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Fiscal austerity and the trade-off between public investment and social spending Christian Breunig University of Toronto Department of Political Science Marius R. Busemeyer Max Planck Institute for the Study of Societies ¨ Prepared the Annual Meeting of the DVPW section “Politik und Okonomie” Cologne, 4.-5. September 2008

Abstract This paper introduces the notion of a budgetary trade-off, which is defined as a situation in which one type of spending is continuously prioritized over another type of spending in the face of fiscal pressure (austerity). In particular, we hypothesize that discretionary spending (in our case: public investment) will be hit harder by fiscal austerity than entitlement spending (public spending on pensions and health). This is because public investment is less severely constrained by legal obligations, and is associated with political interests that are localized and heterogeneous in nature. Furthermore, decisions on investments have a lower degree of visibility, so that they can be used easier to defuse blame. Our empirical analysis relies on a new methodological approach (composite data analysis) that takes into account interdependencies between budgetary categories. Relying on data for 21 OECD countries from 1979-2003, we find a negative impact of our indicator of fiscal stress (government net interest payments) on the budget share of public investment, but a positive (neutral) impact on the budget share of pension (health) spending.

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Introduction

Comparative analyses of the determinants of public spending tend to look at different types of spending separately without taking into account interdependencies between budget categories. This stands in contrast with the empirical reality of governmental decision-making, in which policy-makers are constantly faced with the decision on how to allocate principally scarce public resources across budget categories. However, as we have known since Wildavsky’s theory of incrementalist budgetary decision-making (Wildavsky, 1964), policymakers have little leeway to change budgetary priorities fundamentally. Along similar lines, the “new politics of the welfare state” school (Pierson, 1994, 1996, 2001) has noted the significant resilience of welfare states against far-reaching retrenchment (at least in terms of spending). At the same time, fiscal performance in terms of deficits and levels of public debt has deteriorated in a significant number of OECD countries. On the one hand, this might be seen as a consequence of welfare state resilience, i.e., the effect of attempts of policy-makers to defuse pressure to cut back welfare states by increasing public debt. On the other hand, mounting fiscal pressure has itself consequences with regard to the leeway of action for governments. As happens when the irresistible force of fiscal austerity hits the immovable object of welfare state spending, something’s got to give. In our case, this “something” is public investment. More specifically, we are interested in finding out whether the pressure of fiscal austerity affects different types of spending differently. To this effect, we must take into account that budget categories are not independent of each other. If fiscal austerity affected all budget categories equally, we would not observe any change in the composition of public budget in response to enhanced austerity. In contrast, if some types of spending are affected more than others, we would expect shifts in budgetary priorities as a consequence of increased austerity. The theoretical argument developed below suggests that discretionary types of spending,

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i.e., public investment, will be more affected by austerity than non-discretionary or entitlement spending, i.e. spending on pensions and health. We postulate that there is a budgetary “trade-off” between public investment and social entitlement spending. The following review suggests that he notion of a “trade-off” rises to the surface in a number of literatures, but in our view, it hitherto lacks a more systematic conceptualization. Our argument about the trade-off between social entitlement spending and public investment is based on the heuristical framework of the “new politics of the welfare state” school. We argue that public investment will be hit harder by fiscal austerity because first, it is less severely constrained in terms of legal obligations (i.e., there is no clearly defined entitlement to a specific investment); second, the associated political interests are localized and heterogeneous in contrast to homogeneous and national interests in the case of welfare spending; and third, political decisions on public investment generally have a lower degree of visibility, hence can be easier used to defuse blame. In welfare state politics, the combination of diffuse benefits and concrete costs preclude large-scale retrenchment. In contrast, in the case of public investment, we observe a combination of diffuse or lower political costs on the one hand and concrete benefits in the nature of saved public monies on the other. Hence, public investment suffers from fiscal austerity than social entitlement spending. The paper proceeds as follows: in the subsequent section, we provide a brief literature review on the various uses of “trade-off” concept. Next, we develop our theoretical argument. The empirical section presents our data and the specific methodological approach (composite data analysis). Composite data analysis explicitly models the interdependencies between budget categories. The final section discusses the findings and concludes.

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Literature review

The paper draws its inspiration from a significant, but quite eclectic body of literature on the existence of a trade-off between areas of policy-making. One strand of literature in international relations has framed the idea of a “guns vs. butter” trade-off (Mintz and Huang, 1991; Mintz and Stevenson, 1995; Verner, 1983). The core research question in this literature is whether spending on military/defense crowds out spending on welfare state policies like education, health or social insurance. The intuition behind the guns vs. butter trade-off is that in authoritarian regimes, military elites have a stronger influence on public spending, such that they can expand expenditures for their own purposes instead of investing it in the social and economic development for the public at large. A second strand of literature focuses on the “big trade-off” between efficiency and equality, i.e. between social spending and economic growth (Lindert, 2004; Okun, 1975). Obviously, the relationship between social spending and economic performance is a very important issue in comparative welfare state research, and it is beyond the scope of this paper to present a complete literature review. The most important point to take away is that the concept of a trade-off between growth and social spending again implies that one cannot have the one without giving up the other. That is: welfare state politics are conceived as “politics against markets” (Esping-Andersen, 1985). More recently, however, the Varieties of Capitalism school has been pointing out the complementarities between certain welfare state policies and their role as “politics in markets” (Iversen, 2005). Furthermore, as Lindert (2004) shows, the empirical evidence does not support the thesis of a negative relationship between economic performance and welfare state policies. Finally, a third strand of literature, which is closest in nature to the purpose of the present study, looks at the trade-off between different types of (non-military) public spending. Inspired by the “new politics of the welfare state” approach (Pierson, 1994, 2001), this

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literature addresses the question whether some types of public spending are hurt relatively more by spending cut and retrenchment efforts than other types of spending. For instance, Clayton and Pontusson (1998) show that while the welfare state reforms of the 1980s and 1990s have left levels of social spending virtually unchanged, governments have cut back the vulnerable “service components” (ibid.: 95) of the welfare state and the public sector in general. Castles (2001) also finds a high degree of resilience in social spending, but declining levels of non-social spending. A subcategory of this strand of literature are studies that look at the trade-off between education and social spending (cf. O’Higgens 1988). Comparing OECD countries, Schmidt (2007b:173-174) finds that the size of the budget share of social spending at the beginning of the general retrenchment period that set in during the 1980s has a decisive negative impact on the size of the budget share of education today. Pecchenino and Utendorf (1999) detect a crowding out effect of social security spending on education as well. More evidence on the apparent trade-off between education and social spending comes from studies looking at the sub-national level in federal countries. Garand and Hendrick (1991) show the presence of a spending trade-off in American states, although education seems to suffer less than other types of spending. In contrast, Gold (1995:371) posits that in U.S. states, education “suffers disproportionately during periods of fiscal stress”, when spending on higher education in particular is more affected by spending cuts than other areas of spending. Oberndorfer and Steiner (2006) show that spending on higher education in German L¨ander is negatively affected by an ageing population, while Tepe and Vanhuysse (2008) find a negative impact of public indebtedness on total teacher employment. In summary, we find a quite extensive and diverse literature, in which the notion of a “trade-off” between different areas of policy-making is discussed. However, this literature remains unsatisfying in certain respects: Firstly, we need a clearer conception and definition of the notion of a “trade-off”. A definition of a budgetary “trade-off” needs to be more 5

stringent than the observation that all public monies have to be distributed across budgetary categories somehow. That is, our definition of a trade-off implies a larger amount of “criticalness” than those to be found in the literature. Second, we need a better theoretical understanding of why some types of public spending should be hurt more severely than others. In the account, which we will develop in the subsequent section, we rely on institutionalist arguments about the different nature of public spending categories with regard to the degree of bindingness for governmental policy-makers. Third, from a methodological standpoint, we need to be more aware of the fact that budget shares of spending types have to be analyzed simultaneously, because they are clearly interdependent. Albeit some recent studies (e.g Yildirim and Sezgin, 2002) implement methodological advances, the large part of the empirical studies capture the trade-off effect simply by including one type of spending as an independent variable in the analysis of the other type of spending in a linear OLS framework. Clearly, this procedure does not take into account sufficiently that decisions about the allocation of public monies across budget categories are taken simultaneously and interdependently. Fourth, in our evaluation of the existence of a trade-off between types of public spending, we look at the trade-off between spending on pension, health care and public investment. In contrast to some of the literature introduced above, the latter is chosen instead of education. This is because education actually entails a greater degree of bindingness than public investment, as spending on personnel represent a large share of educational budgets. Given that educational personnel are too a large extent public sector employees with the accompanying employment protection, this budget share is actually less easily adjustable than pure public investment spending.

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Theoretical framework and hypotheses

The notion of spending trade-offs entails a sense of criticalness, i.e. it implies more than the simple year-to-year routine decisions that policy-makers face regularly. In the postwar era of welfare state and public sector expansion, potential trade-off between policy areas could be allayed by increasing the overall size of the budget and/or levels of deficits and public debt. With the onset of the era of fiscal austerity, however, governments increasingly face tough decisions about the distribution of public moneys across budget categories. Mounting budget deficits and levels of public debt have put an end to this strategy of non-contentious decision-making. Given a fixed amount of public revenue to distribute, governmental policymakers face hard decisions in the distribution of these funds. Past levels of public debt have to be serviced through interest payments, so that over time the fiscal leeway for action can become severely constrained. The crucial – and to us: the most interesting – question is whether certain types of spending are hit harder by the pressures of fiscal austerity than other types. Hence, our definition of spending trade-off is a situation in which one type of spending is continuously prioritized over another type of spending in the face of fiscal pressure (austerity). The empirical case of interest is the relationship between public spending on pensions and health on the one hand and public investment on the other. Our key questions are: Why should we expect a spending trade-off between these three types of public spending? Does public investment suffer more severe cutbacks in the face of fiscal austerity than social expenditures? We answer these questions building on the “new politics of the welfare state” approach and its implications for the relative dynamics of entitlement versus discretionary types of spending. The core argument of the “new politics” approach is that welfare states in advanced democracies exhibit a high degree of resilience against far-reaching retrenchment (cf. among

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many others also Huber and Stephens 2001; Stephens, Huber and Ray 1999.1 This resilience basically rests on three “pillars”: (1) institutional characteristica of policy types, (2) political constraints in the form of powerful welfare state clientel groups, and (3) the governments’ ability to manipulate the “visibility’ of policy reforms. Coming back to the first point, Pierson (2001) mainly argues in terms of “path dependence”, “institutional stickiness”, and “lock-in effects”. The institutional basis for these effects lies in the specific institutional structure of many social policies as entitlement programs. In most cases , policy-makers cannot simply decide to reduce spending on pensions by x percent in a given fiscal year. Instead, they have to undergo a long and arduous process of changing the respective entitlement laws. Even then, because policy-makers usually can only change the parameters of entitlement programs (i.e., eligibility criteria, benefit calculation formulas etc.), they still face considerable uncertainty as to whether or when the hoped for savings will materialize. Pension spending is a particular “sticky” policy program. This is because current and prospective pensioners close to retirement enjoy particular rights of protection of confidence. In Germany, for example, pension claims are protected by the constitutional right of property protection, and policy reforms must not “expropriate” future pensioners. As a consequence, the only way to enact major pension reforms is to limit the future increase in pension benefits by changing the benefit formula, although even this measure usually requires long periods of transition. Health spending might be slightly more amenable to reform in that respect, because benefit claimants usually do not enjoy the same level of protection of confidence. Besides institutional constraints, governments face formidable political challenges as well. During the arduous process of adapting entitlement programs, policy-makers are confronted with widespread popular resistance against welfare state retrenchment. As a consequence 1

More recent work on welfare state retrenchment that looks beyond spending on the actual generosity of welfare state programs has partly refuted Pierson’s claim of non-retrenchment (Allan and Scruggs, 2004; Korpi and Palme, 2003).

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of the postwar expansion of welfare states, almost every person in a given country is the beneficiary of some welfare state policy or another. Hence, welfare state programs themselves can become the source or catalyst for political mobilization (Campbell, 2005). To defuse the popular backlash against welfare retrenchment, policy-makers engage in measures of blame avoidance (Pierson, 2001; Weaver, 1986), for example by obfuscating the true impact of reforms or by shifting costs to the future. As Pierson has rightly observed, this constellation of concrete costs in the form of retrenchment in exchange for diffuse benefits (in the form of sustainable welfare policies) in the future usually prevents policy-makers from engaging in far-reaching retrenchment. The case is different for discretionary spending, i.e. public investment.2 Following Clark, Elsby and Love (2002:308), public investment can be regarded as a “soft target”, which governments might find easier to cut than social spending based on entitlement laws.footnoteFor a similar argument, see Turrini (2004:8-9) The reasoning for why investment should be hurt more by retrenchment can be framed in terms of the “new politics” framework: In contrast to the case of welfare state policies, in the case of public investment, policy-makers can trade off diffuse political costs in exchange for concrete benefits. There are three reasons for why political costs are diffuse or generally lower in the case of public investment. First, legal obligations and institutional constraints are far less binding in the case of public investment than in the case of pension or health spending. There is no clearly defined right or entitlement to a certain level of public investment. There is equally no entitlement to have a specific investment carried out in a specific way within a specific time frame, i.e. a public building can be built in varying levels of quality. There is even more discretion on the side of policy-makers with regard to the upgrading of the existing capital stock (i.e. whether and to what extent to fix current deficiencies in infrastructure). 2 In contrast to the large literature on welfare state policies, there is a dearth of political science studies of the determinants of public investments. Notable exceptions are Boix (1998); Freeman and Alt (1994); Keman (2008).

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The low degree of bindingness in the case of public investment stands in contrast with the generally higher degree in the case of entitlement social spending: here, entitlement criteria are clearly spelt out in the relevant laws, and their enforcement is buttressed by courts. In the short term, governments cannot deny benefits arbitrarily if the person fulfills the eligibility criteria (e.g., becomes unemployed or reaches the retirement age), Second, political constraints are different in the case of public investment as well. Whereas clientel groups for entitlements are homogenously defined by the entitlement programs themselves (e.g. pensioners). Furthermore, these clientel groups are localized on the national level of decision-making, because this is usually the level where decisions about social insurance entitlement programs are made.3 In contrast, lobby groups for public investment are localized and heterogeneous. It may be true that on the local level, lobby groups for a specific investment project fit the Olsonian notion of a special interest group. In collaboration with the local member of parliament, this can result in a significant amount of ‘over-investment’, depending on the specific type of electoral system and parliamentary decision-making in a given country. But – and this is the important to remember – in the aggregate, the picture might look very different. In contrast to social spending on entitlement programs, there is no overarching common interest linking local lobby groups with each other. In addition, the common, but diffuse interest of the general population in a high level of public investment may be too low to counteract the pressures from welfare state spending, which is much more directly connected to the voters’ pocketbooks. In other words: voters might have some general interest in a high level of investment, but the individual share of this common interest in each voters’ demand function for public goods is very small compared to other types of policies. This holds true even if individual voters care about a specific local investment. That is: a person might care more about the maintenance of her local public school than 3

With some notable exceptions like the U.S. unemployment insurance scheme.

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about her pension benefits, but besides other people in the locality, there are few other people who care about the local school. Thus, political interests for public investment are localized and heterogeneous compared to homogenous and national interests in the case of entitlement spending. Third and related, there are important differences in the visibility of policy changes between the cases of public investment and entitlement spending. Because social insurance policies are a matter of general concern, they are widely reported and vetted in the media. The need to clearly spell out entitlement criteria also leads to a high degree of visibility when these criteria are changed. In contrast, decisions on public investment are generally not widely perceived in the media. This is because they do not consist of one widely applicable measure of policy change, but of a number of discrete choices on separate projects, each of which usually falls below the threshold of media attention. As a consequence of lower visibility, policy-makers have much more discretion in their decisions on public investment. Summing up, we have argued that there are important differences in terms of institutional and political constraints between public investment and social insurance programmes (pension, health). In a fiscal climate of expansion, these differences might not have any far-reaching consequences. In times of fiscal austerity, however, policy-makers face tough decisions on how to allocate scarce public monies. Therefore, the core hypothesis to be tested is: Public investment will be hurt more by pressures of fiscal austerity than spending on pensions or health, because: (1) it is bound less by legal obligations of protection of confidence than entitlement spending; (2) political interests are localized and heterogeneous compared to homogenous and national interests in the case of welfare spending; and (3) lower visibility in the case of public investment opens up potential for blame avoidance. In other words: in the case of welfare state spending, policymakers are reluctant to relay the pressure of fiscal austerity because concentrated (political) costs stand against diffuse benefits. In the case of public investment, however, political costs 11

of retrenchment can be diffused quite effectively. Additionally, the benefits of foregoing or delaying investments are very concrete in the short term: foregone investments set free public monies that can be spent on other policies. In short, the core hypothesis is that the impact of fiscal stress in the form of mounting interest payments effects the composition of public budgets. We expect explanatory contributions from a number of other variables as well. First, we inquire whether the partisan composition of the government (or partisan inheritance) makes a difference or not. Prima facie, the deduction of partisan preferences on public investment or the general allocation of spending across budget categories is not obvious. Freeman and Alt (1994) could not show any influence of partisan factors on public investment. For Boix (1998), on the other hand, public investments are an important element of a leftist supplyside strategy. However, it could be argued that in times of fiscal stress, social democrats might be tempted to protect cherished welfare state policies, even if this means cutbacks in investment or education. Hence, instead of formulating necessarily ad-hoc hypotheses, we treat the impact of partisanship as an empirical matter and leave its detailed study for future research. Additionally, we include a number of economic and demographic variables that are expected to impact on the relative importance of public investment vis-`a-vis social spending. A larger population share of elderly people, for instance, is expected to lead to an increase in the budget share of pension and health spending (cf. Pampel and Williamson 1992). Changes in the level of economic well-being (captured by GDP per capita) are hypothesized to contribute to higher levels of social spending (Wagner’s law) and lower levels of public investment, because less developed societies tend to spend relatively more on public infrastructure and investment. Higher levels of unemployment contribute to “economic stress” and should have a negative impact on the share of investments, while the effect on the other two budget categories is ambiguous. The total level of public spending is included as well to 12

model the general budget constraint.

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Data

The data employed in this study comprise yearly expenditures for pensions, public investments, and health policies for 21 OECD countries (Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Japan, Netherlands, New Zealand, Norway, Portugal, Spain, Sweden, Switzerland, United Kingdom, United States) and the years 1979-2003. The data are collected from various OECD sources (see the Appendix 1 for details). Public spending on pensions and health are taken from the latest edition of the OECD Social Expenditure Database. Public investment is defined as “gross fixed capital formation” by government as provided in the OECD National Accounts.4 All spending data are given as percentages of GDP. In the theory section, we already highlighted that the spending trade-offs are also constrained by the development of each of the three categories. In the methodology section, we delineate a strategy for modeling this trilemma between pensions, investment, and health spending but we are able to illustrate some stylized facts about this trilemma here. A simple graphical representation of this three-part composition of a budget is a ternary plot (Figure 4). In the plot, a three part composition can be identified by a point. For reading the ternary plot, it is important to recognize that the axes are borrowed from three dimensional space. Each axis runs from zero, at the midpoint of a side of the triangle, to one, at the opposing vertex. Note the three sets of gridlines running parallel to an axis of the plot. The hollow dots on Figure 4 shows that a considerable number of countries (such as Japan 4

This definition of public investment is the commonly used one (cf. Keman 2008; Turrini 2004). It includes government spending on the construction of infrastructure (streets, railways,...), on the purchase of capital goods by government (health care equipment in hospitals, office machinery,...), as well as expenses to ameliorate and maintain the existing capital stock. It does not include types of spending that some might want to regard as investment as well (i.e., spending on teachers in education).

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and the Netherlands) spend considerably more than 20% on public investment in the 1980s. During this time, the budget share of spending on pensions ranged between 23% (Japan) and slightly above 50% (Austria), while health occupied a considerable share in Canada and Denmark (more than 40%) and was much smaller in the United States and Greece. By the year 2000 (full dots), all countries moved towards spending a bigger share of the budget on pensions (between 25–58%). Austria and Germany are among the countries where the share of pension spending is now more than 50%. The plots also suggests that these monies came from both health spending (which now range roughly between 30–48%) and especially public investment (which is below a 5% share in some countries by 2000). Clearly, a sensible analytical strategy should include the spending constraints coming from other budget items. We collected data on the outlined covariates. The Table 1 in the appendix displays the summary statistics. The data generally are measured annually across countries. Interest are the net government interest payments as percentage of GDP and supplied by the OECD Economic Outlook database. Disbursements are total public disbursement as percentage of GDP (again from the OECD Economic Outlook database). Taken from the OECD Health Database, Age over 65 measures the percentage share of the total population that is over 65 years old. Income per Capita is as measured as the national income per capita in US dollars (current prices, PPP) and provided in the OECD Factbook 2007. Unemployment is a measure of the unemployment rate (commonly used definition), taken from the OECD Economic Outlook database. We measure the percent share of cabinet seats of Social Democratic parties using data from Schmidt (2007a). Due to missing data for some variables, we use multiple imputation via Amelia II (Honaker, Blackwell and King, 2006) and then aggregate the estimation results over 10 imputations.

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Country ● Australia ● Austria ● Belgium ● Canada ● Denmark ● Finland ● France ● Germany ● Greece ● Ireland ● Italy ● Japan ● Netherlands ● NewZealand ● Norway ● Portugal ● Spain ● Sweden ● Switzerland ● UnitedKingdom ● UnitedStates

Figure 1: Ternary Plot of the Trade-offs among Pensions, Public Investment, and Health Expenditures. In order to show the development of these trade-offs, the plot includes the budget composition in 1980 (hollow dots) and in 2000 (full dots) for each country.

Pensions

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● ● ● ● ● ● ●● ●●● ● ●0.4 ● ● ●● ● ● ● ● ●● ●● ● ● ● ● ●● ● ● ● ●● ● ● ● ●

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Methods: Compositional Data Analysis

A methodology for estimating the trade-offs between pensions, investment, and labor market spending needs to take into account that multiple categories of spending are not independent from each other (as estimation by separate regressions assumes). When budgets are treated as a composition5 (Aitchison, 1986), we define a budget category wkit as the expenditures in category k{Pensions, Investment, Health} by country i in year t. The unit of analysis then is a single observed budget composition, defined as a collection of wkit that collectively fulfill the budget constraint:

w1it + · · · + wkit + · · · + wKit = 1,

0 ≤ wkit ≤ 1

(1)

Aitchison (1986) shows that the logarithms of the ratios of wkit are independent and unbounded and therefore can be jointly modeled with standard multivariate methods. The additive logratios are computed by selecting a reference category K (i.e. the last category), then constructing the K − 1 ratios of the composition, and finally logging them. In short,

ykit = ln(wkit /wKit )

(2)

While there is no compositional TSCS model readily available, we can make the common pooling assumptions in the comparative politics literature (e.g. common dynamic parameters across units), and can aggregate the logratios across space and time and estimate the following K − 1 equations:

ykit =

P X

φpk yk,i,t−p + xit−1 β k + εkit

(3)

p=1

For each logratio ykit , we specify an equation regressing ykit on one or more of its lagged 5

Other political science applications include Adolph (2006) and Katz and King (1999).

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values as well as a vector of lagged variables xit−1 including Social Democrats, Income per Capita, Age over 65, Disbursements, and Interest. We estimate the system of K −1 equations by seemingly unrelated regressions (SUR), which allows non-zero correlations across the error terms for a given country and period (Zellner, 1962). We aid interpretation of the results by translating the estimates of the SUR back into budget shares while also accounting for the time dynamics. A clear6 way to understand the implications of the model is to examine the response of the composition to a permanent change in each covariate for the fifth year. We present the 90% confidence intervals for these quantities based on stochastic simulation of the iterated response variable (King, Tomz and Wittenberg, 2000). We report the changes in the shares of the three budget categories in order to facilitate comparison.

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Results

Tables 7 and 7 (in the appendix) display the SUR results for the compositional data model. Because they are shifts in logratios of budget shares, a direct interpretation is difficult. As an alternative, we calculated the expected changes in the budget share after five years from a change in each covariate.7 We use dot plots displaying the point estimates and 90% confidence intervals for each budget category (Figures 2 and 3). Each row of the plots shows the effect of a change in the listed covariate on all of the budget categories while holding other variables constant. Figure 2 considers the individual effects including fixed country effects while Figure 3 assesses the model without fixed effect.. First, we find that enhanced fiscal austerity – captured by increases in net interest payments – impacts differently on the budget shares. We also find that the impact of changes 6

It is impractical to consider the whole impulse-response function with that many components and covariates. 7 We usually consider the counterfactual of a one standard deviation change in the covariate.

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in interest payments is stronger in the model without country fixed effects (Figure 3), suggesting that between-effects might be more important than within-effects. In particular, an increase in Interest by 3% leads to an increase in the share of pensions by circa 1%, while investments lose about 1% of its share. These findings statistically significant differences. Health spending is virtually unaffected by increasing fiscal pressures, which is in line with the above suggestion that health is a intermediate case between spending on pensions and public investment. Second, for both models, increases in the size of the pie, i.e. increases in total size of the budget (disbursements), are not evenly distributed across the three components. Roughly speaking, a standard deviation increase in Disbursements results in an at least 3% increase in the share of pensions spending. In the model specification without fixed country effects, the size of the estimated effect is a bit smaller with about 1%. An increase in disbursements does not lead to a statistically significant change in the share of health expenditures. However, the share of public investment is reduced by at least 1% (see Figure 3). Third, both models also indicate that increases (+2%, i.e. one standard deviation) in the growth of the elderly segment of a country leads to an at least 1% increase, on average, in the share of pensions spending. The compositional analysis also reveals that the increase in pensions is compensated by a cut in health and investment spending. However, the confidence band for investment slightly overlaps with zero. Fourth, we detect evidence for the effect of Income per capita on the three spending categories. A one standard deviation increase in income ($7000 per capita) results in a decrease in the share of public investment by about 1% and a reducing in pensions’s share by at leat 1%. These shifts are accompanied by an increase in health spending of more than 2% percent. Fifth, an increase of Unemployment by 3.5% does not effect the share of health spending in a statistically significant way. A rise in unemployment however does show the trade18

off between pensions and investment. While public investment’s share rises by about 1%, pensions’s share are reduced by about the same amount. This finding is interesting, because it seems to suggest that public investment can be used as a labor market measure to boost the economy. Finally, we do not find any systematic effect of Social Democratic parties on any of the three spending categories in our model specifications. Figures 4 and 5 provide additional evidence for our argument. First, we replace the percentage of Social Democrats with Cusack’s measure of cabinet center of gravity. The results are virtually unaffected by this replacement. A rise in interest still displays the expected effects. Most importantly, the new partisan control measure still does not show any statistically significant effects. Leftist cabinets do not alter the share of pensions, investment, and health spending. Second, we substitute interest for gross debt. In a similar vein as our initial finding for interest, and increase in Gross Debt by 28% is expected to increase the share of pensions spending by about 2%. This increase in debt also corresponds to larger than 2% cut in the share of investment. These are statistically significant results and provide further evidence for our theoretical argument.

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Figure 2: Estimated change in the Share of the Budget after 5 Years (with Fixed Effects. Plots show the expected change in the share by budget category after five years under the counterfactual listed at the right. Each row lists a distinct counterfactual, while each column is a different category. Horizontal lines are the 90 percent confidence bands.

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Figure 3: Estimated change in the Share of the Budget after 5 Years (without Fixed Effects). Plots show the expected change in the share by budget category after five years under the counterfactual listed at the right. Each row lists a distinct counterfactual, while each column is a different category. Horizontal lines are the 90 percent confidence bands.

Social Dems +35%

Unemployment +3.5%

Income per Cap +$7000

Age over 65 + 2%

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0







0.02

−0.02 −0.01





0







0.01

Health

0.02



Figure 4: Estimated change in the Share of the Budget after 5 Years (using Cabinet Center of Gravity). Plots show the expected change in the share by budget category after five years under the counterfactual listed at the right. Each row lists a distinct counterfactual, while each column is a different category. Horizontal lines are the 90 percent confidence bands.

Cabinet +1SD Left

Unemployment +3.5%

Income per Cap +$7000

Age over 65 + 2%

Disbursements +9%

Interest +3%

Pensions

0.03

23

0

−0.06 −0.04 −0.02



−0.04 −0.02 0 0.02 0.04 Change in share

0.06





















Investment

0.02



0.04

−0.04

−0.02





0







Health

0.02



Figure 5: Estimated change in the Share of the Budget after 5 Years (using Gross Debt. Plots show the expected change in the share by budget category after five years under the counterfactual listed at the right. Each row lists a distinct counterfactual, while each column is a different category. Horizontal lines are the 90 percent confidence bands.

Social Dems +35%

Unemployment +3.5%

Income per Cap +$7000

Age over 65 + 2%

Disbursements +9%

Gross Debt +28%

Pensions

0.04

7

Discussion and Conclusions

The empirical analysis largely confirms our expectations developed in the theoretical part. In particular, we have found that enhanced fiscal austerity, operationalized in terms of increased interest payments for public debt or in terms of levels of public debt, has a distinct impact on individual parts of the budget categories. In particular, it has been shown that increased fiscal pressure results in a lower budget share of public investments, whereas in the case of pension spending, the budget share even increases. Health represents an intermediate case between the two in that it is not affected by changes in our indicator of fiscal stress. The negative impact of interest payments on public investment shows that the latter is indeed hit harder than other types of non-discretionary public spending in times of austerity. The positive impact of interest payments on pension spending, however, should not be overinterpreted. That is: our theory does not suggest that increased fiscal pressure must lead to a higher budget share of entitlement spending. The positive direction of the effect, however, suggests that the inertia inherent in pension spending is larger than in other cases, say health or public investment. This is easy to see when we consider a case where interest payments increase, and the share of all budget categories – except pensions – declines. As a result, the relative budget share of pensions will increase. Hence, one should not over- or mis-interpret the positive effect of interest payments on the budget share of pensions. What are possible avenues for future research? First, it would be important to know whether we can identify more trade-offs between other budgetary categories. We chose pension spending and public investment as examples, because we believe the trade-off to manifest itself most strongly in these cases. But other plausible examples (education vs. unemployment spending, spending on passive vs. active labor market policies) come to mind, which could be studied in future research. Second, our analysis did not show any systematic partisan effects on the composition of

24

public budgets. Given that we lack a convincing theory of partisan preferences on budget categories and trade-offs, this might not be surprising. Nevertheless, it seems worthy to think more thoroughly about this. For example, the influence of partisanship could be conditional in nature, that is: political parties could relay the pressure of fiscal austerity differently. This could be tested with the use of interaction effects.

25

26

Table 1: Summary statistics of the covariates. M in. 1stQu. M edian M ean 3rdQu. Interest −4.44 1.46 2.86 3.14 4.30 Disbursements 25.36 38.57 46.06 45.86 52.42 Age over 65 8.90 12.20 14.30 13.96 15.50 Income per capita 4756 12700 17440 18190 23140 % Social Dems 0.00 0.00 27.96 34.69 69.04 Cabinet CoG −37.23 −11.02 −1.16 0.64 10.42 Gross Debt 0.48 40.87 59.73 61.98 74.53

Appendix

M ax. 13.46 72.45 19.00 38580 100.00 48.46 159.50

SUR on the Logratios of Pensions and Investment for the Model with Fixed Effects. Estimate Std. Error t value Pr(>|t|) PensionsLRlag1 8.14744e-01 2.55338e-02 31.90842 < 2.22e-16 *** age65 9.53264e-03 3.68543e-03 2.58658 0.00998916 ** nipc -3.11749e-06 7.45517e-07 -4.18165 3.4455e-05 *** disburs 2.80558e-03 9.80554e-04 2.86121 0.00440597 ** interest 2.58792e-03 2.32230e-03 1.11438 0.26567901 proz_sd -4.93506e-06 9.10643e-05 -0.05419 0.95680400 unemploy -4.49330e-03 1.72849e-03 -2.59956 0.00962437 ** Australia -1.95954e-01 4.44372e-02 -4.40968 1.2810e-05 *** Austria -1.00292e-01 5.56530e-02 -1.80210 0.07216260 . Belgium -2.11167e-01 5.67058e-02 -3.72391 0.00021965 *** Canada -2.41110e-01 5.04417e-02 -4.77997 2.3401e-06 *** Denmark -2.18470e-01 5.98412e-02 -3.65083 0.00029035 *** Finland -1.57138e-01 5.32553e-02 -2.95065 0.00332744 ** France -1.34476e-01 5.20252e-02 -2.58483 0.01003927 * Germany -1.51021e-01 5.43578e-02 -2.77827 0.00568085 ** Greece -4.66996e-02 4.51020e-02 -1.03542 0.30099767 Ireland -2.24544e-01 4.84144e-02 -4.63797 4.5525e-06 *** Italy -1.02117e-01 5.10206e-02 -2.00148 0.04590789 * Japan -1.46240e-01 4.62740e-02 -3.16030 0.00167651 ** Netherlands -1.89729e-01 5.29229e-02 -3.58500 0.00037187 *** NewZealand -1.50601e-01 4.55531e-02 -3.30605 0.00101772 ** Norway -2.04268e-01 5.98167e-02 -3.41490 0.00069263 *** Portugal -1.64149e-01 4.90645e-02 -3.34557 0.00088608 *** Spain -8.72191e-02 4.65558e-02 -1.87343 0.06162121 . Sweden -2.21664e-01 6.94339e-02 -3.19245 0.00150411 ** Switzerland -1.21344e-01 4.74773e-02 -2.55583 0.01090296 * UnitedKingdom -2.06671e-01 5.47870e-02 -3.77226 0.00018216 *** UnitedStates -1.32401e-01 4.12011e-02 -3.21353 0.00140009 ** --Estimate Std. Error t value Pr(>|t|) InvestmentLRlag1 8.75236e-01 2.23476e-02 39.16457 < 2.22e-16 *** age65 1.18479e-03 4.66412e-03 0.25402 0.79958862 nipc -4.32905e-06 1.14416e-06 -3.78361 0.00017428 *** disburs -5.69376e-03 1.32096e-03 -4.31033 1.9820e-05 *** interest -5.59798e-03 3.17020e-03 -1.76581 0.07806868 . proz_sd 4.66628e-05 1.22865e-04 0.37979 0.70427230 unemploy 3.38783e-03 2.37190e-03 1.42832 0.15385589 Australia 1.42710e-01 5.06262e-02 2.81889 0.00501985 **

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Austria Belgium Canada Denmark Finland France Germany Greece Ireland Italy Japan Netherlands NewZealand Norway Portugal Spain Sweden Switzerland UnitedKingdom UnitedStates --Signif. codes:

1.98253e-01 2.23389e-01 2.01022e-01 1.87822e-01 2.31115e-01 2.19183e-01 1.33678e-01 1.99951e-01 2.18808e-01 2.51553e-01 2.31457e-01 2.99047e-01 1.81863e-01 2.05285e-01 2.14952e-01 2.10746e-01 2.98867e-01 1.84288e-01 1.34452e-01 2.13095e-01

7.50545e-02 7.21481e-02 5.74577e-02 7.79070e-02 6.92695e-02 6.87346e-02 7.25804e-02 6.15192e-02 5.55824e-02 6.81734e-02 5.92048e-02 6.88022e-02 6.01052e-02 7.74581e-02 6.34109e-02 6.13589e-02 9.06517e-02 6.32026e-02 6.86589e-02 5.44706e-02

2.64145 3.09626 3.49862 2.41085 3.33646 3.18882 1.84179 3.25022 3.93665 3.68990 3.90944 4.34648 3.02574 2.65027 3.38983 3.43465 3.29687 2.91583 1.95826 3.91211

0 *** 0.001 ** 0.01 * 0.05 . 0.1

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0.00852675 0.00207539 0.00051160 0.01629327 0.00091494 0.00152268 0.06612801 0.00123484 9.4964e-05 0.00025026 0.00010594 1.6926e-05 0.00261448 0.00831051 0.00075753 0.00064522 0.00105080 0.00371486 0.05078268 0.00010481

1

** ** *** * *** ** . ** *** *** *** *** ** ** *** *** ** ** . ***

SUR on the Logratios of Pensions and Investment for the Model without the Fixed Effects. Estimate Std. Error t value Pr(>|t|) PensionsLRlag1 9.54576e-01 1.09626e-02 87.07590 < 2.22e-16 *** age65 4.70295e-03 2.04732e-03 2.29712 0.022028 * nipc -2.31600e-06 5.39274e-07 -4.29465 2.1057e-05 *** disburs 1.12020e-04 3.82976e-04 0.29250 0.770029 interest 1.69711e-03 1.14755e-03 1.47890 0.139802 proz_sd 2.07135e-05 8.24820e-05 0.25113 0.801820 unemploy -1.91458e-03 9.50208e-04 -2.01491 0.044453 * constant -1.86649e-02 2.39155e-02 -0.78045 0.435496 --Estimate Std. Error t value Pr(>|t|) InvestmentLRlag1 9.54510e-01 1.25830e-02 75.85689 < 2.22e-16 *** age65 -1.39818e-03 2.35496e-03 -0.59372 0.5529721 nipc -1.60503e-06 7.80374e-07 -2.05674 0.0402333 * disburs -1.85499e-03 5.68333e-04 -3.26391 0.0011747 ** interest -3.75020e-03 1.50587e-03 -2.49039 0.0130864 * proz_sd -4.04263e-06 1.09695e-04 -0.03685 0.9706168 unemploy 2.78903e-03 1.30045e-03 2.14466 0.0324648 * constant 7.04035e-02 3.24153e-02 2.17192 0.0303345 * --Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1

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