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INTEGRATION AND ISOMORPHISM AMONG WELFARE STATES IN THE EUROPEAN UNION*

Jason Beckfield Harvard University

* This is a working draft, prepared for presentation at the Fourth Pan-European Conference on EU Politics, hosted by the European Consortium for Political Research in Riga, Latvia, September 2008. Please do not circulate, cite, or quote without permission. Direct correspondence to Jason Beckfield, Department of Sociology, Harvard University, 33 Kirkland Street, Cambridge MA 02138; E-mail [email protected].

1 ABSTRACT The contemporary institutionalization of an international, regional polity and market in the European Union raises key questions about the role of regional integration in the convergence of European welfare states. To date, sociological work has emphasized processes of industrialization and globalization as the social changes that may drive increasing similarity among welfare states. Building on neoinstitutionalist world polity theory and the Europeanization literature from political science, this paper develops the argument that regional integration drives welfare-state isomorphism by generating, diffusing, and enforcing the adoption of policy scripts concerning “appropriate” welfare policy. The hypothesis that deepening regional integration drives growing welfare-state isomorphism is tested with time-series data on variation in welfare spending and novel measures of regional integration, for 15 European Union countries, over the 1960-1998 period. Results from cointegrating time-series (OLS) and autocorrelation-corrected (OLS with Newey-West standard errors) regression models support the hypothesis: regional integration is associated with a reduction in variation among the welfare states of the European Union. This suggests that in theorizing contemporary changes in the welfare state, sociologists should attend to the institutionalization of regional political economy. Welfare states can be conceptualized as embedded in regional, as well as global, systems and institutions.

2 INTRODUCTION Regional integration – the construction of an international polity and market – offers social scientists the unusual opportunity to develop answers to two key questions that animate the political sociology of the welfare state. First, are welfare states in advanced industrial countries converging around a common model of welfare provision? Second, how closely are welfare state dynamics associated with “globalization,” or, more specifically, the rising density of international political and economic ties? In this paper, I argue that Western European welfare states are growing more similar as a consequence of regional integration. The institutionalization of the European Union creates common rules and understandings that foster the adoption of increasingly similar welfare policies, and the adoption of common policies is reflected in a reduction in variation in welfare spending among European Union welfare states. I assess these arguments using time-series data on 14 countries that were members of the European Union as of 1995: Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, the Netherlands, Portugal, Spain, Sweden, and the United Kingdom. Cointegrating time-series regressions of dispersion in welfare spending on regional integration show some evidence of long-run relationships between regional integration and welfare-state isomorphism. Results are shown for three different measures of the welfare state, and two measures of political integration. In what follows, I contextualize the analysis with a discussion of the theoretical foundations of my argument and an overview of prior studies of welfare-state isomorphism. Next, I discuss methodological details and the results of the analysis. I conclude by highlighting the limitations of the analysis, suggesting some implications of the findings, and proposing some directions for further inquiry into welfare-state isomorphism and regional integration. BACKGROUND The argument that regional integration should bring isomorphic change to welfare states builds on institutionalist world polity theory from sociology and the “Europeanization” literature from political science. World polity theory has been developed to explain the growing international similarity of states across a wide variety of policy domains, notably education policy (Boli and Thomas 1997, 1999; DiMaggio and Powell 1983; Meyer 2000; Meyer and Rowan 1977; Meyer et al. 1997). World polity theory explains the growing similarity of states as a function of the creation and diffusion of world culture. World culture contains “policy scripts,” globally-legitimated models of appropriate state policy. The world polity – the global governance network formed by states and international organizations – has received sustained attention as a carrier of world culture. Specifically, international nongovernmental organizations (INGOs) and intergovernmental organizations (IGOs) create and carry the “policy scripts” that states implement as they join world society. Regional organizations like the European Union have been considered part of the population of IGOs in world polity research.

3 There is mounting empirical evidence that the states that belong to the most international organizations are also the states that most quickly implement policies consistent with world scripts in many domains: education (Bradley and Ramirez 1996; Meyer, Ramirez and Soysal 1992; Schafer 1999), environmental protection (Frank 1997; 1999; Frank, Hironaka and Schofer 2000), science (Finnemore 1993), women’s suffrage (Ramirez, Soysal and Shanahan 1997), welfare provision (Strang and Chang 1993), same-sex sexual relations (Frank and McEneaney 1999), population (Barrett and Frank 1999; Barrett and Tsui 1999), and war (Finnemore 1999). Clearly, membership in world society and association with the carriers of world culture matter for states. A limitation of existing research on the world polity is that not enough attention has been given to the precise associational structure of the world polity (Beckfield 2003a; 2003b). Since the 1950s, there has been dramatic growth in regional political organizations. As a consequence, international ties among states are most dense within regions – the “world” polity exhibits clear regionalization (Beckfield 2003b). This raises the question of how regional international organizations matter for state policy. If political globalization brings the adoption of common policies, does political regionalization? The literature on “Europeanization” from political science suggests that it should (Borzel and Risse 2000; Cowles et al. 2001; Knill and Lehmkuhl 1999; Le Galés 2001; O’Hagan 2004). Europeanization is the process by which the national institutions of EU member states are brought together through the adoption of common EU policies. 1 Synthesizing ideas from these two literatures, I argue that the construction of a European polity should bring isomorphism to European welfare states by generating, diffusing, and enforcing scripts concerning welfare policy. As national European states become integrated into the supranational European polity, national policymakers are increasingly exposed to common European models of the welfare state. 2 Concretely, common welfare policy models are diffused through several mechanisms in the course of European integration: the founding treaties of the European Union identify the coordination of welfare policy as an objective of European integration, the European Commission (the body charged with advancing and monitoring integration) promulgates specific policies in the welfare-state domain, and the development of regional rules in other policy domains indirectly drives the adoption of common social policy. In general terms, the harmonization of European states has been on the European Union’s agenda since its original founding in 1957 as the European Economic Community among Belgium, France, Germany, Italy, Luxembourg, and the Netherlands. As it has expanded to include 15 Western European states by 1995, and 25 states by 2004, welfare policy has remained part of the treaties that have been institutionalized by the European Court of Justice as a constitution. For instance, Article 140 of the 1957 Rome Treaty states: 1

Macmullen (2004) In the language of current European Union policymaking, the specific mechanisms by which policies are “harmonized” include “peer review” (Casey and Gold 2005) and the “open method of policy coordination” (O’Connor 2005).

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4 [T]he Commission shall encourage cooperation between the Member States and facilitate the coordination of their action in all social policy fields under this chapter, particularly in matters relating to: employment, labour law and working conditions, basic and advanced vocational training, social security, prevention of occupational accidents and diseases, occupational hygiene, the right of association and collective bargaining between employers and workers (Treaty Establishing the European Community, consolidated version, C-325, 2002:95). The clear implication is that the founding states of the European Union anticipated common developments in social policy, the impact of which would be to reduce differences among the welfare states of EU members. This commitment to common social policies continues in the current proposed Constitution for Europe. Article III-103 reads: The Union and the Member States, having in mind fundamental social rights such as those set out in the European Social Charter signed at Turin on 18 October 1961 and in the 1989 Community Charter of the Fundamental Social Rights of Workers, shall have as their objectives the promotion of employment, improved living and working conditions, so as to make possible their harmonisation while the improvement is being maintained, proper social protection, dialogue between the social partners, the development of human resources with a view to lasting high employment and the combating of exclusion. To this end the Union and the Member States shall act taking account of the diverse forms of national practices, in particular in the field of contractual relations, and the need to maintain the competitiveness of the Union economy. They believe that such a development will ensue not only from the functioning of the internal market, which will favour the harmonisation of social systems, but also from the procedures provided for in the Constitution and from the approximation of provisions laid down by law, regulation or administrative action (Treaty Establishing a Constitution for Europe, provisional consolidated version, 2004:153-4). It is notable that, reflecting the complex politics of EU social policy, the article mentions both the “diverse forms of national practices” and the “harmonisation of social systems.” This is in keeping with longstanding sensitivities concerning the preservation of cultural diversity within the EU. It is also notable that the proposed constitution anticipates the “harmonisation of social systems” through the “functioning of the internal market” – in other words, it should be regional economic integration, and not regional political integration, that drives harmonization. While the EU’s founding treaties reflect the connection between regional integration and the convergence of European welfare states, the treaties do not contain specific policy recommendations. An example of the diffusion of more specific welfarestate models is the European Commission's white paper on social policy, European Social Policy: A Way Forward for the Union (European Commission 1994). The white paper makes specific policy recommendations, and it is clear that the Commission views the development of common social policies as part of the ongoing creation of the

5 European polity and market. The Commission proposes “a wide-ranging technical revision and restructuring of the coordination of social security provisions” (European Commission 1994, italics mine), and commits to “coordinating provisions for certain new types of benefit created by Member States in recent years, such as education benefits and benefits for persons in need of long-term care.” The European Union’s role in national welfare states and welfare policy is a controversial and, to date, limited one, but it is clear that the EU does engage the welfare state through the dissemination of policy scripts. Further indication of this engagement of social policy and this drive toward coordination is the Commission’s 1993 Green Paper on European Social Policy, which identified “convergence of social policies” and “extension of the coverage of social security coordination” as areas for further action (European Commission 1993). Another example of a specific EU policy that should pressure welfare states to become more similar is the “convergence criteria” of the Maastricht treaty that require low public sector deficits and low debt levels (Boje et al. 1999; Pierson 1996; Pitruzzello 1997; Rhodes 1996; Schulz 2000). Compliance with these convergence criteria limit deficit spending in EU welfare states, and thus should level out differences in welfarestate spending among EU members. EU policy is enforced through several mechanisms, ranging from less formal public pressure placed on member states by high-profile European Commission publications such as the “Internal Market Scoreboard” to lawsuits brought by the European Commission against the member states in the European Court of Justice. Regional policy in other domains may have an indirect effect on welfare policy. One of the EU’s general policies that should foster welfare-state isomorphism is the reduction in economic inequality among EU states and regions. Toward this end, the EU provides poorer member states with development aid in the form of so-called “structural” and “cohesion” funds. These funds include the European Agricultural Guidance and Guarantee Fund (established in 1962 to aid rural areas) and the European Regional Development Fund (established in 1972 to even out the dramatic economic disparities among sub-national regions within the EU). If economic disparities among EU member states are reduced through EU policy, then welfare states in the poorer countries should have the resources to catch up to the more generous EU welfare states. European welfare states may grow increasingly similar with deepening integration, given that regional integration reduces economic differences among national economies in Europe (Beckfield 2004; Ben-David 1993) and thus makes similar resources available to European states. The Maastricht convergence criteria and the structural and cohesion funds represent two examples of specific EU policy that should bring isomorphic change to EU welfare states, but regional political integration creates more diffuse institutional forces as well. In support of “ever closer union,” the European Commission – the body of the EU charged with promoting and monitoring integration – publishes policy papers and issues directives, many of which are aimed at “harmonizing” the policies of member

6 states. 3 Even more diffuse institutional pressures are also at work in the EU. The EU has a common currency, open internal borders, and Europe-wide elections for the European Parliament. The free movement of capital and labor within Europe may also create demands for the alignment of welfare states, as corporations seek common tax and regulatory environments and workers seek familiar social programs. Research on the effects of adoption of the single European currency supports this view, in that monetary union reduces national sovereignty in the areas of fiscal and monetary policy (Dyson 2000; cf. Garrett 2000; Pierson 2001). Scharpf (1999) goes even further, arguing that “negative integration,” or the removal of barriers to international economic exchange within the EU, undermines national sovereignty in the area of social policy and produces “regulatory competition,” or a race to the bottom: Negative integration disables existing national policy solutions by prohibiting subsidies to producers, monopolistic and cartelized practices in the provision of goods and service, and all regulations that have the effect of protecting domestic producers from foreign competitors or of restricting in any way the free mobility of goods, services, capital, and labour across national boundaries. As a consequence, national firms are exposed to more intense competition from suppliers producing under different national systems of taxation, regulation, and industrial relations – which greatly reduces their opportunities for shifting to consumers the costs of higher taxes and wages or more burdensome regulations. At the same time, national capital owners, firms, and skilled professionals are themselves free to move to locations governed by different regulatory regimes. The theoretically expected result, then, is a form of economically motivated “regulatory competition” among nation states and unions which undercuts their capacities to regulate and tax mobile factors of production, and to improve the distributive position of labour through collective bargaining (84-85). The more direct impact of freedom of movement within the European Union can be seen in the 1961 European Social Charter, which is referenced in the Maastricht Treaty and the provisional European Constitution. Article 12 of the Charter commits the signatories: to take steps, by the conclusion of appropriate bilateral and multilateral agreements, or by other means, and subject to the conditions laid down in such agreements, in order to ensure: a equal treatment with their own nationals of the nationals of other Contracting Parties in respect of social security rights, including the retention of benefits arising out of social security legislation, whatever movements the persons protected may undertake between the territories of the Contracting Parties (Council of Europe 1961:8). This is one example of how freedom of movement within the European Union creates pressures for isomorphism among welfare states. This process, whereby the development of common policies in one domain generates demand for common policies in another, resonates with the logic of “functional 3

There is ample evidence that implementation of EU directives varies widely among the member states (Duina 1997, 1999; Duina and Blithe 1999).

7 spillover.” The spillover idea is fundamental to the neofunctionalist theory of integration from political science (Haas 1958). Glossing some complexities, the key insight is that integration is a self-sustaining process driven by the demand that the creation of regional policy in one domain creates for regional policy in other domains. For instance, the creation of the common Euro currency could be understood, in part, as spillover from the policies allowing for free movement of labor and capital across national boundaries, which could themselves be understood, again in part, as spillover from the creation of common markets for goods in the early years of the European Economic Community. But there is a difference between the institutional process that I argue drives welfare-state isomorphism and functional spillover. The difference is that with spillover, new supranational policies are developed by policymakers to ensure the success of existing policies; but with institutional isomorphism, states model themselves on other states as a consequence of being drawn into a strongly institutionalized field. I am arguing that regional integration creates Europe-wide policy scripts concerning “proper” “European” welfare states. Given the apparently strong pressures for the Europeanization of welfare states, there is a growing body of studies within political science that examine convergence, or isomorphism, among European welfare states. The literature is not marked by consensus. Focused case studies fail to find isomorphism (Geyer 1998; Martinsen 2004; Pitruzzello 1997; Schulz 2000; cf. Rhodes 1996), while large-sample quantitative studies have found isomorphism, stability, and divergence (Castles 1995; Corrado et al. 2003; Delhey 2001; Garrett and Lange 1991; Greve 1996; Kosonen 1995; Montanari 1995). There is also a substantial literature bridging political science and sociology that examines welfare-state isomorphism in light of the “logic of industrialism” theory of convergence. According to the logic of industrialism, welfare states should grow more similar as national economies develop greater resources and states face the common problems of population aging (Form 1979; Meyer et al. 1975; Mishra 1976; Weinberg 1969; Wilensky 1975; Williamson and Weiss 1979). Research on convergence among the welfare states of the OECD has produced contradictory findings that seem to depend on the period examined: from 1930-1990, there was convergence among OECD welfare states (Montanari 2001), but from 1960-1980, there was divergence (O’Connor 1988). There are also reasons to expect that convergence among national welfare states may not materialize. Prominent among these is the “varieties of capitalism” approach of Hall and Soskice (2001), which anticipates a maintenance of the institutional differences (among these, welfare states) that confer “comparative institutional advantage” upon national firms. Hall and Sockice are skeptical of the convergence hypothesis (54), and even suggest that cross-national institutional differences may be reinforced with globalization: “Over time, corporate movements of this sort should reinforce differences in national institutional frameworks as, as firms that have shifted their operations to benefit from particular institutions seek to retain them” (2001:57). Campbell (2004:129) makes a similar point, arguing against the globalization thesis of converging national institutions. Pierson (2001) strongly argues against convergence among the advanced democracies: “convergence in national social policy structures is not to be expected … all the authors in this volume share this view” (4).

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Previous work on regional integration and isomorphism is limited in that the analyses do not incorporate measures of regional integration. The typical approach is to examine the trends in variation among EU welfare states, without incorporating measures of integration into a formal model (Delhey 2001; Greve 1996). A partial exception to this general pattern is the comparison of welfare-state isomorphism among EU vs. non-EU states: Montanari (1995) finds that the members of the European Free Trade Area converged more quickly across several measures of the welfare state than did EU member states (conducting the analysis in this way is analogous to including an indicator variable for membership in the EU in a statistical model). This limitation also applies to the analyses of logic-of-industrialism convergence. The typical approach in these studies is to select a sample of industrialized countries and test for convergence, without incorporating a measure of economic development into a formal model (Montanari 2001; O’Connor 1988). I build on these previous analyses of welfare-state isomorphism by employing time-series analysis to model the associations between standard measures of variation among welfare states, a standard measure of economic development, and three novel measures of regional integration. DATA AND METHOD The dependent variables for the analysis are the coefficients of variation (a common measure of inequality that is calculated by dividing the standard deviation by the mean) in three measures of the welfare state. For each measure, the coefficient of variation is based on 14 observations, one each from the 15 members of the European Union as of 1995, less Luxembourg: Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, the Netherlands, Portugal, Spain, Sweden, and the United Kingdom. In a given year, the coefficient of variation indicates the degree of dispersion among EU states in how much they spend on social programs. For ease of presentation, this variable is multiplied by 100. The first measure of the welfare state is social security transfers (benefits for sickness, old-age, family allowances, social assistance, and welfare) as a percentage of GDP. Data are available for the 1970-1998 period, and come from OECD Historical Statistics (2001) and the OECD Statistical Compendium (2003). While there is debate over the proper measurement of the welfare state (Korpi 2003), and certainly this spending measure is limited, I use it for the sake of consistency with previous work (Hicks 1999; Huber and Stephens 2001; Swank 2002). Figure 1 shows the trend in the coefficient of variation in the transfers measure. The coefficient of variation decreases sharply from the early 1970s through the late 1980s, then the rate of decrease slows through the late 1990s. It remains to be seen whether this growing isomorphism is related to regional integration, but the finding that European Union welfare states have grown more similar in their expenditures on social security transfers is suggestive, and is itself a notable finding.

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In response to the argument that programmatic measures of the welfare state such as replacement rates are better indicators of welfare policy (Korpi 2003), I also use two measures that incorporate information on replacement rates. The first is the OECD’s “summary measure of benefits entitlements” (OECD 2002). The OECD’s summary measure is the “unweighted average of 18 Gross Replacement Rates: three household types (single, dependent spouse and spouse in work); three time periods (the first year, the second and third year, and the fourth and fifth years of unemployment); and two earnings levels (average earnings and two-thirds of this level).” (OECD 2002:38). Among the many possible alternatives, I selected this one because it incorporates information on replacement rates, and the income replacement rate is one aspect of the extent of the de-commodification of labor (Esping-Andersen 1990; Korpi 2003), and also because the replacement rate should not be as responsive to recession and unemployment as the level of social expenditure. Data on this measure come from the OECD Benefits and Wages (2002), and are available for every other year from 1961 to 1997. Figure 2 shows the trend in dispersion in the OECD measure of the welfare state. There is clear evidence of growing isomorphism: the coefficient of variation declines slowly through 1971, but the rate of decline accelerates through the 1990s. Although the figure indicates that differences among EU welfare states grew somewhat in 1995 and 1997, the overall impression that can be drawn from the figure is one of notable isomorphic change among the EU welfare states. The third measure is Lyle Scruggs’ decommodification index (Scruggs and Allan 2004). This index is also based in part on replacement rates, but it is somewhat broader than the OECD measure, in that it includes information on pension and sickness benefits. Data on this measure are available for 1971-1998. Figure 3 shows the trend in the coefficient of variation in the decommodification index among the 14 states in the sample. Until around 1989, the level of dispersion in decommodification remains stable, or even increases slightly. After 1989, there is evidence of increasing isomorphism among these 14 European Union states. Consistent with conceptualization of regional integration as having both political and economic dimensions (Fligstein and Stone Sweet 2002), the independent variables are political and economic integration. I use two measures of political integration. First, following Fligstein and Stone Sweet (2002), I measure political integration as the number of cases sent from national courts to the European Court of Justice. This measure improves on measures of political or formal integration used in previous work (typically, an indicator variable for “member of the EU” where the unit of analysis is country, or “establishment of the EU” where the unit of analysis is region or world). Under Article177 of the 1957 Rome Treaty establishing the European Economic Community, national courts forward cases involving EU law to the European Court of Justice, the judicial body with final, binding authority to interpret EU law. Thus, the number of cases forwarded from member states of the EU in a given year is an indicator of claims made on laws of the regional polity by members of national polities. I argue that an increase in the cases

10 sent to the regional court indicates increasing integration of national polities with the regional polity, and deepening institutionalization of the regional polity. A complete time series of observations on this variable is available through 1997; data come from Stone Sweet and Brunell (1999). Figure 4 shows the trend in the number of Article-177 cases forwarded to the ECJ by the 15 EU countries. The figure shows clear evidence of increasing political integration since the 1960s – the number of cases remains very low through 1966, but then begins increasing rapidly, and continues growing through the 1990s. This provides some circumstantial evidence that regional political integration may be associated with welfare-state isomorphism since they grew in tandem, but this cannot be considered conclusive evidence of a connection between the two variables. The second measure of political integration is the number of directives adopted by the European Union in a given year. In the EU, the European Commission is the organization that has responsibility for advancing the adoption of common policies, and monitoring progress toward integration. The Commission also has the authority of legislative initiative, and proposes directives to the Council of Ministers. The Council of Ministers then decides, sometimes in cooperation with the European Parliament, whether to adopt directives. If a directive is adopted, the goals of the directive are binding on the member states, although the member states are free to determine the precise legal mechanism of compliance. Member states comply with EU directives through the adoption of national implementing measures. If a member state fails to comply, the European Commission can bring suit against it in the European Court of Justice under the provisions of Article 169 of the Rome Treaty. Thus, the number of directives adopted in a given year is one measure of the construction of the European polity. Data come from the European Union’s CELEX database (Office of Official Publications of the European Communities 2002). As Figure 4 showed for the first measure of political integration, Figure 5 shows that political integration trends upward over the 1959-1997 period. The difference between the two trends is that the trend in directives seems to follow two different slopes: rapid growth in the 1959-1976 period, and slower (and bumpier) growth thereafter. Economic integration is measured as exports to EU countries as a percentage of total exports. 4 Intraregional exports have been used in previous work as a measure of economic integration (Fligstein and Stone Sweet 2002; Frankel 1997). This measure taps the extent to which the national economies of the EU are embedded in exchanges with other EU countries, and as such this indicator of economic integration has face validity. 5 4

Frankel (1997:21-25) notes that intraregional trade shares will be larger for regions with more countries, which makes intraregional trade shares inadequate measures of regional integration in the context of interregional comparisons. The impact of region size on intraregional trade share also makes time-series analysis problematic, if the size of the region varies over time. Neither issue is relevant to this analysis, since I do not compare regions, and I analyze change in economic integration within the EU-15. 5 Another valid indicator is intraregional investment share; i.e., the proportion of direct investment to/from the region as a proportion of the region’s total direct investment. Unfortunately, data on this measure are

11 Economic integration increases if countries within the region trade with each other more, and economic integration decreases if countries within the region trade with each other less, as a proportion of their total trade. Complete time series of observations on exports by country are available for all EU countries except Austria (which is missing data for 1959) through 1997; the data for Germany are for West Germany through 1990. Data were provided by Andrew Rose and come from the IMF’s Direction of Trade CD-ROM. Calculation of the economic integration measures was straightforward: the exports measure was calculated by dividing the sum of exports to EU countries from other EU countries in a given year by the sum of exports from EU countries in that year. Figure 6 shows the trend in economic integration. Economic integration does not follow as clear a trend as the other variables. It rises steeply through 1965, rises more slowly (and in a bumpier fashion) through 1990, then declines thereafter. There is thus impressionistic evidence that the economic integration series may not be cointegrated (see below) with the two welfare-state isomorphism series. I also include in the models a control for real GDP per capita, to address the conventional convergence hypothesis that welfare states grow more similar as they gain more economic resources and face common social problems (such as population aging). Data for real GDP per capita come from the Penn World Table (Heston et al. 2002). The Penn World Table reports purchasing-power-parity converted GDP figures in 1996 US dollars. This conversion facilitates cross-national comparability. For the analysis of the European Union, I created a real GDP per capita variable for the EU by multiplying each member state’s real GDP per capita by its population, summing the result across the countries, then dividing the total by the sum of the populations of the EU countries for each year. This variable is coded in thousands of dollars. Figure 7 shows the trend in real GDP per capita for 1959-1997. The trend is a near-perfect positive linear trend, indicating consistent economic growth for these 15 EU countries. This growth drops off somewhat during the early 1980s, but continues at close to the same pace thereafter. It appears that economic development also occurred in tandem with welfare-state isomorphism. To assess the relationship between regional integration and the degree of isomorphism among welfare states in Western Europe, I employ time-series analysis (the following discussion draws on Greene [2000], Gujarati [1995], and Wooldridge [2003]). Time-series analysis includes a wide range of specialized techniques for modeling longitudinal dynamics and correcting for the serial dependency (or autocorrelation) that usually renders the more familiar, OLS-based regression techniques problematic. For instance, many time-series variables exhibit strong trends, and it is well-known that regressing one trending variable on another can produce a spurious regression: trending variables are non-stationary (that is, they do not meet the conditions of constant mean and variance over time, and time-independent covariance), and strong associations among trending variables can be caused by the presence of common trends. A typical solution to only available from 1980 onward, which prevents this measure from being a useful addition to the timeseries analysis.

12 the spurious regression problem is to difference (take xt – xt-1) each series until it satisfies the conditions of stationarity, and then employ an estimator that accounts for any remaining autocorrelation among the residuals. 6 This approach is limited, in that differencing removes information about possible long-term relationships among variables. There are two consequences of this loss of information: first, models that use differenced data must be interpreted in terms of short-term changes; second, and more seriously, theories that are expressed in levels cannot be tested with data on short-term changes. Janoski and Isaac (1994) note that in differencing: The researcher, however, often creates a new variable with differences and must be prepared to alter his or her theory to match the new meaning. … Whether level variables or change variables are employed must ultimately depend on the theoretical purposes of the analysis” (34). Along the same lines, Jacobs and Helms (1996:338), who estimate time-series regressions with differenced variables, note that differencing is “a severe remedy” and should not necessarily be implemented in all time-series analyses in a mechanical fashion. There is a special case where level-on-level time-series regression is not plagued by spuriousness, even when the dependent and independent variables trend. OLS regression can be used with trending time-series variables when the variables are cointegrated. Cointegrated time-series meet two conditions: (1) they are integrated of the same order – for instance, if a series is stationary after taking first-differences, it is integrated of order 1, denoted I(1); (2) the residuals from a regression of cointegrated time-series are stationary – that is, they are I(0). Although techniques for cointegrated time-series regression are still evolving, testing the conditions for cointegration is straightforward. The first step is to determine whether the variables in question are integrated of the same order. This can be done by Dickey-Fuller tests for unit roots. If a variable has a unit root, the partial regression coefficient for the variable’s one-year lag equals 1, meaning that the variable can be characterized as a random walk, which is a nonstationary time series. If the DickeyFuller test is significant, the null hypothesis that the variable has a unit root can be rejected. In other words, a significant Dickey-Fuller test statistic is evidence that the variable is stationary. In the context of cointegrated time-series regression, if the DickeyFuller test statistic is significant for two first-differenced variables, the first condition for cointegration of the two variables is satisfied. The second step is to test the residuals from the levels-on-levels regression for stationarity. One of the most popular tests is the Engle-Granger test, itself a modification 6

In sociology, there is no consensus on which of the many techniques that can be applied to time-series data should be applied. See Beck and Tolnay (1990) and Jacobs and Helms (1996) for examples of the use of differencing combined with an autocorrelation correction. See Jenkins, Jacobs, and Agnone (2003) for an example of the use of Prais-Winsten GLS regression using variables in levels. See Isaac and Christiansen (2002) and McAdam and Su (2002) for examples of Poisson and negative binomial regressions using variables in levels, with no correction for autocorrelation.

13 of the Dickey-Fuller test. The Engle-Granger test is conducted by estimating the candidate cointegrating regression, calculating the residuals, and using the Dickey-Fuller test to examine the residuals for a unit root. If the test is significant, there is evidence that the residuals are stationary, and that the time-series variables are cointegrated. A complication with the test is that the critical values for the test do not follow any standard distribution (the test is known as Engle-Granger because Engle and Granger first calculated the appropriate critical values for the test). The critical values depend on several factors, including the number of variables in the cointegrating regression and the number of observations. MacKinnon (1991) calculated simulation-based critical values for a range of parameters, and I use MacKinnon’s critical values for this analysis. If two time-series variables are cointegrated, the usual problems with using OLS to estimate regressions of one time-series variable on another, with both in their original levels, are avoided. Gujarati notes: In general, if Y is I(d) and X is also I(d), where d is the same value, these two series can be cointegrated. If that is the case, the regression on the levels of the two variables … is meaningful (i.e., not spurious); and we do not lose any valuable long-term information, which would result if we were to use their first differences instead. In short, provided we check that the residuals from regressions [like the ones discussed above] are I(0) or stationary, the traditional regression methodology (including t and F tests) … is applicable to data involving time series (Gujarati 1995:726). Likewise, Wooldridge (2003:616-617) writes that “if yt and xt are cointegrated, it turns out that the OLS estimator βˆ from the regression yt = αˆ + βˆx is consistent for β .” Given that the time-series variables used in this analysis satisfy the conditions for cointegration, I follow Greene (2000), Gujarati (1995), and Wooldridge (2003) and estimate OLS regressions using the untransformed time-series in their original levels. By Dickey-Fuller tests for unit roots, the analysis variables are integrated of order 1, thereby satisfying the first condition for cointegration. 7 By Engle-Granger tests, the second condition for cointegration, that the residuals from the cointegrating regression be stationary, or I(0), is also satisfied in several of the models. As a robustness check, I also estimate OLS models with an autocorrelation-consistent covariance matrix estimator, the Newey-West estimator. This model is designed to account for serial autocorrelation in the residuals. As there are some OLS models where the second cointegration condition is not satisfied, the fact that the Newey-West results are consistent with the OLS results is reassuring. I discuss the Newey-West results in the text, but for the sake of space, these models are not shown. 7

There is marginal evidence that the social spending measure of the welfare state and the EU exports measure of economic integration may be I(0). The p-value for the Dickey-Fuller test for a unit root in the social spending series is .029, whereas an inpsection of the correlogram indicates significant autocorrelation in the undifferenced series. The same pattern holds for the measure of economic integration: the p-value for the Dickey-Fuller test is .0134, but the correlogram shows strong evidence of autocorrelation in the undifferenced series. These results are in constrast to those for both differenced series: both the Dickey-Fuller tests and the correlograms show strong evidence that both series are I(1).

14

The analysis proceeds as follows. First, I perform Dickey-Fuller unit root tests for stationarity to assess whether the variables are I(1). Next, I estimate bivariate regressions of each dependent variable on the one-year lag of each independent variable. Following estimation of the model, I then check the residuals for stationarity, using the Engle-Granger test (with critical values from MacKinnon [1991]). Then, for the one dependent variable where the GDP series is cointegrated with the trend in welfare-state isomorphism, I estimate multivariate models that give the associations between welfare state isomorphism and the regional integration measures, net of EU real GDP per capita. For each dependent variable, there are a minimum of four and a maximum of seven models. For each model, I report the coefficient estimates, standard errors, R-squared, and the Engle-Granger test statistics. Where these test statistics are marked with an asterisk, the test is evidence for cointegration (that is, a significant test statistic means that the null hypothesis of nonstationarity in the residuals can be rejected). For other examples of cointegrating regression analysis, see Borjas and Ramey (1994), Caldeira and Zorn (1998), Engle and Granger (1987), Missale and Blanchard (1994), and Stone Sweet and Brunell (1998). RESULTS Table 1 shows results from cointegrating time-series OLS regression models of the coefficient of variation in total social security expenditures. Model 1 includes only the Article-177 cases measure of political integration. The coefficient is statistically significant and negative, which suggests that there is a negative association between political integration and variation in welfare spending. As political integration rises, dispersion among welfare states falls. The small magnitude of the coefficient is due to the scale of the variables involved. The substantive significance of the relationship is suggested by the R2 of .724, which corresponds to a standardized coefficient for political integration of -.851. But the cointegration test is not statistically significant. The EngleGranger test is -2.363, above the 10% significance critical value of -3.199. Model 2 uses the second measure of political integration, the number of EU directives, and the results are consistent with those from Model 1. The association is negative and statistically significant, which is consistent with the hypothesis that political integration reduces differences among welfare states. The relationship between dispersion in welfare spending and EU directives does appear somewhat weaker than that between dispersion in welfare spending and Article-177 cases, as the standardized coefficient in Model 2 is -.789, but overall the results for the two measures of political integration are consistent. The Engle-Granger test for cointegration again fails to reach significance in this model (the test statistic of -2.707 is above the 10% critical value), suggesting that these variables are not cointegrated. Model 3 introduces the measure of economic integration, the percentage of exports from EU countries that go to other EU countries. While the coefficient estimate for the exports variable is statistically significant, the variables are again not cointegrated

15 according to the Engle-Granger test. The test statistic of -.980 is well above the 10% critical value of -3.199. Model 4 includes real GDP per capita for the EU, to assess the hypothesis, drawn from the logic-of-industrialism approach to convergence, that welfare-state isomorphism is associated with economic development. The results suggest that development is strongly associated with welfare-state isomorphism: the coefficient is negative and statistically significant, and the standardized coefficient is -.890. But the Engle-Granger test suggests that the variables are not cointegrated. The nonsignificant results for the cointegration tests suggest that the residuals from the cointegrating regressions are not white noise; i.e., the residuals from these regressions show evidence of significant serial autocorrelation. The nonsignificant Engle-Granger test shows that the null hypothesis of a unit root in the residuals cannot be rejected. To assess the robustness of these OLS results to the remaining serial autocorrelation in the residuals, I also estimated OLS models with an autocorrelationconsistent covariance matrix estimator (ACCME), the Newey-West estimator. Again, for the sake of space, the Newey-West models are not shown. In the Newey-West models, the regression coefficients are still estimated with OLS, but the Newey-West ACCME adjusts the standard errors for autocorrelation (OLS is unbiased but also inefficient in the presence of residual autocorrelation). The Newey-West results are substantively equivalent to those shown in Table 1: in all four models, the coefficient reaches statistical significance at the .05 level. These models suggest that regional integration and economic development are significantly associated with welfare-state isomorphism. Table 2 shows results from models of the second dependent variable, dispersion in the OECD’s “summary measure of benefits entitlements” (OECD 2002). I note that these models must be interpreted with caution, given the small sample. There are only 19 observations on the dependent variable, one for each odd-numbered year between 1961 and 1997. Bivariate models are shown in Table 2. Model 1 is a regression of dispersion in the OECD measure of the welfare state on the Article-177 cases measure of political integration. The coefficient is negative and statistically significant, indicating that higher levels of political integration are associated in less dispersion among welfare states. The relationship is substantively significant as well, as indicated by the high R2 of .894 and the large standardized coefficient of -.945. However, the Engle-Granger test shows that the variables are not cointegrated, as the test statistic of -1.815 falls above the 10% critical value of -3.290. Model 2 is a regression that replaces the Article-177 cases measure with the EU directives measure. The results are substantively identical to Model 1, except that the Engle-Granger statistic is significant in this model (the test statistic is -5.819, well below the 5% critical value of -3.688). This indicates that the substantively large (the standardized coefficient is -.946) and statistically significant association estimated between political integration and dispersion among welfare states in this model represents a long-run relationship. Higher levels of political integration (measured as the number of EU directives) are associated with higher levels of welfare-state isomorphism.

16

The results from Model 3 in Table 3 are substantively identical to the results shown in Model 3 of Table 1: as with the first measure of the welfare state, economic integration is associated with welfare state isomorphism, but the Engle-Granger tests suggests that the variables are not cointegrated. This is evidence that economic integration and welfare-state isomorphism do not have a long-run relationship. This is in contrast to the relationship between welfare-state isomorphism and economic development shown in Model 4. The substantively large and statistically significant coefficient, along with the significant Engle-Granger test for cointegration, suggests that higher levels of economic development are strongly associated with higher levels of welfare state isomorphism. The Newey-West analogues to the models shown in Table 3 suggest that the significant associations in all models shown in Table 3 are robust to correction of the standard errors for serial autocorrelation in the residuals. Because there is evidence that GDP per capita and welfare-state isomorphism are cointegrated, I also estimated models that include GDP per capita as a control. Table 3 shows results from these models that estimate the associations between welfare-state isomorphism and regional integration, net of the strong relationship between welfarestate isomorphism and economic development. Models 1 and 3 fail the cointegration tests (the test statistics, -3.090 and -3.498 respectively, are smaller in absolute magnitude than even the 10% critical value of -3.807), suggesting that welfare-state isomorphism does not have a long-run relationship with Article-177 cases, EU exports, or EU real GDP per capita. However, the results for Model 2 indicate that higher levels of EU directives are significantly associated with less dispersion in the OECD measure of the welfare state. In Model 2, the coefficient for EU directives is statistically significant at the .10 level and substantively large (the standardized coefficient is -.327). The EngleGranger test is also just significant at the .10 level (the test statistic, -3.877, marginally falls below the critical value of -3.807). In sum, the results for Table 4 show some evidence that one measure of political integration is associated with welfare-state isomorphism net of economic development, but the results are hardly conclusive. In the statistical significance of the independent variables, the results from the Newey-West analogues are consistent with those shown in Table 4. The coefficient for the GDP covariate is statistically significant in all three models, but only the coefficient for the EU directives measure of regional integration reaches significance. Table 4 shows results from models of the third dependent variable, dispersion in decommodification. In Model 1, the number of Article-177 cases has a significant negative association with this measure of welfare-state isomorphism. The standardized coefficient is -.468, suggesting a substantial association, but one that is smaller than those shown in Tables 1 and 2. The Engle-Granger test shows that the variables are cointegrated (the test statistic of -3.779 falls below the 5% critical value of -3.567). The results for the other covariates are much weaker. Only the GDP effect reaches

17 significance, but the Engle-Granger test shows that GDP and dispersion in decommodification are not cointegrated. The Newey-West results are substantively identical to those shown in Table 4, except that the GDP coefficient does not reach significance at the .10 level.

SUMMARY AND DISCUSSION This paper develops the argument that the creation of a regional European polity drives increasing isomorphism among Western European welfare states. I argue that differences in welfare spending among the member states of European Union are reduced as regional integration in Western Europe has advanced, because the European Union diffuses “policy scripts” for welfare states. As states grow more deeply integrated into the European Union, and as the European Union generates more regional rules, national policymakers adopt common policies. This convergence on a “European” model of the welfare state may occur through two of the institutional mechanisms identified by DiMaggio and Powell (1983): mimetic isomorphism, whereby EU member states model their policies on other EU member states in an uncertain environment (especially since the 1973 oil crisis); and coercive isomorphism, whereby EU member states implement EU policy directives (or face formal and informal sanctions). Several European Union policies should foster isomorphic change among EU welfare states: among these are the convergence criteria of the Maastricht Treaty, which restrict national autonomy in the areas of fiscal and monetary policy by limiting budget deficits and inflation rates, and the cohesion and structural funds that provide economic aid to poorer regions in an effort to level out macroeconomic disparities within the EU. I assess this argument with time-series data on 14 European Union member states from 1960 to 1998. Descriptive analysis of the trend in dispersion among welfare states shows that variation among the 14 welfare states decreased over this period. This finding of growing isomorphism among EU welfare states holds for three different measures of the welfare state: social security transfers as a percentage of GDP, a common measure of welfare effort; the OECD’s summary measure of benefit entitlement, a measure based on the replacement rates of unemployment benefits; and a decommodification index that includes information on replacement rates from unemployment, sickness, and pension programs. Regressions of dispersion in welfare spending on measures of regional integration suggest that there is an association between regional political integration and growing welfare-state isomorphism: deeper political integration (measured as the number of European Union directives and as the number of Article-177 cases in the European Court of Justice) reduces differences among EU welfare states. Significant associations remain after controlling for another potential force for convergence, economic development (measured as real GDP per capita for the European Union). Before placing these findings in a more general context, it is important to note the specific limitations of this analysis. First, although the results are consistent with the

18 argument that regional integration drives welfare-state isomorphism through institutional mechanisms, these mechanisms are not explicitly tested through incorporation in the statistical models. The mechanisms are unmeasured. Second, although there are statistically significant and strong associations between political integration and welfarestate isomorphism in most models, these associations are not robust across every model, and cointegration tests suggest limited evidence of long-run relationships. Third, although the analysis uses the measure of the welfare state that is arguably the standard in the quantitative comparative literature, and supplements that spending-based measure with two measures that are based on replacement rates, it must be acknowledged that the results could differ with other measures. It would be especially valuable to model variation in measures that more closely reflect the form of the welfare state. Fourth, the analysis would be strengthened by the incorporation of more controls. In particular, including a covariate for world-polity ties would allow for a direct comparison of globalization and regionalization effects. Acknowledging the limitations of this study, the evidence that EU welfare states have converged is still surprising, given the limited evidence in the literature for convergence among welfare states in advanced industrial societies. For instance, O’Connor (1988) finds evidence of divergence among OECD welfare states, and Montanari (2001) finds mixed evidence of convergence and divergence. One explanation for these contrasting findings is that convergence is not a general phenomenon among the rich societies of the world, but instead a place-specific phenomenon among societies undergoing regional integration. This suggests further support for the politicalinstitutionalist argument that it is the creation of regional rules and institutions that drive welfare-state isomorphism, since the regional polity of the EU has a more elaborate set of institutions and stronger coercive force than the world polity. Of course, an alternative explanation is that the findings are driven by measurement, since the previous studies use measures of the welfare state that differ subtly from those used here (O’Connor uses the International Labor Organization’s classification of welfare spending, normed by GDP, and Montanari uses new indicators from Korpi and Palme’s Social Citizenship Indicator Program). Evidence for increasing isomorphism among EU welfare states is, however, consistent with claims from the Europeanization literature. It does appear that European Union member states are becoming more similar, at least in terms of overall welfare spending, replacement rates of unemployment insurance programs, and overall decommodification. It remains to be seen what the direction of this isomorphism is. Future work should focus on the national rather than the regional level of analysis, to determine whether European integration moves welfare states to a more generous model of social provision or pressures welfare states toward retrenchment. Both these scenarios could be tested against the alternative that regional integration reduces welfare spending in the most generous EU welfare states while it increases spending in the least generous states, thus having no average effect on the level of welfare spending in the EU member states.

19 The results suggest that political integration is a stronger force for isomorphism among welfare states than economic integration. This implies that what matters for welfare-state convergence is not common economic pressures from an integrated market, but instead the diffusion of regional rules coupled with strong enforcement mechanisms. Pushing this line of reasoning a step further, this pattern of findings is consistent with the argument that the welfare state exists as an organization in a field that responds to institutional pressures, rather than simply adapts efficiently to economic conditions. Finally, these findings hold several implications for the globalization literature. Political globalization, or the increasing involvement of states in international organizations, is an important force for the development of common policy across a variety of domains (Meyer 2000). The evidence above suggests that the forces for policy convergence are particularly strong at the regional level of analysis, raising the question of how globalization and regionalization interact in the welfare-state domain.

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27 Figure 1. Welfare-State Isomorphism (Coefficient of Variation in Social Spending as a Percentage of GDP) for 15 European Union Countries, 1970-1998

C o e f f . o f V a r . in S p e n d in g

35

18 1970

1980

1990 Year

1998

28 Figure 2. Welfare-State Isomorphism (Coefficient of Variation in the OECD Summary Measure of Benefit Entitlement) for 15 European Union Countries, 1961-1997

77

C o e f f . o f V a r . in O E C D M e a s u r e

70

60

50

40

31 1961

1970

1980 Year

1990

1997

29 Figure 3. Welfare-State Isomorphism (Coefficient of Variation in Decommodification) for 15 European Union Countries, 1971-1998

CV in Decommodification

20

12 1971

1980

1990 Year

1998

30 Figure 4. Political Integration (European Court of Justice Article-177 Cases), 1959-1997

A r tic le - 1 7 7 C a s e s

261

0 1959

1970

1980 Year

1990

1997

31 Figure 5. Political Integration (European Union Directives), 1959-1997

E U D ir e c tiv e s

122

1 1959

1970

1980 Year

1990

1997

32 Figure 6. Economic Integration (Exports to the EU as a Percentage of Total Exports), 15 European Union Countries, 1959-1997

70

E x p o r ts to E U a s % o f T o ta l

65

60

55

48 1959

1970

1980 Year

1990

1997

33 Figure 7. Economic Development (Real GDP per Capita in Thousands of US Dollars) of 15 European Union Countries, 1959-1997

G D P p e r C a p ita , in T h o u s a n d s

21

16

11

6 1959

1970

1980 Year

1990

1997

34 Table 1. Unstandardized Coefficients from OLS Regressions of the Coefficient of Variation in Social Spending on Measures of Regional Integration and Real GDP per Capita, European Union Countries, 1970-1998 Variable

Model 1

Article-177 Cases

-.067** (.008)

Directives

Model 2

Model 3

-.163** (.024)

Exports to the EU, % of Total Exports

-.803** (.349)

EU Real GDP per Capita Constant

R2 Cointegration tests: Dickey-Fuller

Model 4

-1.517** (.150) 33.451** (1.104)

37.144** (1.883)

75.819** (21.977)

49.128** (2.395)

.724

.622

.164

.792

-2.363

-2.707

-.980

-1.803

Notes: Independent variables are lagged one year. Standard errors in parentheses. *p < .10; **p < .05 (two-tailed tests, except cointegration test)

35 Table 2. Unstandardized Coefficients from OLS Regressions of the Coefficient of Variation in the OECD Summary Measure of Benefit Expenditure on Measures of Regional Integration and Real GDP per Capita, European Union Countries, 1961-1997 Variable

Model 1

Article-177 Cases

-.191** (.016)

Directives

Model 2

Model 3

-.398** (.033)

Exports to the EU, % of Total Exports

-2.842** (.490)

EU Real GDP per Capita Constant

R2 Cointegration tests: Dickey-Fuller

Model 4

-3.436** (.226) 74.721** (1.815)

78.598** (2.057)

231.128** (29.952)

103.983** (3.170)

.894

.896

.664

.931

-1.815

-5.819**

-1.839

Notes: Independent variables are lagged two years. Standard errors in parentheses. *p < .10; **p < .05 (two-tailed tests, except cointegration test)

-3.367*

36 Table 3. Unstandardized Coefficients from OLS Regressions of the Coefficient of Variation in the OECD Summary Measure of Benefit Expenditure on Measures of Regional Integration and Real GDP per Capita, European Union Countries, 1961-1997 Variable

Model 1

Article-177 Cases

-.055 (.042)

Directives

Model 2

Model 3

-.138* (.075)

Exports to the EU, % of Total Exports

.303 (.452)

EU Real GDP per Capita

-2.507** (.742)

-2.337** (.638)

-3.705** (.461)

Constant

96.385** (6.567)

96.399** (5.102)

89.096** (22.404)

.938

.943

.933

R2 Cointegration tests: Dickey-Fuller

-3.090

-3.877*

-3.498

Notes: Independent variables are lagged two years. Standard errors in parentheses. *p < .10; **p < .05 (two-tailed tests, except cointegration test)

37 Table 4. Unstandardized Coefficients from OLS Regressions of the Coefficient of Variation in Scruggs Decommodification Index on Measures of Regional Integration and Real GDP per Capita, European Union Countries, 1971-1998 Variable

Model 1

Article-177 Cases

-.012** (.005)

Directives

Model 2

Model 3

-.012 (.013)

Exports to the EU, % of Total Exports

-.008 (.125)

EU Real GDP per Capita Constant

R2 Cointegration tests: Dickey-Fuller

Model 4

-.216** (.104) 17.839** (.638)

17.188** (1.046)

16.815** (7.914)

19.731** (1.691)

.219

.030

.0002

.141

-3.779**

-2.610

-2.435

Notes: Independent variables are lagged one year. Standard errors in parentheses. *p < .10; **p < .05 (two-tailed tests, except cointegration test)

-3.121