Design of substrate supply contracts for biogas plants Preliminary Version: Please do not cite without the author’s permission.
Christian Reise, Ulf Liebe, Oliver Musshoff Department for Agricultural Economics and Rural Development Georg-August-Universität Goettingen Platz der Goettinger Sieben 5 D-37073 Goettingen
[email protected]
Contributed paper prepared for presentation at the 56th AARES annual conference, Fremantle, Western Australia, February 7-10, 2012 Copyright 2012 by Christian Reise, Ulf Liebe, Oliver Musshoff. All rights reserved. Readers may make verbatim copies of this document for non-commercial purposes by any means, provided that this copyright notice appears on all such copies.
Design of substrate supply contracts for biogas plants Christian Reise, Ulf Liebe, Oliver Musshoff Department for Agricultural Economics and Rural Development Georg-August-Universität Goettingen Platz der Goettinger Sieben 5 D-37073 Goettingen
Abstract For a sustainable development of energy production in biogas plants, the continuous supply with substrates is essential. To the authors’ knowledge, there have not been carried out any quantitative investigations of farmers’ choices with regard to supply contracts for biogas plants. Thus, it has been only possible to a limited extent to make predictions for a targeted design of supply contracts. We therefore investigated different factors, which might be relevant for the conclusion of substrate supply contracts, by conducting a survey with 178 German farmers. The survey included a choice experiment, in which participants were confronted with different contract attributes (features). These attributes were varied systematically and thus revealed the influence of each individual feature on the probability of contract conclusion. It becomes clear that the farmers interviewed prefer to conclude contracts with other farmers or with a bioenergy village to non-agricultural investors. The probability of contract conclusion decreases with an increasing lifetime of the contract. However, a contract with a higher sales price is more attractive for the farmers. The investigation of the characteristics of respondents shows that the amount of the premium for one additional year of contractual lifetime depends on the individual valuation of the entrepreneurial freedom of the respective farm manager. It cannot be established that risk-averse farmers tend to prefer contracts with fixed prices over contracts with price adjustment clauses. In addition, there are no great differences in the choice behaviour of farmers who have signed a substrate supply contract and farmers without this experience. Regarding the expansion of renewable energies, these findings are meaningful for a target-aimed design of supply contracts.
Keywords Renewable energy; bioenergy; substrate supply contract; contract design; (labeled) choice experiment
1 Introduction In order to ensure a climate-friendly energy supply in the European Union and in particular in Germany, the expansion of renewable energies constitutes an important political long-term goal (cf., e.g., BMU and BMELV, 2009; Isermeyer et al., 2008). In the future, the different 1
possibilities for the decentralized generation of renewable energies should complement each other in the form of a so-called virtual plant (Arndt et al., 2006) in order to compensate for the respective disadvantages of the other methods like, e.g., the lack of energy storage possibilities. Within the system of sustainable energy supply, the generation of biogas as ‘balancing energy’ is of particular importance. In contrast to wind energy or photovoltaic, for the generation of bioenergy, it is possible to selectively control the supply of the necessary substratum and to store the emerging gas (cf., Schröer, 2010; Schaper et al., 2011). In this way, power generation can be adjusted more easily to demand. For further expansion of biogas generation, it is of central importance that the agricultural sector provides the required amounts of substrates for operating the biogas plants. Larger plants often require supply of additional substrates by third parties. This is relevant in that substrate costs account for about half of the annual total costs of a biogas plant (cf., e.g., Walla and Schneeberger, 2008; FNR, 2009). That is why, it is important to pay particular attention to substrate supply contracts which constitute the interface between substrate growers and biogas plant operators. This begs the question of the farmers’ preferences regarding the design of substrate supply contracts. Currently, maize is one of the most important renewable raw materials used for bioenergy generation (FNR, 2007: 94). This is mainly due to the fact that it provides very high dry matter yields in the moderate climate of Central Europe. All in all, the amount of land used for maize cultivation in Germany was 2.3 million hectares in 2010 (DMK, 2011). Therefore, the present study examines maize supply contracts. So far, there has been carried out a vast number of studies focusing on supply contracts. For example, Katchova and Miranda (2004), Key (2004) as well as Roe et al. (2004) investigated the acceptance of supply contracts for US hog producers. Steffen et al. (2009) asked German dairy farmers about their idea of the contract design with the dairy factories after the abolishment of the milk quota in 2015. Musshoff and Hirschauer (2011) analyzed farmers’ acceptance of supply contracts of ethanol beets. To our knowledge, however, there have not been carried out any quantitative investigations of farmers’ choices with regard to maize supply contracts for biogas plants. Therefore, it has been only possible to a limited extent to make predictions for a targeted design of maize supply contracts. Using choice experiments (CE) preferences of participants for selection decisions can be analyzed and the decision relevance of individual attributes of the respective object of study can be evaluated. CE are very common in field of market research i.e. that they are used to examine purchase decisions of consumers (cf., e.g., Green and Srinivasan, 1990). Furthermore, this method is very effective for valuating ecosystem services (cf., e.g., Adamowicz et al., 1994; Schmitz et al., 2003). Bougherara and Ducos (2006) analyze three hypothetical offers of contractual conservation management agreements by means of a CE. Qin et al. (2011) carry out a CE for evaluating lease contracts of forested land in China. There are several reasons why CE were found to be suitable for investigating farmers’ preferences for the design of substrate supply contracts. In practice, contracts are mostly treated as ‘confidential internals’, so that there is little transparency and thus no sufficient data basis is available. Furthermore, framework conditions vary among different farms making simple comparisons of supply contracts nearly impossible. It therefore seems to be promising to use a direct evaluation method (stated preference method) and work with hypothetical decision situations. In that way, the participants’ selection preferences can be better analyzed 2
than when looking at empirical decisions (Roe and Just, 2009; Just and Wu, 2009) because action alternatives as well as framework conditions are controllable. Contrary to open and direct queries survey, attributes and levels are given in a CE (cf., Qin et al., 2011). In addition, the attributes’ interaction can be taken into account. In CE, it is not necessary to indicate the direct willingness to pay as the latter is derived from the analysis of the choices in form of implicit prices (Schmitz et al., 2003). Moreover, a great advantage of CE is their high external validity (cf., e.g., Hoyos, 2010; Auspurg and Liebe, 2011) as well as the fact that it is less expensive to carry out a CE than applying the Contingent Valuation Method (cf., Hoyos, 2010: 1601). The present study aims to point out important influencing factors for the conclusion of substrate supply contracts for raw material supply of biogas plants and to derive statements regarding the importance of selected integral parts of the contract. We therefore carried out a labeled choice experiment, in which farmers were confronted with different supply contracts. In particular, the following research questions are examined: 1)
‘Contractual attributes’: Do farmers prefer specific contracting partners, lifetimes of contracts and price arrangements?
2)
‘Respondent characteristics’: Which effect does the farmer’s individual valuation of entrepreneurial freedom (flexibility) have on the lifetimes of contracts? Is his/her risk attitude reflected in the contractual price arrangements?
3)
‘Learning effect’: How do the farmers’ experiences with substrate supply contracts influence their decision-making behavior?
The following section 2 provides information about the theoretical background of the study and the hypotheses examined. Subsequently, section 3 describes the study design by first explaining the methodological approach and then describing the arrangements of the CE as well as of the survey. Section 4 provides an overview of the samples and of the substrate supply contracts concluded by the farmers. Afterwards, results are presented in section 5. First, results regarding the desired contract attributes and their importance are presented. Second, hypotheses are tested on the basis of the results from the CE. The paper ends with conclusions and an outlook to future work (section 6).
2 Theoretical background and formation of hypotheses For the economic evaluation of biogas plants, substrate costs are often considered as fixed variable or they are optimized under different framework conditions (cf., e.g., Heissenhuber and Berenz, 2006; Wulf et al., 2006; Keymer, 2009; Gebrezgabher et al., 2010). In these evaluations, substrate availability is often taken for granted. Stürmer and Eder (2010), for example, optimized the supply of a biogas plant in due consideration of the annual costs for cultivation and crop management as well as for harvesting and manure application. Furthermore, the authors also took into account the operating costs for the arable land required.
3
Selection of contracting partners For our research focus, it is necessary that substrate supply is effected by a third party i.e. that it substrate has to be bought in order to operate the biogas plant. Due to the high proportion of water in silage maize and it’s therefore low transport efficiency (cf., e.g., DLR and KIT, 2001; Gruber, 2006; Schulze Steinmann and Holm-Müller, 2010), we cannot assume a large market. That is why, mainly decentralized solutions like regional partnerships come into consideration (cf., e.g., Bahrs et al., 2008). In the first stages of contract conclusion, the available information is incomplete because neither future prices are known nor there is certainty about the (actual) preferences of all contracting partners. Steinhorst and Bahrs (2011) stress the importance of a considered selection of business partners. In the context of substrate supply contracts, there are various operators of biogas plants (e.g., other farmers, non-agricultural investors etc.) that may be potential contracting partners. Thus, the first hypothesis (H) is formulated as follows: H 1 ‘Relevancy of contracting partners’: The kind of contracting partner has an effect on the probability with which a contract is chosen. Valuation of entrepreneurial freedom For many farmers, their independence is very important. Spiller and Schulze (2006), for instance, investigate to what extent German pig farmers are willing to conclude vertically integrated contracts. They confirm a predominantly skeptical attitude resulting inter alia from emotional reasons. Apart from the emotional aspects, the restriction of the entrepreneurial freedom also has financial implications. Musshoff and Hirschauer (2008) examine supply licenses for rye with a guaranteed price by taking into account inter alia the uncertainty regarding the spot market price for rye as well as the option to accept the contract later. For the supply licenses examined, it was shown that only extremely risk-averse farmers should accept the contracts immediately. Restrictive contractual attributes like, for example, a long lifetime of the contract, make the contract less attractive (Roe et al., 2004). These can be compensated ceteris paribus with an autonomy premium (cf., e.g., Key, 2005; Key and Macdonald, 2006). The second hypothesis therefore refers to the ratio between flexibility and lifetime of the contract: H 2 ‘Flexibility and lifetime of the contract’: Farmers value entrepreneurial freedom (flexibility). Depending on the individual valuation, farmers therefore demand with an increasing lifetime of the contract, a rising compensation premium. Importance of risk attitude Agricultural production involves risks (cf., e.g., Tiedemann et al., 2011), which can be reduced by making contractual agreements. Entrepreneurial decisions — like the conclusion of a contract — are therefore dependent on the risk attitude of the farm manager (cf., e.g., Bard and Barry, 2000; Harwood et al., 1999). It is assumed that in real life, entrepreneurs are risk-averse, even though to a different extent (cf., e.g., Andersen, 2008). Risk-averse decision makers are willing to pay a premium for the reduction of their risk. For risk neutral decision makers, risk would not be important and, thus, they would not demand any risk premium. 4
An optimal contract should lead to a balance of the interests of the contracting partners and should therefore consider an adequate price for the acceptance of risks regarding rights and obligations (cf., Jang and Olson, 2010). For this, there are different ways to arrange pricing. Compensation for substrates can be effected at a fixed priced stipulated in the supply contract (in the following referred to as fixed price contract). With this price hedging, however, the option to participate in favorable future price developments is excluded. Roland et al. (2009) discusses alternative price-setting options. Within the scope of several price adjustment clauses, a compensation for future market prices of reference crops (in the following referred to as market price contract) is examined. This approach takes into account the direct opportunity costs of the displaced crops. The substrate price is not guaranteed and can therefore be considered as expected variable for the conclusion of the contract. On the basis of the aforementioned aspects, the following hypothesis has been derived: H 3 ‘Risk attitude and pricing’: Risk-averse farmers prefer fixed price contracts (market price contracts) over market price contracts (fixed price contracts) at otherwise equal contractual attributes. If they commit themselves to a fixed price contract a lower premium than that for risk-seeking farmers has to be paid. Experiences with substrate supply contracts Experiences arise from learning from the solution process of certain problems (cf., Cameron, 1999). However, existing experiences can be transferred only partly to other situations (cf., Loewenstein, 1999). Individuals can make some progress and develop further by having experiences (cf., Cheung and Friedman, 1998). For instance, farmers, who have experience regarding the investment in a biogas plant, are better able to assess the value of investment subsidies than farmers without this experience (cf., Reise et al., 2012). The following final hypothesis is based on these findings: H 4 ‘Learning effects’: Farmers, who have experiences from concluded substrate supply contracts, show a choice behavior that is different from that of farmers without such experiences.
3 Study design 3.1 Methodology Real economic subjects usually pursue multiple targets, which apart from an individual consideration of risk aspects also include internalized moral concepts and non-monetary motivations (e.g., tradition or social recognition) (cf., e.g., Schwartz, 1994; Benz, 2006). Moreover, they show at least partly a bounded rational decision behavior (cf., e.g. Simon, 1956; Selten, 1990; Gigerenzer, 2002; Reise et al., 2012). Hence, there is the danger that the way and speed of the individual’s adaptation behavior in rational-choice approaches, which are exclusively based on profit maximization, are evaluated incorrectly. Alternatively, it is possible to use experimental approaches including laboratory experiments or even surveys with hypothetical decision situations like CE (cf., e.g., Wossinik and van Wenum, 2003). CE are an expansion of the traditional conjoint analysis (consider jointly), which ’looks at all individual attributes coherently by presenting product alternatives, which are as realistic as possible and vary systematically in their levels’ (Enneking, 2003: 255). 5
In CE — a combination of survey and experiment — participants chose one (action) alternative from a selection of different alternatives (so-called choice sets). The selection process is similar to the selection decision of consumers (Hoyos, 2010: 1595; for further literature on CE please refer to Louviere et al., 2000; Hensher et al., 2005). In these experiments, participants are asked to choose one (action) alternative from a presented choice set. This selection decision is often repeated with another choice set. In these choice sets, the attributes examined are varied systematically in order to determine the influence of each individual attribute on the selection decision (cf., e.g., Louviere et al., 2000; List et al., 2006). In that way, the contribution of the utility of each attribute and its level to the total utility (‘utility bundle’) can be determined.
3.2 Design of the CE and questionnaire structure Selection of attributes and their levels Real contracts take into account many contrary interests (cf., Bogetoft and Olesen, 2002). This often finds expression in extensive regulations. For testing the hypotheses, the CE were designed in a way that ‘main attributes’ relevant for contract conclusion were considered. The selection of the attributes and their levels is based on literature research, the analysis of practical and model contracts as well as on expert interviews. The three main attributes ‘contracting partner’, ‘lifetime of the contract’ and ‘sales price’ are presented briefly in the following. Roe et al. (2004) stress the importance of the form of organization of the contracting partner. Thus, in the present study, participants can chose from several different contracting partners. By analyzing practical contracts, we identified the following relevant categories of contracting partners. In concrete terms, we distinguish the contracting partners ‘farmers’, ‘bioenergy village’ and ‘non-agricultural investors’ (see table 1). Not every farmer wants to take a stake in a (collective) biogas plant. Independently of this stake, however, it is often possible to participate in the supply of raw materials of biogas plant of other farmers through substrate supply contracts. In addition, it is possible to support the substrate supply of bioenergy village. According to Ruppert et al. (2008: 10) ‘it is the aim of a bioenergy village to base, if possible, the whole heat and electricity supply of the village on the renewable energy source ‘biomass’ and to operate the biogas plant autonomously.’ Moreover, in praxis, there exist substrate supply contracts for biogas plants that are operated by non-agricultural investors (e.g., power supply companies). Roe et al. (2004) state that a long lifetime of a contract reduces its attractiveness and that this in turn can be balanced by a higher compensation. This is what we want to investigate in the context of substrate supply contracts by offering contracts with lifetimes of different lengths (1.5 and 9 years) to the participants. For larger biogas plants, the sales price often is set by the buyer of the substrate. This ‘counterparty’ would generally set a low initial price and then he/she would wait if contracts were concluded on a sufficient quantity of supply. Otherwise, the substrate price or other contract attributes would be adjusted (cf., e.g., Jang and Olson 2010). Musshoff and Hirschauer (2011) conducted a survey with farmers about supply contracts for ethanol beets and found that subsequent improvement of a contract after an unsuccessful first launch is less accepted by farmers than an immediate higher contract offer. But which price will be accepted by farmers? 6
In the following investigation, we distinguish between contracts at fixed prices and — as a variant of a price adjustment clause — contracts at market prices. In case of compensation at fixed prices, the price is guaranteed by the contracting partner over the whole lifetime of the contract. On the contrary, in case of compensation at market prices, an expected (average) price is assumed. Thus, the price is not guaranteed. The sales prices are indicated as silage maize price and additionally as wheat price equivalent. This additional indication is made because wheat cultivation is very common in Germany and therefore also farmers, who do not have any experience in the cultivation of maize, can easily evaluate this crop. It is assumed that the production of 6 tons of maize displaces the yield of 1 ton of wheat. In order to create as realistic conditions as possible, the substrate prices set (20 €/t, 30 €/t and 40 €/t of silage maize) were taken from literature (cf., e.g., FNR, 2007; Keymer, 2009; KTBL, 2009; Gebrezgabher et al., 2010). For a realistic design of the contract attributes and levels, furthermore, pre-tests and expert interviews were conducted.
Table 1: Attributes and levels of the contract offers Attributes
Descriptor
Levels
Contracting
Different operators of the biogas plants for which the contracts will be
partner
offered:
Lifetime of the
•
Plant operated by farmers;
Farmers;
•
Plant to supply a bioenergy village;
bioenergy village;
•
Plant operated by a non-agricultural investor
non-agricultural
(e.g., electric supply company)
investor
Years over which the contract runs
1; 5; 9
contract Sales price
The contracts can be concluded at fixed prices or at market prices: •
Compensation at fixed prices: Certainly guaranteed price for the entire contract period.
•
Compensation at market prices: In contrast to the fixed price, it cannot be guaranteed. Therefore it is given as expected price.
The prize is specified as silage maize price (in €/t): With an assumed ratio of 1:6 the following prices correspond (in €/t): Maize price
20
30
40
Wheat price
120
180
240
20 €/t; 30 €/t; 40 €/t
Source: authors own presentation
Design of the choice-sets In order to determine the influence of the respective attributes and levels on farmers’ choices, the contract components are varied systematically. The experimental design is the combination of attributes and levels (see table 1) within choice-sets (Hoyos, 2010: 1596). As 7
a full factorial design, the set of all possible attribute-level-combinations, is too large to be evaluated by the participants [(3*3*3)fixed price contract * (3*3*3)market price contract = 729 combinations], a so-called fractional factorial design was created. The selected optimization criterion was an ‘optimal orthogonal in the differenced (OOD) design’ (cf., e.g., Burgess and Street, 2005). This design is for instance implemented in Ngene, which is a software for choice experiments (for software and manual see: http://www.choice-metrics.com). The design optimizes the orthogonality of all main effects of the attributes i.e. the influence of each attribute on the probability of choosing of a contract can be estimated independently of other attributes. Furthermore, maximal differences between the attribute levels within choicesets should be achieved. That means that there are as few as possible equal levels of an attribute in a choice-set. In the present case, 9 choice-sets are necessary to optimally ensure these criteria (maximum D-optimization of 100%). Therefore, the complete 9 choice-sets are presented to all participants in a random order (no division into blocks). An example of the choice-sets is shown in figure 1. Since participants can choose between a fixed price contract and a market price contract, the choice set shown in figure 1 is an example of a so-called labeled CE. Moreover, an opt-out-alternative can be selected, which allows the participants to reject both aforementioned contracts.
Figure 1: Example of a choice-set FIXED PRICE CONTRACT
MARKET PRICE CONTRACT
Contracting partner
Bioenergy village
Farmers
Lifetime
1 year
5 years
Sales price:
Guaranteed
Expected
Maize price (equates wheat price) I choose … (Please click)
20 €/t
30 €/t
(120 €/t)
(180 €/t)
O
O
Neither of the above Source: authors own presentation
Structure of the questionnaire The questionnaire consists of three parts. The first part titled ‘your estimation of potential substrate supply contracts’ starts with the CE in order to eliminate the influence of the other parts of the questionnaire on the response behavior of this part. For comparability reasons, in the CE, participants are asked to put themselves in the position of a farm manager of an arable farm with 100 ha of farmland. For the substrate supply of a newly built, nearby biogas plant, participants are offered two alternative substrate supply contracts for silage maize. Here, participants can choose between a fixed price contract and a market price contract. The contracts differ in the aforementioned levels of the attributes ‘contracting partner’, ‘lifetime of the contract’ and ‘sales price’ (cf., table 1). The second part of the questionnaire focuses on the entrepreneurial freedom and the farmers’ individual risk attitude. Moreover, questions about energy cropping and potentially concluded substrate supply contracts are investigated. 8
The third part of the questionnaire gathers information about the farms and the farm managers themselves.
4 Descriptive statistics The ’Survey about substrate supply contracts between farm managers and operators of biogas plants’ 1 was conducted online in summer 2011. The acquisition of farm managers was supported by several agricultural associations, alumni networks and students of agricultural sciences. In total 178 farm managers completed the questionnaire. In the following, the interviewed farm managers and their farms are described more in detail and an overview of the substrate supply contracts concluded by the participants is provided.
4.1 Farm structural and socioeconomic characteristics Table 2 provides an overview of all farm structural and socio-economic characteristics. Out of all participants, 86.0% are full-time farmers, while 14.0% are part-time farmers. The German average of full-time farmers is around 45.0% and therefore lower than in our sample (BMELV, 2010). Almost half of the participants run arable farms, while another quarter focuses on mixed farming and a fifth on livestock farming. The area cultivated by the farms ranges from 7 to 5,000 ha. The average size of farms’ cultivated area is 283 ha. Compared to the German average of 49 ha (BMELV, 2010), the farms examined are of above-average size. The average soil quality of the sample according to the German soil classification scheme ranging from 0 to 100 is 53.4 points. Around half of the participants completed a study course of agricultural sciences. The proportion of female farmers, who participated in the study, is 4.1%. The age of the farmers ranges between 19 and 73 years, while the average age of all participants is 43 years. Furthermore, the majority of the farmers attach great importance to their entrepreneurial freedom (flexibility). On a 5-point scale ranging from 1 (‘strongly disagree’) to 5 (‘strongly agree’), on average the value of 4.2 was selected. Following the self-assessment of risk attitude developed by the socio-economic panel (SOEP) of the German Institute for Economic Research (DIW Berlin) (Dohmen et al., 2005), the farmers were asked to indicate their risk attitude on a scale ranging from 0 (‘not risk-seeking at all’) to 10 (‘very risk-seeking’). On average, the farmers indicated to be risk neutral (5.5 on the scale). In the sample, the proportion of biogas producing farms, which hold a stake in a biogas plant or even run their own, is 19.7% (35 farms). In total, 97 (54.5%) of the farms that participated in our survey grow energy crops. 73 (41.0%) farm managers concluded substrate supply contracts and therefore have direct experience in this field. 105 (59.0%) farm managers have not concluded such contracts.
1
This survey was jointly conducted with Karol Granoszewski and Achim Spiller as part of the interdisciplinary research project ’Sustainable use of bioenergy: bridging climate protection, nature conservation and society’ and financially supported by the Ministry for Science and Culture of Lower Saxony.
9
Table 2: Average farm structural and socio-economic characteristics of the sample as well as of Germany a) Sample b)
Germany
Full-time farming
86.0%
45.0% c)
Part-time farming
14.0%
55.0% c)
Arable farming
45.4%
16.9% d)
Livestock farming
21.8%
5.8% d)
Forage farming
5.2%
43.7% d
Mixed
25.9%
21.1% d)
Others
1.7%
12.5% d)
Average farmland (ha LN)
283 (497)
49 c)
Soil quality (in points according to the German soil classification scheme)
53.4 (18.3)
42.5 e)
Proportion of farmers holding a university degree
47.4%
n.a.
Proportion of female farmers
4.1%
n.a.
43 (13)
n.a.
Farm income
Farm type
Age of farmers (years) Valuation of entrepreneurial freedom Risk attitude
4.2 (0.6) f)
n.a.
g)
n.a.
5.5 (2.0)
Proportion of biogas producing farms
19.7%
n.a.
Proportion of energy crops cultivators
54.5%
n.a.
Proportion of farmers holding substrate supply contracts
41.0%
n.a.
a)
Standard deviation is indicated in brackets.
b)
Participants (N = 178) did not answer all questions. The number of given answers varies between 169 and 178.
c)
Source: BMELV (2010).
d)
Source: BMELV (2011).
e)
Soil quality was indicated for the German federal state of Lower Saxony. Source: NLS (2001).
f)
Measured on a 5-point scale ranging from 1 (‘strongly disagree’) to 5 (‘strongly agree’).
g)
Self-assessment according to SOEP on a scale ranging from 0 (‘not risk-seeking at all’) to 10 (‘very risk-seeking’).
Source: authors own calculations
4.2 Overview and evaluation of the substrate supply contracts concluded In the following, the substrate supply contracts concluded by the sample farms are explained more in detail. Table 3 provides an overview of the supply contracts, which are categorized according to their lifetime and arrangement of compensation. In 15.1% of the contracts, the lifetime indicated was zero years. Almost one third of the participants (34.3%) have a contract with a lifetime of 3 to 6 years. The remaining 21.9% of the participants have concluded contracts with longer lifetimes ranging from 7 to 20 years. The 73 contracts examined have an average lifetime of 5 years. With regard to compensation, fixed price contracts and contracts containing a price adjustment clause were differentiated. Besides contracts with fixed prices, the term fixed price contracts also includes contracts with fixed price increases — for instance in the form of an annual surcharge of 1.5% — as these are guaranteed and do not depend on the future 10
development of a reference variable. Approximately half of the farm managers (49.3%) concluded a fixed price contract with an average lifetime of 4.5 years. The other half (45.2%) mainly concluded contracts with price adjustment clauses and an average lifetime of 5.8 years. The remaining four substrate supply contracts could not be allocated to any of the two categories because the contract agreement included, for example, the exchange of the substrate for a certain area of land for growing potatoes. A comparison of the compensation arrangements shows that contracts with price adjustment clauses have lifetime that is 1.3 years longer than that of fixed price contracts. Table 3: Overview of the substrate supply contracts concluded Lifetime of the contract (years)
Sample
Mean
(%)
(standard
0
1
2
3
4
5
6
8
9
10
11
12
Fixed price
6
11
2
0
0
9
1
0
0
1
1
3
2 36 (49.3)
4.5 (5.3)
Price adjustment clause
3
5
2
1
2
11
0
1
1
4
0
0
3 33 (45.2)
5.8 (5.5)
Others a)
2
1
0
0
0
1
0
0
0
0
0
0
0
4 (5.5)
1.5 (2.4)
11
17
4
1
2
21
1
1
1
5
1
3
5
73
5.0 (5.3)
Sample (%)
20
(15.1) (23.3) (5.5) (1.4) (2.7) (28.8) (1.4) (1.4) (1.4) (6.8) (1.4) (4.1) (6.8) a)
deviation)
(100.0)
One participant did not make any indications regarding pricing.
Source: authors own calculations
Furthermore, farmers were asked to evaluate the substrate supply contracts, which they had concluded (table 4). In hindsight, 8.2% think that the lifetime of the contracts, which they had accepted earlier, is too short. More than 80% of the participants are content with the lifetime of the contract, which they had chosen earlier. 11.0% think that their chosen and agreed lifetime is too long. In general, farmers are more likely to evaluate the lifetime of fixed price contracts as too long, whereas they are more likely to think that the lifetime of the contracts with price adjustment clauses is too short. With regard to the evaluation of compensation, 19.2% of the participants think that compensation is far too low, 78,1% think that it is adequate and 2.7% find that it is sufficient. For this optimistic statement, it remains to question to what extent the strategic consideration in terms of a ‘cautious evaluation’ played an important role in order to not weaken the individual negotiating position. The categorization into groups shows that 72.2% of the participants of the group, which holds fixed price contracts, and 87.9% of the participants of the group, which holds the contracts with price adjustment clauses, evaluate compensation as adequate. One fourth of the first group but only 9.1% of the second group say that compensation is far too low. All in all, the second group seems to be more content with their chosen arrangement of compensation.
11
Table 4: Evaluation of existing substrate supply contracts (n=73) Lifetime of the contract
Arrangement of compensation
Too short
Adequate
Too long
Fixed price (%) (n=36)
5.6
77.8
16.7
25.0
72.2
2.8
Price adjustment clauses (%) (n=33)
9.1
84.8
6.1
9.1
87.9
3.0
25.0 6 (8.2)
75.0 59 (80.8)
0.0 8 (11.0)
50.0 14 (19.2)
50.0 57 (78.1)
0.0 2 (2.7)
Others a) (%) (n=4) Sample (%) a)
Far too low Appropriate
Sufficient
One participant did not make any indications regarding pricing.
Source: authors own calculations
5 Results 5.1 Desired contract attributes and their importance For the majority of the farm managers interviewed (87.3%), it is important that the contracting partner has an understanding of the special conditions in the agricultural sector. In addition, for 77.0% of the participants it is important that the economic situation of the contracting partner is transparent. Nearly half of the participants (48.4%) prefer regional contracting partners, whereas 18.8% of the participants dislike regional partners. Furthermore, the farm managers were asked to indicate their preferred lifetime of fixed price contracts and their desired reference for price adjustment clauses (table 5). Participants were asked to indicate the in their opinion optimal lifetime of a contract over which the quantity of supply and the sales price should be fixed. 1.7% of the farm managers indicate a contract lifetime of zero. This might mean that they do not want to commit themselves to a specific period of time or, alternatively, they do not want to conclude a contract. The most frequent answers include a contract lifetime of one year (14.0%), three years (34.8%) and five years (27.5%). The mean of the whole sample is 3.6 years (standard deviation: 2.2). The farm managers, who did not conclude any substrate supply contracts, indicate on average a desired lifetime of 3.1 years (standard deviation: 1.6). On the contrary, farm managers, who concluded contracts, want to have on average a contract lifetime of 4.3 years (standard deviation: 2.7). Out of the aforementioned farmers, those with fixed price contracts indicate a desired lifetime of 4.6 years (standard deviation: 3.4), while those who concluded contracts with price adjustment clauses prefer a contract lifetime of 4.0 years (standard deviation: 1.9). Due to the fact that compensations at market prices can be based on different prices, participants were asked to indicate to which (reference) prices compensations should be linked to. To do so, participants could select from four references. These could be selected individually or weighted. Most participants preferred to use the grain price (wheat price) as reference. About half of the participants (53.0%) selected the grain price and thus confirmed the estimation made in the pretests and expert interviews regarding the consideration in the CE. A link of these prices to the general production costs in the agricultural sector and to the development of energy prices was indicated with 17.0% each. The working costs (e.g., labor costs, fuel costs, costs for agricultural service supply agencies) received a share of 14.0%.
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Table 5: Desired lifetime of fixed contracts and desired reference for price adjustment clauses Percentage Lifetime of a fixed contract (N=178) No lifetime (0 years)
1.7%
Short (1-2 years)
23.0%
Medium (3-6 years)
70.8%
Long (7-20 years)
4.5%
Reference for price adjustment clause Grain price (wheat price) (n=147)
53.0%
General production costs in the agricultural sector (n=104)
17.0%
Development of energy prices (n=108)
17.0%
Working costs (labor costs, fuel costs, costs for agricultural service supply agencies) (n=99)
14.0%
Source: authors own calculations
Moreover, participants were asked to state their personal opinion about the importance of different attributes for the design of supply contracts. To do so, participants were asked to rank the four attributes sales price, contracting partner, lifetime of the contract and quantity of supply according to their importance. Table 6 shows that participants attached greatest importance to the sales price (overall rank 1) followed by the respective contracting partner (overall rank 2). Overall rank 3 was attached to the lifetime of the contract, while the quantity of supply follows on overall rank 4 and therefore confirms the statements made in the pretests and expert interviews regarding the subordinate importance of this attribute. Table 6: Rank order of contract attributes Sales price (n=174)
Contracting partner (N=178)
Lifetime of the contract (n=174)
Quantity of supply (n=173)
Rank 1
60.9%
27.5%
9.8%
3.5%
Rank 2
30.5%
19.7%
29.3%
20.2%
Rank 3
7.5%
19.1%
40.8%
32.4%
Rank 4
1.1%
33.7%
20.1%
43.9%
Mean Overall rank a)
1.5
2.6
2.7
3.2
1
2
3
4
From rank 1 (= most important) to rank 4 (= least important).
Source: authors own calculations
5.2 Results of the CE for testing the hypotheses In the survey, all farm managers made 9 choices. They could always select one out three possible contract alternatives, namely ‘fixed price contract’, ‘market price contract’ and ‘optout alternative’. Hence, on the basis of 178 participants, 4806 observations could be generated (178x9x3). The analysis of the CE was based on the investigation of the individual choices. Using the software Stata 11, conditional logit models were estimated on the basis of the data from the CE. This was done to determine the influence of the investigated contract attributes on the probability of contract selection. The following results are also robust when using 13
models that are based on less stringent assumptions compared to conditional logit models (e.g., mixed logit models (see Train, 2003), which amongst others consider the panel character of the data; not presented here). Table 7 reports results of conditional logit models under exclusion of the opt-out alternative. Hence, only observations are included in which a fixed price contract or a market price contract was chosen (2304 observations). The exclusion of the opt-out alternative, however, has hardly any impact on the results of the model estimations. In addition, the opt-out alternative should only be selected if the participants cannot decide between the offered contracts. Thus, it has more of a methodical than substantive quality. This also supports the exclusion of the opt-out alternative from the analysis. In model A it is initially assumed that all contract attributes have the same effect on the selection of a fixed price or market price contract (generic effects). Given this assumption it becomes clear that respondents prefer bioenergy villages and farmers to non-agricultural investors as contracting partners (significant positive effects). This supports hypothesis 1. According to this hypothesis, differences in the probability of contract selection are expected to depend on the contracting partner. With regard to the other contract attributes investigated, the following directions of action can be established: An increase of the lifetime of a contract reduces the attractiveness of the contract (significant negative effect), while an increase of the sales price strengthens its attractiveness (significant positive effect). The question of whether there are differences between fixed price contracts and market price contracts is analyzed by using the models B, C and D. Model B shows that, in case of fixed price contracts, the negative effect of the contract lifetime is lower than in case of market price contracts (-0.02 = -0.14+0.12 versus -0.14). However, the positive effect of the sales price is higher in fixed price contracts than in market price contracts (0.17=0.04+0.13 versus 0.04). The models C and D clarify that a bioenergy village is a more attractive contracting partner for a market price contract than for a fixed price contract (negative interaction effect). Farmers are more preferred contracting partners for fixed price contracts than for market price contracts (positive interaction effect). The following implicit prices result exemplary when dividing the coefficients of the nonmonetary attribute by the monetary attribute (95% confidence intervals in parentheses, with the Krinsky-Robb-procedure, Krinsky and Robb, 1986; using 1000 replications): For an additional year of contract lifetime of a market price contract, farmers would have to receive an additional contract premium of on average € 3.36 (1.82 to 6.88) per ton of maize silage as compensation. In addition, for market price contracts, farmers would be willing to give up on average € 12.16 (1.73 to 26.82) per ton if the contracting partner is a bioenergy village. This high price level suggests the need of further investigations. For some of the survey's participants, the term ‘bioenergy village’ probably has implied wrong associations. In contrast, this high amount could also show non-economic intentions of the farm managers (e.g., an expected image improvement). The results support again the validity of hypothesis 1: The kind of contracting partner is relevant for the selection of a contract.
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Table 7.
Results of the conditional logit models
Fixed price (constant) Bioenergy village
A 0.14+ (1.92) 0.26* (2.37)
B 0.04 (0.50) 0.24* (2.15)
0.24* (2.32)
0.26* (2.15)
-0.08* (-5.90)
-0.14* (-4.62) 0.12* (2.27) 0.04* (3.99) 0.13* (6.67) -546.15 0.316 2304
Fixed price x bioenergy village Farmers
C 0.31+ (1.91) 0.50* (2.45) -0.79* (-2.15)
Fixed price x farmers Lifetime Fixed price x lifetime Price
0.10* (16.50)
Fixed price x price LL Pseudo-R² Observations
-574.49 0.281 2304
-0.14* (-4.62) 0.12* (2.27) 0.04* (3.99) 0.13* (6.67) -546.15 0.316 2304
D -0.20 (-1.44)
-0.21 (-1.13) 0.71* (2.15) -0.14* (-4.62) 0.12* (2.27) 0.04* (3.99) 0.13* (6.67) -546.15 0.316 2304
Note: + p
