American Political Science Review (2018)112.4.939-953 doi:10.1017/S0003055418000436 American Political Science Association 2018 Cabinet Durability and Fiscal Discipline DAVID FORTUNATO Texas A&M University MATT W.LOFTIS Aarhus University Te argue that short government durations in parliamentary democracies increase public spending by driving a political budget cycle.We present a revision of the standard political budget cycle model that relaxes the common (often implicit)assumption that election timing is fixed and known in advance.Instead,we allow cabinets to form expectations about their durability and use these expectations to inform their spending choices.The model predicts that (1)cabinets should spend more as their expected term in office draws to a close and (2)cabinets that outlive their expected duration should run higher deficits.Using data from 15 European democracies over several decades,we show that governments increase spending as their expected duration withers and run higher deficits as they surpass their forecasted life expectancy. abinet durability has inspired a vibrant theoret- the real policy implications of government durability ical and empirical literature in comparative po- Further,by taking into account the uncertainty of cab- litical economy.Ostensibly,political economists inet life expectancies,we uncover a possible resolution study government stability,a concept Laver and to a longstanding discord in the literature on PBCs Shepsle (1998)describe as "self-evidently important," where there is theoretical consensus on the central under the assumption that it is salient to real policy out- prediction,but weak or institutionally dependent em- comes.However,just which outcomes are conditioned pirical evidence for it in advanced democracies.That 4号元 by durability,and how,remain open questions.Here,we is,nearly all previous PBC studies have assumed that take an important step toward answering these ques- elections are fixed,but only about 18%of European tions by presenting theoretical and empirical analy- cabinets survive the maximum constitutional interelec- ses of the relationship between government durability tion period(CIEP).By relaxing the assumption of and public spending.We argue that governments with fixed elections and allowing the cabinet to forecast its shorter life expectancies face more immediate pressure durability,we uncover the evidence of cycling behav- to spend at higher rates to accrue electoral support- ior in advanced Western European democracies that speeding up a political budget cycle (PBC)that would has eluded so many of our predecessors.Indeed,mod- otherwise see spending crescendo in advance of sched- els including expected duration provide significantly uled elections.Our theoretical discussion yields two more explanatory power for observed spending pat- testable implications:(1)governments spend more as terns than models including true duration. their life expectancy withers and(2)governments that Moving forward,we briefly discuss the extant liter- outlive their expected durations will run higher deficits ature on both cabinet durability and public spending, than governments that do not surpass their life ex- highlighting the opportunity for studying the implica- pectancy.Our empirical tests reveal support for these tions of cabinet stability in the former and the discord hypotheses and imply that,in expectation,govern- between theoretical and empirical studies of PBCs in ment stability has a substantial positive impact on fiscal advanced democracies in the latter.We then present well-being. our theoretical approach to the question,derive our hy- In presenting our arguments and analyses,we make potheses,and move on to describe our research design several substantively significant contributions.Our pri- Using public spending data from 15 Western European mary empirical findings improve both our understand- democracies over a period of roughly 50 years,we find ing of public spending and debt accumulation and take robust empirical evidence for our central predictions. an important and overdue step toward understanding GOVERNMENT SURVIVAL David Fortunato is an Associate Professor,Texas A&M University. As comparativists may recall,beginning in the 1970s 2010 Allen Building,4348 TAMU,College Station,TX 77843-4348 and extending through the 1990s,the literature on gov- (fortunato@tamu.edu). Matt W.Loftis is an Assistant Professor,Aarhus University, ernment durability was dominated by debate between Bartholins Alle 7,8000 Aarhus,Denmark (mattwloftis@ps.au.dk). the“attributes'”and“events'”approaches to the ques-. In addition to the editorial team and four anonymous review. tion.2 In short,the attributes approach conceived of ers,we are grateful to Despina Alexiadou,Timm Betz,Martin Bis- gaard,Bill Clark,Jason Eichorst,Carsten Jensen,Andre Kaiser,Pe- ter B.Mortensen,Oli Proksch,Guy Whitten,and Georg Vanberg. as well as participants of the 2016 Annual Meetings of the Pub- I Data taken from Seki and Williams(2014).We define the maximum lic Choice Society and Southern Political Science Association for as 95%or greater.In countries with a 4-year CIEP,by far the most helpful comments and feedback.Replication files are available on common length,the remaining 5%corresponds to 73 days.The typi- the American Political Science Review Dataverse:https://doi.org/10. cal cutoff point for defining early elections is 60 days or more before 7910/DVN/HHMXU3. CIEP expiration (e.g.,Schleiter and Tavits 2016). As Laver(20O3)notes,“durability”and“duration”are distinct con- Received:April 26.2017:revised:December 15,2017:accepted:June cepts.Where durability is a latent quality that may be described,but is 24,2018.First published online:September 5,2018. inherently unobservable,duration,the amount of time a government 939
American Political Science Review (2018) 112, 4, 939–953 doi:10.1017/S0003055418000436 © American Political Science Association 2018 Cabinet Durability and Fiscal Discipline DAVID FORTUNATO Texas A&M University MATT W. LOFTIS Aarhus University We argue that short government durations in parliamentary democracies increase public spending by driving a political budget cycle. We present a revision of the standard political budget cycle model that relaxes the common (often implicit) assumption that election timing is fixed and known in advance. Instead, we allow cabinets to form expectations about their durability and use these expectations to inform their spending choices. The model predicts that (1) cabinets should spend more as their expected term in office draws to a close and (2) cabinets that outlive their expected duration should run higher deficits. Using data from 15 European democracies over several decades, we show that governments increase spending as their expected duration withers and run higher deficits as they surpass their forecasted life expectancy. Cabinet durability has inspired a vibrant theoretical and empirical literature in comparative political economy. Ostensibly, political economists study government stability, a concept Laver and Shepsle (1998) describe as “self-evidently important,” under the assumption that it is salient to real policy outcomes. However, just which outcomes are conditioned by durability, and how, remain open questions.Here, we take an important step toward answering these questions by presenting theoretical and empirical analyses of the relationship between government durability and public spending. We argue that governments with shorter life expectancies face more immediate pressure to spend at higher rates to accrue electoral support— speeding up a political budget cycle (PBC) that would otherwise see spending crescendo in advance of scheduled elections. Our theoretical discussion yields two testable implications: (1) governments spend more as their life expectancy withers and (2) governments that outlive their expected durations will run higher deficits than governments that do not surpass their life expectancy. Our empirical tests reveal support for these hypotheses and imply that, in expectation, government stability has a substantial positive impact on fiscal well-being. In presenting our arguments and analyses, we make several substantively significant contributions. Our primary empirical findings improve both our understanding of public spending and debt accumulation and take an important and overdue step toward understanding David Fortunato is an Associate Professor, Texas A&M University, 2010 Allen Building, 4348 TAMU, College Station, TX 77843-4348 (fortunato@tamu.edu). Matt W. Loftis is an Assistant Professor, Aarhus University, Bartholins Allé 7, 8000 Aarhus, Denmark (mattwloftis@ps.au.dk). In addition to the editorial team and four anonymous reviewers, we are grateful to Despina Alexiadou, Timm Betz, Martin Bisgaard, Bill Clark, Jason Eichorst, Carsten Jensen, André Kaiser, Peter B. Mortensen, Oli Proksch, Guy Whitten, and Georg Vanberg, as well as participants of the 2016 Annual Meetings of the Public Choice Society and Southern Political Science Association for helpful comments and feedback. Replication files are available on the American Political Science Review Dataverse: https://doi.org/10. 7910/DVN/HHMXU3. Received: April 26, 2017; revised: December 15, 2017; accepted: June 24, 2018. First published online: September 5, 2018. the real policy implications of government durability. Further, by taking into account the uncertainty of cabinet life expectancies, we uncover a possible resolution to a longstanding discord in the literature on PBCs where there is theoretical consensus on the central prediction, but weak or institutionally dependent empirical evidence for it in advanced democracies. That is, nearly all previous PBC studies have assumed that elections are fixed, but only about 18% of European cabinets survive the maximum constitutional interelection period (CIEP).1 By relaxing the assumption of fixed elections and allowing the cabinet to forecast its durability, we uncover the evidence of cycling behavior in advanced Western European democracies that has eluded so many of our predecessors. Indeed, models including expected duration provide significantly more explanatory power for observed spending patterns than models including true duration. Moving forward, we briefly discuss the extant literature on both cabinet durability and public spending, highlighting the opportunity for studying the implications of cabinet stability in the former and the discord between theoretical and empirical studies of PBCs in advanced democracies in the latter. We then present our theoretical approach to the question, derive our hypotheses, and move on to describe our research design. Using public spending data from 15 Western European democracies over a period of roughly 50 years, we find robust empirical evidence for our central predictions. GOVERNMENT SURVIVAL As comparativists may recall, beginning in the 1970s and extending through the 1990s, the literature on government durability was dominated by debate between the “attributes” and “events” approaches to the question.2 In short, the attributes approach conceived of 1 Data taken from Seki and Williams (2014).We define the maximum as 95% or greater. In countries with a 4-year CIEP, by far the most common length, the remaining 5% corresponds to 73 days. The typical cutoff point for defining early elections is 60 days or more before CIEP expiration (e.g., Schleiter and Tavits 2016). 2 As Laver (2003) notes, “durability” and “duration” are distinct concepts.Where durability is a latent quality that may be described, but is inherently unobservable, duration, the amount of time a government 939 Downloaded from https://www.cambridge.org/core. 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David Fortunato and Matt W.Loftis government durability as a function of characteristics proposed to jointly model formation and duration by which can be observed at the time of the cabinet's for- Chiba.Martin.and Stevenson (2015).who find signif. mation (e.g.,Warwick 1979;Strom 1985).That is,gov- icant differences between the correlates of durability ernments in general are made more durable by acti- when selection is and is not accounted for.In the in- vating certain features (majority status,for example) terim,we have learned that a government's durability is and coalition governments,in particular,can be made a function of events and attributes such as majority sta- more stable by selecting partners that are compati- tus,the complexity of the bargaining environment,the ble on salient policy dimensions.The events approach, number and size of antiestablishment parties in parlia- by contrast,argued that cabinet stability is primarily ment,and ideological compatibility within the govern- a function of stochastic shocks to the political envi- ment,though the findings of Chiba,Martin,and Steven- ronment (e.g.,Browne,Frendreis,and Gleiber 1984). son(2015)suggest previous estimates of the salience of Warwick(1994)provides a thoughtful and detailed dis- compatibility may have been overstated as a function cussion of this debate. of the aforementioned selection bias.3 Importantly,the The rift between these competing perspectives even- presence of selection bias provides evidence that cabi- tually gave way to an acceptance that both attributes nets can and do forecast their durability. and events were salient to government longevity and What all of this research (and scores of books and that researchers must integrate both into a hybrid articles we have not discussed)has in common is model that considers how cabinets'characteristics its consistent attention to durability as the depen- make them more or less likely to survive the various dent variable.4 Even when the theoretical focus is shocks they may experience,or,how certain shocks not attributes of the cabinet itself,but on alternative may have the potential to reshape the properties of political economic phenomena.like,for example,nat- the status quo government relative to its alternatives. ural resource revenue or interstate transfers.incum- The incorporation of the two approaches into a unified bent duration is still nearly always found on the left- framework is now the dominant theoretical perspec- hand side of the equation(e.g.,Ahmed 2012;Bueno De tive on government stability and exemplified by Lu- Mesquita and Smith 2010).This is likely because most pia and Strom (1995),Laver and Shepsle (1998),and scholars perceive the importance of cabinet longevity Diermeier and Stevenson (2000),who argue that the as self-evident,and on this we do not disagree.Nev- relevant "events"are shocks to the political environ- ertheless,the overwhelming focus on duration as a ment that alter the distribution of bargaining power dependent variable has obscured why scholars were across legislative parties,making alternatives to the sta moved to study it in the first place:the belief that rapid tus quo government more or less attractive,and there- government turnover is,on some normative level,a fore making termination more or less likely. net negative,or at the very least salient to democratic These theoretical innovations went hand-in-hand representation and governance.That is,the entirety of with empirical advances that sought to model the at- this literature is motivated by the assumption that cabi- tributes or events approaches separately (e.g.,Strom net stability has powerful implications for,in the words 1985;Browne,Frendreis,and Gleiber 1986,respec- of King et al.(1990,846),"democratic stability,pol- tively),before moving on to harmonize them.One icy continuity,or even executive dominance over the could argue that,in this respect,the empiricists were legislature"among numerous other,more specific,sub- S5.501g a step ahead of the theorists,with King et al.(1990, stantively interesting and normatively significant po 847;authors'emphasis)presenting a"statistically uni- litical economic outcomes.However,in the political fied model that can be used to explore the impact of science literature,we could find only two empirical particular attributes upon cabinet durability(expected studies making a robust connection between cabinet duration),while maintaining the assumption that the stability,as an independent variable,and democratic duration of any particular cabinet will ultimately be de- outcomes(broadly defined)-one links government in- termined by a stochastic process,such as the random stability (in terms of executive turnover)to decreased incidence of terminal events"-a model that correctly levels of overall satisfaction with democratic gover- predicts government duration within four months on nance (Harmel and Robertson 1986)and the other average. finds that short-term spikes in portfolio volatility de- This is not the case in regard to the next major hurdle crease the efficiency of policy implementation (Huber in the literature:recognizing,and subsequently mod- 1998) eling,the selection problem in cabinet durability.As early as De Swaan (1973),theorists had understood that durability was a critical concern in the formation We note that cabinets not only terminate in dissolution,but also of governments,but it would be several decades until in replacement(Diermeier and Stevenson 1999;Chiba,Martin,and empiricists began to engage this issue in earnest (e.g. Stevenson 2015).As we discuss below in more detail,we model dura- bility by estimating the risk of dissolution,but not replacement,for Merlo 1997;Diermeier,Eraslan,and Merlo 2003)and wo reasons:dissolution is the theoretically salient termination type later still before a solution to the selection problem was and because risk-averse governments have little or no incentive to prepare for replacement rather than(or in addition to)dissolution. We urge interested readers to consult Warwick (1994),Laver spent in office,is observable.We think of duration as a realization of (2003),and Woldendorp,Keman,and Budge(2013)for excellent re- a random variable durability.Here,we are interested in durability views of this literature. for the purposes of predicting duration,but we use these terms,and We note that there is a handful of public economics articles pre- others,such as "stability,"interchangeably. senting evidence that political instability may impede economic 940
David Fortunato and Matt W. Loftis government durability as a function of characteristics which can be observed at the time of the cabinet’s formation (e.g., Warwick 1979; Strøm 1985). That is, governments in general are made more durable by activating certain features (majority status, for example) and coalition governments, in particular, can be made more stable by selecting partners that are compatible on salient policy dimensions. The events approach, by contrast, argued that cabinet stability is primarily a function of stochastic shocks to the political environment (e.g., Browne, Frendreis, and Gleiber 1984). Warwick (1994) provides a thoughtful and detailed discussion of this debate. The rift between these competing perspectives eventually gave way to an acceptance that both attributes and events were salient to government longevity and that researchers must integrate both into a hybrid model that considers how cabinets’ characteristics make them more or less likely to survive the various shocks they may experience, or, how certain shocks may have the potential to reshape the properties of the status quo government relative to its alternatives. The incorporation of the two approaches into a unified framework is now the dominant theoretical perspective on government stability and exemplified by Lupia and Strøm (1995), Laver and Shepsle (1998), and Diermeier and Stevenson (2000), who argue that the relevant “events” are shocks to the political environment that alter the distribution of bargaining power across legislative parties,making alternatives to the status quo government more or less attractive, and therefore making termination more or less likely. These theoretical innovations went hand-in-hand with empirical advances that sought to model the attributes or events approaches separately (e.g., Strøm 1985; Browne, Frendreis, and Gleiber 1986, respectively), before moving on to harmonize them. One could argue that, in this respect, the empiricists were a step ahead of the theorists, with King et al. (1990, 847; authors’ emphasis) presenting a “statistically unified model that can be used to explore the impact of particular attributes upon cabinet durability (expected duration), while maintaining the assumption that the duration of any particular cabinet will ultimately be determined by a stochastic process, such as the random incidence of terminal events”—a model that correctly predicts government duration within four months on average. This is not the case in regard to the next major hurdle in the literature: recognizing, and subsequently modeling, the selection problem in cabinet durability. As early as De Swaan (1973), theorists had understood that durability was a critical concern in the formation of governments, but it would be several decades until empiricists began to engage this issue in earnest (e.g., Merlo 1997; Diermeier, Eraslan, and Merlo 2003) and later still before a solution to the selection problem was spent in office, is observable. We think of duration as a realization of a random variable durability. Here, we are interested in durability for the purposes of predicting duration, but we use these terms, and others, such as “stability,” interchangeably. proposed to jointly model formation and duration by Chiba, Martin, and Stevenson (2015), who find significant differences between the correlates of durability when selection is and is not accounted for. In the interim,we have learned that a government’s durability is a function of events and attributes such as majority status, the complexity of the bargaining environment, the number and size of antiestablishment parties in parliament, and ideological compatibility within the government, though the findings of Chiba,Martin, and Stevenson (2015) suggest previous estimates of the salience of compatibility may have been overstated as a function of the aforementioned selection bias.3 Importantly, the presence of selection bias provides evidence that cabinets can and do forecast their durability. What all of this research (and scores of books and articles we have not discussed) has in common is its consistent attention to durability as the dependent variable.4 Even when the theoretical focus is not attributes of the cabinet itself, but on alternative political economic phenomena, like, for example, natural resource revenue or interstate transfers, incumbent duration is still nearly always found on the lefthand side of the equation (e.g.,Ahmed 2012; Bueno De Mesquita and Smith 2010). This is likely because most scholars perceive the importance of cabinet longevity as self-evident, and on this we do not disagree. Nevertheless, the overwhelming focus on duration as a dependent variable has obscured why scholars were moved to study it in the first place: the belief that rapid government turnover is, on some normative level, a net negative, or at the very least salient to democratic representation and governance. That is, the entirety of this literature is motivated by the assumption that cabinet stability has powerful implications for, in the words of King et al. (1990, 846), “democratic stability, policy continuity, or even executive dominance over the legislature” among numerous other, more specific, substantively interesting and normatively significant political economic outcomes. However, in the political science literature, we could find only two empirical studies making a robust connection between cabinet stability, as an independent variable, and democratic outcomes (broadly defined)—one links government instability (in terms of executive turnover) to decreased levels of overall satisfaction with democratic governance (Harmel and Robertson 1986) and the other finds that short-term spikes in portfolio volatility decrease the efficiency of policy implementation (Huber 1998).5 3 We note that cabinets not only terminate in dissolution, but also in replacement (Diermeier and Stevenson 1999; Chiba, Martin, and Stevenson 2015).As we discuss below in more detail, we model durability by estimating the risk of dissolution, but not replacement, for two reasons: dissolution is the theoretically salient termination type and because risk-averse governments have little or no incentive to prepare for replacement rather than (or in addition to) dissolution. 4 We urge interested readers to consult Warwick (1994), Laver (2003), and Woldendorp, Keman, and Budge (2013) for excellent reviews of this literature. 5 We note that there is a handful of public economics articles presenting evidence that political instability may impede economic 940 Downloaded from https://www.cambridge.org/core. 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Cabinet Durability and Fiscal Discipline All of this is to say that,while the supply of governments want to be reelected and voters factor research devoted to understanding the causes of economic performance into their choices at the ballot government durability is vast and deep,the supply of box.As such,opportunistic governments may stimulate empirical research devoted to understanding the con- the economy (or at least their supporters'economic sequences of government durability is nearly nonexis- prospects)in the short term by increasing spending in tent.As such,whether or not cabinet stability actually hopes that voters will be persuaded of their managerial bears any real policy consequences remains an almost competence.5 Thus,we should observe greater spend- entirely open question,one that we begin to provide an ing in election years or pre-election years. answer to by assessing the relationship between gov- Despite the intuitiveness and simplicity of the theo- ernment longevity and public spending-perhaps the retical account of electoral budget cycles,the literature most significant policy decision that governments must on the subject has been characterized by intense de- make. bate."The endurance of the debate derives from a stark contrast between the commonsense nature of the op- PUBLIC SPENDING portunistic argument and the paucity of evidence sup- porting its key implication"(Clark et al.1998,87-88). Interest in public spending in political economic re Evidence is particularly weak in the case of consol- search is pervasive.Though there are a variety of idated democracies with advanced economies (Bren- themes within the literature,our interest here is in re- der and Drazen 2005).Many scholars argue that one search devoted to the study of public spending as a re- reason for this is the lack of consideration given to alization of the common pool resource problem,partic the structure of political and economic institutions- ularly the research on the presence of PBCs.In short, several of which may provide constraints on the ability government parties are accountable to a subset of the of governments to stimulate spending in the run-up to electorate that has particular spending priorities.Gov- election.For example.Persson and Tabellini(2005)find ernments may engage in directed spending to please that welfare spending tends to increase in the vicinity 4 their supporters,who enjoy the benefits of that spend- of elections to a larger degree in proportional systems ing while bearing only a fraction of its costs.This im- than in single-member systems,because proportional balance between the concentrated benefits accruing to rules broaden the population parties must appeal to government supporters and the costs of expenditures, for support.Rose(2006)provides evidence that formal which are diffused more evenly across the electorate, balanced budget rules constrain PBCs in the American means that demand for spending within the govern- states and Alt and Lassen (2006)argue that fiscal pol- ment's supporting coalition tends to be greater than icy transparency may similarly constrain governments it would be otherwise and the commons (national cof- by exposing their manipulation to voters.Analyzing 19 fers)are at risk of depletion. advanced democracies,they find evidence that cycles Bawn and Rosenbluth (2006)argue that this prob- exist,but only in opaque fiscal environments. lem is exacerbated by increasing the diversity of the This institutional approach to the search for PBCs groups represented by the cabinet,as is the case in sheds light on the discord between the theoretical re- coalition governance,so long as the benefits of spend- search.which had reached a near unanimous consen- ing enjoyed by those groups continue to outpace the sus in the expectation of PBCs,and the empirical re- costs they bear.A similar argument is presented by search that had found inconsistent evidence for them Persson,Roland,and Tabellini(2007).Though subse- in advanced democracies.Cabinets do not operate in quent research by Martin and Vanberg(2013)suggests isolation of their institutional constraints,thus,neither that the temptation to grow public spending as a result should our empirical investigations of their choices. of increasing the number of parties in government may Nonetheless,according to Philips's(2016)meta anal- be mitigated by institutions constraining the budgeting ysis of PBC scholarship,93%of studies ignore institu- process,the robust empirical connection between elec tional variation in the timing of elections by assuming toral incentives and public spending persists.In the ab- that it is fixed and known ex ante,while the remain- sence of strict institutional barriers,governments will ing 7%assume electoral timing is endogenous-that it spend excessively to please their supporters. is chosen by the incumbent.?This is surprising in light The notion that governments have strong electoral of the recent advances in modeling institutional diver- incentives to spend on their supporters is a special case sity in the PBC literature and even more surprising of the intuitive theoretical argument motivating the given the robust literature on the nature of government 四 search for PBCs.The classic argument is as follows: durability and the common sense realization that both of these assumptions are unrealistic for parliamentary democracies. growth,increase government consumption,or increase redistribution (e.g.,Alesina and Perotti 1996:Annett 2001:Carmignani 2009.re. spectively).However,these works are overwhelmingly focused on political violence or revolution when referring to "political instabil- Our primary concern in this manuscript is on public spending,how ity."As such,none consider primarily modern economies and peace. ever,the extant research on political budget cycles has considered ful transitions of power within consolidated democracies,which is not only spending,but also monetary policy,typically focused on our focus here.We also note that Perry and Robertson(1998)include the inflation-unemployment tradeoff,as in the canonical works of a type of government durability measure in an index of executive Nordhaus (1975)and MacRae (1977). consistency that is regressed on a measure of a state's bond risk in a These figures are not reported in the original article but tallied from sample of advanced,stable democracies. the replication materials. 941
Cabinet Durability and Fiscal Discipline All of this is to say that, while the supply of research devoted to understanding the causes of government durability is vast and deep, the supply of empirical research devoted to understanding the consequences of government durability is nearly nonexistent. As such, whether or not cabinet stability actually bears any real policy consequences remains an almost entirely open question, one that we begin to provide an answer to by assessing the relationship between government longevity and public spending—perhaps the most significant policy decision that governments must make. PUBLIC SPENDING Interest in public spending in political economic research is pervasive. Though there are a variety of themes within the literature, our interest here is in research devoted to the study of public spending as a realization of the common pool resource problem, particularly the research on the presence of PBCs. In short, government parties are accountable to a subset of the electorate that has particular spending priorities. Governments may engage in directed spending to please their supporters, who enjoy the benefits of that spending while bearing only a fraction of its costs. This imbalance between the concentrated benefits accruing to government supporters and the costs of expenditures, which are diffused more evenly across the electorate, means that demand for spending within the government’s supporting coalition tends to be greater than it would be otherwise and the commons (national coffers) are at risk of depletion. Bawn and Rosenbluth (2006) argue that this problem is exacerbated by increasing the diversity of the groups represented by the cabinet, as is the case in coalition governance, so long as the benefits of spending enjoyed by those groups continue to outpace the costs they bear. A similar argument is presented by Persson, Roland, and Tabellini (2007). Though subsequent research by Martin and Vanberg (2013) suggests that the temptation to grow public spending as a result of increasing the number of parties in government may be mitigated by institutions constraining the budgeting process, the robust empirical connection between electoral incentives and public spending persists. In the absence of strict institutional barriers, governments will spend excessively to please their supporters. The notion that governments have strong electoral incentives to spend on their supporters is a special case of the intuitive theoretical argument motivating the search for PBCs. The classic argument is as follows: growth,increase government consumption, or increase redistribution (e.g., Alesina and Perotti 1996; Annett 2001; Carmignani 2009, respectively). However, these works are overwhelmingly focused on political violence or revolution when referring to “political instability.” As such, none consider primarily modern economies and peaceful transitions of power within consolidated democracies, which is our focus here.We also note that Perry and Robertson (1998) include a type of government durability measure in an index of executive consistency that is regressed on a measure of a state’s bond risk in a sample of advanced, stable democracies. governments want to be reelected and voters factor economic performance into their choices at the ballot box.As such, opportunistic governments may stimulate the economy (or at least their supporters’ economic prospects) in the short term by increasing spending in hopes that voters will be persuaded of their managerial competence.6 Thus, we should observe greater spending in election years or pre-election years. Despite the intuitiveness and simplicity of the theoretical account of electoral budget cycles, the literature on the subject has been characterized by intense debate. “The endurance of the debate derives from a stark contrast between the commonsense nature of the opportunistic argument and the paucity of evidence supporting its key implication” (Clark et al. 1998, 87–88). Evidence is particularly weak in the case of consolidated democracies with advanced economies (Brender and Drazen 2005). Many scholars argue that one reason for this is the lack of consideration given to the structure of political and economic institutions— several of which may provide constraints on the ability of governments to stimulate spending in the run-up to election.For example,Persson and Tabellini (2005) find that welfare spending tends to increase in the vicinity of elections to a larger degree in proportional systems than in single-member systems, because proportional rules broaden the population parties must appeal to for support. Rose (2006) provides evidence that formal balanced budget rules constrain PBCs in the American states and Alt and Lassen (2006) argue that fiscal policy transparency may similarly constrain governments by exposing their manipulation to voters. Analyzing 19 advanced democracies, they find evidence that cycles exist, but only in opaque fiscal environments. This institutional approach to the search for PBCs sheds light on the discord between the theoretical research, which had reached a near unanimous consensus in the expectation of PBCs, and the empirical research that had found inconsistent evidence for them in advanced democracies. Cabinets do not operate in isolation of their institutional constraints, thus, neither should our empirical investigations of their choices. Nonetheless, according to Philips’s (2016) meta analysis of PBC scholarship, 93% of studies ignore institutional variation in the timing of elections by assuming that it is fixed and known ex ante, while the remaining 7% assume electoral timing is endogenous—that it is chosen by the incumbent.7 This is surprising in light of the recent advances in modeling institutional diversity in the PBC literature and even more surprising given the robust literature on the nature of government durability and the common sense realization that both of these assumptions are unrealistic for parliamentary democracies. 6 Our primary concern in this manuscript is on public spending, however, the extant research on political budget cycles has considered not only spending, but also monetary policy, typically focused on the inflation-unemployment tradeoff, as in the canonical works of Nordhaus (1975) and MacRae (1977). 7 These figures are not reported in the original article but tallied from the replication materials. 941 Downloaded from https://www.cambridge.org/core. Shanghai JiaoTong University, on 26 Oct 2018 at 03:53:05, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055418000436
David Fortunato and Matt W.Loftis In reality,elections are not fixed in the overwhelm- means certain and.in fact,it is the exception rather than ing majority of parliamentary democracies and only the rule. a very small minority of elections could be described We assume cabinet dissolution is stochastic and as strategically timed or"opportunistic"(Schleiter and model government spending accordingly as a func- Tavits 2016).Indeed,an accounting of over 608 Euro tion of the cabinet's electoral expectations-when it pean governments by Seki and Williams(2014)reveals believes the next election will occur either as a result that at least 62%of cabinets terminate in conditions of expiration of the constitutional interrelation period that are not constitutionally mandated elections and (CIEP)or premature dissolution(from here on we use are extraordinarily unlikely to be the product of strate- the words election and dissolution interchangeably)o gic electoral timing-the resignation of the prime min- That is,we assume that governments form beliefs over ister(for health reasons or otherwise),internal dissent their durability and grow public spending accordingly. or loss of parliamentary support.In other words,well If we believe that governments have a preference for over half of all European governments violate the stan- fiscal discipline,all else equal,then this implies a nega- dard assumptions of the extant PBC literature.Gov- tive relationship between expectations of cabinet dura- ernment survivability in parliamentary democracies is bility and public spending.Cabinets should spend less inherently uncertain and,as such,we cannot presume when elections are believed to be distant and spend the timing of elections to be fixed,nor can we assume more when elections are believed to be proximate to the timing is purely a function of the cabinet's tastes.s stimulate electoral support without running burden- Our framework relaxes these assumptions by building some deficits. a model of public spending that incorporates the cabi- Borrowing from Alt and Lassen (2006),a stylized net's expectations for dissolution.More specifically,we representation of this expectation is given in the left construct a predicted duration for each cabinet in our pane of Figure 1 with the x-axis representing the cab- data based upon its observable characteristics at for- inet's life expectancy and the y-axis representing pub- 令 mation and estimate the effect of the cabinet's life ex- lic spending.As the government's expected dissolution 4号 pectancy on its spending choices. point approaches (indicated by the 0 hash on the x- axis),it increases spending to engender electoral sup- DURABILITY AND SPENDING port.After the election,the government(whether or & not the incumbent has returned)lowers spending and As is common in the literature,we make the follow- the cycle begins again.To reiterate:when governments ing assumptions:(1)incumbent governments wish to believe that elections are distant,public spending is be reelected:(2)voters are retrospective,making eval- more modest.When governments believe that elec- uations on the policy outcomes they have recently ob- tions are approaching,however,they begin to spend served but not factoring in the future repercussions of more boldly in an effort to stimulate electoral support these policy choices;and(3)governments believe that This is the central hypothesis that we test below.1 increasing public expenditures will demonstrate com- Thinking of dissolutions as stochastic and public petence by stimulating growth,satiating the spending spending as a function of forecasted durations raises demands of their supporters,or otherwise.The impli- a follow-up question:What happens when the cabi- cation of these assumptions is that governments will net's prediction is wrong-either too generous or too S5.501g increase spending as elections approach to stimulate miserly-by some significant margin?To the former. electoral support.Setting aside,for the moment,the when a cabinet forecasts a duration that is too long and possibility of opportunistic early elections,if we were terminates earlier than expected,it should lose votes to assume that the timing of the election is fixed and In this case,the premature termination would preclude known,our expectation would be higher spending in the government from ramping up spending to stimu- (pre)election years and lower spending in postelection late support and,as a result,its electoral performance years,all else equal,just as those that have preceded us should suffer.This prediction is supported by the ex- have predicted (Alt and Lassen 2006;Rose 2006,etc.). tant literature on electoral timing and success.For ex- However,in the parliamentary democracies that we are ample,Smith(2003)presents compelling evidence that interested in here,the survival of the government un- til the next constitutionally mandated contest is by no 0 Astute readers realize that dissolution does not trigger immediate elections in all cases and,on occasion,a dissolved cabinet may remain in government as "caretaker"until elections can be held.We main- tain that caretaker cabinets are most often charged as custodians s For clarity,in our sample,nearly 75%of cabinets terminate over simply there to shepherd the country to their next cabinet.However. one month before their possible tenure expires and over 60%termi- this is not always the case as Laver and Shepsle(1994)point out,thus nate over six months before their possible tenure expires. we attempt to account for the time caretakers spend in office in our How voters are assumed to generate their expectations for future performance,whether rationally or adaptively,has been a subject of Previouseaders of the manuscript have asked why goverments debate in the PBC literature-we suggest Alt and Lassen (2006)and do not simply wait until the cabinet has dissolved and then spend Clark et al.(1998)for concise reviews.We believe that our assump- prodigiously until the election.Our response is that the gears of gov- tion of a retrospective voter (adaptive expectations)is a better match ernment grind slowly-meaning that governments are likely inca- to what we have learned from the economic voting lterature,not pable of revving up spending overnight-and the effects of spend- only about vote choices per se,but also the structure of economic ex- ing require some time to take effect and to be observed by the elec- pectations and retrospections and the relative weight of recent(quite torate.These factors,combined with constitutional limitations on the high)and distant (quite low)outcomes in determining them (e.g. amount of time between dissolutions and elections make forecasting Duch and Stevenson 2010,2011;Healy and Lenz 2014). and proactive adjustments essential 942
David Fortunato and Matt W. Loftis In reality, elections are not fixed in the overwhelming majority of parliamentary democracies and only a very small minority of elections could be described as strategically timed or “opportunistic” (Schleiter and Tavits 2016). Indeed, an accounting of over 608 European governments by Seki and Williams (2014) reveals that at least 62% of cabinets terminate in conditions that are not constitutionally mandated elections and are extraordinarily unlikely to be the product of strategic electoral timing—the resignation of the prime minister (for health reasons or otherwise), internal dissent, or loss of parliamentary support. In other words, well over half of all European governments violate the standard assumptions of the extant PBC literature. Government survivability in parliamentary democracies is inherently uncertain and, as such, we cannot presume the timing of elections to be fixed, nor can we assume the timing is purely a function of the cabinet’s tastes.8 Our framework relaxes these assumptions by building a model of public spending that incorporates the cabinet’s expectations for dissolution. More specifically, we construct a predicted duration for each cabinet in our data based upon its observable characteristics at formation and estimate the effect of the cabinet’s life expectancy on its spending choices. DURABILITY AND SPENDING As is common in the literature, we make the following assumptions: (1) incumbent governments wish to be reelected; (2) voters are retrospective, making evaluations on the policy outcomes they have recently observed but not factoring in the future repercussions of these policy choices;9 and (3) governments believe that increasing public expenditures will demonstrate competence by stimulating growth, satiating the spending demands of their supporters, or otherwise. The implication of these assumptions is that governments will increase spending as elections approach to stimulate electoral support. Setting aside, for the moment, the possibility of opportunistic early elections, if we were to assume that the timing of the election is fixed and known, our expectation would be higher spending in (pre)election years and lower spending in postelection years, all else equal, just as those that have preceded us have predicted (Alt and Lassen 2006; Rose 2006, etc.). However,in the parliamentary democracies that we are interested in here, the survival of the government until the next constitutionally mandated contest is by no 8 For clarity, in our sample, nearly 75% of cabinets terminate over one month before their possible tenure expires and over 60% terminate over six months before their possible tenure expires. 9 How voters are assumed to generate their expectations for future performance, whether rationally or adaptively, has been a subject of debate in the PBC literature—we suggest Alt and Lassen (2006) and Clark et al. (1998) for concise reviews. We believe that our assumption of a retrospective voter (adaptive expectations) is a better match to what we have learned from the economic voting literature, not only about vote choices per se, but also the structure of economic expectations and retrospections and the relative weight of recent (quite high) and distant (quite low) outcomes in determining them (e.g., Duch and Stevenson 2010, 2011; Healy and Lenz 2014). means certain and,in fact,it is the exception rather than the rule. We assume cabinet dissolution is stochastic and model government spending accordingly as a function of the cabinet’s electoral expectations—when it believes the next election will occur either as a result of expiration of the constitutional interrelation period (CIEP) or premature dissolution (from here on we use the words election and dissolution interchangeably).10 That is, we assume that governments form beliefs over their durability and grow public spending accordingly. If we believe that governments have a preference for fiscal discipline, all else equal, then this implies a negative relationship between expectations of cabinet durability and public spending. Cabinets should spend less when elections are believed to be distant and spend more when elections are believed to be proximate to stimulate electoral support without running burdensome deficits. Borrowing from Alt and Lassen (2006), a stylized representation of this expectation is given in the left pane of Figure 1 with the x-axis representing the cabinet’s life expectancy and the y-axis representing public spending. As the government’s expected dissolution point approaches (indicated by the 0 hash on the xaxis), it increases spending to engender electoral support. After the election, the government (whether or not the incumbent has returned) lowers spending and the cycle begins again. To reiterate: when governments believe that elections are distant, public spending is more modest. When governments believe that elections are approaching, however, they begin to spend more boldly in an effort to stimulate electoral support. This is the central hypothesis that we test below.11 Thinking of dissolutions as stochastic and public spending as a function of forecasted durations raises a follow-up question: What happens when the cabinet’s prediction is wrong—either too generous or too miserly—by some significant margin? To the former, when a cabinet forecasts a duration that is too long and terminates earlier than expected, it should lose votes. In this case, the premature termination would preclude the government from ramping up spending to stimulate support and, as a result, its electoral performance should suffer. This prediction is supported by the extant literature on electoral timing and success. For example, Smith (2003) presents compelling evidence that 10 Astute readers realize that dissolution does not trigger immediate elections in all cases and, on occasion, a dissolved cabinet may remain in government as “caretaker” until elections can be held. We maintain that caretaker cabinets are most often charged as custodians, simply there to shepherd the country to their next cabinet. However, this is not always the case as Laver and Shepsle (1994) point out, thus, we attempt to account for the time caretakers spend in office in our empirical model. 11 Previous readers of the manuscript have asked why governments do not simply wait until the cabinet has dissolved and then spend prodigiously until the election. Our response is that the gears of government grind slowly—meaning that governments are likely incapable of revving up spending overnight—and the effects of spending require some time to take effect and to be observed by the electorate. These factors, combined with constitutional limitations on the amount of time between dissolutions and elections make forecasting and proactive adjustments essential. 942 Downloaded from https://www.cambridge.org/core. Shanghai JiaoTong University, on 26 Oct 2018 at 03:53:05, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055418000436
Cabinet Durability and Fiscal Discipline FIGURE 1.Duration Expectations and Public Spending Predicted Relationship Between Duration Expectations and Spending Comparing Spending Under Accurate and Underestimated Durations estimated Early 0 Very Late Very Early Early 0 Late Very Late Expected Time to Dissolution Expected Time to Dissolution incumbents perform more poorly than expected in creasing spending (our focus here)or calling for early early elections.12 elections,or they may choose to remain in office with- To the latter,when the cabinet forecasts a duration out engaging in opportunistic behaviors and this choice that is too short and terminates later than expected is conditioned on exogenous economic shocks and the there is no impact on the electoral result,but there time remaining in the CIEP.!3 This presents potential should be an increase in the government's propensity hurdles,both systematic and stochastic in nature,that to run deficits.A stylized depiction of this expectation warrant discussion before moving on. is given in the right pane of Figure 1.When the cabi- One possibility is that governments increase spend- net's prediction of its duration is accurate,we should ing to stimulate popularity and call for opportunistic observe an increase in spending,an election,and then elections once estimated support reaches some critical a decrease in spending about the 0 point on the x-axis. level.Under this condition,we may observe a nega- This is shown by the lighter line.The darker line,on tive relationship between expected duration and public the other hand,shows the expectation for an underes- spending,just as we predict,albeit due to an alternative timate of the cabinet's durability.In this case,the gov- (though very closely related)mechanism,because ex- ernment increases spending in expectation of elections, pected durations are correlated with true durations.For but,when the cabinet proves more durable than antici- lack of more clever language,we can call this budget pated,it must continue to spend at the heightened rate cycling under complete electoral endogeneity,as op- until dissolution to maintain its electoral support.The posed to budget cycling under duration uncertainty-a longer these protracted periods of heightened spend- systematic behavior that may confound our ability to ing exceed the cabinet's expectations,the deeper they assess our arguments.Fortunately.theses mechanisms will push the state into deficit.This is the second hy- are empirically differentiable with the data on hand.If, pothesis we test-the longer a cabinet outlives its ex- as we argue,governments form expectations of their pected duration,the greater its deficit spending. durability and plan their spending accordingly,then ex- Before moving on to our design,it is important pected durations should provide more predictive power to note that cabinet dissolutions are not entirely for observed rates of spending.On the other hand,if stochastic-cabinets must terminate at the end of the elections are,on average,chosen opportunistically af- CIEP and may choose to terminate for strategic rea- ter governments have increased spending,then true sons(given that the institutional context allows)at any durations should provide more predictive power for time.The first issue is easily accounted for and we ex- observed rates of spending,because,in this case,spend- plain that below.The second issue requires a bit more ing and electoral timing are codetermined.To pre- contemplation.Recalling Kayser(2005),cabinets may view our empirical results,spending patterns are better choose to influence potential electoral results by in- 12 Schleiter and Tavits(2016)also present evidence(their Table 1) 13 To be clear,Kayser(2005,21)does not discuss spending in partic. ular,but a generalized and directly unobservable alteration to policy that incumbents suffer electoral losses in unforeseen early elections "that shifts resources from the future to the present."This distor- relative to regular elections. tionary policy can take many forms. 943
Cabinet Durability and Fiscal Discipline FIGURE 1. Duration Expectations and Public Spending Predicted Relationship Between Duration Expectations and Spending Expected Time to Dissolution Spending Very Early Early 0 Late Very Late Expected Dissolution Comparing Spending Under Accurate and Underestimated Durations Expected Time to Dissolution Spending Very Early Early 0 Late Very Late Accurate Estimate Underestimated incumbents perform more poorly than expected in early elections.12 To the latter, when the cabinet forecasts a duration that is too short and terminates later than expected, there is no impact on the electoral result, but there should be an increase in the government’s propensity to run deficits. A stylized depiction of this expectation is given in the right pane of Figure 1. When the cabinet’s prediction of its duration is accurate, we should observe an increase in spending, an election, and then a decrease in spending about the 0 point on the x-axis. This is shown by the lighter line. The darker line, on the other hand, shows the expectation for an underestimate of the cabinet’s durability. In this case, the government increases spending in expectation of elections, but, when the cabinet proves more durable than anticipated, it must continue to spend at the heightened rate until dissolution to maintain its electoral support. The longer these protracted periods of heightened spending exceed the cabinet’s expectations, the deeper they will push the state into deficit. This is the second hypothesis we test—the longer a cabinet outlives its expected duration, the greater its deficit spending. Before moving on to our design, it is important to note that cabinet dissolutions are not entirely stochastic—cabinets must terminate at the end of the CIEP and may choose to terminate for strategic reasons (given that the institutional context allows) at any time. The first issue is easily accounted for and we explain that below. The second issue requires a bit more contemplation. Recalling Kayser (2005), cabinets may choose to influence potential electoral results by in- 12 Schleiter and Tavits (2016) also present evidence (their Table 1) that incumbents suffer electoral losses in unforeseen early elections relative to regular elections. creasing spending (our focus here) or calling for early elections, or they may choose to remain in office without engaging in opportunistic behaviors and this choice is conditioned on exogenous economic shocks and the time remaining in the CIEP.13 This presents potential hurdles, both systematic and stochastic in nature, that warrant discussion before moving on. One possibility is that governments increase spending to stimulate popularity and call for opportunistic elections once estimated support reaches some critical level. Under this condition, we may observe a negative relationship between expected duration and public spending, just as we predict, albeit due to an alternative (though very closely related) mechanism, because expected durations are correlated with true durations.For lack of more clever language, we can call this budget cycling under complete electoral endogeneity, as opposed to budget cycling under duration uncertainty—a systematic behavior that may confound our ability to assess our arguments. Fortunately, theses mechanisms are empirically differentiable with the data on hand. If, as we argue, governments form expectations of their durability and plan their spending accordingly, then expected durations should provide more predictive power for observed rates of spending. On the other hand, if elections are, on average, chosen opportunistically after governments have increased spending, then true durations should provide more predictive power for observed rates of spending, because,in this case, spending and electoral timing are codetermined. To preview our empirical results, spending patterns are better 13 To be clear, Kayser (2005, 21) does not discuss spending in particular, but a generalized and directly unobservable alteration to policy “that shifts resources from the future to the present.” This distortionary policy can take many forms. 943 Downloaded from https://www.cambridge.org/core. Shanghai JiaoTong University, on 26 Oct 2018 at 03:53:05, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055418000436
David Fortunato and Matt W.Loftis explained by expected durations.We also add that,if empirical correlates of cabinet stability.Thus,to gen- cycling under electoral endogeneity was the norm,then erate our measure of a government's life expectancy past PBC research would not have failed to recover ev- which we will impute to the cabinet,we accept the col- idence of cycling behavior in these countries as often as lective wisdom of the discipline and derive our mea- it has. sure from the extant literature.More specifically,we A second possibility is that cabinets privileged by estimate the survival model described in Chiba,Mar- some exogenous shock creating a windfall of popular- tin,and Stevenson (2015),which accounts for poten- ity may call early elections without having to ramp up tial selection bias induced by strategic formations by spending in the manner we predict-a stochastic oc- jointly modeling formation and duration.Note that currence that may confound assessment of our the- as King et al.(1990)explain,this duration model cap- oretical argument.Of course,this second possibility tures "events"in its stochastic component(distributed would not produce our predicted relationship,rather, Weibull in this case).while including"attributes"as the this type of opportunistic behavior would bias against measured covariates in its systematic component.For recovering support for our hypothesis.And,because all cabinets in our data,we use the model estimates to our focus is the effect of cabinet durability on pub- predict the number of days the cabinet will last before lic spending,rather than the relationship among eco- dissolution. nomic inputs (e.g.,spending,inflation),economic out- Importantly,we do not pool the risks of dissolution puts(e.g.,growth,unemployment),and electoral timing and replacement.15 We make this choice for two rea- and performance,opportunistic elections of this type sons.First,the risk type that is theoretically salient is are stochastic nuisances rather than threats to design dissolution and,as such,we do not want replacement credibility.We also note that if the true process guiding terminations contributing to our durability estimates spending patterns is some combination of systematic Second,cabinets have no incentive to prepare for re- cycling under electoral endogeneity and stochastic op placement rather than dissolution.In the event of a portunism,then,again,true durations would provide a replacement,the incumbent loses its governing status better fit to our spending data vis-a-vis expected dura- and is consigned to opposition.Given what we have tions.We return to this issue and other potential con- learned about the collective memory of voters,when founders in a short section on robustness following our the next election arrives,it is not the displaced incum- empirical analysis bent that is the focus of competency evaluations,but its successor and any choices made by the displaced RESEARCH DESIGN incumbent are likely to be irrelevant (or nearly so)to the election outcome (Healy and Lenz 2014).16 Taken To test our hypotheses,we first develop a model of together,these factors imply that a cabinet's best strat- duration expectations for the cabinet.We assume that egy would be to ignore replacement risk when generat- cabinets take into account the observable characteris- ing its expectations for durability.Fortunately,the data 是 tics of their government and accordingly generate their allow us to bring evidence to bear on the question of expectations for its duration,with greater or lesser de- expectation formation under competing risks and we grees of certainty.That is,because governments cannot discuss this in the robustness section. reasonably be expected to foresee the precise timing of Our public spending analysis is conducted at the S5.501g "critical events"such as economic downturns,political country-year level.Therefore,to capture each cabinet's scandals,or abrupt fluctuations in public opinion,the expected remaining time in office when the budget is best information they have to generate their expecta- set,we subtract from the cabinet's total predicted life tions are the life cycles of governments past,the observ- the number of days the cabinet has already served at able characteristics of those governments,and the at- the time it presents its annual budget to the legisla- tributes of their own cabinet-a form of Muth's (1961) ture.This estimate of the cabinet's remaining life ex- classic rational expectations.14 pectancy is the covariate of interest in our models of The most obvious starting point for estimating these public spending(explained in detail below).We expect expectations is the rich political science literature on this to have a negative relationship to public spending the durability of governments discussed above.After in general-that a cabinet will spend more as its ex- the work of,for example,King et al.(1990),Laver and pected duration dwindles-and a negative relationship Shepsle (1998),Diermeier and Stevenson(2000),and to deficit spending-that a cabinet will spend less re- Chiba.Martin,and Stevenson(2015),there can be little sponsibly as its expected duration dwindles.Of course. 四 doubt that political scientists have amassed an impres- our measure of the cabinet's duration expectations is sive understanding of the theoretical foundations and estimated with error,and,as such,we take care to model this error structure. 14 For the purposes of research design,there is much to recommend estimating durations from the observable characteristics of the cabi- 1s In estimation,replacements are right censored. net at the time of formation.Most importantly,however,is that these 16 A third consideration would be that,in addition to being much L durability estimates are not endogenous to the changing political less common than dissolution terminations,replacement hazards are economic climate (e.g.,growth,scandal,militarized dispute,etc.)and effectively flat,indicating that they are the product of a much more are therefore free of potential "feedback effects,"where spending is stochastic process(Diermeier and Stevenson 1999).As such,the de- conditional upon on durability expectations,and durability expecta- gree to which cabinets are able to forecast relatively accurate expec tions are then updated conditional on the effects of spending.and tations of replacement terminations vis-a-vis dissolution would be s00n. impaired. 944
David Fortunato and Matt W. Loftis explained by expected durations. We also add that, if cycling under electoral endogeneity was the norm, then past PBC research would not have failed to recover evidence of cycling behavior in these countries as often as it has. A second possibility is that cabinets privileged by some exogenous shock creating a windfall of popularity may call early elections without having to ramp up spending in the manner we predict—a stochastic occurrence that may confound assessment of our theoretical argument. Of course, this second possibility would not produce our predicted relationship, rather, this type of opportunistic behavior would bias against recovering support for our hypothesis. And, because our focus is the effect of cabinet durability on public spending, rather than the relationship among economic inputs (e.g., spending, inflation), economic outputs (e.g., growth, unemployment), and electoral timing and performance, opportunistic elections of this type are stochastic nuisances rather than threats to design credibility.We also note that if the true process guiding spending patterns is some combination of systematic cycling under electoral endogeneity and stochastic opportunism, then, again, true durations would provide a better fit to our spending data vis-à-vis expected durations. We return to this issue and other potential confounders in a short section on robustness following our empirical analysis. RESEARCH DESIGN To test our hypotheses, we first develop a model of duration expectations for the cabinet. We assume that cabinets take into account the observable characteristics of their government and accordingly generate their expectations for its duration, with greater or lesser degrees of certainty. That is, because governments cannot reasonably be expected to foresee the precise timing of “critical events” such as economic downturns, political scandals, or abrupt fluctuations in public opinion, the best information they have to generate their expectations are the life cycles of governments past, the observable characteristics of those governments, and the attributes of their own cabinet—a form of Muth’s (1961) classic rational expectations.14 The most obvious starting point for estimating these expectations is the rich political science literature on the durability of governments discussed above. After the work of, for example, King et al. (1990), Laver and Shepsle (1998), Diermeier and Stevenson (2000), and Chiba,Martin, and Stevenson (2015), there can be little doubt that political scientists have amassed an impressive understanding of the theoretical foundations and 14 For the purposes of research design, there is much to recommend estimating durations from the observable characteristics of the cabinet at the time of formation.Most importantly, however, is that these durability estimates are not endogenous to the changing political economic climate (e.g., growth, scandal, militarized dispute, etc.) and are therefore free of potential “feedback effects,” where spending is conditional upon on durability expectations, and durability expectations are then updated conditional on the effects of spending, and so on. empirical correlates of cabinet stability. Thus, to generate our measure of a government’s life expectancy, which we will impute to the cabinet, we accept the collective wisdom of the discipline and derive our measure from the extant literature. More specifically, we estimate the survival model described in Chiba, Martin, and Stevenson (2015), which accounts for potential selection bias induced by strategic formations by jointly modeling formation and duration. Note that, as King et al. (1990) explain, this duration model captures “events” in its stochastic component (distributed Weibull in this case), while including “attributes” as the measured covariates in its systematic component. For all cabinets in our data, we use the model estimates to predict the number of days the cabinet will last before dissolution. Importantly, we do not pool the risks of dissolution and replacement.15 We make this choice for two reasons. First, the risk type that is theoretically salient is dissolution and, as such, we do not want replacement terminations contributing to our durability estimates. Second, cabinets have no incentive to prepare for replacement rather than dissolution. In the event of a replacement, the incumbent loses its governing status and is consigned to opposition. Given what we have learned about the collective memory of voters, when the next election arrives, it is not the displaced incumbent that is the focus of competency evaluations, but its successor and any choices made by the displaced incumbent are likely to be irrelevant (or nearly so) to the election outcome (Healy and Lenz 2014).16 Taken together, these factors imply that a cabinet’s best strategy would be to ignore replacement risk when generating its expectations for durability. Fortunately, the data allow us to bring evidence to bear on the question of expectation formation under competing risks and we discuss this in the robustness section. Our public spending analysis is conducted at the country-year level. Therefore, to capture each cabinet’s expected remaining time in office when the budget is set, we subtract from the cabinet’s total predicted life the number of days the cabinet has already served at the time it presents its annual budget to the legislature. This estimate of the cabinet’s remaining life expectancy is the covariate of interest in our models of public spending (explained in detail below).We expect this to have a negative relationship to public spending in general—that a cabinet will spend more as its expected duration dwindles—and a negative relationship to deficit spending—that a cabinet will spend less responsibly as its expected duration dwindles. Of course, our measure of the cabinet’s duration expectations is estimated with error, and, as such, we take care to model this error structure. 15 In estimation, replacements are right censored. 16 A third consideration would be that, in addition to being much less common than dissolution terminations, replacement hazards are effectively flat, indicating that they are the product of a much more stochastic process (Diermeier and Stevenson 1999). As such, the degree to which cabinets are able to forecast relatively accurate expectations of replacement terminations vis-à-vis dissolution would be impaired. 944 Downloaded from https://www.cambridge.org/core. Shanghai JiaoTong University, on 26 Oct 2018 at 03:53:05, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055418000436
Cabinet Durability and Fiscal Discipline Data and Model Construction government can reasonably expect to remain in office For our main analyses,we gather data on several through the CIEP without holding elections.21 By estimating a distribution of expected durations decades of budgeting in 15 European democracies that for each of our sample cabinets,we have a straightfor- allow for parliamentary dissolutions-the same data ward way of accounting for the uncertainty of these analyzed by Bawn and Rosenbluth(2006)and Martin predictions.This is important for both empirical and and Vanberg(2013).17 Our dependent variables are the theoretical reasons.Empirically.this variable is,after OECD calendar-year estimates of central government all,an estimate with an associated error structure and spending as a percentage of GDP and this spending fig- ignoring this error may bias our estimates of the rela- ure minus central government receipts as a percentage tionships of interest,and therefore bias our substantive of GDP,where greater values indicate greater deficits. conclusions.Theoretically,expectations rarely take the Budgets in our sample are typically submitted in the form of a point when they are generated by individu- latter half of the year for spending in the following cal- als and are explicitly distributions when they are gen- endar year.Most submission dates fall between August erated by a collective,whether it is a system of firms and October of the calendar year preceding the budge a betting market,or the ministers composing a cabi- year,though dates as early as July and as late as april net.If we assume that rational expectations are dis- of the budget year appear in the data.8 The data also tributions that are,in the aggregate,centered on the include information on several political economic char most probable (or,most expected,given the state of the acteristics salient to budget-making,which we discuss world)outcome as Muth (1961)theorized and others below. have found empirically,then modeling these distribu- The explanatory variable of interest is the cabinet's tions,rather than merely their central tendency,is crit- predicted duration-the number of days it expects to ical to hypothesis testing. remain in office-at the time the budget was submit- We model these distributions by estimating our ted.We derive the measure by first reestimating Chiba spending and deficit models 1,000 times-once for 4号元 Martin,and Stevenson's (2015)model of government each prediction of cabinet survival.Thus,for each it- duration,which jointly estimates cabinet formation and survival.9 To account for uncertainty in this esti- eration,we impute an expected remaining duration for mate,we employ a nonparametric bootstrap.20 At each each cabinet-year in our data using a single set of boot- strapped survival predictions,estimate the spending of the 1.000 bootstrap iterations,we randomly resam- and deficit models,and record the results.This yields ple the data,with replacement,from our set of 432 cab 1,000 regression results for the main models which we inets and reestimate the model.We then use the model summarize and interpret below,but we first discuss the estimates to predict the duration for each cabinet in our construction and estimation of the spending models. data,record the predictions,and reiterate,generating a Alongside our focal variable (predicted duration), distribution of 1.000 predicted survival times for each we include a set of political economic control vari- cabinet. ables borrowed from Bawn and Rosenbluth(2006)and For each cabinet-budget year in our spending data Martin and Vanberg (2013)to account for potential we alter these distributions in two ways:(1)we subtract confounders to our relationship of interest while keep- the number of days the cabinet has served at the time ing our substantive results comparable to previous re- of budget submission and(2)we trim any expected du- search.The measurement of these covariates and the rations that exceed the CIEP back to the expiration of reasons they are included in the models are described the CIEP.Predicted durations exceeding the CIEP are in great detail by Bawn and Rosenbluth and Martin fairly rare,but must nonetheless be accounted for-no and Vanberg,so we do not reiterate that information here.We provide,instead,a more general discussion of 17 Sample countries include Austria(1971-2006).Belgium (1971- the rationale motivating inclusion of these covariates 2007.Denmark(1972-2009).Finland(1971-2007),France(1979- 2009),Germany(1971-2009),Greece(1979-2004),Ireland(1971- which break down into three groups:variables captur- 2009).Italy (1971-2008).Luxembourg (1991-2004).the Nether- ing the government's taste for public spending;vari- lands(1971-2006),Portugal(1978-2009),Spain(1980-2009),Sweden ables accounting for the state's revenue supply and en- (1971-2009),and the United Kingdom (1971-2009).Notably,Nor- titlement burden;and variables indicating institutional way.which is included in the Bawn and Rosenbluth(2006)sample.is constraints on spending depth and responsibility omitted here because its elections are fixed. 18 Budget dates were coded from OECD First,consider spending tastes,or the breadth of Journal on Bud- geting country issues (http://www.oecd.org/governance/budgeting spending demands within the cabinet.There is broad 四 oecdjournalonbudgeting.htm).Each reports the deadline by which theoretical consensus in the literature is that left- the government must present the annual budget to parliament,typi- leaning parties prefer to spend more than right-leaning cally between August and October of the preceding year.For coun parties and we account for this by including Pow- tries not covered by the Journal on Budgeting,we refer to the respec- tive constitution or applicable legal framework.In cases in which the ell's (2000)measure of the cabinet's ideological po- budget deadline was unclear or fell within two months of a change sitioning:the mean,seat-weighted,left-right stance of of government,the exact date on which the budget was presented to parliament was located in the respective parliamentary archives, ensuring that all budgets are attributed to the correct cabinets. The constitutional interelection period is included in our cabinet 19 This is a conditional logit model of the government selection stage. duration model and is a powerful duration predictor.We note,how- joined to a Weibull survival by means of a Gaussian copula function ever,that model estimates using durations that are not trimmed to See Chiba,Martin,and Stevenson(2015)for details. CIEP also support our central predictions. 20 Bootstrapped model estimates are available in the Appendix. 22 But see Clark(2009)for opposing evidence. 945
Cabinet Durability and Fiscal Discipline Data and Model Construction For our main analyses, we gather data on several decades of budgeting in 15 European democracies that allow for parliamentary dissolutions—the same data analyzed by Bawn and Rosenbluth (2006) and Martin and Vanberg (2013).17 Our dependent variables are the OECD calendar-year estimates of central government spending as a percentage of GDP and this spending figure minus central government receipts as a percentage of GDP, where greater values indicate greater deficits. Budgets in our sample are typically submitted in the latter half of the year for spending in the following calendar year.Most submission dates fall between August and October of the calendar year preceding the budget year, though dates as early as July and as late as April of the budget year appear in the data.18 The data also include information on several political economic characteristics salient to budget-making, which we discuss below. The explanatory variable of interest is the cabinet’s predicted duration—the number of days it expects to remain in office—at the time the budget was submitted.We derive the measure by first reestimating Chiba, Martin, and Stevenson’s (2015) model of government duration, which jointly estimates cabinet formation and survival.19 To account for uncertainty in this estimate, we employ a nonparametric bootstrap.20 At each of the 1,000 bootstrap iterations, we randomly resample the data, with replacement, from our set of 432 cabinets and reestimate the model.We then use the model estimates to predict the duration for each cabinet in our data, record the predictions, and reiterate, generating a distribution of 1,000 predicted survival times for each cabinet. For each cabinet-budget year in our spending data, we alter these distributions in two ways: (1) we subtract the number of days the cabinet has served at the time of budget submission and (2) we trim any expected durations that exceed the CIEP back to the expiration of the CIEP. Predicted durations exceeding the CIEP are fairly rare, but must nonetheless be accounted for—no 17 Sample countries include Austria (1971–2006), Belgium (1971– 2007), Denmark (1972–2009), Finland (1971–2007), France (1979– 2009), Germany (1971–2009), Greece (1979–2004), Ireland (1971– 2009), Italy (1971–2008), Luxembourg (1991–2004), the Netherlands (1971–2006),Portugal (1978–2009), Spain (1980–2009), Sweden (1971–2009), and the United Kingdom (1971–2009). Notably, Norway, which is included in the Bawn and Rosenbluth (2006) sample, is omitted here because its elections are fixed. 18 Budget dates were coded from OECD Journal on Budgeting country issues (http://www.oecd.org/governance/budgeting/ oecdjournalonbudgeting.htm). Each reports the deadline by which the government must present the annual budget to parliament, typically between August and October of the preceding year. For countries not covered by the Journal on Budgeting, we refer to the respective constitution or applicable legal framework. In cases in which the budget deadline was unclear or fell within two months of a change of government, the exact date on which the budget was presented to parliament was located in the respective parliamentary archives, ensuring that all budgets are attributed to the correct cabinets. 19 This is a conditional logit model of the government selection stage, joined to a Weibull survival by means of a Gaussian copula function. See Chiba, Martin, and Stevenson (2015) for details. 20 Bootstrapped model estimates are available in the Appendix. government can reasonably expect to remain in office through the CIEP without holding elections.21 By estimating a distribution of expected durations for each of our sample cabinets, we have a straightforward way of accounting for the uncertainty of these predictions. This is important for both empirical and theoretical reasons. Empirically, this variable is, after all, an estimate with an associated error structure and ignoring this error may bias our estimates of the relationships of interest, and therefore bias our substantive conclusions. Theoretically, expectations rarely take the form of a point when they are generated by individuals and are explicitly distributions when they are generated by a collective, whether it is a system of firms, a betting market, or the ministers composing a cabinet. If we assume that rational expectations are distributions that are, in the aggregate, centered on the most probable (or,most expected, given the state of the world) outcome as Muth (1961) theorized and others have found empirically, then modeling these distributions, rather than merely their central tendency, is critical to hypothesis testing. We model these distributions by estimating our spending and deficit models 1,000 times—once for each prediction of cabinet survival. Thus, for each iteration, we impute an expected remaining duration for each cabinet-year in our data using a single set of bootstrapped survival predictions, estimate the spending and deficit models, and record the results. This yields 1,000 regression results for the main models which we summarize and interpret below, but we first discuss the construction and estimation of the spending models. Alongside our focal variable (predicted duration), we include a set of political economic control variables borrowed from Bawn and Rosenbluth (2006) and Martin and Vanberg (2013) to account for potential confounders to our relationship of interest while keeping our substantive results comparable to previous research. The measurement of these covariates and the reasons they are included in the models are described in great detail by Bawn and Rosenbluth and Martin and Vanberg, so we do not reiterate that information here. We provide, instead, a more general discussion of the rationale motivating inclusion of these covariates which break down into three groups: variables capturing the government’s taste for public spending; variables accounting for the state’s revenue supply and entitlement burden; and variables indicating institutional constraints on spending depth and responsibility. First, consider spending tastes, or the breadth of spending demands within the cabinet. There is broad theoretical consensus in the literature is that leftleaning parties prefer to spend more than right-leaning parties22 and we account for this by including Powell’s (2000) measure of the cabinet’s ideological positioning: the mean, seat-weighted, left-right stance of 21 The constitutional interelection period is included in our cabinet duration model and is a powerful duration predictor. We note, however, that model estimates using durations that are not trimmed to CIEP also support our central predictions. 22 But see Clark (2009) for opposing evidence. 945 Downloaded from https://www.cambridge.org/core. Shanghai JiaoTong University, on 26 Oct 2018 at 03:53:05, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055418000436
David Fortunato and Matt W.Loftis each member of the cabinet,where greater values indi- than a point,we cycle through its 1.000 estimated val- cate a more right-leaning government.23 Following the ues,imputing each into our spending and deficit models above discussion on the common pool resource prob. in turn,estimating,and recording the results.We also lem in budgeting-as the diversity of spending priori- generate error estimates on our cabinet ideology mea- ties grows,the cabinet's temptation to spend to please sure following Lowe et al.(2011)and model these in its supporters increases-we include the number of the same fashion parties in the cabinet.We also include the effective The results of our first model,public spending,are number of legislative parties(Laakso and Taagepera summarized in Table 1.25 For our covariate of inter- 1979)to account for the possibility that diverse spend- est,expected duration,there is a statistically signifi- ing priorities outside the cabinet may coax budgets up- cant negative parameter estimate,indicating,as we pre- ward in a similar fashion. dicted,that decreasing expected duration will increase Our second set of controls are meant to account for a the cabinet's level of public spending.Further,each of state's ability or need to grow its spending obligations. our control variables,when reaching statistical signif- That is,does the state in question have the resources icance,are signed in the sensible direction and com- needed to increase spending responsibly,or,are there port with previous research on spending(e.g.,Bawn characteristics of the state that should systematically and Rosenbluth 2006:Martin and Vanberg 2013).giv- increase its spending obligations?These variables in- ing us confidence that our model is properly specified. clude:the overall level of economic productivity(mea- To better illustrate the predicted effect of expected sured as per capita GDP),a state's integration into the duration on public spending,Figure 2 plots the substan- 元 modern trade economy(called"trade openness"in the tive effect of a reduction in expected cabinet duration tables below;the export/import fraction of GDP),its from three years to one year,aggregated across all of unemployment rate,and the percentage of likely non- our 1,000 models.Each light density in Figure 2 plots productive population-those under 15 years of age the distribution of predicted changes in spending as a and those 65 and over (called the "dependency ratio"). percentage of GDP resulting from this reduction in the Finally,we include two variables meant to cap- expected durability of the cabinet from a single boot- ture domestic and supranational spending constraints. strap iteration.Thus,the shape of each light density il- The first is Martin and Vanberg's (2013)"budgetary lustrates the estimation uncertainty in one of our 1.000 constraint index,"a summary of formal rules that models and the light vertical lines mark the fifth per- "[c]onstrain the ability of parties to push for spending, centile of each distribution (our criterion for statistical and,"generate incentives for parties to oppose spend- significance).The thicker,darker lines give the global ing demands by their partners"(p.956).This variable density and fifth percentile over all bootstrap iterations. is bounded between 0 and 1 and is interacted with the Taken together,the figure shows that,not only is our number of parties in the cabinet.The second is a binary criterion for statistical significance met in virtually all variable indicating that the budget was submitted af- bootstrapped models,but also that there is very little ter the adoption of the Maastricht Treaty,which placed variation in this result across the 1,000 bootstrapped limits on the total debt a member state could carry,as models. well as the size of the deficit a state could generate in More substantively,on average,the decrease from any given year.Interested readers may see summary three years to one year of expected duration (about a S5.501g statistics for all variables in the appendix. 1.5 standard deviation change)increases public spend- With variables in hand,we now turn to estimation. ing by 0.26%of GDP.This is a very large spending in- We are analyzing panel data with substantial cross- crease.Using 2010 GDP and spending figures in US sectional variation,but also a great deal of autocor- dollars,we can get a better sense of how salient this relation within units.Following Bawn and Rosenbluth effect is:for Denmark(GDP $320 billion)the increase (2006)and Martin and Vanberg (2013)we estimate would be roughly $844 million,for the Netherlands an autoregressive distributed lag model (ADL),in- (GDP $836 billion)the increase would be over $2.2 cluding(one year)lags of both the dependent vari- billion,and for Germany in the same year(GDP $3.4 ables and independent variables as well as concurrent realizations of the economic variables and estimate panel-corrected standard errors.This is in keeping with that the VIF on expected duration is about 4.3,which is well under Philips's(2016)conclusion that modeling data dynam- the typical level of concern(10). We have summarized the 1,000 spending(and deficit)models in ics is vital in the analysis of public spending,as ignor- a familiar tabular format for the sake of clarity.We note,however, ing the autoregressive properties of spending patterns that these models should technically be assessed individually since 四 can lead to inflated estimates of cycling behavior.24 As parameter point estimates and standard errors from regressions us ing predictions from different bootstrap iterations of the cabinet sur- our focal explanatory variable is a distribution.rather vival model are not fully comparable-even though the substantive effects we generate from them are.We can make fully reliable com- parisons using so-called "pivotal statistics"(e.g.,z-scores)to draw 23 These positions are derived from the Comparative Manifestos conclusions about statistical significance of effect parameters across Project data following Fortunato,Martin,and Vanberg(2018)and the 1,000 spending or deficit models.Statistics are considered pivota nousreviewer correety points out that ADL models if their sampling distribution does not depend on unknown parame- ters,making them a good choice for comparing across models as we particularly those with lagged and contemporaneous values of co- do (Shao 2003).The results of this more appropriate comparison lead variates,can create multicollinearity and this is certainly the case with to exactly the same conclusions but make for a potentially confusing our model.However,the construction does not induce collinearity presentation,therefore we have included the appropriate graphic in for the variable of interest-a variance inflation factor test reveals Appendix Figure A.3. 946
David Fortunato and Matt W. Loftis each member of the cabinet, where greater values indicate a more right-leaning government.23 Following the above discussion on the common pool resource problem in budgeting—as the diversity of spending priorities grows, the cabinet’s temptation to spend to please its supporters increases—we include the number of parties in the cabinet. We also include the effective number of legislative parties (Laakso and Taagepera 1979) to account for the possibility that diverse spending priorities outside the cabinet may coax budgets upward in a similar fashion. Our second set of controls are meant to account for a state’s ability or need to grow its spending obligations. That is, does the state in question have the resources needed to increase spending responsibly, or, are there characteristics of the state that should systematically increase its spending obligations? These variables include: the overall level of economic productivity (measured as per capita GDP), a state’s integration into the modern trade economy (called “trade openness” in the tables below; the export/import fraction of GDP), its unemployment rate, and the percentage of likely nonproductive population—those under 15 years of age and those 65 and over (called the “dependency ratio”). Finally, we include two variables meant to capture domestic and supranational spending constraints. The first is Martin and Vanberg’s (2013) “budgetary constraint index,” a summary of formal rules that “[c]onstrain the ability of parties to push for spending,” and, “generate incentives for parties to oppose spending demands by their partners” (p. 956). This variable is bounded between 0 and 1 and is interacted with the number of parties in the cabinet. The second is a binary variable indicating that the budget was submitted after the adoption of the Maastricht Treaty, which placed limits on the total debt a member state could carry, as well as the size of the deficit a state could generate in any given year. Interested readers may see summary statistics for all variables in the appendix. With variables in hand, we now turn to estimation. We are analyzing panel data with substantial crosssectional variation, but also a great deal of autocorrelation within units. Following Bawn and Rosenbluth (2006) and Martin and Vanberg (2013) we estimate an autoregressive distributed lag model (ADL), including (one year) lags of both the dependent variables and independent variables as well as concurrent realizations of the economic variables and estimate panel-corrected standard errors. This is in keeping with Philips’s (2016) conclusion that modeling data dynamics is vital in the analysis of public spending, as ignoring the autoregressive properties of spending patterns can lead to inflated estimates of cycling behavior.24 As our focal explanatory variable is a distribution, rather 23 These positions are derived from the Comparative Manifestos Project data following Fortunato, Martin, and Vanberg (2018) and others. 24 An anonymous reviewer correctly points out that ADL models, particularly those with lagged and contemporaneous values of covariates, can create multicollinearity and this is certainly the case with our model. However, the construction does not induce collinearity for the variable of interest—a variance inflation factor test reveals than a point, we cycle through its 1,000 estimated values,imputing each into our spending and deficit models in turn, estimating, and recording the results. We also generate error estimates on our cabinet ideology measure following Lowe et al. (2011) and model these in the same fashion. The results of our first model, public spending, are summarized in Table 1. 25 For our covariate of interest, expected duration, there is a statistically significant negative parameter estimate,indicating, as we predicted, that decreasing expected duration will increase the cabinet’s level of public spending. Further, each of our control variables, when reaching statistical significance, are signed in the sensible direction and comport with previous research on spending (e.g., Bawn and Rosenbluth 2006; Martin and Vanberg 2013), giving us confidence that our model is properly specified. To better illustrate the predicted effect of expected duration on public spending,Figure 2 plots the substantive effect of a reduction in expected cabinet duration from three years to one year, aggregated across all of our 1,000 models. Each light density in Figure 2 plots the distribution of predicted changes in spending as a percentage of GDP resulting from this reduction in the expected durability of the cabinet from a single bootstrap iteration. Thus, the shape of each light density illustrates the estimation uncertainty in one of our 1,000 models and the light vertical lines mark the fifth percentile of each distribution (our criterion for statistical significance). The thicker, darker lines give the global density and fifth percentile over all bootstrap iterations. Taken together, the figure shows that, not only is our criterion for statistical significance met in virtually all bootstrapped models, but also that there is very little variation in this result across the 1,000 bootstrapped models. More substantively, on average, the decrease from three years to one year of expected duration (about a 1.5 standard deviation change) increases public spending by 0.26% of GDP. This is a very large spending increase. Using 2010 GDP and spending figures in US dollars, we can get a better sense of how salient this effect is: for Denmark (GDP $320 billion) the increase would be roughly $844 million, for the Netherlands (GDP $836 billion) the increase would be over $2.2 billion, and for Germany in the same year (GDP $3.4 that the VIF on expected duration is about 4.3, which is well under the typical level of concern (10). 25 We have summarized the 1,000 spending (and deficit) models in a familiar tabular format for the sake of clarity. We note, however, that these models should technically be assessed individually since parameter point estimates and standard errors from regressions using predictions from different bootstrap iterations of the cabinet survival model are not fully comparable—even though the substantive effects we generate from them are. We can make fully reliable comparisons using so-called “pivotal statistics” (e.g., z-scores) to draw conclusions about statistical significance of effect parameters across the 1,000 spending or deficit models. Statistics are considered pivotal if their sampling distribution does not depend on unknown parameters, making them a good choice for comparing across models as we do (Shao 2003).The results of this more appropriate comparison lead to exactly the same conclusions but make for a potentially confusing presentation, therefore we have included the appropriate graphic in Appendix Figure A.3. 946 Downloaded from https://www.cambridge.org/core. Shanghai JiaoTong University, on 26 Oct 2018 at 03:53:05, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055418000436
Cabinet Durability and Fiscal Discipline TABLE 1.Aggregated Results from Bootstrapped Model of Spending as Percent of GDP Pooled Model Fixed Effects Variable Mean SD p Mean SD p Expected Duration -0.0003 (0.0001) 0.03 -0.0004 0.0002) 0.01 Parties in Government 0.2435 (0.1215) 0.02 0.3443 (0.1760) 0.03 ENP 0.0353 (0.0745) 0.32 -0.1563 (0.1127) 0.08 Caretaker Time 0.8323 (0.7833) 0.14 0.0399 (0.9191) 0.48 GDP per Capita 1.4593 (0.1805) 0.00 1.4814 (0.1848) 0.00 Unemployment Rate -0.4262 (0.0776) 0.00 0.4154 (0.0778) 0.00 Lagged Dependency Ratio 0.1136 (0.3364) 0.37 0.2072 (0.3373) 0.27 Trade Openness 0.0194 (0.0177) 0.14 0.0165 (0.0184) 0.19 Maastricht Era -0.4691 (0.2568) 0.03 -0.2645 0.3440) 0.22 Government Ideology -0.1133 (0.0793) 0.08 _0.0274 (0.0879) 0.38 Budgetary Constraint Index(BCI) 0.7499 (0.4616) 0.05 1.1879 (0.7405) 0.06 Parties in Government x BCI _0.4466 0.2139 0.02 -0.6252 (0.2871) 0.01 Spending 0.9295 0.0112) 0.00 0.8931 (0.0214) 0.00 GDP per Capita -1.4092 (0.1766) 0.00 -1.4388 (0.1883) 0.00 Unemployment Rate 0.3694 (0.0759) 0.00 0.3799 (0.0774) 0.00 Concurrent Dependency Ratio 0.0519 (0.3339) 0.44 0.1740 (0.3379) 0.30 Trade Openness -0.0218 (0.0175 0.11 0.0250 (0.0180) 0.08 Intercept 1.4287 (1.7487) 0.21 4号元 N 488 488 0.9626 0.9635 'asn p=directional certainty,fixed effects not shown trillion)the increase would be just shy of $9 billion predicted spending as the lagged spending value.As To contextualize these figures,this increase equates the figure shows,persistent cabinet instability of this to roughly 11.5%,16.5%,and 176%of the unemploy- magnitude can substantially increase spending over the ment cash transfers made in these countries,or 18.9%. long term. 是 19.7%,and 19.5%of defense spending in these coun- We now move on to our deficit models,which are tries,respectively.These effects are quite large and we estimated and presented in the same fashion as above are quite certain of them,indeed,only 1 in 1,000 models in Table 2.As with our spending model,our covari- yields a certainty estimate that does not meet the p< ate of interest,expected cabinet duration,is negative 0.05 criterion and fewer than 1%of all posterior draws and clearly different from zero,indicating that as the are greater than 0.This is very strong support for our cabinet's expected time in office draws to a close it first hypothesis:cabinets spend more as their expected begins to spend less responsibly-i.e..running ever- time in office dwindles. higher deficits.Further,as before,the control variables Of course,the effects of durability should be larger with robust estimates are all signed in the direction that and much longer lasting than this one-time increase. we would expect,making us confident in the model however.Budgets tend to be remarkably sticky.As specification.We also note here that there are really such,small increases made here and there have a ten- three ways to estimate this model:using only the ex- dency of becoming effectively permanent.Following pected remaining duration,folding that expected dura- Williams and Whitten (2012),we illustrate the com- tion into a binary variable,indicating that the cabinet pounding nature of cabinet fragility in Figure 3 where has outlived its expectations(duration <0),or estimat- we plot the public spending of Austria under two ide- ing an implied interaction of the duration measure and alized scenarios:one in which Austria always forms the indicator.We present the results of the first method four-year cabinets (dark triangles)and one in which it in the main text to match the previous analysis,how- always forms two-year cabinets (light circles).To gen- ever all three produce very similar results and the re- erate the values,we use the parameter estimates sum- maining two models are given in the Appendix. marized in Table 1 to predict Austrian spending lev- As predicted,expected duration is negative and the els from 1985 to 2005.using its observed covariate val- estimate is strongly significant (p <0.01).As above. ues over that period,with the exception of expected we interpret these results graphically by predicting the durability and lagged spending.For one case,we count change in deficit size as a function of a change in ex- down expected duration from four years to one year pected cabinet duration(using the fixed effects model and repeat;for the second case,we count down from results,once again).The difference here is that we two years to one year and repeat.Also,for each year change expected duration from one year to-1 year, (after the first)we use the mean of the previous year's indicating that the government has outlasted its life 947
Cabinet Durability and Fiscal Discipline TABLE 1. Aggregated Results from Bootstrapped Model of Spending as Percent of GDP Pooled Model Fixed Effects Variable Mean SD p Mean SD p Lagged Expected Duration –0.0003 (0.0001) 0.03 –0.0004 (0.0002) 0.01 Parties in Government 0.2435 (0.1215) 0.02 0.3443 (0.1760) 0.03 ENP 0.0353 (0.0745) 0.32 –0.1563 (0.1127) 0.08 Caretaker Time 0.8323 (0.7833) 0.14 –0.0399 (0.9191) 0.48 GDP per Capita 1.4593 (0.1805) 0.00 1.4814 (0.1848) 0.00 Unemployment Rate –0.4262 (0.0776) 0.00 –0.4154 (0.0778) 0.00 Dependency Ratio 0.1136 (0.3364) 0.37 0.2072 (0.3373) 0.27 Trade Openness 0.0194 (0.0177) 0.14 0.0165 (0.0184) 0.19 Maastricht Era –0.4691 (0.2568) 0.03 –0.2645 (0.3440) 0.22 Government Ideology –0.1133 (0.0793) 0.08 –0.0274 (0.0879) 0.38 Budgetary Constraint Index (BCI) 0.7499 (0.4616) 0.05 1.1879 (0.7405) 0.06 Parties in Government × BCI –0.4466 (0.2139) 0.02 –0.6252 (0.2871) 0.01 Spending 0.9295 (0.0112) 0.00 0.8931 (0.0214) 0.00 Concurrent GDP per Capita –1.4092 (0.1766) 0.00 –1.4388 (0.1883) 0.00 Unemployment Rate 0.3694 (0.0759) 0.00 0.3799 (0.0774) 0.00 Dependency Ratio –0.0519 (0.3339) 0.44 –0.1740 (0.3379) 0.30 Trade Openness –0.0218 (0.0175) 0.11 –0.0250 (0.0180) 0.08 Intercept 1.4287 (1.7487) 0.21 N 488 488 R2 0.9626 0.9635 p = directional certainty, fixed effects not shown trillion) the increase would be just shy of $9 billion. To contextualize these figures, this increase equates to roughly 11.5%, 16.5%, and 17.6% of the unemployment cash transfers made in these countries, or 18.9%, 19.7%, and 19.5% of defense spending in these countries, respectively. These effects are quite large and we are quite certain of them,indeed, only 1 in 1,000 models yields a certainty estimate that does not meet the p < 0.05 criterion and fewer than 1% of all posterior draws are greater than 0. This is very strong support for our first hypothesis: cabinets spend more as their expected time in office dwindles. Of course, the effects of durability should be larger and much longer lasting than this one-time increase, however. Budgets tend to be remarkably sticky. As such, small increases made here and there have a tendency of becoming effectively permanent. Following Williams and Whitten (2012), we illustrate the compounding nature of cabinet fragility in Figure 3 where we plot the public spending of Austria under two idealized scenarios: one in which Austria always forms four-year cabinets (dark triangles) and one in which it always forms two-year cabinets (light circles). To generate the values, we use the parameter estimates summarized in Table 1 to predict Austrian spending levels from 1985 to 2005, using its observed covariate values over that period, with the exception of expected durability and lagged spending. For one case, we count down expected duration from four years to one year and repeat; for the second case, we count down from two years to one year and repeat. Also, for each year (after the first) we use the mean of the previous year’s predicted spending as the lagged spending value. As the figure shows, persistent cabinet instability of this magnitude can substantially increase spending over the long term. We now move on to our deficit models, which are estimated and presented in the same fashion as above in Table 2. As with our spending model, our covariate of interest, expected cabinet duration, is negative and clearly different from zero, indicating that as the cabinet’s expected time in office draws to a close it begins to spend less responsibly—i.e., running everhigher deficits. Further, as before, the control variables with robust estimates are all signed in the direction that we would expect, making us confident in the model specification. We also note here that there are really three ways to estimate this model: using only the expected remaining duration, folding that expected duration into a binary variable, indicating that the cabinet has outlived its expectations (duration < 0), or estimating an implied interaction of the duration measure and the indicator.We present the results of the first method in the main text to match the previous analysis, however all three produce very similar results and the remaining two models are given in the Appendix. As predicted, expected duration is negative and the estimate is strongly significant (p < 0.01). As above, we interpret these results graphically by predicting the change in deficit size as a function of a change in expected cabinet duration (using the fixed effects model results, once again). The difference here is that we change expected duration from one year to –1 year, indicating that the government has outlasted its life 947 Downloaded from https://www.cambridge.org/core. Shanghai JiaoTong University, on 26 Oct 2018 at 03:53:05, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055418000436
David Fortunato and Matt W.Loftis FIGURE 2.The Effect of Expected Duration on Spending Effect of Reducing Expected Duration from 3 Years to 1 Year Criterion met 0.999 Overall 5th percentile 0.079 Mean effect=0.26%GDP -0.5 0.0 0.5 1.0 Change in Public Spending(%GDP) expectancy by a year (there are several such cases in pirical evidence suggest that cabinets forecast their our sample).These results are given in Figure 4,where durability,plan their spending to crescendo as fore- the densities illustrate the entire distribution of pre- casted dissolution approaches,and,if they prove more dicted deficit changes and the vertical lines illustrate durable than expected,continue to spend lavishly to the fifth percentile of each distribution.First,the ef- maintain support until dissolution.This suggests that fects,as before,are very large.The change from an ex- incumbents prefer to continue to serve their present pected one year of remaining time in office to outliving term,running the country ever higher into deficit,than expectations by one year results in an average 0.422% to call early elections.At the least,this evidence sug- increase to the deficit.This is a substantial and norma- gests that,on average,incumbents are more averse tively significant increase,not only because increases to to the uncertainty of elections than they are to in- the present deficit are so large,but also because the true curring the wrath of voters for irresponsible spend- long term cost of this deficit increase is compounded by ing.A broader interpretation of this finding is that the interest payments made over the debt clearing win- incumbents are more averse to electoral uncertainty dow.Notice also that we are extremely confident in the than most current characterizations of the literature direction of the effect-each model yields an estimated may imply-that we have perhaps been too cavalier certainty of p<0.05. in our assumptions of an incumbent's willingness to It is worth taking a moment to consider how this call for new elections.Of course,there is good reason MM//:sdny finding informs our understanding of how incumbents for this.Though some dissolution models had built in value their current time in office as opposed to their electoral uncertainty (e.g.,Kayser 2005),a simplifying electoral prospects.Our theoretical arguments and em- assumption of many more formal models of dissolution 948
David Fortunato and Matt W. Loftis FIGURE 2. The Effect of Expected Duration on Spending Effect of Reducing Expected Duration from 3 Years to 1 Year Change in Public Spending (%GDP) Density of Effects −0.5 0.0 0.5 1.0 0 Max Effect of Reducing Expected Duration from 3 Years to 1 Year Criterion met 0.999 Overall 5th percentile 0.079 Mean effect = 0.26% GDP expectancy by a year (there are several such cases in our sample). These results are given in Figure 4, where the densities illustrate the entire distribution of predicted deficit changes and the vertical lines illustrate the fifth percentile of each distribution. First, the effects, as before, are very large. The change from an expected one year of remaining time in office to outliving expectations by one year results in an average 0.422% increase to the deficit. This is a substantial and normatively significant increase, not only because increases to the present deficit are so large, but also because the true long term cost of this deficit increase is compounded by the interest payments made over the debt clearing window. Notice also that we are extremely confident in the direction of the effect—each model yields an estimated certainty of p < 0.05. It is worth taking a moment to consider how this finding informs our understanding of how incumbents value their current time in office as opposed to their electoral prospects.Our theoretical arguments and empirical evidence suggest that cabinets forecast their durability, plan their spending to crescendo as forecasted dissolution approaches, and, if they prove more durable than expected, continue to spend lavishly to maintain support until dissolution. This suggests that incumbents prefer to continue to serve their present term, running the country ever higher into deficit, than to call early elections. At the least, this evidence suggests that, on average, incumbents are more averse to the uncertainty of elections than they are to incurring the wrath of voters for irresponsible spending. A broader interpretation of this finding is that incumbents are more averse to electoral uncertainty than most current characterizations of the literature may imply—that we have perhaps been too cavalier in our assumptions of an incumbent’s willingness to call for new elections. Of course, there is good reason for this. Though some dissolution models had built in electoral uncertainty (e.g., Kayser 2005), a simplifying assumption of many more formal models of dissolution 948 Downloaded from https://www.cambridge.org/core. Shanghai JiaoTong University, on 26 Oct 2018 at 03:53:05, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055418000436
