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4th Norwegian-German Seminar on Public Economics Grand Hotel Sonnenbichl, Garmisch-Partenkirchen 16 – 17 September 2005 Fiscal Decentralization, Interjurisdictional Competition and Welfare Spending Jon H. Fiva CESifo Poschingerstr. 5, 81679 Munich, Germany Phone: +49 (89) 9224-1410 - Fax: +49 (89) 9224-1409 [email protected] http://www.cesifo.de Fiscal Decentralization, Interjurisdictional Competition and Welfare Spending Jon H. Fiva* Center for Economic Research Department of Economics, Norwegian University of Science and Technology, N-7491 Trondheim, Norway (E-mail: [email protected]) Abstract This paper studies the relationship between fiscal decentralization and welfare spending. Utilizing new panel data on fiscal decentralization for 19 OECD countries, a robust negative relationship is established. The results are interpreted to be driven by fiscal competition. Fiscal decentralization yields increased fiscal competition which makes it harder for welfare states to redistribute between income groups. JEL Classification: H11, H53, H73, H77 Keywords: Fiscal federalism, sub-national fiscal autonomy, fiscal competition, redistribution. First draft: May, 2005. This version: August 3, 2005 Comments welcome! * I thank Dan Stegarescu for making his data available to me. Funding from the Norwegian Research Council under the FIFOS program is highly appreciated. 1 1. Introduction A large literature in public finance going back to Stigler (1957) and Musgrave (1959) has warned against the consequences of decentralized responsibility for redistribution. Policies that are redistributive in nature give rise to a phenomenon that resembles adverse selection: net beneficiaries of redistributive policies are attracted to generous jurisdictions, while net contributors are repelled (Wildasin 1991, 1994). This gives sub-central levels of government incentives to behave strategically in the setting of tax rates and welfare benefits. Empirical analyses have provided strong support for this notion of strategic interaction (for a summary see Wilson (1999) on tax competition and Brueckner (2000) on welfare competition). The main concern in the theoretical literature is that such fiscal competition can lead to levels of taxation and welfare benefits that are suboptimal seen from the society’s point of view. Nonetheless, have many countries assigned considerable responsibility for redistribution to sub-central levels of government. Consequently, one would expect to find that more fiscally decentralized countries will facilitate stronger intergovernmental competition, yielding a smaller public sector.1 Following Oates (1985) a large empirical literature has looked for evidence of downward pressure on tax revenues from decentralization of taxing powers. There exists some empirical evidence suggesting a negative relationship between fiscal decentralization and the size of government (see the discussion in Stein, 1999:365 and Rodden, 2003). However, an even harder task than to establish the relationship between decentralization and the size of government is to assert the welfare consequences of such a relationship. The welfare consequences are dependent on how one envisions public-sector decision-making. The literature on collective choice suggests a range of possibilities including everything from benevolent planners who seek to maximize the ‘well-being of society’, to utility maximizing bureaucrats with preferences for budgetary slack. In the former case fiscal competition is clearly welfare-reducing.2 But when governments not always act in the best interest of the citizens, fiscal competition may help to constrain a public sector that would otherwise have been inefficiently large (the argument of Brennan and Buchanan (1980)). In this paper I do not explicitly aim to evaluate whether fiscal competition is “good or bad”, I simply acknowledge that a more decentralized governmental structure will make it harder to carry out redistribution. Hence fiscal decentralization is expected to be negatively associated 1 Note that if the strategic interaction is driven by yardstick competition it is not clear that overall redistribution goes down with increased decentralization. 2 The magnitude of the welfare loss is however an open question. 2 with welfare spending. This is also what the empirical cross country literature on decentralization and redistribution has found. However these studies often rely on a simple federalism dummy to capture fiscal decentralization (as for example Swank, 2002: 89, insert more references). But as Rodden (2004:496) points out – if intergovernmental competition is driving the negative effect of decentralization on redistribution, a simple dummy for federalism seems to be a very poor proxy. This paper offers a systematic analysis of fiscal decentralization on welfare state effort. To motivate the analysis I present a model based on Wildasin (1991). Wildasin’s benchmark model of interjurisdictional migration shows how decentralized responsibility for the ‘redistribution branch’ yields lower redistribution in equilibrium. The empirical analysis is based on panel data from 19 OECD countries3 over the period 1965 to 1999. The analysis is distinctive in at least two ways. First, I base inference on both cross country and within country variation. This empirical methodology is more rigorous than what is common in the welfare state literature, which typically base it’s inference on pure cross country variation or pooled ordinary least squares (OLS). Here I also pursue these strategies, but in addition I evaluate how a full battery of dummy variables for both country and year fixed effects affects the results. Second, I apply a new data set developed by Stegarescu (2004) that focuses on sub-central government revenue decentralization. Stegarescu’s contribution is to differentiate between revenue of sub-central government levels according to their ability to determine revenue sources autonomously. Strict use of account data, which is common in the fiscal decentralization literature, may give rise to confounded results because correspondence between budgetary items and actual decision making might be imperfect. Measuring welfare spending as social security transfers of GDP, I find evidence consistent with the interjurisdictional competition hypothesis. Estimation methods that rely on cross country and within country inference both suggest that a one standard deviation increase in fiscal decentralization reduces the share of spending on social security out of gdp with around 2 percentage points. 3 The 19 countries included in the analysis are: Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Ireland, Japan, Netherlands, New Zealand, Norway, Portugal, Spain, Sweden, Switzerland, the United Kingdom and the United States. 3 The rest of the paper is organized as follows. Section 2 presents the theoretical framework and the main hypothesis. Section 3 describes the data on fiscal decentralization, while section 4 introduces data on welfare spending and presents the econometric design. In section 5 the results are presented. Section 6 discusses possible endogeneity problems and section 7 concludes. 2. Theoretical framework A large literature initiated by Stigler (1957) and Musgrave (1959) warns against decentralized responsibility for redistribution. Sub-central governments face incentives to set taxes and transfers to influence the location of households. When mobility is high this may give a level of redistribution which is ‘too low’ seen from the country’s point of view. To clarify this migration externality, I adapt David Wildasin’s (1991) model of income distribution in a common labor market, also discussed by Brueckner (2000) and Saavedra (2000). Wildasin’s benchmark model of interjurisdictional migration shows how decentralized responsibility for the ‘redistribution branch’ yields lower redistribution in equilibrium. The central mechanism is the mobility of welfare clients. In Wildasin’s model it is the endogenous determination of wages that equilibrate migration flows and prevents a complete ‘race to the bottom’. Wheaton (2000) presents an alternative framework where the equilibrating mechanism is idiosyncratic preferences for location among the poor. Consider a country composed of I local governments, indexed from i= 1, …I, with two kinds of households, ‘rich’ and ‘poor’. Each poor household is endowed with 1 unit of labor and are assumed to be perfectly mobile across local governments at no migration costs. The rich households are endowed with other factors of production and are assumed to be immobile. The overall sizes of both groups are fixed. The wages of the poor are determined in a common competitive labor market and thus reflect the marginal productive of the poor. Each jurisdiction produces a numeraire good with similar production technology given by f i li , which is a strictly increasing and concave function of the number of poor households, li , employed in jurisdiction i. The wage in a jurisdiction is hence equal to wi households earn the remaining income yi f i ' li and rich f i li f i ' li li . The latter represents rents to rich households earned by other factors of production, possibly income from rich households labor. 4 Redistribution from rich to poor is in this model driven by altruistic preferences. The rich households care for the poor living in their region and are willing to incur tax liabilities to support redistributive transfers. Each welfare client (poor households) in jurisdiction i thus receives a transfer of income denoted, bi , and each taxpayer (rich households) pays an equal bi li , where ni is the number of rich households ni share of the total transfers in the jurisdiction, in the jurisdiction. Let ui yi , zi denote the utility of the rich, where zi wi bi is the income of the poor households. The utility function is increasing and concave in both arguments. Because of costless mobility of welfare clients zi is equal for all jurisdictions. Thus across all jurisdictions z wi bi for some net income, z, and consequently we have the following relation securing migration equilibrium: f j' l j b j , i z j . fi ' li bi (1) The equilibrium mechanism is the assumption of a common labor market ensuring that wages equilibriate migration flows. Let L denote the total number of poor households in the economy, then in equilibrium the following condition must hold: I ¦l L. i (2) i 1 Equation (1) and (2) determine the distribution of welfare clients across jurisdictions and their common net income, z , conditional on bi , i=1, …, I. Differentiating (2) with respect to b j yields I wli ¦ wb i 1 0, (3) j and differentiating (1) with respect to b j yields 5 wz wb j fi '' li wli 1, for i wb j wz wb j fi '' li wli , for i z j wb j j , (4) and rearranging wli wb j wz 1 1 '' '' , for i wb j f i li f i li wli wb j wz 1 '' , for i z j wb j f i li j , (5) Substituting this into (3) to solve for z as a function of the parameters (b1 ,..., bI ) yields wz wb j where V j 1 / f l j '' j 1 V j ! 0, (6) .4 And (5) can be written: I ¦ f l '' i i i 1 wli wb j V j 1 wli wb j Vj f i '' li f i '' li ! 0, for i j . (7) 0, for i z j When b j increases, jurisdiction j is more attractive and poor households migrate from other jurisdictions into jurisdiction j. Without the common labor market which introduces offsetting wage movements, then all the poor would move to the jurisdiction with the highest benefits. 4 V j > 0,1@ . When welfare clients are evenly distributed across all local governments then V j 1 . I 6 Moving on to the choice of benefit levels, I assume that the decision is taken by a representative rich household in each jurisdiction. Assuming that each rich household receives an equal fraction (1/n) of total non-poor income, then his utility is given by: § f l fi ' li li bi li ' · , f i li bi ¸¸ . u yi , zi u ¨¨ i i ni ni © ¹ (8) Each jurisdiction maximizes (8), taking into account the migration effect in (7) and viewing uz other jurisdictions benefit levels as fixed. Letting MRS yi , zi uy denote the marginal rate of substitution between poor people’s consumption and own consumption, then: MRS yi , zi wyi / wbi . wzi / wbi (9) Considering a symmetric Nash equilibrium where number of welfare clients are evenly distributed across all jurisdictions, then wzi wbi 1 I wyi wbi 1 ni § 1 1 1· bi ( 1) li ¸ ¨¨ '' I I ¸¹ © f i li , (10) and consequently the first order condition can be written: ni MRS yi , zi 1 f i li '' bi (1 I ) li . (11) The right hand side of (11) gives the private marginal social cost to taxpayers in jurisdiction i. This yields ‘too low’ provision of welfare benefits seen from the society’s point of view. To understand this, consider the first order condition in the no-mobility case: ni MRS yi , zi li . (12) 7 Because the RHS of (11) is larger than the RHS of (12) the welfare benefits are larger in the mobility than in the no-mobility case. This reflects that the marginal cost of increasing the welfare of the poor is larger in the mobility case. To see the intuition behind this result consider the representative tax payer’s decision problem. He compares altruistic gains from helping the poor to an increase in the tax burden. If the poor do not move, then the tax burden rises only because each of a fixed number of poor recipients receives a larger benefit. However, when welfare migration occurs, the size of the jurisdiction’s poor population grows as its welfare benefit becomes more generous. Generosity is thus more costly with welfare migration. Note that because the concern about welfare migration depress welfare benefits in all jurisdictions, no jurisdiction succeeds in repelling welfare clients and the equilibrium is characterized by all jurisdictions setting lower benefits than they would in the no-mobility case. The welfare benefits are therefore “too low” seen from the nation’s point of view (Brueckner 2000). The key point in this model is that redistributive activity in any one jurisdiction creates external benefits for other jurisdictions because their tax bases increase and their redistributive burdens diminish. With decentralized responsibility for redistribution, this externality is not internalized by taxpayers in jurisdiction i. The socially optimal benefit level in each state corresponds to the one chosen in the immobility case. This gives rise to the following hypothesis: Fiscal decentralization yields increased fiscal competition which makes it harder for welfare states to redistribute between income groups. 3. Measuring fiscal decentralization – new data on decentralization of tax revenue Fiscal decentralization reflects how responsibilities for tax revenues and public expenditures are distributed among different tiers of government. The complexity of the governmental structure makes it challenging to capture this in one single dimension. The standard approach is to make use of accounting measures such as revenue or expenditure shares for sub-central relative to central government to proxy for fiscal decentralization. As thoroughly discussed by Ebel and Yilmaz (2003), Rodden (2004) and Stegarescu (2004) this approach might be problematic. Whether sub-central governments’ expenditure is funded by intergovernmental grants, some revenue sharing program or own-source revenue through independent taxes and user charges clearly makes a difference. What one typically observes is that decentralization appears as higher in the expenditure than the revenue dimension. Such vertical fiscal 8 imbalance implies that one should rather look for measures of ‘revenue decentralization’ than ‘expenditure decentralization’, in particular when one wants to use fiscal decentralization as a proxy for fiscal competition (which is the case here). However utilizing account data for revenue decentralization can also be problematic since central governments can, and often do, significantly limit the fiscal autonomy of lower levels of government. Thus, a larger share of sub-central revenues out of total tax revenues does not necessarily imply greater fiscal dependence from central government. Until recently, virtually all cross-country studies have ignored the distinction between locally determined taxes, ‘piggybacked taxes’ or shared taxes (Stegarescu, 2004:3).5 OECD (1999) tries to overcome this problem and present cross country data which explicitly focused on the role of taxation in determining the fiscal autonomy of sub-national governments. The study aimed to classify taxes in terms of the kind of autonomy they provided to state and local governments, hence focusing on ‘revenue decentralization’. Stegarescu (2004) draws on the analytical framework provided by OECD (1999) and expands their dataset to cover 23 OECD countries for a long time span (1965 to 2001). Stegarescu’s data distinguishes between different kinds of sub-central government revenue according to the degree of discretion sub-central governments have on determining them autonomously. In this respect the data represent a major improvement compared to existing measures of fiscal decentralization. In this analysis I utilize Stegarescu’s data for 19 OECD countries. 4 countries are excluded because of size (Luxembourg and Iceland) and uncertainty with respect to data availability (Greece and Italy). The key explanatory variable in the empirical analysis conduct below is decentralization. decentralization measure the revenue share of sub-central government relative to general government, but contrary to what is common in the literature this variable only includes revenues where the sub-central government has discretion over tax rate, tax base or both.6 Stegarescu (2004) finds that using the conventional measure of revenue decentralization typically overestimates the degree of fiscal decentralization. This is particularly the case for Austria, Belgium, Germany and Portugal (Stegarescu, 2004: 11-12). Descriptive statistics for decentralization is reported in appendix table A.1. The data show a 5 There are numerous cross-national studies that utilize ‘naïve’ accounting measures as proxy for fiscal decentralization, see for example the studies of Panizza (1999) and Arzaghi and Henderson (2005) that use fiscal decentralization as the dependent variable. Rodden (2004:481) provides an overview of studies that use fiscal decentralization as an explanatory variable to explain the size of governments, economic growth, corruption and macro economic stability. Most of these studies are cross-country analyses that use the Government Finance Statistics (GFS) of the International Monetary Fund. 6 The variable is denoted ’tdec1’ in Stegarescu (2004). 9 trend towards an increasing role for sub-central governments in most of the countries. There is a significant increase in local tax autonomy over time in for instance in Belgium, France and Spain according to this measure. Some countries have also moved in the direction of less subcentral tax autonomy, such as Ireland, Norway and the United Kingdom. 4. Empirical specification The full data matrix used in this paper comprises 19 OECD countries over 35 years (1965 through 1999). I follow among others Rodrik (1997), Huber and Stephens (2001), Garrett and Mitchell (2001) and Swank (2002) and proxy for welfare spending by utilizing OECD’s measure of transfer payments as a percentage of GDP (sstran) as dependent variable. Social security transfers are defined as “benefits for sickness, old-age, family allowances, etc., social assistance grants and welfare benefits paid by general government” (Armingeon et al., 2004). Descriptive statistics for this variable for each country is reported in appendix table A.2.7 Comparing 1965 to 1995 we find that all countries have expanded their share of spending on social security out of gdp. The data reveals large cross country differences, but also considerable within-country differences. The average spending on social security out of GDP increased from 9% in 1965 to 16% in 1995. This measure is certainly not a perfect measure of welfare spending, but I believe it is reasonable to argue that it captures important aspects of the welfare state, in particular the effort to carry out redistribution. Another approach to try to tap ‘welfare state effort’ would be to directly try to measure reduction in inequality before and after taxes and transfers. Bradley et al. (2003) and Iversen and Soskice (2004) follow this approach and use data from the Luxembourg Income Study to measure “the percentage reduction in the gini coefficient from before to after taxes and transfers” (Iversen and Soskice, 2004). Although some people are very optimistic about the “pre/post approach” (see for example the introduction in Mahler and Jesuit, 2004) it also has it flaws (see the discussion in Bergh, 2005). Hence, I have decided to focus on the OECD measure of social transfers.8 The empirical specification is given by: 7 sstran is not available for all years for all countries, the total number of missing observations for sstran is 35, in particular due to data on New Zealand (ends in 1983). Only France has interrupted time series. Decentralization is missing for 63 observations (primarily because 6 countries only have data from 1973 onwards). Leaving out Spain before 1977 and Portugal before 1975 leaves us with an unbalanced panel of 552 observations on 19 countries. 8 Mahler and Jesuit (2004:24) finds a raw correlation between the two measures of ‘welfare state effort’ of 0.72. 10 sstranit D E decentralizationit J controlsit H it (13) where sstranit is welfare spending in country i at time t. E measures the effect of fiscal decentralization on welfare spending and is the coefficient of interest. If fiscal decentralization increases fiscal competition, which reduces the ability to redistribute, then E will come out with a negative sign. To evaluate the importance of fiscal decentralization on welfare spending it is essential to take into account all other potentially important determinants of welfare spending, thus a matrix of controls is included.9 Cameron (1978) was one of the first to put the attention to the linkage between international and domestic economy in explaining the growth of the public sector. He finds the openness of the economy to be the best single predictor of the growth of public revenues relative to GDP. He interprets this to be driven by heavier unionization in more open countries which increases demand for public sector spending. If this assertion is correct then openness should be an important predictor of social security spending. In my regressions I control for both openness (measured as the sum of exports and imports divided by GDP) and share of union members in the labor force (union). The latter variable is only included in some specification because I haven’t been able to find data that covers all countries. In addition I control for per capita income (l_rgdp) to capture ‘Wagner’s Law’ which implies income elastic demand for public sector spending. Furthermore I control for country size (l_population) and the share of people that are: living in rural areas (ruralpop), are under 15 years (under15) and are above 65 years (above65), respectively. In addition to these proxies for political demand I also control explicitly for partisanship by including the share of the cabinet from left (govleft) and center (govcent) parties. Business cycle dynamics are often highlighted as central sources of variations in social welfare provision, and unemployment is included to capture both automatic entitlement pressures and political demands. Meltzer and Richard (1981) argue that a more skewed income distribution will increase political support for redistribution. A similar logic may apply to voter turnout (vturn), since it is reasonable to argue that non-voter turnout is concentrated among the poor. Increased turnout is expected to increase support for redistribution.10 9 Descriptives are included in appendix table A. 3. Unemployment and voter turnout may be problematic control variables if they are dependent of current welfare spending and consequently endogenous. The results reported below are robust to the exclusion of these variables. 10 11 Utilizing panel data, inference can be based on both cross country and within country variation. Pooling all the data and running an ordinary least squares (OLS) regression on (13) provide consistent and unbiased results only if the error term can be considered as random across countries and over time. This is a strong assumption to make. A potential remedy is to estimate a restricted version of (13) which includes a full battery of time and country fixed effects, given by: sstranit D i G t E decentralizationit J controlsit H it (14) A problem with this approach is that sstran and decentralization do vary considerably less within than across countries. Including country fixed effects, thus, removes a lot of variation in the data. Hence, it can be fruitful to base the analysis on both estimations of (13) and (14). The standard approach in welfare state research is to rely on a specification like (13) (see for example the book length studies of Huber and Stephens (2001) and Swank (2002)). This approach is also common in the ‘Searching for Leviathan’ studies (initiated by Oates (1985)). In section 4 I present estimation results both based on one year ‘snapshots’ as well as OLS on means, pooled OLS, random effects (RE) and fixed effects (FE) estimation.11 5. Results A first investigation of the relationship between fiscal decentralization and welfare spending is provided in table 1. Table 1 about here. Specification (1), (2) and (3) are ‘snapshot’ cross country regressions from 1975, 1985 and 1995. The effect of decentralization on sstran is as expected negative for all years, but it is only statistically significant for the 1975 regression. Pooling all the years together yields a coefficient of -0.07 which is highly statistically significant.12 Including a full set of time dummies to soak up common time specific shocks does not alter this result (specification (5)). 11 The estimation procedure is based on annual data, but one could also utilize data averaged over multi-year periods. Although the latter approach reduces the degrees of freedom it might make it more sensible to include time lags in the specification and will reduce measurement error if measurement error is not correlated over time. In future work I will test the model on data with 5-years averages. 12 Pooling the data can give a downward bias in the standard errors. I intend to present panel corrected standard errors in the next revision of the paper. 12 The coefficient is estimated to be -0.09. Finally I apply the pure between estimator (OLS on means) and find similar results. A coefficient of approximately -0.1 indicates a moderate, but far from irrelevant economical impact. A one standard deviation increase in decentralization reduces the share of social security out of gdp with around 1.7 percentage points, or around 1/3 of a standard deviation. The result is consistent with the hypothesis presented in section 2. When local governments have responsibility for redistribution, household mobility introduces a migration externality which yields lower redistribution in equilibrium. Generous redistributive programs will serve to attract low-income households and chase away those with higher incomes whose taxes must finance the transfers. In the political decision making process this aspect is taken into account when determining taxes and transfers. The negative association reported in table 1 is thus interpreted to be driven by interjurisdictional competition. Previous research has found a negative relationship between a simple dummy for federalism and welfare spending. Cameron (1978) for example, whose main contribution was to discuss the role of an open economy in promoting public spending, found that federalism ‘dampens the degree of expansion in the public economy’ (Cameron 1978:1253). Some have interpreted the negative effect of federalism to be driven by fiscal competition. Consequently it is of interest to investigate whether the effect of decentralization is robust to the inclusion of a dummy for federalism. In table 2 I report alternative specifications where federation is a dummy equal to 1 if the country is a federation and zero otherwise.13 A simple dummy for federation does not have the same explanatory power as decentralization. However, when both decentralization and federation are included (specification (9) and (10)), they both have a statistically significant impact on welfare spending. Surprisingly the two effects seem to be quite independent of each other.14 The effect of fiscal decentralization is unaltered when federation is included in the pooled OLS specification (comparing (5) to (9)). And the effect of federation is estimated to be in the same range as a one standard deviation increase in fiscal decentralization. The pooled OLS specifications suggest that federal institutions yield a reduction in social security out of gdp of around 2 percentage points. I’ve also tried an interaction term with federation and decentralization, but it came out statistically insignificant and is not reported (t-value of -0.7). 13 The following countries were coded as federations: Australia, Austria, Belgium (since 1993), Canada, Germany, Spain, Switzerland and the United States. 14 Note that the raw correlation between decentralization and federation is a mere 0.33. 13 Table 2 about here. Cross-country evidence has a number of shortcomings. As discussed above, it may be problematic to base inference on variation between countries if cross section heterogeneity is large. If there are some inherent features of different countries that affect welfare spending which are not accurately captured by any of the included regressors, than the correct approach is to include a full set of country dummies. Garrett and Mitchell (2001) criticize the standard approach in welfare state research and argue that leaving out country fixed effects is likely to give substantial bias in the results. In the following I report different specifications that take into account country fixed effects (FE). These are reported in table 3. The pooled OLS estimator is also included for comparison. Specification (11) is based on the random effects (RE) estimator which can be considered a ‘compromise’ between OLS and FE. Baltagi (2001:15-18) shows that RE is a matrix weighted average of the within estimator (FE) and the between estimator (OLS on means) where each estimate is weighted with the inverse of the corresponding variance. Pooled OLS on the other hand gives equal weight to both between and within variation. RE is going to be closer to FE the larger the part of the variance of the error term that is due to the country specific term. Table 3 about here. Controlling for country specific fixed effects, I again find the estimated effect of decentralization on sstran to be statistically significant.15 Interestingly the coefficient of interest is of the same magnitude in all the specifications, from -0.09 to -0.15. The effect of decentralization is not sensitive to leaving out vturn or unemployment or including union. I conclude that the OLS effect is robust to the inclusion of a full battery of time and country fixed effects. Other determinants of welfare state effort On theoretical grounds it is not clear how increased integration into the world economy affects welfare spending. On the one hand, is economic integration likely to create 15 The Hausman test rejects the null hypothesis that the random effects specification is appropriate (pvalue=0.003), comparing (11) and (12). 14 competition for cross country mobile factors in a similar fashion to the theoretical framework put forward in section 2. Hans-Werner Sinn, among others, has been concerned about this development for the European welfare states: “… opening the border and allowing factors of production to move freely across them makes it more and more difficult to maintain the welfare state. … The people who make a net contribution to financing the state transfer their economic activities to the low-tax countries to rid themselves of their responsibilities, and the net recipients of government resources congregate in the well-established welfare states where they the make the existing financial problems even worse” (Sinn, 2003:65). However, it can also be argued that welfare spending is expected to increase if governments expand the welfare state to provide a cushion against external risks. The existing empirical evidence on the effect of economic integration on welfare spending is ambiguous. Relying on cross country data Rodrik (1997) finds a strong positive association between openness and welfare spending which he understands to be driven by increased demand for a more active government role in providing social insurance. However when he controls for year and country fixed effects he finds that increased openness have resulted in reductions in social spending. My analysis reproduces these findings and is also consistent with Garrett and Mitchell (2001) who also rely on FE estimation. I.e. it seems like countries that traditionally have been very open to trade (for example Belgium, Denmark, Netherlands and Norway) have more generous welfare states and that this is reflected in the OLS regressions. However, the FE estimations suggest a negative effect of openness on welfare spending. Relying on specification (12), an increase in the shares of imports plus exports in GDP of 5 percentage points (a total of 10 percentage points) results in a reduction in welfare spending of about 0.3 percentage points.16 Controlling for the share of the work force that is members in unions the effect is almost three fold. Closer integration into the world economy seems to make it harder to undertake redistributive taxation and sustain generous social programs. The remaining controls show the more or less expected pattern. Based on fixed effects estimation, I find that country size seems to be negatively associated with welfare spending. However since openness and l_population are highly collinear one might worry that multicollinearity makes it hard to separate out the true effects.17 I have tried specifications where openness and l_population respectively are left out, but the coefficients are basically 16 This is close to identical to Rodrik’s (1997) estimate. Alesina and Wacziarg (1998) argues, for example, that it is not openness, but country size that actually explains government expenditure. This does not seem to be the case here. 17 15 unaltered. I find strong positive effects of unemployment and voter preferences (proxied for by population shares). Based on specification (13) I find that a 1 percentage point increase in the unemployment rate increases the share of social security out of gdp with 0.49 percentage points. Lindert (1996:10) finds that higher voter turnout seems to raise all kinds of government expenditures. This result is only confirmed in the cross country regressions. Wagner’s law is also supported by the cross country estimates, but it is not robust to the inclusion of fixed effects. The impact of unionization on welfare spending is strong and positive. Union is nonetheless only included in specification (13) because including it reduces the sample substantially, in particular because two countries are excluded (Portugal and Spain). I do not find any robust effects of political color. Christian democratic government seems to be associated with more welfare spending but the effect vanishes if unions are controlled for. Note that my model only captures the short-term impact of Left and Center governments. 6. Endogeneity The results above suggest a robust negative relationship between fiscal decentralization and welfare spending. However, one can question whether this reflects a causal relationship from fiscal decentralization to welfare spending. The estimation method utilized above hinges upon the assumption of strict exogeneity of fiscal decentralization. Acemoglu (2005) argues, in a more general setting, that political institutions hardly can be taken as exogenous: “This is because different political institutions will generate different policies, and thus lead to different economic outcomes, and rational economic (and political) agents should understand not only the implications of different policies but also the implications of different political institutions. The logic of political economy therefore forces us to also think of political institutions as endogenous” (Acemoglu, 2005: 12). Previous research on decentralization has also found decentralization to be a complex process which is a product of many factors including cultural heritage and geography (Arzaghi and Henderson (2005) and Panizza (1999)). In this setting it will be particular problematic to take decentralization as exogenous if preferences of political actors for decentralization are affected by the current level of redistributional spending. Note that if the political pressure to centralize is stronger in countries with less welfare spending, then this will give an attenuation bias in the estimates above. However, whether there is a bias and in what direction it goes is an open empirical question. To address this problem an instrumental variable which is correlated with fiscal 16 decentralization, but not with welfare spending is warranted. A variable that incorporates the geographic variance in demands for public goods should according to Oates’ (1972) decentralization theorem be a candidate for a valid instrument. I hope to be able to address the potential endogeneity problem in future work. 7. Conclusions This paper studies the relationship between fiscal decentralization and welfare state effort. Utilizing new panel data on fiscal decentralization for 19 OECD countries, a robust negative relationship is established. The estimated coefficient is remarkably stable through a variety of specifications including the pure between estimator, pooled ordinary least squares, random effects and fixed effects estimation. A one standard deviation increase in fiscal decentralization is estimated to reduce welfare spending out of gdp with approximately 2 percentage points. The results are interpreted to be driven by fiscal competition: due to household mobility, countries with decentralized responsibility for redistribution find it harder to redistribute between income groups. Generous redistributive programs will serve to attract low-income households and chase away those with higher incomes whose taxes must finance the transfers. In future work I will have a closer look at the within country variation. Several countries have gone through considerable reforms in the time period under study and it would be interesting to study these reforms in particular. Moreover I also intend to have a closer look into the possible endogeneity problem related to fiscal decentralization. 17 References Acemoglu, Daron (2005): “Constitutions, Politics and Economics: A Review Essay on Persson and Tabellini’s The Economic Effects of Constitutions”, NBER working paper no. 11235. Aleisna, Alberto and Romain Wacziarg (1998): “Openness, Country Size and Government”, Journal of Public Economics 69, 305-321. Armingeon, Klaus, Phillip Leimgruber, Michelle Beyler and Sarah Menegale (2004): Comparative Political Data Set 1960-2002, Institute of Political Science, University of Bern. Arzaghi, Mohammad and J. Vernon Henderson (2005): “Why Countries Are Fiscally Decentralizing”, Journal of Public Economics 89, 1157-1189. Baltagi, B.H. (2001): Econometric Analysis of Panel Data, John Wiley & Sons Ltd, Chichester, England. 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(1999): “Theories of Tax Competition”, National Tax Journal 52, 269-304. 20 23.24*** 1.52** 0.21*** 98.41** 139.78*** -4.17* -1.83 0.11 L_RGDP L_POPULATION RURALPOP UNDER15 OVER65 GOVLEFT GOVCENT UNEMPLOYMENT No No Country fixed effects 18 18 OLS (1985 only) 17 17 OLS (1975 only) Number of countries Number of observations OLS (1995 only) 18 18 0.07 0.16 2.76 3.10 57.71 39.07 0.09 0.96 6.81 3.02 0.05 St.error 0.667 No No 0.22*** 0.61*** 3.85 -6.19** 265.61*** 45.52 0.25*** -1.31 20.73*** -3.67 -0.01 Coefficient (3) Pooled OLS 552 19 0.02 0.03 0.48 0.41 10.31 7.25 0.02 0.17 0.82 0.74 0.01 St.error 0.583 No No 0.12*** 0.23*** 3.04*** -0.66 106.87*** 12.07* 0.10*** 0.06 6.47*** 0.07 -0.07*** Coefficient (4) Pooled OLS 552 19 0.02 0.05 0.46 0.40 9.71 7.03 0.02 0.16 1.09 0.71 0.01 St.error 0.651 No Yes 0.12*** 0.39*** 2.25*** -0.87** 118.93*** 6.07 0.15*** 0.19 12.14*** 2.21*** -0.09*** Coefficient (5) No No OLS on means 19 19 0.16 0.38 6.35 8.63 112.04 64.64 0.12 1.40 8.70 7.54 0.08 St.error 0.291 0.11 0.17 5.71 -2.10 113.67 19.77 0.11 -0.24 12.28 -0.14 -0.12 Coefficient (6) 21 Note: Standard errors in parentheses. ***, ** and * denotes significance at 1%, 5% and 10% level respectively. A constant term is included in all regressions (not reported). Estimation method 0.646 0.11 0.29 3.39 2.09 61.74 42.86 0.12 1.17 8.08 5.43 0.08 St.error 0.837 R2adj No 0.11 0.55* -0.49 4.68** 89.26 -19.20 0.28** 2.50** 18.16** 19.49*** -0.08 Coefficient No 0.06 0.31 3.37 2.26 38.55 39.32 0.06 0.71 4.39 4.98 0.06 St.error (2) Year fixed effects 0.17*** 13.31** OPENNESS VTURN -0.13** DECENTRALIZATION Coefficient (1) Table 1 Determinants of welfare spending (measured as SSTRAN) based on cross and within country variation 19 552 OLS on means 19 552 Pooled OLS Number of countries Number of observations Pooled OLS 552 19 0.01 St.error 0.651 No Yes -0.09*** Coefficient (5) No No OLS on means 552 19 0.08 St.error 0.290 -0.12* Coefficient (6) Pooled OLS 552 19 0.30 0.01 St.error 0.676 No Yes -1.87*** -0.09*** Coefficient (9) OLS on means 552 19 2.11 0.07 St.error 0.486 No No -4.04*** -0.16*** Coefficient (10) table 1 is included in all regressions (not reported). 22 Note: Standard errors in parentheses. ***, ** and * denotes significance at 1%, 5% and 10% level respectively. A constant term and control variables as in specification (5) in Estimation method R 0.223 2.53 St.error 0.636 adj No No 2 Country fixed effects -3.03 No 0.31 Coefficient Yes -2.01*** St.error (8) Year fixed effects FEDERATION DECENTRALIZATION Coefficient (7) Table 2 Comparing federalism to fiscal decentralization as determinants of welfare spending (SSTRAN) 12.14*** L_RGDP 6.07 118.93*** -0.87** 2.25*** 0.39*** 0.12*** UNDER15 OVER65 GOVLEFT GOVCENT UNEMPLOYMENT VTURN No No Country fixed effects 19 552 RE 19 552 Pooled OLS Number of countries Number of observations 0.02 0.04 0.36 0.26 12.11 7.32 0.03 0.44 1.10 1.08 0.02 St.error 0.00 Yes Yes FE 552 19 0.873 0.41*** 0.80** -0.29 120.76*** 36.43*** 0.17*** -6.44*** 1.11 -3.14*** -0.15*** Coefficient (12) 0.02 0.04 0.37 0.27 14.05 7.82 0.04 2.46 1.19 1.22 0.03 St.error Yes Yes FE 464 19 0.910 9.20*** 0.01 0.49*** 0.17 -0.44 80.82*** 52.96*** 0.31*** -3.57 -1.55 -8.79*** -0.15*** Coefficient (13) 1.56 0.02 0.05 0.37 0.28 17.15 8.36 0.05 2.98 1.20 1.50 0.03 St.error 0.30 -0.25 FE 558 19 0.850 Yes Yes 103.55*** 33.20*** 0.19*** -8.83*** -1.20 -3.08** -0.14*** Coefficient (14) 0.39 0.29 14.91 8.29 0.05 2.66 1.20 1.32 0.03 St.error 23 Note: Standard errors in parentheses. ***, ** and * denotes significance at 1%, 5% and 10% level respectively. A constant term is included in all regressions (not reported). Estimation method 0.376 0.651 R2adj Yes 0.03 0.41*** 0.98*** -0.39 113.38*** 34.56*** 0.07** -0.59 2.27** -2.39** -0.10*** Coefficient Yes 0.02 0.05 0.46 0.40 9.71 7.03 0.02 0.16 1.09 0.71 0.01 St.error (11) Year fixed effects UNION 0.15*** RURALPOP 0.19 2.21*** OPENNESS L_POPULATION -0.09*** DECENTRALIZATION Coefficient (5) Table 3 Determinants of welfare spending (measured as SSTRAN) based on within country variation 24 Country Mean St. dev. Minimum Maximum 1965 1975 1985 1995 Australia 20.33 1.75 18.19 24.23 N/A 19.94 18.55 22.47 Austria 3.48 0.21 2.90 4.03 N/A 3.62 3.31 3.76 Belgium 11.32 7.38 5.31 24.55 6.59 6.30 6.88 23.61 Canada 51.56 2.19 46.31 55.36 52.14 47.08 52.44 54.66 Denmark 29.50 1.65 25.96 31.97 N/A 29.02 27.63 31.48 Finland 25.91 2.06 22.67 32.18 23.14 26.90 26.15 29.50 France 12.48 7.18 1.13 20.05 N/A 2.18 15.59 19.96 Germany 7.46 0.40 6.49 8.01 N/A 7.76 7.89 6.49 Ireland 5.85 4.00 2.14 13.78 13.78 8.66 2.72 2.81 Japan 32.02 2.41 27.80 37.54 28.33 32.17 34.07 34.13 Netherlands 3.83 0.92 1.92 5.20 N/A 1.92 4.41 4.73 New Zealand 7.47 0.90 6.29 9.07 9.07 7.18 6.37 5.17 Norway 26.96 2.91 23.11 31.51 N/A 31.51 23.11 25.53 Portugal 1.57 1.28 0.00 3.36 N/A 0.00 0.41 2.85 Spain 10.17 3.64 5.68 21.98 N/A N/A 8.16 12.86 Sweden 39.88 4.94 30.77 47.56 30.77 36.31 40.46 47.02 Switzerland 56.71 2.10 52.41 61.50 54.33 61.50 57.06 56.99 United Kingdom 10.94 3.77 4.74 14.25 13.77 13.56 12.89 4.88 United States 36.93 1.68 33.42 39.08 34.38 38.30 37.52 38.58 Note: decentralization is defined as sub-central government own tax revenue divided by general government total tax revenue. Only tax revenue from taxes where the sub-central government autonomously can change the tax rate, tax base or both are included in the nominator. Appendix Table A.1 Descriptive statistics for decentralization for each country 25 Country Mean St. dev. Minimum Maximum 1965 1975 1985 1995 Australia 8.39 1.00 6.30 9.90 5.80 8.60 9.60 8.60 Austria 18.78 1.39 15.30 21.10 11.23 16.90 20.40 19.50 Belgium 17.49 3.11 12.40 22.70 12.40 18.80 21.70 16.60 Canada 10.65 2.32 6.00 14.60 6.10 10.20 12.20 13.20 Denmark 16.90 2.49 11.10 21.20 8.30 13.80 16.30 20.40 Finland 13.02 5.53 7.00 24.00 7.00 8.50 14.80 22.20 France 19.10 1.89 15.50 22.10 16.40 20.40 22.10 18.50 Germany 16.87 1.38 13.50 19.30 12.30 17.60 16.20 18.10 Ireland 11.64 3.16 5.90 17.20 5.90 12.70 16.60 11.30 Japan 9.32 3.21 4.50 14.60 4.80 7.70 11.00 13.40 Netherlands 23.27 4.92 12.60 28.80 11.50 24.10 26.10 15.30 New Zealand 12.33 2.45 9.71 16.84 9.89 11.58 N/A N/A Norway 15.19 0.99 13.30 17.10 9.00 13.60 14.80 15.80 Portugal 11.38 1.15 8.60 13.90 N/A 8.60 10.80 11.70 Spain 15.57 1.95 10.40 18.40 N/A N/A 16.00 17.20 Sweden 16.78 4.08 9.20 23.40 9.20 14.20 18.20 21.30 Switzerland 11.14 2.37 6.50 14.10 7.40 12.50 13.70 11.20 United Kingdom 11.85 2.59 7.60 16.00 7.60 9.90 13.80 15.40 United States 10.22 2.24 5.40 13.00 5.40 11.40 11.00 13.00 Note: sstran is defined as social security transfers as a percentage of GDP. Consists of benefits for sickness, old-age, family allowances etc., social assistance grants and welfare benefits paid by general government. Appendix Table A.2 Descriptive statistics for sstran for each country Total trade (export + imports) as a share of RGDPL. Gross union members out of total labor force OPENNESS UNION 16.71 0.04 0.03 1.27 13.51 4.20 0.39 0.32 13.40 0.28 0.28 0.17 21.93 0.22 0.13 16.62 27.72 6.10 0.35 0.24 76.86 9.72 0.52 0.40 B E D D A** D A** A** A** C C C C C 4.78 St.dev 14.14 Mean A* Source 0.07 0.09 8.70 35.00 0.00 0.00 0.00 14.78 2.95 0.15 0.06 0.00 4.50 Min 0.84 1.77 10.32 95.80 1.00 1.00 24.10 19.42 71.98 0.33 0.18 61.50 28.80 Max original source see Armingeon et al. (2004). Descriptives based on 552 observations (union excluded). Comparative Welfare States Data Set (Huber et al. (2004)). *Original source is OECD historical statistics, various years, table 6.3. ** For Stegarescu’s data set (2004), (C) The World Development Indicators, (D) The Penn World Table Version 6.1 (Heston et al. (2001)) and (E) Note: The data are collected from five different data sources: (A) The Comparative Political Data Set (Armingeon et al. (2004), (B) Dan Log of RGDPL Social security transfers as a percentage of GDP. Consists of benefits for sickness, old-age, family allowances etc., social assistance grants and welfare benefits paid by general government. Sub-central government own tax revenue divided by general government total tax revenue. Only tax revenue from taxes where the sub-central government autonomously can change the tax rate, tax base or both are included in the nominator. Share of population 0-14 years of age Share of population 65 years of age and above Total population Log of total population Share of population living in rural areas Unemployment rates, standardized as far as possible according to OECD criteria Cabinet composition: share of government from left parties, weighted by days Cabinet composition: share of government from center parties, weighted by days Voting turnout in percent Real GDP per capita in 1996 international dollars (Laspeyeres) Definition L_RGDP VTURN RGDP GOVCENT GOVLEFT UNEMPLOYMENT YOUNG OLD POPULATION L_POPULATION RURALPOP DECENTRALIZATION SSTRAN Variable Appendix Table A.3 26