉS, V. and GAVUROVá, B. (2014). Innovation policy as the main accelerator of increasing the competitiveness of small and medium-sized enterprises in Slovakia. Procedia Economics and Finance. Vol. 15 (2014), pp. 1478 - 1485. UNESCO-UIS (2014). Guide to Conducting an R&D Survey: For countries starting to measure research and experimental development. Montreal, Canada: UNESCO Institute for Statistics.

Contact information doc. Ing. Martina Halásková, Ph.D. VŠB - Technical University of Ostrava Sokolská třída 33, 701 21 Ostrava 1 Czech Republic [email protected] RNDr. Pavel Bednář, Ph.D. Tomas Bata University in Zlín Mostní 5139, 760 01 Zlín Czech Republic [email protected]

48

Incentives to Our Generosity Marie Hladká Abstract Motivation represents a foundation corestone on which analyses in a number of the humanities and social sciences are built. For a long time, economists have seen motivation as connected with the act of giving, trying to interpret it in the context of the neoclassical economics assumptions. On the basis of representative theoretical models, Ziemek (2003) distinguishes three basic categories of motives underlying the act of giving: altruism, egoism and investment. They also form the basis of this paper. The objective of this paper is to find answers to the question what mainly motivates the Czech population in their decisions to make a donation and whether there is any interdependence among such motives. I also ask what the relationship is between the determining motives and the rate or frequency of donating. The donation models that I analyse and use as the basis of my research are nowadays considered being the principal or at least interesting donation models commonly taken into account by economists in their work. I have only focused on microeconomics models to make the text clearly targeted. Key words: Altruism, charitable giving, motive JEL Classification: C91, D01, D64 1 Introduction Issues related to charitable donating have been researched not only in the behavioural sciences, psychology or economics; experts in the fields of marketing, fundraising and political affairs also deal with them. Non-profit studies analyse donorship especially as regards its potential to increase the share of private resources in incomes of non-profit organisations. Therefore, many authors (Schervish, 1997; Sargeant, 1999; Bekkers, Wiepking, 2010, Gittell, Tebaldi, 2006; Marx, Carter, 2014; Andreoni, Payne, 2011; and other) still ask the question: what are the variables that influence donors’ behaviour both positively within the sense of its volume or frequency and negatively within the sense of its restriction or absence? The current social sciences literature that identifies/defines factors with an influence on donating is considerably extensive. Of course, its approaches and methodologies depend on a specific scientific discipline, the nature of an applied empirical investigation and also on the respective motivation agent being analysed. Most studies deal only with a specific variable. The authors (Schervish, 1997; Bekkers, Wiepking, 2010 and others) who attempt to provide a complex picture of motives that encourage individuals to make donations are not numerous. I divided the variables impacting the process of the donor’s decision-making into internal and external ones. It is a division that is neglected by some researches (Lloyd 2004; Marx, Carter, 2014 and others) who interconnect individual variables, creating an unclear picture of the motives influencing the donor’s decisions. However, in my opinion it is necessary to differentiate between internal variables, which arise from the underneath of individual people and create their nature and personality, and external variables, which are independent of specific individuals although they may influence them. I term the internal variables as motives for donating, and the external variables as determinants. All these variables influence the process of the donor’s behaviour. In this paper, I only pay attention to one group of variables – motives. The goal of this paper is to find answers to the question what mainly motivates the Czech population in their decisions to make a donation and whether there is any interdependence among such motives. I also ask what the relationship is between the determining motives and the rate or frequency of donating. I present my own categorization of the motives that may influence the individual’s decision to make a donation. These motives are subsequently analysed with the aim to find out how important they are in the Czech population, to evaluate mutual relationships (strength) between the given motives, and to determine the extent to which these motives influence the value of a provided donation or the frequency of donating. This is important not only as regards the theory of the donor’s behaviour but also as regards potential impacts on the practice of recruiting and retaining new donors. 1.1 Theoretical Starting Points of the Research The starting points for the classification of the motives having an influence on donating and subsequent empirical tests are microeconomics models that may be used to interpret donating in accordance with the microeconomics apparatus. These models work with the level of utility gained by the donor, specifically considering three basic types of benefits. Donating is based on various obvious or hidden motives and brings the individual various benefits. The following table classifies three basic types of benefits of an act of donating for the donor.

49

Table 1 - Potential benefits from an act of donating

Benefit Altruistic benefit Personal benefit Exchange value benefit

Benefit source The benefit is based on an improved condition of a donee. The donor is interested in increasing other people’s benefits. The donor obtains his or her own benefit from an act of donating (warm-glow, social integration, etc.) In exchange for his or her donation, the donor obtains benefits such as experience, influence, information, etc.

Source: Author, adapted according to Ziemek (2003).

Economists consider the above specified sources of utility/benefits to be the key ones in explaining the donor’s behaviour. We can use the definitions of these three benefits as the basis on which we can build four microeconomics models depicting the process of the donor’s decision-making. The given models and their basic motives are shown in the following table. Table 2 - Microeconomics models explaining an act of donating

Model Public Goods Model

Benefit Altruistic benefit

Private Consumption Model

Personal benefit

Investment Model

Exchange value benefit

Impure Altruism Model

Altruistic/personal benefit

General motive To increase the offer of public goods To be pleased by an act of donating, the “warm-glow” utility To gain experience, knowledge and contacts on the labour market Combination of the first and the second model

Source: Author, adapted according to Ziemek (2003).

Classification of Motives for the Use of Empirical Testing On the basis of theories formulated using the public goods model, private consumption model, investment model, and impure altruism model (Ziemek, 2003), I have identified three basic groups of motives underlying donors’ decisionmaking. They are altruism, egoism and investment. For the use of my own empirical testing, I herein present my own identification and classification (based on the previous theoretical economic models) of the most important variables that we can come across in various researches. Because I do not know all the existing internal variables that enter the process of the donor’s decision-making, I work only with those that have been identified in the most significant studies. They include first of all Arrow (1974), Collard (1978), Batson (1987), Andreoni (1989), Andreoni (1990), Schervish (1997), Sargeant (1999), Kolm (2000), Bennett (2003), Kottasz (2004), Lloyd (2004), Smith (2005), Ranganathan, Henley (2008), Bekkers, Wiepking (2010), and Marx, Carter (2014). Outcomes of the research survey will be presented and the following motives analysed: with respect to altruism, they included empathy, affection, fellow feeling, compassion, solidarity, mercy, pity, respect, gratefulness, social rules, believing in justice, conviction, social responsibility, moral duty, and religious obligation. With respect to egoism, they included profit/remuneration opportunity, desire for power, self-centredness, recognition, political influence, the feeling of irreplaceability, fear, concerns, warm-glow, reciprocity, conscience, desire to sacrifice oneself, reputation, doing a good turn to society, the need to help, the need of belonging. In the case of investment, they included personal contacts, skills, socio-economic status and job opportunities. 2 Material and Methods The number of researches that have been conducted about private donations to NGOs in the Czech Republic is very limited (for example Frič, 2001; Hladká, Šinkyříková, 2009; Řežuchová, 2011). I therefore executed my own empirical testing that focused on all factors that could influence donating, i.e. internal and external factors. The objective of the research was to identify factors that have an influence on decisions to donate financial means to non-profit organisations taken by individuals in the Czech Republic, and to analyse these factors as regards their mutual relationships. At it has been stated herein above, this paper however focuses on presenting the outcomes that only capture an influence of internal variables, i.e. motives. The research questions concerning motives were worded as follows: RQ 1: What motivates individuals in the Czech Republic to provide a donation? (significance of motives) RQ 2: What is the interdependence of these motives? (strength of the relationship between the motives) RQ 3: What is the relationship between the individual’s motives and the amount of a provided donation? RQ 4: What is the relationship between the individual’s motives and the frequency of donating? RQ 5: Influence some socio-demographic groups the motives? The data were collected through a questionnaire survey. During the survey (all data referred to 2013) I had to cope with some restraints that individual respondents were also acquainted with. There were three types of restraints on the research. The factors influencing donations in the Czech Republic related only to the following donations: 50

1.

Provided to non-governmental non-profit organisations: respondents were acquainted with the specification of the non-governmental non-profit organisation, its definition and examples of the typical legal forms that these organisations acquire. 2. Individual: the research was related only to donations made by individuals in a society. Corporate donations were not included in the research. 3. Monetary: respondents considered only donations of money, not donations of free time, in-kind donations (e.g. clothes), donations of their skills, etc. Interviewer: The primary source of data was the questionnaire survey. It was done by a trained team supervised and methodically supported by the authors of this paper. Respondents: The personal interview survey was carried out in March and April 2014; a total of 442 completed questionnaires were obtained. Interviewers approached respondents with a request to fill in a questionnaire. The respondents filled in the questionnaire on their own, having instructions available how to proceed. The basic set consisted of the population over the age of 18 living on the territory of the Czech Republic. Furthermore, the author worked with available (random) sampling, when people who are “at hand” are selected to comprise a set (sample) of respondents. On a small and randomly selected sample, the author tries to determine what features may have units that should be examined.Conclusions resulting from the analysis are therefore related only to this selective set. The data collection phase was followed by an analysis of the collected data. Some questions had to be first classified according to the selected categories and marked with codes. The obtained data were analysed by means of mathematical-statistical methods that are commonly used in similar cases. The following were specifically used for the analysis:  Indicators for the descriptive analysis/statistics: distribution; absolute, relative, and cumulative frequency; measures of central tendency (the mean, median, mode), standard deviation, standard error of the mean.  Functions for the correlation analysis: the Pearson correlation coefficient (establishes how strong is a relationship between variables), the ANOVA method based on the F-test (the analyses of dispersion was used for its ability to evaluate the relation among a quantitative variable and one or more qualitative variables). The assessment of the correlation coefficient value and the effect (influence) arising from it was as follows: r ϵ (0.1; 0.3) small, r ϵ (0.3; 0.5) medium, r ≥0.5 strong effect/strength of a relationship. The method ANOVA is based on assessment of relationships between the variances of the sample sizes being compared – the equality of mean values testing is converted to the equality of two variances testing (F-test). The goal towards which the application of the ANOVA method is directed is either to accept the H0 null hypothesis or to reject H0 (on a selected level of significance). In this perspective, it is a common test of statistical hypotheses. The calculation method was therefore the same as the method used for the testing of classical hypotheses. The basic statistics used in the analysis of variance is generally the F testing criterion, which is used to test the hypothesis whether mean values in the groups determined by an acting factor (or factors) differ more than the mean values influenced by the action of natural variability (the accidental fluctuation). 3 Results and Discussion The following section propounds results according to the set of research questions; submit answers and topics to muse. What motivates individuals in the Czech Republic to give money to NGO‘s? Are these motives depending on each other? In analysis of donors and non-donors behavior there were found out motives which determined (greater or lesser weight) the decision making process. The results were analyzed first for respondents who gave in 2013 the gift (the donors), but also separately for respondents who did not provide a gift (non-donors). The following table presents the results of mutual comparison, the difference between the percentages of individual responses acquired donors and nondonors one hand, but also mutual comparison of average values marked on the scale. A value of 1 was assigned to response "completely agree" value 2 to response "rather agree", value 3 to response "do not know" value 4 to response "rather disagree", value 5 to response "completely disagree". The lower the average value, the more respondents were identified with a given statement, the higher the average value, the less respondents were identified with a given statement. The first half of the table through difference of the percentual points between donors and non-donors clearly shows that donors identify themselves (in the case of altruistic motives) or don not identify themselves (in the case of some egoistic or investment motives) with the given statements to a greater extent than non-donors. It is apparently from the positive differences exceeding ten or twenty percentual points. The most controversial in declaring attitudes between donors and non-donors appeared indicator no. 15 (I consider giving money as moral duty.). Donors identified unambiguously with the statement (they answered positivity), but non-donors did not identify unambiguously with the statement (they answered negatively). Interesting findings also brought indicator no. 6 (I give money to those whom I am grateful for something.). Although it is an altruistic motive, non-donors identified with him, while donors answered rather negatively (they do not identify with him). An important finding is the further fact that among non-donors do not conscience weigh (If I do not help, I feel guilty.). The question was answered by more than 10 % non-donors than donors by label "completely disagree". Non-donors do not agree (in terms of percentage representation) much more 51

than donors with the motives of moral obligation also or religious duty. For selfish motives play greater role among donors than non-donors motives such as feeling good, or the desire for self-sacrifice. The second part of the table compares the average values which were chosen on the scale from the respondent. They submit similar results as the first part of the table, there are present from another point of view. Light boxes highlight the higher average value, dark boxes indicates a lower average value. The same average values achieve donors and nondonors in two motives: appreciation and acquisition of skills. The most significant difference between average values reaches the motive of moral obligation; its size is one percentage point. The most significant impact among donors have these motives: feeling good (average 1.7), moral obligation (1.8), the desire for self-sacrifice (1.9), conviction (1.9). The donors identify at least with the motives: the desire for power, profit opportunities and rewards, reciprocity. Among the motives, whose influence could not the donors identify belong a faith in justice (injustice suppression) or social responsibility of entrepreneurs and companies. Donors do not completely identify with any investment motives. The most significant impact among non-donors have these motives: moral obligation (2.2), the desire for selfsacrifice (2.3), conviction (2.4), feeling good (2,4). These are therefore quite identical motives as of donors; the degree of their influence is lower. At least the non-donors identify with the motives: religious duty, desire for power, awards. By non-donors we can capture much more unanswered questions. Non-donors do not have such a clear view of what influence their attitudes and opinions on giving. In the last year they did not provide a gift that is way they do not think about the act of giving as often as donors. Causality could also be reversed. Seeing that non-donors have not a clear view on what should stay in the background of the act of giving, they are less determined to give money.

NONDONOR

X'

modu s

GENERALLY

medi an

DONOR

Completely disagree

Rather disagree

I do not know

Rather agree

Completely agree

Table 3 - A comparison of donors and non-donors motives

SD

SE

2,56

2

2

1,20

0,06

2,9

2,61

2

2

1,19

0,06

2,2

2,5

2,36

2

2

1,11

0,05

2,2

2,7

2,46

2

2

1,17

0,06

-6,0

2,0

2,5

2,26

2

2

1,16

0,06

10,1

9,8

3,4

2,8

3,08

3

2

1,36

0,07

-4,6

-1,8

0,3

3,9

4,0

3,93

4

4

1,01

0,05

5,7

-5,0

-6,5

-6,1

2,0

2,6

2,30

2

2

1,07

0,05

5,8

4,6

-1,7

1,3

-7,9

3,1

3,4

3,27

3

4

1,19

0,06

10.

16,6

1,5

-9,8

-2,3

-4,2

1,9

2,4

2,18

2

2

1,05

0,05

11.

7,9

13,2

-7,4

-6,5

-6,0

2,2

2,6

2,41

2

2

1,07

0,05

12.

-4,7

-9,1

-0,2

10,0

5,7

3,1

2,7

2,94

3

2

1,21

0,06

13.

17,8

13,5

-11,0

-14,3

-4,7

2,1

2,9

2,52

2

2

1,11

0,05

14.

18,8

-5,9

-2,3

-5,1

-3,8

1,8

2,2

2,03

2

2

1,02

0,05

15.

21,8

16,2

-8,9

-17,3

-11,0

2,4

3,4

2,92

3

2

1,29

0,06

religious duty profit opportunities, rewards desire for power

16.

6,6

5,8

-2,6

0,5

-10,0

4,1

4,5

4,29

5

5

1,15

0,06

17.

2,4

-6,0

-6,3

-11,2

21,5

4,5

4,2

4,35

5

5

1,01

0,05

18.

0,5

-4,3

-2,7

-6,5

14,3

4,6

4,4

4,50

5

5

0,88

0,04

self-centeredness

19.

-6,4

-14,3

0,2

6,5

14,9

3,6

2,9

3,23

4

4

1,36

0,06

awards

20.

0,5

2,6

-3,1

-9,8

11,6

4,4

4,4

4,41

5

5

0,91

0,04

political influence feeling of irreplaceable fear, worry

21.

-1,7

-0,5

-6,0

-3,7

13,7

4,2

4,0

4,09

5

5

1,02

0,05

22.

2,4

0,8

-6,3

-6,3

12,0

4,2

4,1

4,14

4

5

1,01

0,05

23.

8,1

-5,2

-0,6

0,9

-1,9

2,8

2,9

2,86

3

2

1,26

0,06

good feeling (warmglow)

24.

21,6

4,1

-11,1

-7,2

-6,5

1,7

2,4

2,06

2

2

1,07

0,05

25.

7,8

13,1

-5,0

-5,0

-7,5

2,3

2,8

2,57

2

2

1,22

0,06

reciprocity

26.

-0,7

-0,6

-7,5

-9,9

19,5

4,4

4,1

4,27

5

5

1,06

0,05

conscience desire for selfsacrifice reputation

27.

-0,7

0,8

9,1

2,4

-10,7

3,8

4,0

3,91

4

5

1,14

0,05

28.

17,3

-3,7

-3,4

-6,2

-2,6

1,9

2,3

2,13

2

2

1,02

0,05

empathy

1.

Difference between the percentage representation of donors and non-donors 14,3 0,3 -12,6 -0,8 0,1

affection, sympathy compassion, solidarity mercy, pity

2.

16,3

2,7

-5,2

-3,2

-9,3

2,3

3.

12,2

0,0

-5,4

-4,0

-1,1

4.

11,3

5,3

-5,3

-4,0

-5,5

esteem

5.

21,3

-0,6

-7,8

-6,1

appreciation

6.

-2,7

-18,3

2,3

social rules

7.

1,9

5,5

8.

14,5

9.

Variable

faith in justice conviction

social responsibility moral obligation

revenge to society need to help need to belong somewhere personal contacts

The average value on the scale 2,4 2,7

29.

0,6

2,7

-7,6

-3,0

9,0

3,7

3,6

3,70

4

4

1,10

0,05

30.

-2,5

-4,3

-1,7

1,9

7,9

4,2

3,9

4,05

4

5

1,13

0,05

31.

2,6

7,9

0,9

-2,5

-6,3

2,8

3,1

2,99

3

2

1,30

0,06

32.

6,7

-0,4

2,8

-5,3

-2,1

2,6

2,8

2,74

2

2

1,17

0,06

33.

3,3

2,8

-2,4

5,3

-8,2

3,2

3,4

3,27

3

4

1,27

0,06

34.

2,9

-2,2

-7,3

-9,3

16,8

4,2

4,0

4,14

5

5

1,08

0,05

52

skills

35.

-1,3

1,5

3,6

-2,5

0,0

4,1

4,1

4,07

4

5

1,03

0,05

socioeconomic status

36.

1,5

-0,9

-5,3

-3,0

9,0

4,1

4,0

4,05

4

5

1,05

0,05

jobs opportunities

37.

0,1

-1,0

-9,6

-9,7

22,9

4,4

4,1

4,25

5

5

1,00

0,05

Source: Author.

Table presents the results of descriptive statistics for individual motives. It is a calculation of the average / mean value (X '), median, modus, standard deviation (SD) and standard error of the mean (SE). The interdependence between the motives was examined on the basis of Pearson's correlation coefficient (r). Evaluation of the correlation coefficient and the resulting effect/ tightness relationship was as follows: small r ϵ (0,1; 0,3), medium r ϵ (0,3; 0,5), high effect r ≥0,5. It was found high interdependence between investment and egoistic motives. Overview of dependence including the interdependence value provides the following table. Table 4 - The distribution of motives pairs with high interdependence value into three basic groups of motives Altruism Egoism

Investment

Altruism x .505 .502

x

Egoism

Investment

.595 .634 .569 .541 .508 .503 Source: Author.

.586 .554 .504

Among altruistic motives were represented moral obligation (once) empathy (once) social responsibility (once) between egoistic motives were represented profit opportunities (four times) awards (three times), fear and worry (once). High statistical dependence can we find among investment motives: personal contacts (three times), socioeconomic status (four times), jobs opportunities (four times). Italics values are indicated by pairs of motives which have reached similar mean values of identifying with them, dark printing value present pairs of motives identified from respondents at least. The greatest degree of correlation can be found between the motives that have a minimal impact on individual giving. Medium dependence between motives is represented in the results greatly. In summary, these motives belonged largely among altruistic motives. Other pairs are the pairs where one of the motives is a good feeling (warm-glow). The low level of dependence is evident for example in pairs where one of the motives is a religious duty, revenge to society, need to help or need to belong somewhere. How can we describe the relationship between individual motives and the amount of giving? How can we describe the relationship between individual motives and frequency of giving? The results and findings present dependence of motives on the amount or frequency of the gift. The sample size was constructed from 214 donors, the average value of the gift was in the amount of 4 418 CZK (data exclusive of respondents who did not indicate the amount of their gift). These amount of gift is much lower than the average gift mentioned in the tax returns for 2012, which amounted to over 13 000 CZK (Financial report, 2014). The results of comparison may be due to the fact that in the survey failed to include also irregular donors whose donate a large amount to NGO‘s, and they administer these gifts in tax returns. It is likely that in the research were integrated rather smaller donors, even though they may belong to the regular or selfless donors (their frequency and willingness to donate is obvious). Donors provided the highest average amounts of gifts are distinct by their identification with motives: religious duty, profit opportunities and rewards, reciprocity, reputation, personal contacts, socioeconomic status and employment opportunities. The results thus show that the most generous donors are motivated more likely by selfish or investment motives. In comparison with the average level of identification with a given motives from all donors, not just from the most generous, these are motives with much lower rate of identification. Although the willingness of most donors is affected by altruistic motives, this is not valid for the most generous donors. In connection with the frequency of the giving we can denote respondents as repetitive donors, but not regular donors. Respondents who donated money to NGOs were asked in the questionnaire how often they provided the gift. Options offered (1) only once (2) number of time (3) regularly. For the second and third options, respondents could specify how many times they provided the gift, or how regularly they provided the gift. The answers showed that more than half of the respondents (55 %) gave a gift several times (most of them said 2x, 3x or 4x), more than a third (35 %) gave a gift only once. The remaining 10 % of respondents regularly provides gift (usually every month, i.e. 12x). Most frequently offer gift donors who identify with the motives: social rules, profit opportunities and rewards, political influence and need to help, or do not identify with the motives: empathy, compassion and solidarity or beliefs. Similarly, as was presented in the analysis of the gift amount, most frequently donors are affect egoistic motives. These donors are distinguished by her little identification with some significant (in terms of willingness to donate money) altruistic motives. 53

Influence some socio-demographic groups the motives? Interdependence was tested by one-factor ANOVA. Within three socio-demographic groups (economic, demographic, social) have a statistically significant effect on the motive most often following indicators: age, socio-economic profile, gender, marital status and religion. All indicators belong to the group demographic variables. It may be noted that among the motives that are most significantly affected by selected socio-demographic determinants we can include: moral obligation, affection, social responsibility, self-centered, faith in justice, religious duty, reputation, personal contacts. All these motives are influenced by at least three socio-demographic determinants. Gradually I present the particular socio-demographic determinants in conjunction with motives that significantly affect them. Affordability - net monthly income of the respondent significantly affect motives: moral duty, self-centredness and personal contacts. Affordability - net monthly household income was significantly influenced by motives of social responsibility and selfsacrifice. Age significantly affects motives: affection, compassion and solidarity, gratitude, social rules, faith in justice, social responsibility, moral obligation, a religious obligation, the opportunity to profit, reputation, need to help, personal contacts and job opportunities. Gender significantly affects motives: affection, compassion and solidarity, compassion, respect, faith in justice, conviction, appreciation, fear, feeling good, reciprocity, socio-economic status. Education significantly affects motives: social rules and egocentrism. Socio-economic profile significantly affects motives: affection, compassion, faith in justice, social responsibility, moral obligation, lust for power, self-centeredness, fear, feeling good, reciprocity, and reputation. Religious significantly affect motives: the belief, social responsibility, moral obligation, a religious duty, self-centered, self-sacrifice. Home town significantly affects motive awards. Marital status significantly affects motives: affection, conviction, social responsibility, moral obligation, a religious duty, political influence, conscience reputation. Political orientation significantly affects the motive of revenge to society. Volunteerism and civil participation - work in NGOs significantly affects motive need to belong somewhere. Volunteerism and civil participation - involvement in NGOs significantly affect motives: the need to belong somewhere and personal contacts. Models and experiences of youth - significantly affects motive jobs opportunities. 4 Conclusion The objective of this paper was to present my own categorization of motives that can influence decisions to make a donation to a non-profit organisation, test the concerned motives empirically and ascertain their significance for the Czech population. In the paper, I answer the five basic questions: What motivates individuals in the Czech Republic to provide a donation (significance of motives)? What is the interdependence of these motives (strength of the relationship between the motives)? What is the relationship between the individual’s motives and the amount of a provided donation? What is the relationship between the individual’s motives and the frequency of donating? Influence some socio-demographic groups the motives? Although it is somehow possible to measure and identify which motives influence decisions to make a donation, the influence or the willingness to donate cannot be identified with the donorship rate (or a respective amount of the provided donation). The research outcomes document that in the case of some donors who can be characterized by high willingness to make donations (the willingness to donate is derived from the ratio of donors to non-donors for a selected variable) a low donorship rate (the donorship rate is derived from the amount of a provided donation) can be observed concurrently. Donors can be found who do not significantly incline to the motives being studied, nevertheless can be characterized as the most generous donors. The direction and strength of a behaviour is determined by motives, its manner is however determined by situational factors too: behaviour adapts to a situation and so the same objective can be reached in various situations (Nakonečný, 1999). The statement can be also applied to the donor’s behaviour. It is influenced by a number of obvious and hidden internal or external variables, with various causal relationships existing between them. Hence, it is not possible to define a complex overview of all variables for any situation and any research sample or scientifically define dependence relationships. References [1] ANDREONI, J. (1989). Giving with Impure Altruism: Applications to Charity and Ricardian Equivalence. Journal of Political Economy. Vol. 97, no. 6, pp. 1447-1458. [2] ANDREONI, J., PAYNE, A. (2011). Is crowding out due entirely to fundraising? Evidence from a panel of charities. In Journal of Public Economics. Vol. 95, No. 5-6, pp. 334-343. [3] ARROW, K. (1974). Gifts and Exchanges. In Philosophy and Public Affairs. Vol. 1, No.4, pp. 343-362. [4] BATSON, C. D., SHAW, L. L. (1991). Evidence for Altruism: Toward a Pluralism of Prosocial Motives. In Psychological Inquiry. Vol. 2, No. 2, pp. 207-227. 54

[5] BEKKERS, R., WIEPKING, P. (2010). A Literature Review of Empirical Studies of Philanthropy: Eight Mechanisms That Drive Charitable Giving. In Nonprofit and Voluntary Sector Quarterly. Vol. 40, No. 5, pp. 924973. [6] BENNETT, R. (2003). Factors underlying the inclination to donate to particular types of charity. International Journal of Nonprofit and Voluntary Sector Marketing. vol. 8, no. 1, pp. 12-29. [7] COLLARD, D. (1979). Altruism and Economy: A Study in Non-Selfish Economics. In The Economic Journal. Vol. 89, No. 355, pp. 681-683. [8] Financial report. (2014). [online] The number of taxpayers who have exercised in income tax - return for the tax period of 2000 to 2012 deductible "value of the gift / gifts". Available on http://www.financnisprava.cz/cs/ dane-apojistne/analyzy-a-statistiky/udaje-z-danovych-priznani. [9] FRIČ, P. (2001). Dárcovství a dobrovolnictví v České republice: (výsledky výzkumu NROS a Agnes) /Donating and Volunteering in teh Czech Republic: (Results of the Research Executed by NROS and Agnes/. 1st edition. Prague: Agnes. ISBN: 80-902-6337-2. [10] GITTELL, R., TEBALDI, E. (2006). Charitable Giving: Factors Influencing Giving in U.S. States. Nonprofit and Voluntary Sector Quarterly. Vol. 35, no. 4, s. 721-736. [11] HLADKÁ, M, ŠINKYŘÍKOVÁ, T. (2009). Dárcovství v očích veřejnosti /Donating as Seen by the General Public/. Brno: Společnost pro studium neziskového sektoru. ISBN: 978-80-904150-4-1. [12] KOLM, S. Ch. (2000). Introduction to the Economics of Reciprocity, Giving and Altruism. In GÉRARD-VARET, L., KOLM, S. Ch., MERCIER YTHIER, J. The economics of reciprocity, giving, and altruism. New York: St. Martin's Press. 387 p. ISBN 03-122-2956-9. [13] KOTTASZ, R. et al. (2004). Differences in the Donor Behavior Characteristics of Young Affluent Males and Females: Empirical Evidence from Britain. VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations. Vol. 15, no. 2, pp. 73-96. [14] LLOYD, T. (2004). Why rich people give. London: Association of Charitable Foundations. 366 p. ISBN 978-1897916-117. [15] MARX, J., CARTER, V. (2014). Factors Influencing U.S. Charitable Giving during the Great Recession: Implications for Nonprofit Administration. In Administrative Sciences. Vol. 4, No. 3, pp. 350-372. [16] NAKONEČNÝ, M. (1999). Sociální psychologie /Social Psychology/. 1st edition. Prague: Academia. 287 pp. ISBN 80-200-0690-7. [17] RANGANATHAN, S. K., HENLEY, W. H. (2008). Determinants of charitable donation intentions: a structural equation model. International Journal of Nonprofit and Voluntary Sector Marketing. vol. 13, no. 1, pp. 1-11. [18] ŘEŽUCHOVÁ, M. (2011). Dárcovství v číslech /Donorship Expressed in Figures/. Brno: Společnost pro studium neziskového sektoru. ISBN: 978-809-0415-065. [19] SARGEANT, A. (1999). Charitable Giving: Towards a Model of Donor Behaviour. Journal of Marketing Management. Vol. 15, no. 4, pp. 215-238. [20] SCHERVISH, P. G. (1997). Inclination, Obligation, and Association: What We Know and What We Need to Learn about Donor Motivation. Critical Issues in Fund Raising. pp. 110-138. [21] SMITH, V. H. et al. (1995). The private provision of public goods: Altruism and voluntary giving. Journal of Public Economics. Vol. 58, no. 1, pp. 107-126. [22] ZIEMEK, S. (2003). The economics of volunteer labor supply: an application to countries of a different development level. New York: Peter Lang. 229 p. ISBN 36-315-1389-5.

Contact information Ing. Marie Hladká, Ph.D. Masaryk University Lipová 41a, 602 00 Brno Czech Republic [email protected]

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Dependency of Pension Insurance Contributions on the Number of Raised Children Martin Holub Abstract Pensions systems, similarly as other subsystems of the government’s social policy, must react to the socio-demographic developments within society, including but not limited to increasing life expectancy, changes in family practices, and birth rate numbers. The current discussion on the form of a pension reform within the Expert Committee on Pension Reform also involves unconventional approaches that are not supported by economic theory and/or global practice. The paper analyzes one specific proposal consisting in the differentiation of pension insurance contributions based on the number of dependent children. It thoroughly analyzes the given proposal from both microeconomic and macroeconomic perspective and assesses it within the context of the contemporary theory of pension systems. Based on the performed analysis, it concludes that the proposed measure is not appropriate, systemic and only brings partial effects for children with families in respect of the foreseen objectives – i.e. support of families with children – as it does not comprise all forms of family life, and that there are more suitable measures under the existing social policy that would lead to the fulfilment of the defined objectives. Keywords: non-contributory periods, old-age pension, social contributions JEL Classification: H55, J26, G22 1 Introduction There have recently been unprecedented discussions on pension reforms, not only in European countries. Social systems of nearly all European countries, including the Czech Republic, face problems associated with the economic and population development of our postmodern society. Although the inclusion/consideration of child-rearing periods has had a long tradition (not only) within the Czech pension system, present discussions on methods and potential of a pension reform in the Czech Republic have resulted in proposals for modifying the method of considering the child-rearing process within parents’ pension claims and pension benefit amounts (Hyzl 2004, Hampl 2014). Members of the Expert Committee on Pension Reform established by the Ministry of Labor and Social Affairs have been talking about potential introduction of differentiation of pension insurance contributions based on the number of raised children – in connection with reconciling transfers between families with children and society, considering child-rearing expenses, and in connection with low birth rates (Expert Committee on Pension Reform, 2015). These deliberations partially relate to efforts aimed at increasing the birth rate and ensuring “better” conditions for families with children, and partially to efforts aimed at ensuring long-term financial sustainability of the pension system. The objective of this paper is to present the proposed theoretical concept of the relation of pension insurance contributions based on the number of raised children within the pension system, critically analyze this concept, and identify the concept’s strengths and weaknesses. Based on the analysis and positioning of the concept within the concept of the Czech pension system, the paper aims to present recommendations for the Czech government policy, thereby supplementing ongoing discussions on the general direction of the pension system reform in the Czech Republic. 1.1 Consideration of child-rearing periods within the pensions systems of EU Member Countries The child-rearing periods are taken into account in all EU Member Countries for the purpose of pension security, irrespectively of the selected social security system. Differences between individual countries only exist in terms of the scope of inclusions of such periods. The inclusion of the child-rearing periods shows significant variability within the pension systems of individual EU Member Countries. For the most part, early child-rearing periods are taken into account (usually three to four years). Potential gaps in the parents’ pension insurance contributory periods, resulting from the child-rearing process, may be compensated in the form of payments of contributions for the given period by the government or parents may voluntarily purchase pension claims. Child-rearing periods may partially serve solely for filling in insurance period gaps when determining pension eligibility (supplementation of the minimum number of years necessary for pension benefits eligibility). The child-rearing process is rarely taken into account by including non-contributory periods, for which no social insurance contributions are made. Child-rearing periods may be excluded for the purpose of pension calculation to prevent reduction of the attained income, from which pensions are calculated. In some countries, the child-rearing process is taken into account in the form of benefits linked to a place of residence; these benefits are similar to family benefits; however, they have direct or indirect impact on later pension benefits assessment (these benefits may be included in the insurance contribution assessment base). In countries that apply a point-based system, child-rearing bonuses are credited to insureds’ individual accounts or insurance periods are increased in the form of bonuses. In exceptional cases, the statutory retirement age is reduced – either for parents or for mothers raising children. In the Czech Republic, the child-rearing period is currently taken into account in the form of a non-contributory period, affecting both the pension eligibility and pension amounts. A non-contributory period is defined as caring for a child up 56

to 4 years of age. Such childcare may be included for the purpose of future pension benefits for both women and men; however, no single period may be simultaneously included for several people. Moreover, the retirement age for women in the Czech Republic is reduced based on the number of raised children. However, this special privilege for women is being gradually eliminated, ultimately ensuring uniform retirement age of 67 years for men and women born in 1977. 1.2 Concept of relation of insurance contributions on the number of raised children The idea of considering child-rearing periods in pension eligibility or amount has been discussed in Europe since the 1980s, e.g. Borchert (1981) - in discussing the reform of the German pension system – recommends that child-rearing periods be taken into account in assessing the minimum period of insurance and proposes to introduce a special pension component – so-called parental pension. In his work, Bental (1989) examined the search for balance between the population growth and the accumulation of capital. He demonstrates that Pareto efficiency may be achieved for pay-asyou-go social security systems, where benefits are determined proportionally to the number of raised children. Cigno (1996) examines the relation between low birth rates and savings rate. Using specific data for Germany, Italy, United Kingdom, and the United States of America, he demonstrates that the expansion of social security systems has led to lower birth rates in the countries under review. More specific proposals for resolving these issues already start to appear at the beginning of the 21st century in the work of Sinn (2006), where the author deals with the relation between investments in human capital and a pension security system. The author concludes that social security represents good old-age security for people with no children, but also results in strong de-motivational factors in terms of investments in human capital. Some authors (e.g. Cigno 2009) then propose an introduction of an alternative pension security system to existing traditional social insurance systems; such system would allow individuals to claim pension benefits via their children, in whom they invested during child rearing. Pension systems, where the pension amounts depend on the number of children, are referred to as Child pension or CPAYG and, as Vostatek (2015) puts it, these pensions are not for the benefit of children, but simply “for children”. Child pensions refer to a social-political project of providing oldage pensions to parents with three or more children, something that has been recommended for a long time, particularly by Sinn and Werding. Child pensions are designed as universal benefits, independent of income. According to the concept, parents with one child are entitled a one third of the child pension and parents with two children receive two thirds of such pension. Pensioners with no children do not receive anything, as they did not invest in having and raising children. The CPAYG concept is further elaborated particularly in Germany, as Sinn (2013) expanded on his work; he studies the relation of social security contributions and the number of children, proposing a supplementary system of private insurance for people with no children or parents with a low number of children, where the insurance contribution amount would increase with a declining number of children. He proposes three children as the initial value for zero insurance contributions. Another German author, Werding (2014), examines the possibility of introducing pension security insurance contribution discounts or deductions to ensure fair insure contributions for people with children. The key premise here is, too, the idea that pension security may be achieved either by investing in a social security system (savings) or by investing in human capital (children) or as a combination of both. The differentiation of insurance contributions based on the number of dependent children (children being raised) may be introduced separately, as was the case in Slovakia, where it was introduced for a very short period of two years, or it may supplement CPAYG – e.g. as proposed by Sinn (2013) or Hyzl et al. (2004) in their respective works. Slovakia was the only European country to apply the institute of lower old-age insurance contributions for employees in the period of 1 January 2004 – 31 December 2005. The total insurance contribution rate for employees amounted to 4%, with potential reduction of 0.5% per each child. Since the resolution had been adopted against the government’s will, was non-conceptual and unfair, it was discontinued two years later and replaced by higher child-related tax bonus. Potential dependence of insurance contributions on the number of raised children, both negative and positive, also appeared in reform proposals of the Portuguese Socialist Party in 2005, with the former Prime Minister Sokrates proposing lower pension insurance contributions for parents with more than two children and increase of insurance contributions for people with no children or one child, claiming that “after all, wealth generated by the future generations will guarantee income of future pensioners” (Linhas, 2006). However, the proposal has never been implemented – due to strong criticism both by liberals, who criticized the measure as being functionless and suspected that the government solely wanted to use it to increase current pension insurance revenue, the account of which was nearing deficit, and by left-wing politicians, who viewed the measure as special treatment for large families, and also resulted in negative position of social partners, with the largest trade union organization CGTP referring to the proposal aimed at introducing variable contribution rates based on the number of children as absurd in its statement. With regard to the Czech Republic and the Czech pension system, the Expert Committee on Pension Reform proposes differentiation of pension insurance contribution rates for families with children. The objective of the given measure should be partial reconciliation of transfers between families and society in terms of the status of households with equal incomes, as well as the promotion of the merit principle by taking into account the way working parents contribute to raising future generations of insurance contribution payers. The Expert Committee on Pension Reform believes the potential introduction of the given measure will reduce the overall financial burden for families with children during the period of raising dependent children, as such period is associated with significant increase in child-related expenses and considerable reduction of income recalculated per household member. The Expert Committee on Pension Reform proposes an increase of the basic pension insurance contribution rate to 29% from the existing 28% - within the component paid by employees to 7.5%. Such basic rate would apply for households 57

with no children. Households with one child would be subject to a 28% rate (6.5% insurance contribution paid by employees), households with two children would be subject to a rate of 26.5% (5% insurance contribution paid by employees), households with three children would be subject to a rate of 24% (2.5% insurance contribution paid by employees), and households with four or more children would be subject to a rate of 21.5%, i.e. no insurance contributions paid by employees. For this purpose, a child would mean any individual without means living within a single household with his or her parents and up to the age of 26 years. Therefore, the insurance contribution rates would only be reduced during the actual child-rearing period, not throughout the period of insureds’ gainful activity. Both parents would be eligible to claim the insurance contribution reduction, provided they live in a common household; furthermore, both parents with shared custody (by a court decision) would also be eligible to claim the reduction. 2 Materials and Methods In constructing micro and macroeconomic models that simulate the proposed differentiation of insurance contributions, statistical data files were used as initial input variables; however, these files had to be limited and modified on a model basis. The data on insurance contribution payers were taken from the Czech Social Security Administration data, with a file on recalculated number of insurance contribution payers and number of pensioners in 2013 used as the start point. The structure of insurance contribution payers – classified by the number and age of children within (even singleparent) families and by the household type and economic activity of spouses/partners (as appropriate), based on the data collected during the 2011 Population Census – was then applied to the number of actual insurance contribution payers in the given year. Only economically active individuals (i.e. solely those, who actually paid insurance contributions/taxes in the given year and for whom the tested measure could be applied) were taken into account for the model calculations. Using such adjusted data, characteristics of economically active population (insurance contribution payers), classified according to the number of children (from 0 to 4 or more), were determined; the characteristics were then applied to the population of 2013. By reweighing the converted economically active insurance contribution payers, we arrived at a model structure of current insurance contribution payers. The insurance contribution payer structure, based on the number of children being raised, is shown in the following table 1. Table 1 – Number and structure of insurance contribution payers subject to pension insurance contribution rate discount/sanction based on the number of children Child considered by both parents Number of children considered Representation - % Number of payers (‘000) 0 36.61 1,545 1 26.63 1,124 2 30.44 1,285 3 5.35 226 4 0.75 32 5 0.15 6.5 6+ 0.06 2.7 Total 4,219 Source: Own calculations based on data from the Czech Social Security Administration and 2011 Population Census.

Microeconomic effects of the said measure on individual income level of families as well as macroeconomic effects of the given measure on the pension insurance system were calculated. The microeconomic implications of the proposed measure were examined using an example of a hypothetical individual with income at the average wage level (taken into account in the amount of the general assessment base for 2013 of CZK 25,913). When assessing the social implications of the calculated alternatives, the final relief was compared with average child-rearing expenses, as determined by the Czech Statistical Office. 3 Results and Discussion The impact of the proposed reform measure on individual income level of hypothetical individuals may be examined with the use of microeconomic models. The impact on the overall pension system balance may be assessed by means of a macroeconomic model.

58

3.1 Microeconomic analysis Number of children considered 0 1 2 3 4+

Table 2 – Differentiation of pension insurance contribution rates and contributions Insurance Insurance Insurance Insurance Employee’s contribution contribution contributions – contributions – savings rate – total rate – employee employee total 29.0 7.5 1,943 7,515 - 259 28.0 6.5 1,684 7,256 0 26.5 5.0 1,296 6,867 389 24.0 2.5 648 6,219 1,037 21.5 0 0 5,571 1,684 Source: Own calculations based on legal regulations applicable in 2014.

The aforementioned calculations indicate that monthly payments for an individual with no children and income at the average wage level would increase by CZK 259 as a result of the measure consisting in the increase of the basic insurance contribution rate by 1 percentage point. In case of a single-child household, the income level would not change compared to the existing situation – the disposable income of such household would remain the same. With regard to a household comprising two adults with income at the average wage level and two children, the proposed measure would generate monthly savings of CZK 778, i.e. 6.2% of costs of such family associated with 2 children (CZK 12,552 according to the Czech Statistical Office 2003). With regard to a household comprising two economically active adults and three children, the savings arising from reduced pension insurance contributions would amount to CZK 2,074 – i.e. 12.8% of costs of such family associated with 3 children (CZK 16,236 according to the Czech Statistical Office 2003). In case of a family with 4 or more children and both parents being economically active, the savings resulting from the lower insurance contributions would amount to CZK 3,368. In case only one of the adult household members is economically active (most likely for households with 3 and more children, where the mother is on a maternity/parental leave with the youngest child), the total savings for a three-child household would amount to CZK 1,037 and mere CZK 1,648 for a four-child household, i.e. marginal part of the family budget covering less than 7% of costs associated with having three children. The distribution of the provided benefits within the entire spectrum of insurance contribution payers is interesting. 46% of all insurance contribution payers would not be eligible for any support (sing-child households) compared to the existing situation, whereas 45% of households with children (two children) would generate total monthly savings of CZK 778 with both parents working. We can deduce relative unfairness of the said approach based on the calculations made. Since the child-rearing costs are more or less stable and independent – to a certain degree - of the family income, the insurance contribution reduction is directly dependent on the income level; therefore, the said contribution in the form of potential insurance contribution reduction provides different contributions for the “same” child-rearing process. The question is whether this is the idea behind the original concept of flexible support of families with children under the pension system – i.e. equal facilitation of the child-rearing process for all families. By nature, this measure that is associated with insurance contribution rate reduction solely for economically active people results in a significant number of parents that will not be eligible for such benefit – simply due to not having gainful activity. Similarly interesting is the comparison of lifelong household income in case of child rearing. Using an example of a family with 2 children – i.e. the most frequent model of a family in the Czech Republic in the recent decades and still predominant within the declared preferences of future parents – the change in the household income as a result of the given measure will be calculated. On a model basis, we will consider a household with two economically active adults, two children born three years apart, with one completing high-school and the other one graduating from university. The parent’s average period of insurance is foreseen at 43 years, whereas they collect income at the average wage level for the entire period. The calculation is performed using current prices. The performed comparative calculation indicates that, under applicable terms and conditions, both parents would pay insurance contribution of 28% for the period of 43 years, corresponding to about CZK 3,744,000 of insurance contribution paid per person. Based on the alternative proposed by the Expert Committee on Pension Reform, parents would pay increased rate of 29% for 14 years, basic rate of 28% for 13 years, and reduced rate of 26.5% for 16 years. The total insurance contribution paid for the period of 43 years would roughly amount CZK 3,713,000 per person. Therefore, the proposed measure would generate savings of CZK 62,000 over 43 years of insurance contribution payments for a household of two economically active adults and two children, i.e. an insignificant amount, particularly taking into account the model presumption of continuous gainful activity of both parents, which is in fact unattainable. 3.2 Macroeconomic analysis The macroeconomic impact of the proposed alternative that foresees the contribution increase or reduction, depending on the number of the insured’s children (with a single-child household being the base state) on the pension system balance may be both negative and positive, as revenue may either increase or decrease; in simple terms, it will depend on the proportion of households with and without children in the given year. The following table describes the impact of the proposed measure on the pension system balance, with a precondition of the model population constructed on the basis of the above mentioned restrictions. 59

Table 3 – Macroeconomic effects of varying insurance contribution rate based on the number of children Collected contributions – mil. CZK

Number of children considered

Insurance contribution rate - %

0 1 2 3 4 Total

Total rate – proposed change 29.0 28.0 26.5 24.0 21.5

Total rate – present situation 28.0 28.0 28.0 28.0 28.0

Employee’s contributions – proposed change 7.5 6.5 5.0 2.5 0

Employee’s contributions – present situation 6.5 6.5 6.5 6.5 6.5

Proposed change 139,307 97,832 105,855 16,834 2,729 362,557

Present state 134,503 97,832 111,847 19,639 3,554 367,375

Number of payers (‘000) 1,545 1,124 1,285 226 41 4,219

Balance change (mil. CZK) 4,804 0 -5,992 -2,806 -825 -4,819

Source: Own calculations based on legal regulations applicable in 2014.

It is clear from the aforementioned calculation that the proposed differentiation of pension insurance contribution rates depending on the number of raised children within a family would result in a loss of the pension system revenue of CZK 4.8 bn. in the form of uncollected contributions. In this case, the sanctions imposed on people with no children would not compensate the lower insurance contributions caused by a relief to families with two or more children. The question thus is, whether the insurance contribution reduction for families with more than one child had been configured correctly. For example, if the insurance contribution rate were to decrease by 1 percentage point for each child in a family, it would lead to a deficit reduction of nearly CZK 4 bn. The loss of revenue must also be increased by higher administrative costs that would arise from the given measure. No materials of the Expert Committee on Pension Reform explain the definition of the contribution insurance rates for families with children in any way. 3.3 Critical analysis from the perspective of theory The PAYG pension system reform measures adopted throughout the world so far have brought, among others, stronger relation of contributions made by insureds to the pension insurance system and the final pension benefit; so far, no country has opted for the transition to the CPAYG concept or dependence of insurance contribution amounts on the number of raised children on a long-term basis. Although existing problems of pay-as-you-go pension systems associated with declining birth rates may lead to an impression that such systems depend on relations between different generations, this fact does not substantiate the creation of new pension security concepts that would take into account the number of raised or conceived children. As stated by Vostatek (2015), the child pension concept or dependence of insurance contributions on number of raised children does not fit into any of the basic welfare regimes. Other reasons for rejecting the concept are as follows. It is highly problematic to view children as a “system contribution”, i.e. as an investment, not only from an ethical point of view. From an economic perspective, we face a problem of assessing investment costs and economic “performance” of children. One possibility is to limit investment costs solely to costs of education; however, this does not really simplify the situation at hand, since funds invested in education do not necessarily say anything about the way such education was used in the labor market, where employees’ remunerations are formed as the subsequent basis for the payment of contributions. Another issue of the discussed concept, currently unexplained by existing theory, is the fact that there is no uniformity of a raised child (as presumable system contribution) and future insurance contribution payer (as actual system contributor). It is virtually impossible and undesirable to ensure such uniformity, also due to the openness of the Czech Republic and associated movement of workforce within the EU. Similarly as no one can guarantee that a child will turn into an insurance contribution payer, no one can guarantee that he or she starts paying pension insurance contributions in the Czech Republic. Therefore, the initial premise of the given differentiation of pension insurance contribution rates based on the number of raised children – i.e. by taking into account the way working parents contribute to raising future insurance contribution payers – is wrong. The concept of the relation of insurance contributions and the number of children comprises inherent relative unfairness consisting in different absolute change of insurance contribution depending on the income level. Since the child-rearing costs are more or less stable and independent of the family income; however, the insurance contribution reduction is directly dependent on the income level, the said contribution in the form of potential insurance contribution reduction provides different contributions for the “same” child-rearing process. The concept that involves introduction of the insurance contribution differentiation based on the number of children in the Czech Republic, as proposed by the Expert Committee on Pension Reform, would lead to further increase of the already high burden imposed on labor in the form of insurance contribution for a significant part of the population. 4 Conclusion Although the concept of the dependence of pension insurance on the number of raised children has been mentioned in different alternatives in the past two decades, it has nearly always concerned mere theoretical proposals without any economic calculations or at least qualified estimates. For example, Sinn (2013) in his work proposes insurance contribution rate for people with no children at around 6 to 8%, once again, without any specific rationalization of the 60

given level. The proposal of the Expert Committee on Pension Reform does not clearly declare the criteria used to determine the selected pension insurance contribution rates either. The idea of introducing variable pension insurance contribution rates based on the number of raised or conceived children is presently not applied within any pension system in the world. Model calculations for pension insurance contribution rates reductions have demonstrated that the burden on households with average incomes would only be reduced insignificantly. The alternative of introducing variable insurance contribution rate based on the number of children in the Czech Republic, as proposed by the Expert Committee on Pension Reform, would lead to further increase of the already high burden imposed on labor in the form of insurance contribution for a significant part of the population. The differentiation of pension insurance contribution rates for families within children is a non-systemic measure that is unfair to children’s parents, as it does not affect all parents, but solely those who have gainful activity. For example, groups of parents, who are most at risk of poverty – i.e. single parents and parents with 3 and more children, who are more often unemployed or only have part-time jobs and would essentially need such support the most – would have no or only minimum benefits from the given measure. The proposed concept is only unfair in respect of economically active parents, since each child is “valued” differently, based on his or her parents’ income; the higher the income, the higher the valuation. A more effective and fair solution with lower administrative burden consists in, for example, assisting families with children under the tax system in the form of a tax deduction for each raised child, with higher number of parents in need being eligible for the support in the form of a tax bonus compared to the proposed concept. Based on the above mentioned analysis of the proposed concept of differentiation of the social insurance contribution rates, the author recommends that the Czech Republic avoids such type of solution in the course of the continuing pension insurance reform. A significant risk of applying such concept consists in a problematic theoretical basis associated with the quantification of its effectiveness that is difficult to grasp. A significant risk of this alternative form of considering child-rearing process within the pension security arises from either negative or virtually no experience with its application within foreign pension systems. Acknowledgements This paper was supported from the University of Finance and Administration research project “Review of the Czech pension system” in 2014 (No. 7765), financed from a grant to scientific institution. References [1] BENTAL, B. (1989). The old-age security hypothesis and optimal population growth, Journal of Population Economics 1, 285-301. [2] BORCHERT, E. J. (1981). Die Berücksichtigung familiärer Kindererziehung im Recht der gesetzlichen Rentenversicherung, Duncker & Humblot GmbH 1981. [3] CIGNO, A. (2009). How to Avoid a Pension Crisis: A Question of Intelligent System Design. IZA Policy Paper No. 4. Institute for the Study of Labour, [online]. [cit. 2015-05-25] available from: http://ftp.iza.org/pp4.pdf [4] CIGNO, A. – ROSAMI, F.C. (1996). Jointly determined saving and fertility behavior: Theory and estimates for Germany, Italy, UK and USA. European Economic Review 40: pp 1561-1589. [5] CZSO. (2003). Selection survey on family living cost in terms of raising children, CZSO 2003, Prague. [6] CZSO. (2011). Population Census), 2011, Prague. [7] HAMPL, O. (2014). Methodology of transfer analysis between families and society. Working paper. OKPDR, Prague. [8] HYZL, J., RUSNOK, J., ŘEZNÍČEK, T., KULHAVÝ, M. (2004). Pension reform for Czech Republic (innovation approach). ING Czech and Slovak republic, Prague. [9] LINHAS, T. (2006). Estratégicas da reforma da segurança social Apreciação da CGTP-IN: uma proposta, Lisbon. [10] Expert Committee on Pension Reform. (2015). Proposal of pension contribution differentiation for families with children [online]. [cit.2015-05-25] available from http://www.duchodova-komise.cz/wpcontent/uploads/2015/05/N%C3%A1vrh-diferenciace-sazeb-pojistn%C3%BDch-odvod%C5%AF-pro-rodiny-sd%C4%9Btmi-21.-kv%C4%9Btna-2015.pdf [11] SINN, H-W. (2006). Europe's Demographic Deficit - A Plea for a Child Pension System, De Economist 153, 2005, pp. 1-45, Tinbergen Lectures, Electronic reprint June 2006, University of Munich, [online]. [cit. 2015-0525] available from: http://epub.ub.uni-muenchen.de [12] SINN, H.-W. (2013). Das demographische Defizit – die Fakten, die Folgen, die Ursachen und die Politikimplikationen. Ifo Schnelldienst, Vol. 66, No. 21. [13] SINN, H.-W. (2014). Land ohne Kinder – die Fakten, die Folgen, die Ursachen und die Politikimplikationen. Vortrag vor der nordrheinwestfalischen Akademie der Wissenschaften. Düsseldorf, 2014. [online]. [cit. 2015-0525] available from: https://www.cesifo-group.de/ifoHome/events/individual-events/Archive/2014/vortrag-sinnlmu-20141215/main/05/text_files/file/document/Vortrag-Sinn-2014-Land-ohne-Kinder.pdf [14] VOSTATEK, J. (2015). Děti, penze a pojistné, Fórum Sociální politiky 2/2015. [15] Werding, M. (2014). Familien in der gesetzlichen Rentenversicherung: Das Umlageverfahren auf dem Prüfstand. Gütersloh: Bertelsmann Stiftung. 61

Contact information Ing. Martin Holub, Ph.D. University of Finance and Administration, Prague Estonská 500, 100 00 Prague 10 Czech Republic [email protected]

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Does the Information Age Free Consumers from Asymmetric Information or Enslave Them in Attention Poverty? Petr Houdek, Petr Koblovský, Daniel Šťastný, Marek Vranka Abstract Providing people with more information and more options may seem as a good policy. However, because of limited attention and cognitive resources, people are not able to use all available information and freedom of choice effectively in order to achieve their own best interests. When cognitive resources and attention are depleted, decision making becomes shallow and intuitive, often unable to take important aspects of given situations into account – even though this information is readily available. An intuitive decision making may lead to suboptimal outcomes by overestimating the importance of the most salient cues and disregarding the less obvious future consequences. Although this creates a demand for decision making aides that could be satisfied by markets, policy regulation may be necessary in some areas. We provide specific examples of problems arising from limited attention together with solutions based on behavioral economics approach to policy making known as nudging. Keywords: Limited attention, cognitive biases, information asymmetry, libertarian paternalism, nudging JEL Classification: D03, D82 1 Introduction The concept of limited attention is a pleonasm. People never perceive the world as a whole. Attention is by definition always focused only on certain stimuli. However, we will use the term “limited attention” in our article in order to highlight problems faced by consumers who have to process ever growing volume of information coming from a wide range of competing sources. There are millions of products available on store shelves nowadays. Even an ordinary supermarket offers about 40 thousand different articles. In contrast average household is able to cover a major part of its consumption by using only approximately 150 products, which means that it must filter out the residual of 39 850 kinds of products most of the time (Trout, 2005). The extreme but frequently studied inability to effectively discriminate between alternatives is known as a decision overload or the paradox of choice (Iyengar & Lepper, 2000; Schwartz, 2005). A state of mind, in which the possible choices are so abundant that the consumers’ motivation to choose is significantly reduced, can lead to lower product satisfaction, disappointment or even to a complete inability to decide. In reality such intensive decision-making paralysis is rather rare (Scheibehenne, Greifeneder, & Todd, 2010). More frequently, consequences of the limited attention can be observed when customers underestimate or overlook information with eminent impact on the quality or final price of a product or service. Typical examples are goods with shrouded attributes (Gabaix & Laibson, 2006). For example, manufacturers of printers offer cheap products, but do not inform customers about the prices of costly patented ink cartridges (for which the total costs exceed price of the printer about 10 times over the lifetime of the product) and in fact customers are really not able to calculate the price of printing at the time they buy their printers. Banks advertise the benefits of their accounts, but do not promote the full range of charges and fees associated with them. Banking and financial sectors have an especially high incentive to sell complex and confusing products. In an environment of myopic, unsophisticated customers financial firms achieve extra profit because customers pay higher transaction fees for lower product yield (Célérier & Vallée, 2014; Stango & Zinman, 2009). There are many other ways in which limited attention affects decision-making. For example, buyers focus primarily on digits of prices which are on the left and they pay less attention to digits on the right – so called “left-digit bias”. The bias has a potential to cause significant losses when prices create salient “break-points”. Using American used cars market data Lacetera, Pope, and Sydnor found that “cars with odometer values between 79,900 and 79,999 miles are sold on average for approximately $210 more than cars with odometer values between 80,000 and 80,100 miles, but for only $10 less than cars with odometer readings between 79,800 and 79,899” (2012, p. 2207). The exact same pattern was identified on German market too (Englmaier, Schmoller, & Stowasser, 2013). Englmaier et al. additionally discovered that customers pay higher attention to the year of first registration than to the date of registration (ceteris paribus, cars manufactured in January are sold for a higher price than cars from December of the previous year while the similar variation is not observed between months within one year). Numerous other studies have demonstrated that consumers pay only limited attention to important product characteristics or price. When a household starts paying via automatic bill payment (ABP) for energy residential electricity consumption increases (Sexton, 2014). Consumers underestimate the costs of transportation and packaging (Brown, Hossain, & Morgan, 2010; Hossain & Morgan, 2006). They misjudge prices of grocery store products when taxes are excluded from price tags and the total price is paid at the counter (Chetty, Looney, & Kroft, 2009; Goldin & Homonoff, 2013; Houdek & Koblovský, 2015). Buyers are influenced and easily manipulated by irrelevant and/or outdated stimuli that attract their attention (Ariely, Loewenstein, & Prelec, 2003; Simmons-Mosley & Malpezzi, 2006), or buy insurance only based on temporarily salient risks (Browne & Hoyt, 2000); for other examples see Bordalo, Gennaioli, & Shleifer (2013) or DellaVigna (2009, sec. 4.2). 63

Presented findings convincingly document how even overabundant amount of information can lead to suboptimal decision when attention as a resource is limited. In the next section, the article continues by discussion of cognitive mechanisms responsible for biased information processing, attention depletion, and the impact of both phenomena on quality of consumer choice. The section 3 is devoted to discussion of market forces and economic and technological innovations that contribute to mitigation of information asymmetry and creation of more easily navigable markets for consumers. However, we argue that firms will be still able to (ab)use limited attention of consumers for their own benefits. In section 4, we therefore propose solutions inspired by the behaviorally informed policy (Thaler & Sunstein, 2008), which would restrict these exploitative strategies and which would generally mitigate negative aspects of limited attention. The conclusion is devoted to the summary of benefits and costs of proposed solutions and suggestions for further research. 2 Cognitive basis of limited attention Lay people as well as some traditional economists consider cognitive processes costless and instantaneous. Because of this, people routinely overestimate the capacity of human attention: they commonly believe that when some important information is easily available, they would immediately and reliably notice it and use it. However, even a dramatic event such as swapping one person for a different one during a conversation can easily escape one’s attention. In a field study by Simons and Levin (1998), a researcher approached a pedestrian on a university campus asking for directions. While the pedestrian was explaining the way to the researcher, two other confederates carrying a door walked between them, interrupting their conversation and momentarily blocking the view. As they were passing, one confederate switched place with the researcher who had originally asked for directions. When a different group of people was asked to estimate the proportion of those who would notice such swap, their average answer was 100% (Levin, Drivdahl, Momen, & Beck, 2002). In reality, only less than a half of the pedestrians (46%) noticed the swap. But perhaps the most striking demonstration of this so-called inattentional blindness comes from a study in which 24 radiologist were asked to examine a series of scan images looking for signs of possible tumors. Only four radiologists have noticed that an image of gorilla was presented on the last scan. Others have missed the gorilla completely – although an eye-tracker camera showed they had looked directly at it (Drew, Vo & Wolfe, 2013). These and many similar findings show several things about the nature of human attention: First of all, human attention is a scarce resource – it simply is not possible to focus on everything that is occurring around us. Secondly, things outside of our attentional focus are virtually non-existent for us, even when they are directly in front of our eyes. And finally, we do not pay attention to unexpected things or to things that are dissimilar to things on which we are currently focusing our attention (Simons & Levin, 1998). The attention allocation is usually intuitive and automatic. Most of the time, people are in a sort of stand-by mode: they are not deeply focused on anything in particular and they perceive only the most basic and salient aspects of their surroundings. This setting is probably adaptive from an evolutionary perspective as it allows people to perform routine tasks without excessive effort and also to quickly react to possible emerging threats, signaled by a sudden movement or sound. People are also able to consciously focus their attention on a specific task. Then they can take even less salient and not obviously important aspects (e.g. future consequences, complex features, etc.) of the given situation into consideration. This is, however, much more energetically taxing, as an effort has to be made to suppress possible distractors and actively look for non-obvious features and not-easily-available information regarding the task in question (Pocheptsova, Amir, Dhar & Baumeister, 2009). More importantly, according to current cognitive theories, people have to their disposal only a limited amount of selfcontrol that can be used for attention management (Baumeister, Bratslavsky, Muraven, Tice, 1998). Once all available self-control is depleted, attention cannot be focused very well. People then become distracted more easily and their decision making falls under the influence of intuitive processes guided by only the most salient features of a given situation (Pocheptsova et al., 2009). Less obvious aspects such as hidden taxes, fees and add-ons paid in the future or health consequences are as “invisible” for them as the gorilla on a medical scan mentioned above. As a result, performance of any complex decision-making task suffers. Results from a study by Vohs and colleagues (2008) suggest that even a simple activity of making choices (between consumer goods or college courses) can deplete self-control. Therefore it seems that the sole presence of many information sources and options between which people have to constantly choose impairs the following information processing and further decision making. This can easily lead to a vicious cycle because suboptimal decisions lead to worse outcomes, less cognitive resources in the future and less sophisticated attention management (Shah, Mullainathan, & Shafir, 2012). 3 Market Solutions to Information Asymmetry All instances of information asymmetry (IA) tend to leave some mutually beneficial transactions unexploited. This explains the existence of market forces – incentives for the very market participants – operating towards mitigating or eliminating the inefficiency caused by IA. It is in fact another margin of the entrepreneurial discovery process (e.g. Kirzner, 1997). Much like the entrepreneurs search for the right product to offer, for the right distribution channel or packaging, they also search for ways of credibly communicating the fact they are superior to competition. And while we typically think of sellers as the entrepreneurs, the same process takes place among buyers as well as among third parties 64

who see a frustrated beneficial transaction between (prospective) sellers and buyers as a market niche, as an entrepreneurial opportunity. While all of the three distinct groups have in the long run the same incentives, the level of actual discovery efforts corresponds to the degree to which they are aware of IA and its costs, and, of course, to the amount of entrepreneurial spirit and talents these groups have. Concentration of these qualities among sellers on most markets explains why such innovations are empirically more often coming from sellers rather than buyers. But all groups, we show below, have developed some ways of eliminating the negative effects of IA and were in this benefited by the information age. The traditional quality signaling tools used by sellers such as brand names and various certifications and warranties (technical or satisfaction) were greatly complemented by the low cost of communication. It enabled sellers to disclose more effectively, to communicate information aimed at “educating” their customers. This intensifies competition and can make it harder for sellers to get away with “tricking” their customers by concealing information. Product comparisons can be made more complex, long-run and available to wider public (e.g. Feldman et al., 2007). On top of advantages based on mere cheaper communication, the current cheaper and better technology (e.g. vehicle telematics) enables some sellers to collect information on product-related behavior of their customers, mitigating moral hazards or outright fraud in insurance business, and on product markets as well (Ippisch, 2013, Alharaki et al., 2010). In a similar vein, the screening activities traditionally relied upon by buyers are greatly enhanced in their effectiveness by the low cost of communication. On innumerable web-based discussion fora, prospective buyers can now draw on experience of actual users of most products with a reasonable history on the market at costs close to zero (Amblee & Bui, 2011). Moreover, information technology gives rise to innovations on the part of buyers that transcends the usual experience sharing. It is now possible to monitor actual contract performance much more closely. The use of agreed upon materials or technology procedures or the location in time, for example, can all be checked upon in real time or ex post (Dellarocas, 2003; Lewis, 2011; Resnick et al., 2006; Brustein, 2013). Third parties come in essentially as outside providers of signaling or screening, assisting either of the two parties to a transaction in activities mentioned above. And given the technological nature of the information age, it is the third parties whose scope of activities is most dramatically enlarged by its coming. Their original area of activity as independent testing/certifying agency, itself enhanced by an easier information dissemination and customer reach, expanded into territories and modes of business previously hard to imagine (Dewan & Hsu, 2004; Roberts, 2011). First, the lower cost of information gathering created a space for third parties in products comparisons, which in turn became a natural environment and a platform for traditional information/experience sharing among users and prospective buyers, making it all the more easier to find relevant information and, perhaps even more importantly, make sense of it. The seemingly minor innovation of rating users’ experience or sellers’ rating (e. g. the 5-star rating) dramatically improves the intelligibility of a review (Masum et al., 2012). Second, the information technology made it much easier for third parties to become effectively intermediaries between sellers and buyers. Innovations like eBay, Uber or AirBnB now make some previously non-existent transactions possible. And this is not only because the sellers and buyers would not typically know about each other, but, more importantly, because they provide both parties the necessary information about the other party (its rating) that reduces the risk of mutual engagement. While there is typically much heterogeneity and some biases in such feedback, it does not render it useless (e.g. Saeedi, 2014), and platforms can and do learn from mistakes in their reputation mechanisms (Nosko & Tadelis, 2015). And third, the ease and low cost of information flow in some cases blurs the traditional difference between business and private activity, which not only boosts competition, but puts both sides of the transaction on equal footing. Instead of a large hotel chain contracting with an odd one private customer, we have now transactions between an odd one customer and an odd one owner of an apartment (e.g. Zervas et al., 2015). Now the effect of the information age on tools mentioned above has generally been a bifurcated one: a) the low cost of data collecting, searching and sorting has dramatically boosted their effectiveness, tending to eliminate many of the traditional IA concerns (Cowen & Tabarrok, 2015), b) the information-rich environment in which these tools are used is congested and contains more noise leading to the information and choice overload, tending to exacerbate some IArelated concerns. While the net effect in each particular case is ultimately an empirical question, there is some reason for optimism. This is because b) feeds back into a). Any negative effect (choice overload, too many attributes, shrouded prices, too complex or misleading product information, incomprehensible contracts or even outright deception), to the extent it is recognizable as negative by market participants, creates an entrepreneurial opportunity one may cash on (e.g. no fine print policy, recommended products, comparative advertising). Despite all the entrepreneurship and ingenuity, the market solutions of IA are far from perfect and complete. Insufficient competition or non-repeated nature of given business may cause the disciplining pressure on sellers to be insufficient to go all the way full disclosure and honesty. Even if there is such pressure, reaching perfection is likely to be too costly for the sellers. Finally, even if we assume the most optimistic scenarios on the part of the sellers, the way to perfection would be ultimately thwarted by limited attention of the buyers we referred to above. On the other hand, perfection is a false benchmark (Demsetz, 1969), and it has to be recognized that self-interest of market participant deploys a powerful antidote to IA. Nonetheless, this is not to say (much less to prove) that spontaneous solutions achieved by market participants cannot be improved upon (assisted or catalyzed) by policy. When designing such policy, however, it must be borne in mind that its design and enforcement is itself costly (not least because it is likely to create IA problems of its own) and this cost must be carefully weighed against its perceived benefits. The traditional regulatory responses to IA have not been 65

very careful at that (Winston, 2007, pp. 27-60). The next section is then devoted to a discussion of policies better geared to pass this test. 4 Behaviorally informed policies As indicated, the information abundance may lead to suboptimal and costly choices for many (Campbell et al., 2011). Referring to the findings on suboptimal choices, legal scholars regularly suggest paternalistic regulations to minimize the consequences of certain alleged suboptimal choices (usually with an argument of the necessity to protect people). It goes without saying, many of such regulations limit the freedom of choice, distort the market and, most importantly, could cause unexpected and unpredictable consequences. Moreover, certain regulations which are created to “protect” individuals from their choices have a small or no effect or may even harm the consumers by creating a virtual feeling that the consumers are protected by the regulations (and by the state), which creates ground for a moral hazard. Also, protected consumers may have a higher difficulty to learn from their mistakes, which may eventually lead to losses of higher magnitude (Wright, 2007). However, there are ways to improve decision making even without taking away freedom of choice. Richard Thaler and Cass Sunstein (2003) suggested that the way choices are presented always influences decisions, even when there is no explicit intention to do so. As an example they describe a cafeteria owner who has to present items she is intending to sell in a certain arrangement and it is up to her which order she chooses. Although everybody can freely choose from the whole selection, the placement matters – items in the front and at the eye level are sold more often and in larger quantities compared to those in the rear or at the ankle level. Thaler and Sunstein asked whether a conscious cafeteria owner who has her customers’ health in mind should not purposely place healthy items (fruits and vegetables) to the “best-selling” places and the unhealthy items (such as popcorn) to places where customers may still find them if they are looking for them. They called the concept of influencing choice process of people while simultaneously securing maximum freedom of choice libertarian paternalism and argued that even the state may adopt such approach to policymaking. Interventions designed in the spirit of libertarian paternalism are often called nudges because they are not meant to force people to make certain choices. Instead they are supposed just to gently push them in the desired direction. It has been argued that in order for a nudge to be successful it should maintain freedom of choice, be transparent and be tested before being implemented (Thaler & Sunstein, 2003). Additionally, designing nudges can benefit from following two rules: (1) Use of welfare-maximizing default options whenever it is possible. An illustrative example comes from the lack of organs available for transplantation in the US. It is most probably caused by a wrong choice of a default donor status – the default is not being an organ donor and people have to opt-in to become donors. In countries where the default is being a donor (with the possibility of opt-out), the organ donation is much less of a problem (Davidai, Gilovich, & Ross, 2012). (2) Simplification and increases of ease and convenience – simple and easily understandable options are always preferred to complex choices. For example, a law required to provide maximum number of available choices for the US citizens who were choosing a package of prescription drugs covered by the medical insurance. This resulted in an overabundance of choices – the provided coverage plans offered from 40 to 160 option that were difficult to compare and evaluate. Naturally, under such circumstances, the elderly, who were supposed to be the primary beneficiaries of the plans, were confused and made suboptimal decisions or no decisions at all and 25 percent of them remained uncovered by any plan. Subsequently, some states passed a law that allowed random selection of a plan for unsubscribed individuals in order to boost the participation in the scheme. The idea was that after gaining experience with the randomly selected plan, people would later change the plan for one better suited for them. However, only a small number of people changed the plan which lead to further inefficiencies (Thaler & Sunstein, 2008, pp. 159–170). How can the described policy be improved? Thaler and Sunstein suggest several ways: first – automatic enrollment with intelligent assignment. Instead of random assignment of one of 140 plans, a person could be assigned a plan that fitted such person’s drug intake in the last 3 months. By doing so, people would have most of their required drugs covered by the default plan (but they would still be able to change the plan if they decide to). Another option would be to sponsor development of a “drug calculator” which would – based on the drug intake data – indicate in a comprehensible way the most compatible plans. Such “calculator” would require the plan providers to regularly supply data about the plans in a unified manner to a database which should be made mandatory by policy-makers. Such reports – Thaler and Sunstein label them with an acronym RECAP (Record, Evaluate and Compare Alternative Prices) – would “greatly improve people’s ability to make good choices” (Thaler & Sunstein, 2008, p. 94). Naturally, such calculators may be helpful in many instances where an identical or very similar products are difficult to compare and evaluate (such as gas, electricity and water supplies, credit cards, telecommunication, internet fees, etc.). There are many other ways for the government to support market forces and tackle the problem of limited attention using reasonable defaults and requiring simplified disclosures in unified formats. An article by Thaler and Benartzi (2004) depicts a scheme that significantly improved retirement savings of employees (which are usually smaller than optimal) by a simple combination of automatic enrollment and automatic adjustments of deposits in case of salary increases. Regretfully, the Czech government was obviously unaware of this article when it passed the law on the second pension pillar (which introduced opt-in default and produced tens of pension funds, leading to confusion and low adoption rates and which is currently being revoked). Using policies informed by these and similar insights from psychology provides ways to improve many aspects of people's lives ranging from health (Milkman, Beshears, Choi, Laibson, & Madrian, 2012) to financial literacy (Drexler, Fischer, & Schoar, 2014). 66

However, not all nudges are successful. Mandatory calorie labeling of food adopted by most western jurisdictions serves as an example of such failure. These regulations were supposed to provide consumers with a useful guidelines on the calories intake. The purpose of this was to fight the most widespread western disease – obesity. However, obesity does not seem to have been tackled at all and at least with the calorie labels it is clear why – people keep ignoring them (Liu et al., 2014; Elbel et al., 2009; Finkelstein et al., 2011). Moreover, there are indications that some consumers (usually those who are the most endangered group) seek “best calorie deals”: when deciding between a two-dollar canned soup with 500 calories or one with 600 calories, they tend to opt for more calories for the money. Thus, people seem to use the provided information in a way that goes against the aim of the regulation. This shows that even theoretically well supported nudges sometimes fail, which makes the necessity to test them in controlled field experiments before their full implementation even more obvious. 5 Conclusion With communication becoming cheaper and easier, people are exposed to more and more information. At the same time, however, our ability to process the information with paying full attention stays rather limited. Thus one may ask whether more information and wider portfolio of choices always improve our lives. We suggest that at some level people are incapable of making efficient decisions, efficiently identify and evaluate preferences and compare alternatives and options hence eventually making suboptimal decisions. Suboptimal decisions result in dissatisfaction. On several real-life examples we show that the information overload may lead to such dissatisfaction. Are there any ways to lower the suboptimality of our decision in the current world? We suggest that well-thoughtthrough nudging – a recent approach to policy making, based on a work of Sunstein and Thaler (2003) – might be a promising start. Nudges being simple, cheap interventions aimed at helping people overcome their cognitive limitations in decision making do not directly limit freedom of choice in a way that bans or taxes do. Moreover, they are usually very efficient as they primarily target intuitive processes and guide them in directions that lead to beneficial outcomes. In general, policies based on nudging aim to complement decision-making processes with elements to that help people make intuitively the same decisions they would make if their cognitive resources were not limited. Alternatively, lowering the cognitive load by making interactions with institutions more intuitive may sometimes help people as well. 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Contact information Ing. Petr Houdek J. E. Purkyne University in Ústí nad Labem Moskevská 54, 400 96 Ústí nad Labem Czech Republic [email protected] Ing. Petr Koblovský, Ph.D. J. E. Purkyne University in Ústí nad Labem Moskevská 54, 400 96 Ústí nad Labem Czech Republic [email protected] doc. Ing. Daniel Šťastný, Ph.D. J. E. Purkyne University in Ústí nad Labem Moskevská 54, 400 96 Ústí nad Labem Czech Republic [email protected] Ing. Mgr. Marek Vranka Charles University in Prague nám. Jana Palacha 1/2, 116 38 Praha Czech Republic [email protected]

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Using Implicit Rental Cost as a Measure of Poverty Robert Jahoda, Jiří Špalek Abstract Social exclusion is often accompanied by spatial detachment which usually has a form of concentration of socially excluded households in segments of cheap housing of less quality or otherwise unattractive housing. In our analysis we analyse whether we can identify such socially excluded households in the data using housing costs indicators. We concentrate only on the rental segment of the housing market. We argue that existence of households which have to pay an inadequately high rent makes the possibility for poverty identification, especially if we compare the actual housing costs with the costs implicit. In the results section we present information on these households and discuss whether we identified the right group. Besides the data analysis we show that the interplay of individual parts of the housing policy led to a situation when some households pay an inadequately high rent which the state considerably contributes to. Although the problem concerns about 1% of Czech households, consequences of a failure to solve the situation can be critical for both the citizens themselves and the public sector. Our paper may serve as a basis for future analysis of alternative policy impacts. Keywords: Housing, tenure, choice, expenditures, determinants JEL Classification: D12, P36, R21 1 Introduction Social exclusion, which is defined by, inter alia, Lux et. al. (2011) as detaching a person or groups of people from common life of the majority society, is often accompanied, in particular in urban areas, by spatial detachment as well. Spatial exclusion usually has a form of concentration of socially excluded households in segments of cheap housing of less quality or otherwise unattractive housing. Such locations where the concerned social groups are concentrated are then targeted by a number of social policy measures. The reason is that the households that live there are caught in a trap as they cannot move to another location due to their low (or non-existent) incomes or discrimination in the labour market or in a common life. The households that belong to these communities are often economically inactive, their income consists in particular of social benefits and unreported incomes that are, in some cases, obtained through illegal activities. A low level of education, restricted possibility to obtain income from work activities (additionally accompanied by high economic disincentives to accept an economic activity) lead to a limited mobility of these households and emergence of excluded locations. As standard, situations of existence of excluded communities should be solved at the municipality level with the assistance of the state. The support to households should lie in securing adequate housing and social work which should result in higher chances in the labour market for adult family members and the quality participation in preschool and compulsory school education for dependent children. However, if the state fails in this role, the family has to rely on a limited offer of housing, depends on social benefits and the consumption model that does not give preference to the role of education. Taking into account the lack of financial reserves in such households, the housing is usually of a rental type. However, as some studies (see HATEFREE, 2014) showed, for example a Romany family has a small chance to find a standard rental dwelling. In this situation, households usually depend on a limited offer when rental flats of a lower quality are rented for the maximum possible level of prices at which the state pays housing benefits. Households living in halls of residence (that have usually not received a final inspection certificate for these purpose) found themselves at the very bottom as the high prices charged there do not correspond to the quality of the provided housing. It was first of all the state that enabled emergence of socially excluded communities because it was absent in social work and provision of adequate and economically affordable housing to poor households. In addition, the situation was exacerbated by postponed deregulation of rental housing and related privatisation of the municipal housing fund. The problem can be furthermore related to the concept of fiscal federalism in the field of social policy. This is the example when decisions about the amounts and entitlements to allowances are centrally administered and municipalities are mere providers without their own competences and incentives enabling them to solve the situation locally. Such a situation happened in the Czech Republic after 2007 reform of the Housing Allowance and Social Assistance benefits. Nowadays, the uncertainty about the division of competences between the central and municipal administration levels is also admitted by the Czech Ministry of Labour and Social Affairs (MPSV, 2014): “The increased costs could have further resulted from a vague stipulation of responsibilities of municipalities for securing housing for their inhabitants as well as insufficient execution of social work in municipalities and the very questionably stipulated obligation of municipalities to execute social work when beneficiaries receiving supplements for housing can be provided another form of accommodation provided that municipalities are able to support them in searching standard dwellings and to enhance their competences, which are often insufficient, to find and keep such dwellings.” Taking into account what was described herein above, the goal of the paper is to find out whether we are able to identify socially excluded households in the CZ-SILC statistical survey using costs of housing as an indicator. For reasons of further use of research method, it is required to assess the proposed methodology as a way of identification troubled household. As an essential prerequisite, the possibility to simulate an alternative social policy in the housing sector requires that a group of households possibly affected by the poverty business should be found. The rest of the 70

paper is organized as follows. In the second chapter we present the data used in following analysis and summarize the methodology. The results-chapter discusses shows main results of data analysis and impacts of one of many alternative housing policies are presented. The last chapter concludes. 2 Material and Methods 2.1 Data We will analyse the Czech microdata from the Social and Living Condition survey that was held in the spring of 2013 and the outcomes of which were released for scientific purposes in the autumn of 2014 (see CZSO, 2014). The survey was performed in about 8,000 households; so that the equivalent for the whole society could be calculated, each of the households was assigned a weight. The survey gathers the basic demographic information about each of the households as of the date of the survey, the housing-related costs and household incomes for the previous year. The basic characteristics of the households with respect to the tenure status and obtained housing allowance is shown in the following table 1. Table 1 – Households and the Housing Allowances paid out to them in the breakdown by the tenure status and the year when the household moved in a flat Tenure status 1 2 3 4 5 6 Total Households [in thous.] lived before 2012 (95.7%) frequency [in %] 39.7 29.7 10.1 16.8 .0 3.7 100.0 lived since 2012 (4.3%) frequency [in %] 15.0 22.1 6.0 0.0 8.7 100.0 48.2 frequency [in thous.] 1 653.0 1 256.6 426.2 775.9 1.7 169.1 4 282.5 Total (100%) frequency [in %] 38.6 29.3 10.0 .0 3.9 100.0 18.1 Housing allowance [in mil. CZK] lived before 2012 (92.4%) frequency [in %] 10.7 13.6 7.0 66.5 0.0 2.3 100.0 lived since 2012 (7.6%) frequency [in %] 7.7 1.0 0.0 0.0 5.4 100.0 85.9 frequency [in mil. CZK] 426.5 516.6 262.9 2 778.7 0.0 104.7 4 089.5 Total (100%) frequency [in %] 10.4 12.6 6.4 0.0 2.6 100.0 67.9 Note: 1 – own house; 2 – own flat; 3 – cooperative (ownership); 4 – rented flat; 5 – flat from employer; 6 – living with relatives, friends. Source: own calculation.

The table shows that only 18% of Czech households live in rental housing but this type of housing draws nearly 68% of Housing Allowances. On the other hand, 78% of households own their dwellings (own house, own flat, cooperative) but they draw only 29% of the paid out allowances. The table also shows that the households that have moved in the past two years (in total representing 4.3% of all the surveyed households but 7.6% of the volume of paid out allowances) inhabit rental housing to a greater extent – the share is 48.2%, and the rental type of housing also comprises the biggest share in the recipients of the Housing Allowance – 85.9% of the whole group of households that have moved in the past two years. The table also shows that CZK 4.1 billion were paid in total in the form of the allowance, which slightly falls short behind the sum of CZK 5.7 billion stated by Czech MoLSA. Therefore, the SILC 2013 survey seems to slightly undervalue the households that receive the Housing Allowance, therefore, the scope of the problem that we wish to indicate using the data from SILC 2013 will probably be slightly underestimated too. The following table 2 show that about 3.2% of Czech households draw the housing allowance. Regionally, the housing allowance is not evenly distributed. For example in the Moravia-Silesia region the proportion of the beneficiaries is as high as 8.7%, while in the neighbouring Zlín region it is only 0.6%. Table 2 –Household and Housing Allowance paid distribution in the breakdown by regions households beneficiaries within region REGION [frequency in %] [in %] Prague 13.4 3.3 Central Bohemia 11.7 1.0 South Bohemia 6.1 2.1 Pilsen 5.6 0.9 Karlovy Vary 3.0 5.6 Ústní nad Labem 7.9 4.9 Liberec 4.1 3.6 Hradec Králové 5.3 1.6 Pardubice 4.8 1.2 Vysočina 4.7 1.9 South Moravia 10.8 3.4 Olomouc 5.9 2.8 Zlín 5.2 0.6 Moravia-Silesia 11.7 8.7 Total 100.0 3.2 Source: own calculation.

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The households that have lived in a flat since 2012 will have to be eliminated from the following analysis. The reasons for this elimination are described in detail in the methodology chapter; here, it is sufficient to state that the fact that these households are beneficiaries receiving the housing allowance (for 2012) is not related to the characteristics of their current housing. We have eliminated about 4.3% of households from the following analysis. Comparing these households with all households, we can say that this elimination concerns, to a greater extent, households in rental housing (here, we have eliminated 11.6% of households). The households being eliminated also rely on social benefits to a greater extent (6.4% of the households draw the Housing Allowance and 5.3% draw the Social Assistance benefits) and on incomes from economic activities to a lesser extent than it is usual in the whole society. The aforementioned suggests that although it is correct from the methodological point of view that we have eliminated the households that have lived in a flat since 2012 from our further analysis, on the other hand it seems that it is these households where the group of households that we have been looking for can be found. As regards the housing costs, there are no significant differences between the group of households that we have eliminated and the rest of the society. The following table 3 shows that the market price of housing is lower for the households that will be eliminated from our analysis. However, this difference is influenced by the households living in their own dwellings (lines 1-3), to a lesser extent by households in rental housing that are targeted by our analysis. As regards the price of housing, there are much bigger differences between households with respect to their entitlement to the Housing Allowance. The average market price of the housing for the households drawing the Housing Allowance accounts for about 60% of the average price of the housing for the households that do not draw it. The stated ratio does not differ very much with respect to the tenure status of the household. Table 3 – The average expected market price of a home per m2 [in CZK] Is the household eligible to the Housing Length of home occupancy Allowance Tenure status No Yes lived since 2012 lived before 2012 Total (96.8%) (3.2%) (4.3%) (95.7%) 1 – own house 28 303 16 570 28 190 21 216 28 309 2 – own flat 23 154 14 775 23 004 21 288 23 062 3 – cooperative (ownership) 19 209 13 291 19 018 16 576 19 084 4 – rented flat 24 101 23 095 14 716 22 439 23 181 5 – flat from employer 29 690 29 690 29 690 6 – living with relatives, 27 084 17 386 26 880 22 905 27 299 friends Total 25 114 14 866 24 781 21 687 24 922 Source: own calculation.

Total 28 190 23 004 19 018 23 095 29 690 26 880 24 781

2.1 Method To meet the goal of the analysis and identify the group of households that live in poverty, we have combined the statistical and factual analysis. In the first part of the chapter, it is first of all necessary to identify the group of households that could be exposed to the poverty. Of course, the SILC statistical survey does identify this type of households using AROP indicators. In our analysis we rather focus on housing cost as an alternative gauge of the poverty. In creating such an expert estimate, we proceed from the knowledge of the form of the SILC survey and the text that described the form of benefits towards housing and the characteristics of the households that are usually classified as socially excluded. Therefore, they are households living in rental housing, while their living conditions represent a combination of rental dwellings of a low quality and a high rent paid for them. Specifically, we defined the concerned households by means of the following three conditions which must be concurrently met: i. The household lives in rental housing ii. The household receives the Housing Allowance iii. The rent/implicit rent (the rent that equals to the market price of a property) ratio is high As it was already stated, all households that changed their housing in 2012 or 2013 had to be eliminated from the analysis. The reason is that the entitlement of these households to the Housing Allowance (the SILC 2013 records the allowances received in 2012) can be expected not to be related to the level, price and quality of their current housing. If a household became entitled to the Housing Allowance in 2012, the entitlement probably arose on the basis of the quality and costs of the household’s original dwelling (by the end of 2011 or the beginning of 2012) and now we are not able to relate the entitlement to the Housing Allowance to the level of the current housing. It is possible that the household will become entitled to the Housing Allowance or its current entitlement to it will be forfeited on the basis of the current housing. However, we will not be able to identify this fact (if any) until the data of SILC 2014 are published in the autumn of 2015. As we have already indicated, the 4.3% of the households to be eliminated from our analysis will rather include those households that we try to identify in our paper. The reason is that the households that moved in 2012 and 2013 are the Housing Allowance beneficiaries to a greater extent and use rental housing more often. Therefore, the group of households we have identified is likely to be broader in fact.

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As regards condition (iii), we consider any values >1.5 to be a “high” ratio. They are therefore the cases when the actually paid rent exceeds the usual rent that would correspond to the market price of a given dwelling by one half. In constructing the implicit rent, we proceed from the values published by Czech Statistical Office that determines the amount of the annual implicit rent as 3.74 % of the market price of a dwelling. The market price of a dwelling is given by an estimate provided by a surveyed household. 3 Results and Discussion In the following chapter we present the main findings of the performed analysis in the following part of the paper. We use mainly descriptive statistics to show that the households we have identified can actually be those that are exposed to the poverty. The basic overview of the current rent to imputed rent ratio is shown in the following figure 1. We can take no account of the households living in their own houses because these households do not pay any rent. Accordingly, the households living in their own flats do not pay any rent to a third person; in their case, the regular payment has a form of contributions to the repair fund. The amount of the contribution is then related to the market price of a flat. Apart from the contributions to the repair fund, owners of cooperative flats can also pay the cooperative loan repayments that are related to the acquisition of a cooperative flat. It is not a standard rent in their case either. The figure shows that the average rent to imputed rent ratio for the above specified households is always lower than 1 and that although there is a difference between the households with and without the Housing Allowance, it only amounts to about 0.25. Figure 1 – Average proportion of the rent and imputed rent of household with and without the Housing Allowance. Source: own calculation.

Contrariwise, the studied indicator differs substantially for the households in rental housing. Naturally, the average ratio of the studied indicator for this type of households is higher than for households in owned homes. The reason is that, in addition to the costs of maintenance of the respective flat, the rent payment also includes the price for the rented flat paid to the owner of the flat. The average ratio of the actual rent to the imputed rent thus amounts to a value of 1.26 for the household that does not receive the Housing Allowance. Contrariwise, the average value of the studied indicator for the household that is entitled to the benefit amounts to 2.69. Of course, a question arises why the difference in the studied indicator for the households with and without the entitlement to the benefit is 0.25 for the households in owned homes and 1.43 for the households in rental housing. The table in the appendix shows a detailed picture of the households presented in the previous figure. The table implies that the ratio of the actual rent to the imputed rent for 24.9% of the households in rental housing that do not receive the Housing Allowance is higher than 1.5. In this case, they are households that voluntarily pay a rent higher than the corresponding imputed rent. However, the average amount of the rent for the households in rental housing that are not entitled to the Housing Allowance practically does not differ taking into account various levels of the actual/implicit rent ratio that we study. Then, it is probably quite natural that there are households that pay their rent in an amount higher than the sum that would correspond to the amount of the imputed rent; this is related rather to the amount of the imputed rent than the actual rent. The situation is completely different in the case of households that receive the Housing Allowance. These households generally pay a higher rent; however, there is an absolutely substantial difference in the case of the households in the group selected by us (52.3% of the households in rental housing with an entitlement to the Housing Allowance); their average amount of the actual rent per m2 amounts to the highest values from all the studied households. Furthermore, the descriptive statistics implies that the households identified as SEL have a higher number of members and dependent children, a low number of economically active persons and, on the other hand, the highest number of the unemployed. If the proportion of the households that we can describe as households with a low level of education (without or elementary education) is about 8%, it is nearly 48% in the group selected by us. The housing quality itself we can say, that the SEL households have considerably more serious problems with the quality of their flats (individual indicators or the aggregate Housing Deprivation indicator) than the other types of 73

households. Accordingly, these households have similar problems with the household material deprivation and the ability to pay their bills. The composite index of material deprivation for the selected group of households achieves much higher values that for the rest of households. Furthermore, it is startling that about 37% of the households from the selected SEL group have had rent debts in the past 12 months. We conclude the descriptive statistics by providing information about the regional distribution of households comprising the group we have selected (see the following table 4). The analysis has shown that the households that are likely to become exposed to the poverty business really live, to a greater extent, in the regions that are generally considered to be regions with a higher concentration of socially excluded communities. It is especially given by economic problems of a structural character existing in these regions (in particular recession of the heavy industry). These households relatively more often live in small to medium municipalities that have no capacities to solve their situation efficiently. Not only do they not have financial means, they often do not have the necessary housing stock either or the personnel and professional capacities that would enable to find and enforce a suitable solution. Table 4 – Household and Housing Allowance paid distribution according to regions Selected All households households REGION [frequency in %] [frequency in %] Prague 13.4 9.7 Central Bohemia 11.7 2.2 South Bohemia 6.1 7.2 Pilsen 5.6 2.2 Karlovy Vary 3.0 11.5 Ústní nad Labem 7.9 20.7 Liberec 4.1 4.7 Hradec Králové 5.3 0.0 Pardubice 4.8 0.0 Vysočina 4.7 1.0 South Moravia 10.8 1.1 Olomouc 5.9 0.0 Zlín 5.2 0.0 Moravia-Silesia 11.7 39.5 Total 100.0 100.0 Source: own calculation.

4 Conclusion We showed in our paper that the interplay of individual parts of the housing policy led to a situation when some households pay an inadequately high rent which the state considerably contributes to. As a result, benefits towards housing significantly grew between 2007 and 2014 in the Czech Republic. The Czech society perceives entrepreneurs making profit on people in poverty as persons who enrich themselves on the Czech social security system by abusing poor households. Of course, the problem can be also seen from another point of view. These entrepreneurs are the only ones who currently deal with the poverty problem, creating an alternative to the social policy of the state in the area where the state abandoned its position in the past years. We showed in our paper that although the problem concerns about 1% of Czech households, consequences of a failure to solve the situation can be critical for both the citizens themselves and the public sector. The households affected by the problem pay higher rents while the quality of their housing rather corresponds to much lower rent levels. Because in most cases they are fully dependent on social benefits, their motivation to solve their own situation by means of incomes from economic activities is very low. As the authors of the paper we realise that the paper is, to a considerable extent, descriptive and even normative in some places. It is our first version of the paper that deals with the situation being described. We will therefore be glad to hear from the discussant or other participants in the Public Economics and Administration 2015 conference how to increase the quality of the paper in its following versions. We will welcome every opinion and assistance. Acknowledgements The authors are thankful to the Grant Agency of Masaryk University for the grant No. MUNI/A/1232/2014. References [1] JAHODA, R., ŠPALKOVÁ, D. (2009). Analyzing the Distribution Aspects of Rent Regulation/Deregulation in the Czech Republic, Urbanismus a zemní rozvoj, 12 (4): 28-37. [2] JAHODA, R., ŠPALKOVÁ, D. (2012). Housing-induced Poverty and Rent Deregulation: A Case Study of the Czech Republic, Ekonomický casopis / Journal of Economics, 60(2):146-168. [3] MPSV (2014). Measures adopted by the Ministry of Labour and Social Affairs in respect to subjects making profit on people in poverty. Unpublished. 74

[4] HATEFREE (2014). Výzkum: Mladí neměří Romům stejným metrem. [online]. [cit.2015-05-15]. Available: http://www.hatefree.cz/vyzkum-mladi-nemeri-romum-stejnym-metrem [5] CZSO (2014). Příjmy a životní podmínky domácností - 2014. [online]. [cit.2015-05-15]. Available: https://www.czso.cz/csu/czso/prijmy-a-zivotni-podminky-domacnosti-2014

Contact information doc. Ing. Robert Jahoda, Ph.D. Masaryk University Lipová 41a, 60200 Brno Czech Republic [email protected] doc. Mgr. Jiří Špalek, Ph.D. Masaryk University Lipová 41a, 60200 Brno Czech Republic [email protected]

Appendix

1

2

3

4

5

6

Total

0-1 1 - 1.5 1.5 Total 0-1 1 - 1.5 1.5 Total 0-1 1 - 1.5 1.5 Total 0-1 1 - 1.5 1.5 Total 0-1 1 - 1.5 1.5 Total 0-1 1 - 1.5 1.5 Total 0-1 1 - 1.5 1.5 Total

1609.8 0 0 1609.8 1119.5 41.9 32.2 1193.7 315.5 53.9 31.8 401.1 324.3 136.0 152.8 613.1 1.7 0 0 1.7 148.4 1.3 0.5 150.1 3519.2 233.0 217.4 3969.6

100.0 0.0 0.0 100.0 93.8 3.5 2.7 100.0 78.6 13.4 7.9 100.0 52.9 22.2 24.9 100.0 100.0 0.0 0.0 100.0 98.8 .8 .3 100.0 88.7 5.9 5.5 100.0

0.0

0.0 34.6 123.7 226.8 42.9 44.8 120.6 241.5 70.5 64.4 122.4 260.5 126.2 6.4

6.4 2.9 106.1 342.4 4.8 21.1 122.2 252.9 39.7

15.3 0.0 0.0 15.3 19.0 1.7 1.2 21.9 9.9 1.7 2.2 13.8 18.6 16.3 38.2 73.1 0.0 0.0 0.0 0.0 2.8 0.0 0.0 2.8 65.6 19.7 41.6 126.9

100.0 0.0 0.0 100.0 87.0 7.6 5.4 100.0 71.8 12.4 15.8 100.0 25.4 22.4 52.3 100.0 0.0 0.0 0.0 0.0 100.0 0.0 0.0 100.0 51.7 15.5 32.8 100.0

0.0

0.0 52.2 118.4 237.6 67.3 58.8 110.3 248.5 95.2 67.1 123.9 429.4 269.1

7.0

7.0 43.3 122.3 414.4 177.1

1625.1 0.0 0.0 1625.1 1138.5 43.6 33.4 1215.5 325.4 55.6 34.0 414.9 342.9 152.3 191.0 686.2 1.7 0.0 0.0 1.7 151.2 1.3 0.5 153.0 3584.8 252.8 258.9 4096.5

100.0 0.0 0.0 100.0 93.7 3.6 2.8 100.0 78.4 13.4 8.2 100.0 50.0 22.2 27.8 100.0 100.0 0.0 0.0 100.0 98.9 .8 .3 100.0 87.5 6.2 6.3 100.0

Average proportion of the rent and imputed rent [in %]

Column N %

Count [in thousands]

Average proportion of the rent and imputed rent [in %]

Column N %

Count [in thousands]

Average proportion of the rent and imputed rent [in %]

Column N %

Is the household eligible to Housing Allowance in SILC 2013 (income reference year 2012)? NO YES Total

Count [in thousands]

Proportion of the actual rent and imputed rent

Tenure status

Table: Household distribution according tenure status, HA eligibility and the proportion of actual and imputed rent.

0.0

0.0 34.9 123.5 227.2 43.3 45.2 120.3 242.0 71.4 64.6 122.6 294.3 141.4 6.4

6.4 3.0 106.1 342.4 4.9 21.5 122.2 278.8 44.0

Source: own calculation.

75

Consequences of the Czech Housing Market Deformation Hana Janáčková Abstract Housing can be classified as basic human needs. Purchase of adequate ownership housing is important investments for most households. For rental housing households must consider the part of rent expenditure paid in the total household income. For this reason, financial considerations of households in this area depend on the activities of the state (public administration) in housing - on housing policy. Market system of housing allocation, whether ownership or tenancy, is based on the fact that housing is a scarce good. Its allocation is based on supply and demand. The market system in the area of housing can sometimes have a negative impact on some households, the market is unable to satisfy certain groups of the population that are not able or willing to accept market price. For these reasons, there is a more or less regulation of the market. Regulation is both on the demand and supply side, and the government determines the rules of behaviour for all economic entities of the housing market. This article submits results of analysis of selected regulatory interference of the Czech state in the Czech housing market and assesses their implications deforming the market. The first part describes tools of supports and the second part discuses deformations and analyses their consequences on the supply side of housing market and on demand side. Keywords: housing, housing market, regulation JEL Classification: D82, D01, D04 1 Introduction The goal of many market economies, and, specifically, housing policies is firstly to create a stable, more developed, and particularly more efficient housing system enabling each household to find housing matching its socio-economic situation. And secondly, to increase overall housing affordability for households. Market system allocating home ownership and rental housing is based on the fact that housing is a commodity. Its allocation is based on supply and demand. In a pure market system, household expenditures on housing should reflect the actual cost of acquisition, maintenance and administration of housing in the given locality. Impact of the market system in the housing sector may be highly negative in the social sphere if the market is unable to satisfy certain groups of the population that are not willing or able to accept the market price, and therefore they lack housing affordable for them. We are talking about a market failure. Other social issues may include postponing starting a family or a decrease in the number of births per woman, or the concentration of certain households, and possibly price fluctuations compared to the usual price of housing in the immediate vicinity. These fluctuations can be in both directions. For these reasons, more or less regulated housing market exists virtually in all industrialized countries (including the Czech Republic). State intervention in the market should, however, be implemented so that they do not hamper its functioning. In principle, there are two ways the state can through redistribution of wealth and income ensure greater equality in the housing market, thereby ensuring increased availability of housing for low and middle income groups of households: the demand strategy – individual targeted subsidy rising income of needy households, or the bidding strategy – hosing benefit reducing the price of housing and subsequently reducing costs of needy households –subsidies for construction, modernization, and operation of social housing leading to the determination of the amount of rent below the market value). Increase or decrease in social welfare. Programs and living concepts in most industrialized countries are not uniform. These include measures in the sphere of land management policies, financing, subsidies, tax rebates, sufficient information for all market participants, etc. The previous literature investigating the correlation both between house prices changes and consumption changes focuses and between house prices and credit constraints. Both source of literature represent widespread empirical finding. The first literature explains that changes in house prices affect household wealth. Recent papers based on data supporting this hypothesis include Muelbauer and Murphy (1990), Campbell and Cocco (2007) and Browing et al. (2013). The second hypothesis is that both consumption and house price are influenced by common factors. Expectation about productivity growth affect wages and expected income over the life cycle. (King 1990; Pagano 1990). These common factors may affect both consumption and house prices in the same direction. The third explanation focuses how house price increases may generate additional equity and thereby improve the possibility for owners to borrow against their housing equity Muelbauer and Murphy (1990) and Campbell and Cocco (2007). So that a lot of authors don´t focus so much too attention of housing price deformation problems the aim of that paper is to describe deformations of Czech housing market and analyses their consequences on the supply side of housing market and on the demand side. The method of analysis, comparative and descriptive methods and method of induction at processing primary resources are used in this paper. This issue is addressed using Ministry of Regional Development (2014, 2015) data of Czech Republic spending on housing from 2008–2014. First, the article focuses on strategies of support for housing. The pros and cons of each strategy are discussed. The current support tools for housing in the Czech Republic are described and analysed. A trend that can be observed 76

recently in the Czech Republic, is a retreat from the across-the-board support to individual instruments – specifically focused. The final part of the article is devoted to the issue of the housing allowance and supplement. 2 Housing support in the Czech Republic The tools offering supply strategy to support the housing market in the Czech Republic include programs supporting construction of rental housing and technical infrastructure owned by municipalities, which are intended for lower and middle income groups of households. It is also possible to include programs to support the construction of nursing homes. Loans to individuals and legal entities for the repair and modernization of residential buildings, programs to support housing fund repairs and regeneration of prefabricated housing are intended for all owners: municipalities, private for-profit and non-profit investors, and households. Extensive use of these tools is often criticized for its low efficiency in the provision of special needs in housing for the lowest income households. The instruments of demand strategies include individual subsidies to satisfy social needs of households. The purpose of these subsidies on the demand side is to reduce housing expenses from the disposable income of households and provide the necessary relation in consumer spending of individual income groups of households. The main tools in this area in the Czech Republic include equity subsidies, allowances and additional payments for housing, tax relief. 1. Equity subsidies relate primarily to the acquisition or renovation of home ownership. It is an interest subsidy of mortgage loan to households, supporting building society account savings, subsidies to reduce the energy intensity of housing, interest subsidies for legal persons (Community of owners, housing cooperatives). 2. Tax relief in housing can have various forms. The most common procedure is a basic deduction of interest on loans contracted for the purchase of dwellings from the basis for calculating income tax. Furthermore, it is a property tax (immovable property tax in the Czech Republic). There may be a temporary exemption from certain taxes (for some time after final approval). 3. The tools of supporting the demand side of housing include a housing allowance and from 2007 housing supplement. The system of a housing allowance and housing supplement has its advantages, especially when compared to the across-the-board and object subsidies: directness, its provision allows owners of rental houses normally manage the housing stock, even if his tenants belong to socially disadvantaged households, and it can be flexible if properly defined – its disbursement can respond quickly to changes in the financial situation of individual households as well as to extensive changes in living standards in society. Such aid or non-insurance benefits (they are paid from taxes and by employment offices) generally do not aim to promote housing construction; they only address the availability of housing for low-income groups of households. Therefore, they result in an adaptation of the relationship between household income and its expenditure on housing. A considerable increase in the importance of the housing allowance and housing supplement is mainly related to the period when the main problem ceases to be a housing shortage, and it is the housing affordability – particularly for vulnerable households. Development of such housing aid is mainly connected with:  changes aimed at reducing public spending in all areas and hence in the sphere of housing,  the improvement of the overall situation in the housing sector and the rising living standards of the population, allowing to focus the state aid primarily on really needy households,  the change of policy, consisting in a departure from the prevailing supply and support programs and focusing on supporting the demand side and preference selection principles in aid,  greater use of market mechanisms in housing and the simultaneous increase in the costs of living. The negative characteristics of these housing subsidies include: creating long-term budgetary commitments, their disbursement may result in increased demand in the housing market and the market rents because they increase purchasing power of the population. At some point, this increased demand may lead to raising housing prices (depending on the elasticity of the demand). A considerable disadvantage is the large administrative burden of the system. Problems can also be associated with the need to coordinate with the overall social security system on the one hand, and other supportive measures in the housing sector on the other hand. The drawback may be an anti-stimulation effect arising when the allowance does not force its recipients to seek adequate housing or discourages them from increasing their income. If the contribution is not limited, its provision may cause the owners of the blocks of flats to raise rents “with impunity” without causing population mobility towards finding affordable housing. A last disadvantage can arise from the combination and synergy of the aforementioned disadvantages. The conditions of entitlement to a housing allowance in the Czech Republic is regulated by § 24 of Act no. 117/1995 Coll., On State Social Support, as amended. The current system of housing allowances in the Czech Republic takes into account household income, and it does not take into account household wealth, it takes into account housing costs exceeding the amount of the product of the decisive income in the family and a coefficient of 0.30. The amount of the housing allowance is determined as the difference between the cost of housing (normative housing costs) and a multiple of applicable income and coefficient of 0.30 (0.35 in Prague). Payment of housing allowance is limited to 84 months during the last 10 calendar years. The housing allowance is linked to permanent residence and lease contract.

77

The housing supplement is paid on the basis of Act no. 111/2006 Coll., On Assistance in Material Need, as amended, which came into force with the beginning of deregulation of rents in the Czech Republic, which ended completely as at 31 December 2012. Housing Supplement is a non-insurance benefit. This benefit in material need is to address the lack of income to cover housing costs if income including the housing allowance from the state social support system is not sufficient for the person or family. The benefit is provided to a tenant or flat owner who is entitled to a living allowance. The amount of the housing supplement is established so that after paying justified housing costs (i.e. rent, services related to housing and energy costs) the person or family has subsistence amount left. The payment of the housing supplement is for a limited period, like the housing allowance. Since the beginning, the housing supplement has been provided for tenants of the entire flat, but according to Section 33-35, Subsection. 2 of the Act no. 111/2006 Coll., On Assistance in Material Need also for tenants of residential rooms in facilities intended for permanent housing. This provision has caused the emergence and expansion of so-called “hostels” in the Czech Republic, with all its implications, see below. The provision was annulled as at 1 January 2014. The housing supplement, however, is not still bound to permanent residence. 3 Results and their Discussion Before we continue, it is worth mentioning that on 31 December 2012 the possibility of unilateral increase in rents was ended by Act no. 107/2006 Coll in the Czech Republic. After more than 20 years, so called rent control was cancelled. Henceforth, changes in the rent may be to negotiated on the basis of an agreement between the lessor and the tenant. The first step in any analyses of consequences of the Czech housing market deformation is naturally the remuneration. All support programs in the Czech Republic, and the financial amounts derived from the budgets of state institutions are analysed from 2008 to 2015. Aid schemes are divided according to whether they are intended to support the supply side or the demand side. From Table 1 it is evident that, although housing policy in the Czech Republic falls in principle within the competence of the Ministry of Regional Development, its role in terms of allocation of state finances is marginal. Totally inefficient allocation of competences between the sectors of the Ministry of Finance (hereinafter MoF), Ministry of Labour and Social Affairs (hereinafter MoLSA), Ministry of Regional Development (hereinafter MRD), Ministry of the Environment (hereinafter MoE), State Housing Development Fund (hereinafter SHDF) and State Environmental Fund (SEF hereinafter) is completed by prioritizing the “power” ministries in the areas of expenditure in housing. According the stated statistics, housing expenditures in 2015 will be nearly 23,000 million CZK, i.e. about 2.2 % of the national budget expenses. The share of expenditure on housing in the formation of the nominal GDP of the Czech Republic in 2014 amounted to 0.47%. [5] [7] Subsidies arising from the Czech public budgets go through MRD and SHDF, MF, MoE and SEF, but the largest amount directed to housing comes from MoLSA (62 %, i.e. 14.3 billion CZK in 2015), see table 1. It can be stated that the current housing policy does not fall only under one ministry. The ministries support both the supply and/or demand side of the housing market. 3.1 Supports for the supply side and their consequences Now we will look closely at the different instruments of supply support that are currently used, which sources of funding arise, and what is the impact on the market and the behaviour of individual economic entities. First, the table shows the development of these support tools since 2014 with the assumption of the approved budget for 2015. After a long period of recession (2009 to 2014), the municipalities, which had to face a loss of revenue in their public budgets, and on the contrary increases in spending, considerably reduced or completely stopped new construction of rental flats owned by municipalities (decrease in aid from MRD from 101 million CZK in 2009 to 21.85 million CZK in 2015). Newly implemented programs to support the construction of subsidized apartments, enabling that means can be drawn by all owners, i.e. physical and legal entities, and municipalities. In 2015, the planned expenditure of MRD amounts to 426.77 million CZK. Finally, there are temporary support programs planned only for a limited number of years. These programs support the construction for people affected by a natural disaster. SHDF has grant and loan programs to cover the costs associated with residential construction and modernization of housing. It is about 1,000 million CZK per year. There are arguments and critical opinions that support on the supply side, through the construction and modernization of flats may be ineffective – the cost of construction due to missing market equalization processes can be higher than in the case of the free market effect (overpriced purchases of building materials and construction work), as well the problem with administrative allocation of subsidies. On the other hand, the supply form of support is associated with lower administrative costs than direct subsidies paid based on examining the income and financial circumstances of applying household (to stimulate demand) and less likely stigmatization of users of this type of state aid. 3.2 Support for the demand side and their consequences The support for mortgage loans comes from the MRD. This is the amount of 28 million – 48 million CZK per year. Supporting building society account savings falls under the Ministry of Finance, and after legislative changes, the support decreased from 14,220 million CZK in 2008 to assumed 5,200 million CZK in 2015. 78

The negative characteristics of these two forms of housing support can be seen in the creation of long-term budgetary commitment, payment may result in increased demand in the market, because it means increasing purchasing power of households. The equity subsidies also include support for improving the energy performance of housing. These programs can include the Green Savings program (2009-2012), New Green Savings (2013), and New Green Savings (2014-2020), where the funds come from MOE through SEF. The intention is to reduce the energy intensity of buildings, thereby reducing operating expenses related to housing (electricity, gas, water, heat), which have shown much greater growth since 1990 than inflation in the Czech Republic. The support is aimed at both the existing housing stock and new construction. [6] The costs are very volatile (for example, in 2012 it was 9,108 million CZK, but in 2014 the expenditure was 195 million CZK). The expected amount for 2015 is 700 million CZK, see table 1. According to the owners who apply for the support, one of the potential drawbacks of these programs is the fact that it is necessary to finance the entire investment first, and subsequently, a portion of the funds is returned to the investor according to the energy savings. Some entities cannot even submit such requests due to lack of funds. Municipalities and companies have the advantage that they can apply for a subsidy from EU funds (the revitalization of objects). Households do not have this possibility. The result in the local markets may be increase in the cost of labour and building materials due to the growth in demand for renovations; the entities that receive subsidies may not behave effectively and try to decrease the price when concluding of the contract, because they receive part of the resources. Another consequence may be the lack of building capacity in the short term, however, due to the seasonality of construction works, the start of work can significantly shift or prices may be raised for the prioritized construction works (inelastic supply in the short term). Finally, there may be an asymmetry of information (covert activities and information) on the part of construction companies, when they have more information about their opportunities, capacities, quality of construction materials and labour. The average return on investment in revitalization, energy efficient buildings is on average 11 to 13 years. Subsidies are provided for precisely predefined areas. In recent years, it is the case of the so-called “boiler subsidies”, provided to homeowners, using solid fuel boilers from the Moravian-Silesian, Pilsen, Central Bohemian, Usti and Hradec Králové Regions since 2013. Subsidies are provided within the Environmental Operation Program for 2014 – 2020. The objective of this Joint Program to support the replacement of boilers is to reduce air pollution from small combustion sources up to heat output of 50 kW, i.e. local heating systems using solid fuel. The subject of the grant is to replace the existing manually filled solid fuel boilers with new efficient low-carbon heat sources. However, again for the solid fuel boiler. Tax relief in an ownership housing sector has so far failed to provide figures in the Czech Republic. In fact, these expenses are higher: after accounting for losses from indirect fiscal support (tax deductions, tax exclusion). Housing support programs are often changed in the Czech Republic and we cannot talk about the steady development of such aid in the future. Thus, as already mentioned, an important form of indirect subsidy, which is applied in the area of home ownership in the Czech Republic, is the income tax reduction through the interest on the mortgage loan repaid. The volume thus granted tax relief is really great, see above. But the question is whether this relief really helps to stimulate development of home ownership and who is supported by it. The surveys, which were carried out on this subject, quite unambiguously shows that tax relief directed to the property sector, favour higher-income segments of the population; therefore, their distributive effect is rather negative because it increases the gap between social strata of society. And if they are once introduced, they are difficult to remove, since they are associated with a strong group of potential voters. However, restricting these negative consequences, which are particularly noticeable in combination with a strongly progressive tax system, is possible by determining the income ceiling limiting provision of tax relief; this approach is already applied in some European countries. The increase in the expenditure spent on the housing allowance and housing supplement is very rapid. For 2015 it is planned to spend 58.7 % of the planned total expenditure of the state on housing, i.e. 13,500 million CZK (in 2008 these expenses amounted to 2,091 million CZK). Since 2008 until 2015, these expenditures have increased almost 6.5 times, see table 1! In 2008, supporting building society account savings amounted to 14,220 million CZK and it has gradually fallen to 5,200 million CZK in 2015, see Table 1. Support for mortgage loans amounted to 47.7 million CZK in 2008 and the level of aid in recent years is fluctuating; in 2015 it is scheduled to spend 28 million CZK, see Table 1. From the above it can be stated that in recent years, the state replaced the demand-oriented support strategy of supporting building society account savings with spending on housing allowances. It can partly be explained by the fact that rent regulation was finished as at 31 December 2012, which caused a concern that low-income households might be left without affordable housing or elderly citizens would have to move after deregulation in old age. We will focus below on how increasing this tool of supporting demand was reflected in the behaviour of economic agents in the market. Before we continue, it is necessary to look at the definition of the concept of social housing.  The narrowest concept has mostly the form of public rental housing, which means rental housing stock, which is owned by municipalities or other public bodies. This is such a market segment that should be designed for the lowest income households or housing designed to tackle the housing shortage escalated in various social situations. Allocation is performed not on the market principle, but according to the administrative system, 79

which the institution determines by its internal regulation. The rent covers only part of the cost, eliminating the profit. The loss is covered from the public budget intended for social purposes.  In a broader sense, social housing includes rental housing stock owned by non-profit organizations (i.e. private bodies) and various forms of cooperative housing.  Finally, a broadly worded definition depending on the method of financing, understands social housing as any housing whose construction or operation was to some extent supported from public funds (including, therefore, private ownership and rental housing, using support from public funds under specified conditions). With such a co-investment, most municipalities (public institutions) disclaim any possibility to influence the selection of tenants and rents. In the Czech Republic, owners and operators of social rented housing are currently municipalities (towns and cities) that provide rental housing within the framework of their housing policies, helping to solve the housing problems of its territory. Apart from them, to a lesser extent, social housing in the Czech Republic is also provided by a variety of nonprofit, i.e. public benefit organizations whose goal is to provide quality, affordable housing (with reasonable, mostly economical rent) and evenly manage (often with state support) their property. They also include various charitable organizations, clubs, etc. Finally, in recent years, private natural or legal persons engaged in business for profit greatly expanded the provision of social housing, and it is due to increased spending on housing allowances and supplements. The typology of social housing by M. Harloe distinguishes two basic models of social housing (Harloe, 1995). The first model is a mass social housing, characterized by extensive programs of social rented housing, which is designed for a relatively wide layers of the population. This model, according to the author, is connected with the increase in public expenditure and high levels of state intervention in the housing sector. The second model is called the residual one and is characterized by narrower programs aimed at lower-income households. It is applied during the period of the highlighted role of the private sector in the housing sector and in the period of budget cuts in the sphere of housing. The above-mentioned concepts should be understood as the extreme limits of the spectrum in which the approaches of individual countries range. Regardless of these different approaches, however, the aid in the form of non-profit rental housing should always be focused on disadvantaged population groups, whose temporary or permanent impairment of the economic situation is associated with certain stages in the life cycle of a family or with health problems, etc. At present, the form of social housing in the Czech Republic is based on a broad definition of social housing, see above. The current legislation allowed the emergence and expansion of so-called hostels, where only a room is available for rent, or accommodation is offered for the amount per person per month. The accommodated people usually obtain all of those rents in the form of the housing allowance and mainly the housing supplement. These allowances and supplements are addressed to people but they are often transferred directly to account of the owner of the hostel. There is a concentration of problematic population at one place. Finally, it should be noted that the housing allowance is linked to permanent residence and lease contract, while the housing supplement is not bound to permanent residence. The impacts of this housing support:  Increasing rents – households, which will receive the housing allowance and/or the supplement have higher buying power in the rent market compared to households whose income is predominantly a taxed salary. Working household are often forced into contracting higher rents that are being deformed due to effective demand of households dependent on these benefits. Therefore, the rents in hostels and flats where the tenants are recipients of benefits are higher than the usual price of rents in the locality. However, the quality of housing is often in the original condition or lifetime limit. Dominant owners of flats in the area and owners of hostels often advertise offer to help tenants arrange these benefits. Because the current system allows to pay almost any rent through benefits, this causes a spillover of state spending on private accounts of owners of flats and hostels.  The concentration of low-income population, which mostly consists of jobless people. Hostels are occupied by people with very low or no income or in great debts, mostly unemployed or working illegally;  increased crime rate in the surroundings of hostels and also increased need for movement and intervention of the police in the area (disturbing public order, civil coexistence, crime rate, drug issues);  constructional and technical condition of hostels is very neglected and often lacks any restorative maintenance and compliance with hygiene standards;  influx of providers of inferior services and goods (bazaars, pawnshops, casinos, betting shops) near the hostels  very rapid outflow of companies from the area (compared to households, businesses are highly mobile and their rapid outflow is motivated by concerns of possible theft or concerns about the loss of clients who do not want to come to the area with the increased incidence of crime and the presence of problem population);  permanent dissatisfaction of the population (original - permanent residents);  their outflows from the locality over a longer period – increasing the supply of properties for sale;  the associated reduction in the normal prices of residential immovable property in the area;  almost zero possibility of municipalities to control the creation and operation of hostels in their territory. A debate can be lead whether this latest concept of social housing, i.e. the provision of rental housing for socially needy households, is fulfilling its purpose, or whether there is a spill over of wealth to private providers of housing from the public budget. The amendment to Act no. 111/2006 Coll., On Assistance in Material Need still ensures the right to housing supplement as per section 33 to 35 for the owner of the apartment, who uses it, or any other person and their family members 80

(spouse, minor children) using the flat on the basis of agreements, decisions or other legal title. In these cases, the municipality is obliged to inform the competent authority in aid in material distress at its request whether the person ask it for assistance in obtaining adequate housing, whether the person was offered such housing on the part of the municipality, and whether this offer was accepted by the person. The housing supplement is provided for the use of a flat, or other living space and accommodation. The Act newly defines the housing standards. [8] As at 1 May 2015 there has been a recent change of Act no. 111/2006 Coll., On Assistance in Material Need; the housing benefits (the housing allowance and supplement) continue to be paid by employment offices, but the new condition is approval by the relevant municipal authority, confirming that the recipient actually lives in a hostel. When the Employment Office asks the municipality for “confirmation”, the municipality issues the confirmation based on the supplied data, or not. The municipality may take into account whether the applicant for the benefits has no debts to the city or municipality, whether s/he is a permanent resident of the place, the number of offenses at the city police, the applicant should have at least one year of employment, etc. Municipalities have recently complained that they only receive information on the applicant's name and the name of the hostel from the Employment Office. Municipalities do not know whether the applicant had worked or not, whether it has a criminal record, etc. Legal enactment enabling the municipality to decide on applicants without supporting documents appears to be almost meaningless and does not solve anything, on the contrary, it increases administrative costs. There is also concern (whether justified or not) that it will create more homeless people who will not get these benefits. 4 Conclusions The paper presented the results of an analysis of selected regulatory interference of the state in the housing market and assessed their implications deforming the market. First, the article focused on strategies of support for housing. The pros and cons of each strategy were discussed. The current support tools for housing in the Czech Republic were described and analysed. A trend that can be observed recently in the Czech Republic, is a retreat from the across-theboard support to individual instruments – specifically focused. The final part of the article discussion was mainly devoted to the issue of the housing allowance and housing supplement. References [1] BROWNING, M. et al. Housing wealth and consumption: micro panel study. The Economic Journal, 123 (May), pp. 401– 428. [2] CAMPBELL, J. and COCCO, J. (2007). How do house prices affect consumption? Evidence from micro data. Journal of Monetary Economics, 54(3), pp. 591–621. [3] HARLOE, M. (1995) The People's Home? Social Rented Housing in Europe Oxford: Basil Blackwell. [4] MUELBAUER, J. and MURPHY, A. (1990) Is the UK balance of payments sustainable? Economic Policy, vol. 11(3), pp.345–383. [5] JANÁČKOVÁ, H. (2004) Vybrané mikroekonomické charakteristiky trhu bydlení v České republice. FrýdekMístek: SLU – OPF v Karviné. [6] MINISTRY OF REGIONAL DEVELOPMENT. Vybrané daje o bydlení. April 2012. [online]. [cit.2015-06-20]. Available from http://www.mmr.cz/getmedia/6035d611-ac2b-4de4-9e4b-580d1f6e10cf/vybrane-udaje-bydleni-2012.pdf [7] MINISTRY OF REGIONAL DEVELOPMENT. Vybrané daje o bydlení. May 2014. [online]. [cit.2015-06-20]. Available from http://www.mmr.cz/getmedia/0f40fca0-0fb5-4fb3-b7ec-9fe33f7bc67f/Vybrane-udaje-bydleni-2013.pdf [8] MINISTRY OF REGIONAL DEVELOPMENT. (2015) Vybrané daje o bydlení. May 2015. [online]. [cit.2015-0620]. Available from http://www.dustojnestarnuti.cz/res/data/006/000782.pdf [9] STATE ENVIROMENTAL FUND. Společný program na podporu výměny kotlů. [online]. [cit.2015-06-20]. Available from https://www.sfzp.cz/sekce/697/spolecny-program-na-podporu-vymeny-kotlu/ [10] CZECH STATISTICAL OFFICE (2015). Database of Annul National Accounts. [online]. [cit.2015-06-20]. Available from http://apl.czso.cz/pll/rocenka/rocenka.indexnu?mylang=EN [11] Act no. 111/2006 Coll., on Assistance in Material Need, as amended. [12] Act no. 117/1995 Coll., on State Social Support, as amended.

Contact information Ing. Hana Janáčková, Ph.D. VŠB - Technical University of Ostrava Sokolská třída 33, 701 21 Ostrava 1 Czech Republic [email protected]

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Appendix

Prefabricated housing regeneration Support for the construction of rental flats and technical infrastructure owned by municipalities Support for the construction of subsidized apartments Support for replacing lead water pipes water in residential buildings Support for the construction of council housing for people affected by natural disasters Support for the provision of temporary alternative accommodation and other related equipment as a result of floods or other natural disasters Support for mortgage loans MRD in total Subsidies to cover part of the costs associated with the construction of flats for persons with limited incomes - NV 146/2003 Coll. Subsidies investors and providers of rental housing (social housing, housing support in small municipalities) NV no. 333/2009 Coll. PANEL program - NV 299/2001 Coll. - Interest subsidies, novellas. NV 325/2006. Grants to owners of prefabricated houses and apartments for repairs - NV 63/2006 Coll. Subsidies for the construction of cooperative housing - Act 378/2005 Coll., NV 465/2005 Coll. Loans for the construction of cooperative housing Act 378/2005 Coll., NV 465/2005 Coll. Loans to municipalities for repair and modernization of flats - NV 396/2001 Coll. Loans for construction of dwelling persons ml. 36 years - NV 97/2002 (up to 200 ths. CZK) Loans for purchase of housing for young people up to 36 years - NV 616/2004 (300 thous. CZK) Subsidies on loans ml. people in the construction or acquisition of housing Loans for home building phys. Persons affected by the floods - NV 396/2002, 28/2006 (repair and reconstruction of housing Loans and grants to municipalities for repair and modernization of housing fund - Floods in 2009, NV 396/2001 Coll. Loans for housing modernization young people up to 35 years - NV 28/2006 (up to 150 ths. CZK) Loans to individuals and legal entities to support the construction of rented flats according NV no. 284/2011 Coll. Loans physical and legal persons for repair and modernization of residential buildings according NV no. 468/2012 Coll. SHDF in total

2015 budget assumption

2014

2013

2012

2011

2010

2009

2008

Table 1 Czech Republic spending on housing (million CZK)

181,661

183,016

149,984

231,297

180,418

142,392

194,102

110,99

89,463

101,065

94,644

37,350

34,370

22,033

13,000

21,850

118,567

120,581

165,729

124,237

257,359

192,261

241,530

426,77

24,612

10,839

6,520

5,850

3,210

8,285

9,431

10,49

x

50,600

16,413

11,136

x

x

x

27,50

x

64,380

87,773

0,060

x

x

x

X

47,677

27,461

41,546

47,984

41,883

33,995

21,575

28,00

461,980

557,942

562,609

457,914

517,240

398,966

479,640

625,60

135,60

31,69

11,499

x

x

x

x

x

x

12,89

35,955

7,196

3,301

x

X

754,54

827,37

909,84

913,40

919,65

898,07

876,490

859,30

140,00

2,700

x

x

x

x

x

x

15,60

x

x

x

x

x

x

x

94,980

30,170

x

x

x

x

x

x

40,560

15,220

3,160

15,930

13,519

6,980

5,900

20,00

1,20

x

x

x

x

x

x

x

898,74

815,37

837,72

318,51

5,10

x

x

77,88

86,87

96,00

82,09

73,50

55,60

42,21

0,12

1,88

6,40

5,60

0,299

x

1,00

x

90,14

4,30

1,40

0,00

x

x

150,72

x

x

x

x

0,15

40,33

100,00

x

x

x

0,00

9,65

48,64

153,31

300,00

x

x

x

x

x

254,816

587,54

600,00

597,92

60,00

20,00

2 772,26

2 005,32

1 902,00

1 384,38

1 029,17

1267,56

1706,78

1959,30

Supporting building society account savings Property damage of banks (2014-13 estimate) Total MF) MF in total

14220,12

13261,72

11743,48

10729,04

5290,05

4953,391

4761,00

5200,00

373,53

279,19

231,44

199,78

173,769

141,883

130,00

110,00

14593,65

13540,91

11974,91

10928,81

5 463,82

5095,274

4891,00

5310,00

Housing allowance + supplement since 2007 Contribution to the special aid (to r. 2011 benefit for flat modification, 2015 estimate) Benefit for the use of barrier-free flat

2 091,84

2 791,58

4 207,12

5 491,20

7405,6

10216,7

12092,8

13500,00

65,57

59,78

53,58

55,97

375,50

787,90

805,40

850,00

9,34

8,84

9,53

9,18

0

0

0

0

MoLSA in total Ministry of the Interior (MoI) in total Integration of Asylum Seekers Green Savings

2 166,75

2 860,20

4 270,22

5 556,35

7781,10

11004,60

12898,20

14350,00

8,84

15,65

12,12

16,06

15,97

16,82

9,56

20,00

x

3,29

1 998,81

8 600,24

9 108,10

431,64

62,08

New Green Savings 2013

x

x

x

x

x

x

99,18

New Green Savings call 2014

x

x

x

x

x

x

34,04

MoE - SEF – Green Savings In total MRD+SHDF+MF+MoLSA+MoI+MoE

x

3,29

1 998,81

8 600,24

9 108,10

431,64

195,30

700,00

20 003

18 983

20 721

26 944

23 548

16 275

20 180

22 965

Source: [6][8]+elaborated by the author.

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Cooperative Educational Model Reflecting Graduate Employability on Labour Market as an Indicator of Structural Relevance and the Quality of Educational System Anna Juřicová, Karel Plunder Abstract The educational system and study field supply should reflect economic reality and employer requirements. Decentralization of national economy management, change in the forms of ownership and subsequent change in education management, and the design of educational programmers lead inevitably to the increased need of monitoring the whole system in order to adapt not only to local but also to systemic strategic national needs. The paper focuses on the analysis of possibility to introduce elements of vocational education dual system in the vocational education system in the Czech Republic. Attention is paid to seeking possibilities of the cooperation between employers and secondary vocational schools when preparing students for their future occupations. Efforts are made to find cooperation forms of employer and educational institution cooperation when preparing students for future employment in real work environment. Also creating conditions whereby vocational education will be able to reflect significantly employer requirements and needs well in advance and thus ensuring human resources for employers and future graduate employability on labour market. Through interconnection of functional links and systemic elements the cooperative educational model and educational conditions should be made up and the content of education should get adapted to labor market need. Keywords: Educational system, labour market, graduate rate of unemployment, employability of graduates JEL classification: H 10, H 39 1 Introduction In general, education is regarded as one of the most significant factors that have an impact and play a key role in economic growth or stagnation of a country. It stimulates higher competitiveness of an economy, reflects in the growth of labour productivity or the decrease of unemployment rate and the ability of individuals to get a job on labour market. In the long-term, employers have been calling attention to unsatisfactory level of secondary vocational school graduates who lack necessary competencies. This makes graduate smooth transition to labour market complicated as they do not meet qualification criteria for individual occupations. It is not only a matter of engineering and technology development, but also of the development and changes in corporate culture. The cooperation of educators and practitioners on determining education content, implementing vocational training programmes and practice in real work environment could contribute to good preparation and meeting labour market demanding requirements for graduates. The cooperation of secondary vocational schools and employers is needed on preparing young people for future occupations, however responsibility for education as a whole should be left to schools. The objective of this paper is to assess the implementation of vocational education dual system in the Czech Republic in accordance with domestic traditions, real conditions and legal regulations. The model analyses and compares the possibilities of implementing of at least partial elements of the dual system. The model leads to functional cooperation of educational institutions and employers and enables to study complex phenomena and process elements. 2 Structure and variability of initial vocational education If we focus on initial vocational education, it is perceived as upper secondary education that falls into - according to international education classification - scale ISCED 3 - higher secondary education – which distinguishes two basic types of education:  General education – the content of educational programmes is specialized in less than 25%  Vocational or occupational education – the content of educational programmes is specialized in more than 25 %; such programmes prepare students for exercising specific profession groups and enable to get specific qualifications recognized on labour market. Vocational education starts from the level of upper secondary education that usually begins after compulsory school attendance is completed. At the moment, in the EU countries there are many systems of vocational education and possible specifications fluctuate between two extreme poles. On one hand, there is a vocational educational system with a small share of practice - essentially it corresponds to the vocational educational system in the Czech Republic; on the other hand there is solely a system of dual vocational training where training in firms prevails. The structure and variability of vocational education, management and funding methods in the European countries is very diverse. However, despite the differences in education, economic and cultural conditions in individual countries some general trends can be found. Among them there is democratization of education, gradual linking of general and vocational training; the rate of interconnection between educational institutions and practice is diverse.

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3 The system of vocational education divided according to management roles  key role in the management of vocational education is played by market  key role in the management of vocational education is played by government Combination of these two groups is the cooperative system  vocational education management in cooperation of government and market Some countries cooperate on the system of vocational education management as they recognize that neither market nor government are not fully able to separately and efficiently manage vocational education, and therefore they participate together in the management. Such system of vocational education management is in place in Germany, Austria and Switzerland. In these countries the management structure is clearly determined and involves economic sector that plays an important role and participates in the basic concept of vocational education in the form of contractual share between an enterprise and a student. Which means that students are trained in a specific occupation according to clearly defined training content directly in the company. It can be noted that at seemingly similar initial situation and conditions quite different forms of one system emerged based on structural national specifics. Recently there have been increasing discussions about the possibility to introduce a dual system in our educational system. It needs be taken into account, however, that we should not make a mistake in simple implementation of the dual system in our conditions. We should respect and consider our historical development and uphold tradition that is reflected in vocational education in the CR which should be fostered. Good functioning of the education dual system requires concord of large amount of factors. Among them there is the administration system applicable in practice, efficient administration structures and functional links, compulsory membership in industry associations, legislation support, and quality of management mechanisms, last but not least, the ability to motivate and get young people interested in vocational education. Key elements of vocational education are firms. It is necessary to determine firms' interest in joining the vocational education system, encourage their social engagement in training young people, and for that purpose determine qualitative indicators of such firms' training centers with the aim to create conditions for establishing an efficient network of firms providing high-quality workplaces suitable for vocational education. In established dual systems such functioning network has been created and maintained over a long period. In the CR after 1989, this system of cooperation of vocational schools and employers was broken and, due to economic changes, the cooperation was either terminated or its forms were changed. It will be complicated to continue this cooperation with regard to the fact that also the forms of ownership changed. It is more difficult to build or restore such network of vocational firm workplaces in the countries that strive to continue and restore vanished cooperation forms taking into consideration that such links ceased to exist within the system, and if they persisted, it was largely based on individual efforts and personal relationships. Cooperation systems are missing and enterprises in newly emerged market economies do not have long-term tradition and economic stability. These circumstances should be perceived in a complex way. It needs to be understood and take such measures that are necessary to speed up the introduction of systemic elements that would enable creating, out of one-shot training, module and project activities, a large and sustainable network of social links and firms' training centers that will be strong part of the vocational education system. Measures should be taken that contribute to creating the system of rights and obligations among interested parties and encourage firms' interest in systemic education of students. Such changes should be attractive for companies and should be sustainable. In the Czech Republic, sound legislation support is missing for introducing a functional dual system. The basic principle of functional link and firm and school cooperation in the Czech Republic is the cooperative model of vocational education that takes account of dual system elements, but respects and is based on actual conditions of the CR. It differs from the standard dual system in the field of legislation, finance and student status, see table 1. Cooperative model of vocational education deals with the following issues: 1. legislation support, 2. funding possibilities, 3. student education in practical matters a) getting required output in the form of school and employer participation in the content of educational programmes and their implementation, b) professional training timeframe, c) method of final examinations.

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Table 1 Comparison of Dual System with the Cooperative Model of Vocational Education Dual system Cooperative model of vocational education amended by a separate act specifying the rights and can be implemented within existing legislation Legislation obligations of interested parties framework with just smaller legislation amendments student has double status: he/she concluded an employee contract with the enterprise; he/she is a school student status remains Student status student in the school responsibility for final exams remains up to schools; final exams are secured by employers or their Responsibility for employers take part in exams are members of associations final examinations examining committees employers bear most of the student vocational multi-source funding (government, employers) Funding training cost Source: NUV – National Education Institute - project POSPOLU.

At the moment, conceptual actions are being prepared for implementation of this cooperation model and preparation of professional for labour market. Individual measures supporting school and employer cooperation are being introduced – the elements of cooperative model. 4 Cooperative model The word derives from the Latin model - modus, modulus - and reflects the degree pattern, a possible way of solving“1. By (Bacik 1977, p. 323) a model is "building a character that is able to substitute object to be examined so that the study provided new information on the object." The model is also portrayed by analogy creation, while not capturing all of the original, but only those parts that appear relevant. Let us examine complex phenomena such as systems. The development of engineering and technology is quite rapid and occupations become obsolete. Individual contents are subject to requirements for job development whereby individual ones disappear and existing occupations need to be filled with new content by new required competencies or new occupations need to be created. To get new generations prepared for life and work in the global world “does not mean to get them prepared for replacing older employees which is the way to economic stagnation”, but to take more into account technological and developing trends of industries. “The Czech system, including its institutions, has not found so far a mechanism of getting continuously adapted to social and economic changes of the global world” 2. Vocational education should flexibly and continuously react to required changes through changing the content of educational plans arising from the development of qualifications, needs of individual enterprises as well as the entire economic development. The starting point is to include employer requirements that are stated in the National Qualification System in the form of qualifications into the system of initial education so that employers can through them have influence on school graduate professional profile. Created cooperative model enables school and firm cooperation using dual system elements at implementing student vocational training and professional experience in the real work environment. It is based on existing possibilities and conditions in the CR with the aim to meet requirements of both schools and employers and thus contribute to vocational education development. Considering the complexity of the system and sector link difficulty it is sometimes hard or even impossible to include affecting elements and links and incorporate them into one functional system. When describing and analyzing individual components of the cooperative model and its implementation procedures it has been ascertained that it is necessary to start the mentioned elements linking together as they are interrelated. Suggested mechanism enables to ensure the transfer of requirements for occupation development, adapt educational programmes to development and new requirements, and conduct revisions of such programmes easily and quickly so that real sector supply is provided. Created model interconnects functionally the field of education with that of employers. The diagram at Fig. 1 shows the cooperation relations of individual entities at the level of secondary vocational schools and employers. The relations and the links arising of them were summarized in three basic spheres. The objective of these basic spheres and their cooperation links is achieving work coordination of individual entities and creation of long-term strong links directing to the optimization of sector supply on the education side and adequate human resource for employers.

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Figure 1 - Cooperation of schools and employers. Source: Veselý A and.J. Kalous. Teorie a nástroje vzdělávací politiky. 2006.

The first level describes the cooperation of schools and employers ensuring the structural sector relevance and education quality. At this level employer quantity and occupation requirements are provided for student preparation in a given school as a human resource. Such direct cooperation helps create realistic sector and quantity educational supply of secondary schools based on employer actual requirements and thus contributes to providing human resources for a cooperating employer. The second level focuses on joint action when popularizing technical branches and creating joint recruiting activities. Part of such activities is providing information on the possibilities and conditions of graduate employability in given sectors for a specific employer. Admission exam process is fully under the school responsibility. The third level ensures the link between vocational education and real practice. Based on contractual terms and conditions it implements vocational training and practice performance straight in real work environment. Here the cooperation of educators with practitioners takes place. The increase of quality of graduate competencies so that they meet employer needs is helped by mutual cooperation that reflects in the content of educational programmers. And last but not least, it does also in the cooperation on the preparation and common action at final exams and participation of practitioners in such exams. Such passed final exam guarantees employers the competencies required by them. Among the factors that will have impact on graduate transition to practice and make to easier there are acquired work habits, skills and competencies required by the employer, orientation in corporate environment, and the knowledge of company processes and culture. They will help getting a job in the company where vocational training or professional experience took place. For employers such graduate who underwent training and experience in a given company and is familiar with its operation becomes a suitable candidate for employment. That would prevent imbalance in sector supply, unwanted duplication and lack of clarity of provided information. Distinction between individual levels helps monitor, record and transform the development of needs and requirements of social partners into standards, educational programmes and other documents in relation to the needs of the national economy. Improving the quality of such procedures and creating systemic links means in particular pay attention to the quality and relevance of education content and determined the standards of continuous verifiable outputs. The system approach could also be applied to creating strategies at various levels. Effects  cooperation – the school-employer network will help create optimum sector supply and corresponding school network based on the continuous contractual cooperation of schools and companies,  inclusion of employer requirements for competences into school educational programmes,  linking school educational programmes and framework educational programmes to corresponding occupation qualifications of the National Qualification System,  enabling the students of initial vocational education to prepare for occupation qualifications of the National Qualification System already within the school educational process,  support gradual standardization of education content arising from National Qualification System requirements. In the cooperative model concept it is assumed that the cooperation of schools and companies should be coordinated at the national and regional level as well as the level of educational institutions. The objective would be to coordinate an effort of individual entities so that school graduates are equipped with required competences and gain comparable qualifications regardless of where they completed vocational training or professional experience programme. 86

Therefore from the viewpoint of system transformation it is key to enable linking to the existing institutional framework and functional system – the National Occupation System, the National Qualification System, the Framework Educational System and the School Educational Programmes. It is necessary to ensure in the educational programmes that graduates have needed transferable competencies. That can only happen when enterprises are interested in getting involved and engaged in youth preparation for their future occupations. Education has to be economically advantageous for companies, at least from the medium- and longterm view, so as they are interested and willing to offer room for education. Enterprises often provide room for education not only for their own benefit but also because of their social responsibility. School and employer cooperation subsequently brings additional positive effects due to savings of the costs spent on worker recruitment, less job changing associated with local knowledge, reduction of bad hire risk, shorter on-job training, lower cost of additional employee vocational education; companies become less dependent on labour market. Employers already understand that the cooperation with educational institutions is beneficial for them. They do expect immediate effect based on cost calculation as compared to immediate benefit, but they want to get involved in the preparation of students for future jobs and thus to ensure human resources continuity fostering enterprise stability and growth, competitive advantage and social recognition. Students “have to be prepared in schools not only for the life in the middle of the 21 st century, but also for the life right after school graduation and even for the life in the course of school attendance” 3. 5 Conclusion Based on the results of analysis of current vocational education state, taking into account the traditional cooperation forms of vocational schools with employers, the assumptions of possibility for full introducing the dual educational system were not confirmed. Cooperative model in this modeling level fulfils the explanatory function of link interconnection and systematization. The model shows the importance of links and relations leading to the change of cooperation concept provided existing elements of the system are used. In this concept, this model can also be a source and starting point to new procedures and conceptual changes and can teach to confront intentions with practice. It can enable and direct further development of the cooperation in order to early adapt study field supply of secondary vocational schools based on the identification and prediction of labor market needs. References [1] BACIK, F. (1977). K otázkám modelováni vzdělávacích a výchovných objektů. Pedagogika. No. 3, p. 321–343. [2] KADEČKA, S. (2003). Právo obcí a krajů v České republice. Praha: C. H. Beck. 408 p. [3] KOUDELKA, Z. (2007). Samospráva. Praha: Linde. 399 p. [4] MAŇAK, J.; ŠVEC, Š. ŠVEC, V. (eds). (2005). Slovník pedagogické metodologie. Brno: Paido. [5] PAŘÍZEK, V. (2006). Perspektivní varianty vzdělávací politiky. Pedagogika 1993, vol. 43, No. 2, p. 5-20. Quoted as per: Teorie a nástroje vzdělávací politiky. [6] KALOUS, J., VESELÝ, A. (editors). Teorie a nástroje vzdělávací politiky. Praha: Karolinum, 2006. 172 p. ISBN 80-246-126-07. [7] České školství v mezinárodním srovnání: Stručné seznámení s ukazateli publikace OECD Educationat a Glance 2011. 1st issue. Praha: Ústav pro informace ve vzdělávání, 2011. [8] Rámec Strategie konkurenceschopnosti a výchozí náměty NERVu: Závěrečná zpráva podskupin Národní ekonomické rady vlády pro konkurenceschopnost a podporu podnikání. Úřad vlády České republiky, Národní ekonomická rada vlády (NERV). Praha, 2011. 308 s. ISBN 978-80-7440-050-6. Vzdělanost, p. 121-162. [9] STRAKOVÁ, J. Analýza naplnění cílů Národního programu rozvoje vzdělávání v České republice (Bílé knihy) v oblasti předškolního, základního a středního vzdělávání [online]. 13.3.2009 [cit. 2012-01-20]. Dostupný z WWW: 11 Each factor was matched with numbers of resposes and % ratio from total amounts of responses of students/ artists surveyd. Based on this step, we could evaluate each factor an ordinal number, according to importance. 1 – the most important and 5 – the least important factor.

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creative industries in the city and live, and therefore do not perceive the offer of housing as a major factor. Transport accessibility in turn may be subject to the condition that their production may not be realized outside the city.

Ordinal Nr. 1 2 3 4 5

Table 1 - Development of the city with regard to the infrastructure – potential and established creatives Potential creatives (students) Established creatives % from total % from total number of number of Factor Factor respondents respondents (120) (73) Traffic acessibility 33% Historical monnuments/heritage 19% Appartments offer, schools of high quality 26% Traffic acessibility 15% Price affordability of land 19% Schools of high quality 8% Amounts of restaurants, cafes, bars 18% Amounts of restaurants, cafes, bars 5% Historical monuments /heritage 18% Appartments offer price affordability of land 4% Source: Author based on survey.

An analogous analysis is also performed for the factors of environmental quality. The results are shown in Table 2. In this part of the survey respondents were asked: What are the factors of environmental quality they preference was marked on a scale from 1 to 5 (highest to lowest). Table 2 shows that the requirements of potential and established creatives and are largely different. Students as potential creative individuals as the most important factor that would motivate them to settle in the city, considered plenty of parks and green public spaces. For less significant were tagged cleanliness of the city, or link with nature. Legal link with nature played a major role for the creatives already established in their activities. These two studies showed that the lowest level of importance was attributed to the factor proximity of recreational area. It can be postulated that this is due to the fact that recreational areas are man-made environment. So that cannot substitute the connection with nature, such as the presence of parks and green public spaces.

Ordinal Nr. 1 2 3 4 5

Table 2 - Quality of environment with regard to infrastructure - potential and established creatives Potential creatives (students) Established creatives % from total number of Factor Factor respondents (120) Parks and green public spaces 29% Connection with nature Cleanness in the city 28% Air cleanness Connection with nature 27% Parks and green public spaces Air cleanness 21% Cleanness in the city Proximity of recreational area 10% Proximity of recreational area Source: Author based on survey.

% from total number of respondents (73) 14% 10% 8% 4% 3%

Based on results from questionnaire surveys, of which the first one constitutes a representative sample of finishing student, however the second one does not, it is possible to identify the bond that deliver the ability to formulate some partial conclusions: - respondents working in the creative industries are mainly concentrated in large cities, where the best conditions for development are created, and also further promotion of their work envisages, - the questionnaire survey showed that the vast majority of creative artists is mainly concentrated in the Bratislava region, - for potential creatives (students) plays a particularly important role "hard infrastructure", while for those who already operate in the territory was particularly important the presence of "soft infrastructure", - an assumption, that people working in the creative industries need to connect with nature was confirmed. They prefer parks, green public spaces more than “man-made” recreational areas, which cannot substitute the contact with nature, - the results point out that the largest percentage of people who have experience and collaboration with the city, are active mainly in art, music, architecture, internet services and electronic entertainment industry. On the other hand, the largest percentage of respondents who did not cooperate with the city acted in advertising, design or crafts, - regarding the measures that the respondents would accept to support their creation, dominates in particular the greater financial support, for example in the form of subsidies, unused municipal buildings for reduced rent, or better connection and cooperation with other cities, businesses and universities. 4 Conclusion The results achieved documented some interesting facts from the perspective of the claims creative class possess on urban environment for its establishment, or coming to the city. At potential creative individuals is was prioritizing 217

requirements for local facilities with respect to housing, transportation availability and the conditions for its own activities and its presentation and implementation. Established individuals are more oriented on amenities, as other authors and theorists claims in their studies and emphasize in the creative city and creative class. For representatives of the city management it is a very important information and observations, which should be transferred to the creation of documents and measures, including tools for maintaining and attracting creative individuals to cities and should respect the specific claims of the two groups in urban policy. At the same time it should be emphasized, that the orientation on creative economy should be carried out by respecting the existing local economy and promoting it as such. Focusing on elements of the creative economy is not the only approach, but not to use this potential may represent lost opportunities for improving the competitiveness of the city as precondition for improving the quality of life of its inhabitants. Acknowledgements The contribution has been designed as part of the project VEGA no. 1/0965/15 "Performance management in local government and its application in selected villages in Slovakia". References [1] CHRISTOPHERSON, S. Creative Economy Strategies for Small and Medium Size Cities: Options for New York State, Revised version of paper prepared for the Quality Communities Marketing and Economic Workshop, Albany New York, 2004, [online]. dostupné na internete: < http://www.community-wealth.org/_pdfs/articlespublications/anchors/paper-christopherson.pdf> [cit. 2012-01-10] [2] COSTA, P., et all. 2007. A discussion on the governance of ´Creative Cities´: Some insights for policy action, Oslo: Norsk Geografisk Tidsskrift – Norwegian Journal of Geography, č. 61, s. 122-132. [3] Creative-based Strategies in Small and Medium-sized Cities: Guidelines for local authorities. [online]. INTELI: Inteligência em Inovação, Centro de Inovação Jún 2011. [cit. 2012-01-10]. Dostupné na internete: [4] FLORIDA, R. 2002b. The Rise of the Creative Class: And how it´s Transforming Work, Leisure and everyday Life. New York: Basic Books, 424 s. [5] HOSPERS, G. J. 2003. Creative Cities in Europe. Urban Competitiveness in the Knowledge Economy. In Intereconomics. Review of European Economic Policy. roč. 2003. s. 260-269. Dostupné na internete: < http://intereconomics.eu/archive/suche.php?query_string=creative+Cities+in+Europe&search.x=0&search.y=0> [6] HOWKINS, J. 2001. The Creative Economy: How People Make Money from Ideas. London: Penguin Books. 288 s. [7] CHOVANEC, M. – REHÁK, Š. 2012. Exploring Spatila Patterns of Creative Industries with Firm Level Micro Geographic Data. In: Regional Direct 2/ 2012. 10 – 35 p. [8] IVANIČKOVÁ, A. 2011. Malé mestá – priestor a možnosti kreatívnych činností. In: JEŽEK – KAŇKA. Konkurencieschopnost a uržatelný rozvoj malých měst a venkovských regionů v ČR. Plzeň: Západočeská univerzita. s. 34-54. ISBN 978-80-261-0094-2 [9] KLOUDOVÁ, J. a kol. 2010b: Kreativní ekonomika – trendy, výzvy, příležitosti. Praha : GRADA Publishing, a. s., 2010. 224 s. ISBN 978-80-247-3608-2. [10] KMECOVÁ, N. 2014. Kreatívna trieda ako stimul rozvoja mesta: diplomová práca. Bratislava: Ekonomická univerzita, 2014. 70 s. [11] KOZÁKOVÁ, V. 2014. Vplyv kreatívnej ekonomiky na rozvoj územia – dizertačná práca. Banská Bystrica: Univerzita Mateja Bela v Banskej Bystrici. [12] KOZÁKOVÁ, V. - VAŇOVÁ, A. 2012. Podporné mechanizmy kreatívnej triedy z pohľadu zemia. In Sociálnoekonomická revue: vedecký časopis Fakulty sociálno-ekonomických vzťahov Trenčianskej univerzity Alexandra Dubčeka v Trenčíne. roč. 10 č. 2, s. 56-65. [13] KYSELICOVÁ, S. 2015. Tvorba prostredia pre kreatívnu ekonomiku v zemnej samospráve. Bratislava: Ekonomická univerzita, 2015. 78 s. [14] LANDRY, Ch. 2008: The Creative City: A Toolkit for Urban Innovators. Earthscan Publications Ltd. ISBN-13: 978-1844075980 [15] REHÁK, Š. 2014. Kreatívna trieda a kreatívne mestá. Teoretický koncept a jeho limity. In Sociológia: časopis pre otázky sociológie. - Bratislava: Sociologický ústav SAV, 2014. ISSN 0049-1225, 2014, roč. 46, č. 5, s. 599619. [16] VAŇOVÁ, A. 2010. Kreatívna ekonomika a rozvoj zemia (z pohľadu marketingu zemia) publikované v rámci KLOUDOVÁ, J. 2010. Kreativní ekonomika: vybrané ekonomické, právní, masmediální a informatizační aspekty. Bratislava: Euro Kódex, 2010, 210 s. [17] Východiská koncepcie na podporu kult rneho a kreatívneho priemyslu v Slovenskej republike. [online]. 81. schôdza Vlády SR 14.12.2011. [cit. 2012-01-10]. Dostupné na: [18] Zelená kniha – uvoľnenie potenciálu kult rneho a kreatívneho priemyslu. [online]. European Commission. [cit. 2012-01-10]. Dostupné na: < http://ec.europa.eu/culture/documents/greenpaper_creative_industries_en.pdf > [19] ŽÁRSKA, E. A KOL. 2007. Komunálna ekonomika a politika. Bratislava: Ekonóm. 218

[20] 120 dotazníkov čiastkového výskumu KRENAR „Kreatívna trieda v miestnom ekonomickom rozvoji“. Katedra verejnej správy a regionálneho rozvoja NHF EU Bratislava: apríl- máj 2013 a 73 dotazníkov November – December 2014.

Contact information prof. Ing. Elena Žárska, CSc. University of Economics Dolnozemská cesta 1, 852 35 Bratislava Slovak Republic [email protected]

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Collective of authors Organised by: Department of Public Economics, Faculty of Economics, VŠB – Technical University of Ostrava Edited by: Ivana Vaňková Title: Proceedings of the 11th International Scientific Conference PUBLIC ECONOMICS AND ADMINISTRATION 2015 Issued in: Ostrava, Czech Republic, 2015, 1st edition Number of pages: 219 Published by: VŠB - Technical University of Ostrava, 17. listopadu 15/2172, 708 33 Ostrava-Poruba Printed by: RETIS GROUP s.r.o., Nádražní 2, 794 01 Krnov, Czech Republic Number of copies: 200

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