sovereign default risk and decentralization: evidence for emerging markets

European Journal of Political Economy 32 (2013) 113–134

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European Journal of Political Economy

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Sovereign default risk and decentralization:Evidence for emerging markets

Stefan Eichler⁎, Michael HofmannTechnische Universitaet Dresden, Faculty of Business and Economics, Dresden D-01062, Germany

a r t i c l e i n f o

⁎ Corresponding author. Tel.: +49 351 46335902; fE-mail addresses: [email protected] (S.

0176-2680/$ – see front matter © 2013 Elsevier B.V. Ahttp://dx.doi.org/10.1016/j.ejpoleco.2013.06.009

a b s t r a c t

Article history:Received 24 January 2012Received in revised form 26 June 2013Accepted 29 June 2013Available online 6 July 2013

We study the impact of decentralization on sovereign default risk. Theory predicts thatdecentralization deteriorates fiscal discipline since subnational governments undertax/overspend,anticipating that, in the case of overindebtedness, the federal government will bail them out. Weanalyze whether investors account for this common pool problem by attaching higher sovereignyield spreads to more decentralized countries. Using panel data on up to 30 emerging markets inthe period 1993–2008 we confirm this hypothesis. Higher levels of fiscal and politicaldecentralization increase sovereign default risk. Moreover, higher levels of intergovernmentaltransfers and a larger number of veto players aggravate the common pool problem.

© 2013 Elsevier B.V. All rights reserved.

JEL classification:F34G12H74

Keywords:Sovereign default riskDecentralizationCommon pool problemEmerging marketsPanel regression

1. Introduction

Several government bailouts were to be observed in decentralized countries in the past, where significant shares of subnationalgovernment liabilities were transferred to the federal government. For instance, several bailouts of overindebted subnationalgovernments occurred in Argentina in the 90s (Nicolini et al., 2002), in Brazil since the late 1980s (Bevilaqua, 2002), in Bolivia at thebeginning of the 2000s (International Monetary Fund, 2006), and in Mexico in the second half of the 90s (Trillo et al., 2002). A majorbailout in Brazil occurred, for example, in 1997, when subnational debts of about 12% in relation to GDP were restructured and partlyforgiven by the federal government (Bevilaqua, 2002). Subnational government bailouts do, however, occur not only in developingcountries, but also in OECD countries such as Australia, Germany, Italy, and Sweden (von Hagen et al., 2000) and in Spain(Sorribas-Navarro, 2011).

The problem with these bailout policies is that a common pool problem is created at the lower levels of government. Subnationalgovernments anticipate that in the long run their public debt can be shifted to the entire federation, because the federal governmentcannot credibly rule out subnational government bailouts (Bordignon et al., 2001; Goodspeed, 2002). Thus, subnational governmentsview public debt as a commonpool resource. The benefits of local tax cuts or the provision of public services financed through borrowingaccrue locally, whereas the burden of funding accrues in the long run nationwide. Through this imbalance between local benefits andnationwide funding the overall costs of public provision are not fully internalized at the subnational level (Weingast et al., 1981). Eachlocal government considers only its share in the nationwide tax base and disregards the externality to the other local governments,whichemerges through its spending and taxing decisions. This setting of decentralized fiscal decisions and indirect access to nationwiderevenue sources through borrowing biases the fiscal policy decisions at the subnational level to overspending and/or underutilization of

ax: +49 351 46337790.Eichler), [email protected] (M. Hofmann).

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114 S. Eichler, M. Hofmann / European Journal of Political Economy 32 (2013) 113–134

their own revenue sources, which contributes to larger fiscal deficits and a build-up of subnational public debt (Hallerberg and vonHagen, 1999; Velasco, 2000). This common pool problem leads to lower fiscal discipline and unsustainable debt levels in decentralizedcountries. The funding of subnational governments through intergovernmental transfersmay evenworsen the commonpool problembyincreasing subnational government's perception of possible bailouts. Furthermore, more veto players in a decentralized political systemmay aggravate fiscal problems by delaying or impeding the implementation of fiscal consolidationmeasures (Tsebelis, 1995; Schalteggerand Feld, 2009).

Several interesting studies have empirically analyzed the impact of fiscal decentralization on public budget deficits. Using mixedsamples of developing and developed countries, several papers find that a higher degree of decentralization deteriorates the fiscalsituation of the government (de Mello, 2000; Fornasari et al., 2000; Rodden, 2002), while Phlekanov and Singh (2007) find insignificanteffects. Considering OECD and non-OECD countries separately de Mello (2000) finds that in developing countries fiscal decentralizationincreases fiscal deficits, while in developed countries decentralization may improve the budget balance for the federal government. ForOECD countries, Baskaran (2010) finds that decentralization reduces fiscal deficits, while Thornton and Mati (2008) find no significantimpact. Using a mixed sample of developed and developing countries, Neyapti (2010) finds that decentralization reduces fiscal deficits.The positive impact of fiscal decentralization may arise as local governments have better local information and may therefore betterallocate fiscal resources at the local level than the central government. Moreover, decentralization may improve tax compliance as localgovernments are viewed asmore accountable and transparent to the local taxpayers. Neyapti (2010) consequently argues that the fiscaldisciplining effect of decentralization depends on the quality of institutions of a country.

We study the impact of decentralization on sovereign default risk, i.e. the risk that a government will not fully pay back publicdebt. In the literature, several determinants of sovereign default risk have been identified, such as, high public debt levels (Edwards,1984, 1986; Dailami et al., 2008; Manasse and Roubini, 2009); political business cycles (Block and Vaaler, 2004); the design of thepolitical system (van Rijckeghem and Weder, 2009; Saiegh, 2009; Kohlscheen, 2010); fiscal deficits (Schuknecht et al., 2009; vonHagen et al., 2011);more volatile economic fundamentals and financialmarkets (Hilscher and Nosbusch, 2010); and a poor quality ofinstitutions (Faria et al., 2011).

We contribute to the literature by analyzing the impact of fiscal and political decentralization on sovereign default risk. Theorypredicts, and several empirical studies confirm, that decentralization leads to fiscal deficits, a build-up in subnational debt levels, and (inthe long run) to bailouts of subnational governments by the federal government. If investors anticipate these adverse effects ofdecentralization, wewould expect that decentralized countries have higher levels of sovereign default risk.We test this hypothesis usinga panel of up to 30 emerging economies in the period 1993 to 2008.Weuse the EmergingMarkets Bond Index (EMBI) spreads to indicatethe sovereign default risk of a country, which measures the difference between the return on a country's U.S. dollar-denominatedsovereign bonds minus the return on U.S. treasuries.

We focus on emerging markets rather than on developed countries for several reasons. First, the EMBI is only available for emergingmarkets. EMBI spreads are not affected by exchange rate risk and are thus a relatively good measure for sovereign default risk in across-country setting. Second, except for the current financial crisis in the eurozone, sovereign debt crises have been a developingcountries' problem in the past and thus sovereign yield spreads should have more variation for an emerging market sample. Third, therelatively poor quality of institutions observed in developing countries may amplify the moral hazard effects of decentralization andmitigate possible positive effects of decentralization on the sustainability of public finances (Neyapti, 2010).

Our results suggest that decentralization leads to higher sovereign default risk in emerging economies. First, we find that higher levelsof decentralization (measured by expenditure and revenue decentralization) increase sovereign yield spreads, suggesting that sovereignbond investors take the extent of de facto fiscal decentralization into account when evaluating sovereign default risk. Using interactionmodels, we find that the impact of fiscal decentralization on default risk is more pronounced for countries with a small public bondmarket. Second, we find that intergovernmental transfers even increase sovereign default risk by providing incentives to implementunsustainable fiscal policies at the subnational level. Third, higher levels of political decentralization, such as (partly) autonomouslegislation at subnational levels, also increase sovereign default risk, suggesting that the de jure ability of subnational governments tobuild up debt at the (long run) expense of the federal government scares investors. Finally,we findweak evidence that a larger number ofveto players in a decentralized political system increase sovereign default risk, which lends support to the hypothesis that delayed orimpeded fiscal consolidations can lead to unsustainable debt levels and, consequently, increase the risk of debt default.

2. Literature

2.1. Empirical literature on the determinants of sovereign default risk

Since sovereign debt defaults are associated with losses for investors, it is crucial for them to estimate sovereign default riskand to include this risk into the prices of sovereign bonds. Existing empirical studies of sovereign default risk have either focused on theincidence of actual debt defaults (Manasse and Roubini, 2009; Saiegh, 2009; Van Rijckeghem andWeder, 2009; Kohlscheen, 2010) or onsovereign default risk reflected in bond prices (Edwards, 1986; Mauro et al., 2002; Block and Vaaler, 2004; Dailami et al., 2008;Schuknecht et al., 2009; Hilscher and Nosbusch, 2010; Faria et al., 2011).1 Most studies usemacroeconomic variables that determine thesolvency of the government in order to study the determinants of sovereign default risk or actual debt defaults. In his seminal papers,Edwards (1984, 1986) finds that a higher debt to GNP ratio, a lower foreign exchange reserve to GNP ratio, and a lower investment to

1 Sturzenegger and Zettelmeyer (2008) estimate recovery values ranging between 30% and 75% for the debt restructurings in Russia, Ukraine, Pakistan,Ecuador, Argentina, and Uruguay in the period 1998–2005.

115S. Eichler, M. Hofmann / European Journal of Political Economy 32 (2013) 113–134

GNP ratio increase sovereign default risk. Manasse and Roubini (2009) classify three types ofmacroeconomic vulnerabilities that leadto sovereign debt defaults in emerging economies: insolvency/debt unsustainability; illiquidity; and deterioration of macroeconomicfundamentals. Dailami et al. (2008) report that domestic andU.S. factors determine sovereign risk of emerging economies. Higher U.S.interest rates increase sovereign risk in emerging economies, but only significantly if countries are near insolvency. Hilscher andNosbusch (2010) find that the volatility of terms of trade, past sovereign defaults, and global risk factors determine sovereign defaultrisk in emerging markets.

Schuknecht et al. (2009) find that higher public debt and higher fiscal deficits increase sovereign default risk in the EuropeanUnion. Using an updated dataset, von Hagen et al. (2011) report that after the outbreak of the subprime crisis, the determinants ofEuropean bond spreads are the same as before the crisis and that after the collapse of Lehman Brothers bond spreads react moresensitively to deterioration in the sustainability of public finances. Faria et al. (2011) compare the determinants of sovereign yieldspreads in the pre-World War I (WWI) era (1905) and in the modern period (2002). Their findings suggest that good institutionsand large endowments of human capital have attracted international sovereign bond investors and lowered sovereign yieldspreads both samples.

An emerging literature focuses on the impact of political institutions on sovereign default risk. Block and Vaaler (2004) studythe impact of the political business cycle on sovereign debt ratings and spreads. They find that sovereign credit ratings aredowngraded in election years and that sovereign bond spreads are higher before elections than after elections. Manasse andRoubini (2009) also provide evidence of a political business cycle. The risk of debt defaults is rising prior to presidential elections,particularly if elections coincide with large amounts of short-term debt and relatively rigid exchange rate regimes. VanRijckeghem andWeder (2009) find that in democracies, the presence of sufficient checks and balances or a parliamentary systemreduces the risk of external debt defaults if the economic fundamentals are sufficiently strong. In non-democratic regimes, therisk of defaults in domestic debt is low if the regime is characterized by a high degree of stability, low polarization, or long tenure.Kohlscheen (2010) finds that in parliamentary democracies, where the government needs the support of the legislature to stay inoffice, the government is less likely to default on external debt than in presidential democracies. What is more, he finds thatsovereign debt defaults are less probable for multi-party governments, lower turnover of the executive, effective checks andbalances, and at the end of presidential office terms. Saiegh (2009) obtains the result that multi-party governments are less likelyto default on their debt than single-party governments.

2.2. Empirical literature on the impact of decentralization on the budget balance

Several papers study the effect of fiscal decentralization on the budget balance for single federal countries2 or a panel of countries.The data base and the most important results of the panel studies are reviewed in Table 1.

Many studies that use a mixed sample of developing and developed countries find evidence that an increase in the extent offiscal decentralization – measured by subnational expenditures or revenues as a share of total expenditures (expendituredecentralization) or revenues (revenue decentralization), respectively – worsens the fiscal balance at the subnational level(Rodden, 2002; de Mello, 2000).3 Since federal governments regularly bail out overindebted subnational governments, severalstudies also find a negative impact of fiscal decentralization on the federal government's budget balance (Fornasari et al., 2000) oron the general government's budget balance (Rodden, 2002). Moreover, de Mello (2007) and Rodden (2002) provide evidencethat vertical fiscal imbalances – i.e. the funding of subnational governments through intergovernmental transfers instead of ownsubnational tax sources – lead to larger fiscal deficits.

Some authors argue that fiscal decentralization can also improve fiscal balances by forcing the government to implement moretransparent rules and well-designed institutions. This view is supported by Neyapti (2010) and Baskaran (2010), who find thatfiscal decentralization reduces the fiscal deficits or net borrowing of the general government. Fiscal decentralization may lead tobetter fiscal discipline as the local governments may have better local information and may therefore be more efficient inallocating fiscal resources at the local level than the central government. Another advantage of fiscal decentralization may be thattax compliance may be higher as taxpayers may view the local government as more transparent and accountable in adecentralized regime than the central government. Consequently, positive effects of decentralization on fiscal budgets are foundfor OECD countries (Baskaran, 2010; de Mello, 2000) or mixed developing and developed country sets (Neyapti, 2010).4 de Mello(2000), for instance, observes that subnational transfer dependency worsens the fiscal balance of federal governments innon-OECD countries, whereas in OECD countries an improvement is observed. Furthermore, de Mello (2000) finds significantnegative effects of all decentralization measures (expenditure decentralization, revenue decentralization, vertical fiscalimbalances) on the budget balance in a sample of 13 non-OECD countries. Thus, the fiscal burden of fiscal decentralizationseems to be larger in developing countries, because decentralization is not accompanied by the necessary institutionalbackground. Developing countries are therefore ideal candidates when studying the negative aspects of decentralization. Thestudy of Neyapti (2010) explicitly controls for the quality of institutions to analyze the impact of decentralization on the fiscal

2 Examples are: Cabasés et al. (2007) for Spain (borrowing restrictions are effective but higher own tax revenue leads to larger municipal borrowing); Dahlberget al. (2008) for Sweden (discrete grants lead to higher local spending but have no effect on local tax rates); Schaltegger and Feld (2009) for Switzerland (fiscaldecentralization significantly increases the probability of a successful fiscal consolidation). Moreover, Rodden et al. (2003) study the impact of decentralization onfiscal balances for a range of countries.

3 Phlekanov and Singh (2007) find no significant impact of expenditure decentralization on the subnational budget balance.4 Baskaran (2010) examines an OECD sample. de Mello (2000) does separate regressions for a sample of 17 OECD countries and a sample of 13 non-OECD

countries. Neyapti (2010) uses a mixed country sample with 10 OECD and 6 non-OECD countries.

Table 1Panel studies on the effect of decentralization on fiscal sustainability.

Authors Data Dependent variable Independent variables Method

Effect on fiscal deficitsFornasari et al.(2000)

1980–9415 developingcountries, 17developedcountriesYearly data

Federal budgetbalance % — GDP

Expenditure Decentralization (−)Revenue Decentralization (?)

First difference estimation

de Mello (2000) 1970–9517 OECD-countries5-yearaverages


Expenditure Decentralization (?)Revenue Decentralizationt − 1 (−)Subnational Fiscal Dependency (+)

Seemingly unrelated regression

Subnational budgetbalance % — GDP

Expenditure Decentralization (?)Revenue Decentralizationt − 1 (−)Subnational Fiscal Dependency (?)


de Mello (2000) 1970–9513 non-OECDcountries5-yearaverages


Subnational Fiscal Dependency (−) Seemingly unrelated regression

Subnational budgetbalance % — GDP

Expenditure Decentralization (−)Revenue Decentralization (−)


Rodden (2002) 1986–9633 developed anddevelopingcountriesYearly data

Subnational budgetbalance % —

expenditureTotal budgetbalance % —

expenditure

Subnational Fiscal Dependency (−)Expenditure Decentralization (−)Revenue Decentralization (−)Revenue Decentralization (−)Subnational fiscal Dependency (?)

Arellano and Bond (1991) GMM estimator

Phlekanov andSingh (2007)

1982–200043 developed anddevelopingcountriesYearly data

Subnational budgetbalance % — revenue

Expenditure Decentralization (?) Between estimator

Thornton and Mati(2008)

1970–2001 17OECD-countriesYearly data


Expenditure Decentralization (?) Fixed effects estimation

Neyapti (2010) 1980–199816 developed anddeveloping countriesYearly data

Total budgetbalance % — GDP

Expenditure Decentralization (+)Revenue Decentralization (+)

Pooled OLS

Baskaran (2010) 1975–200117 OECD-countriesYearly data

Change in net generalgovernment debt toGDP ratio

Expenditure Decentralization (−)Revenue Decentralizationt − 1 (?)Subnational Fiscal Dependency (?)

First difference estimation

Effect on fiscal consolidationBaldacci et al.(2006)

1980–200125 non-OECDcountriesYearly data

Dummy success inreaching fiscaladjustmentDummy Success inmaintaining fiscaladjustment

Dummy Subnational Authority (−) Probit estimations

Schaltegger andFeld (2009)

1980–200126 Swiss cantonsYearly data

Dummy success inreaching fiscalconsolidation

Expenditure Decentralization (+) Probit and conditional logit estimations

Notes: The signs in parentheses indicate at 10% significance level a significant positive effect (+), a significant negative effect (−), and a non-significant effect (?).


balance. In general, her findings suggest that higher levels of fiscal decentralization reduce fiscal deficits underlining potentialpositive effects of decentralization. Using interaction models Neyapti (2010) finds that the deficit reducing effect of revenue andexpenditure decentralization is more pronounced in countries with a large population. This suggests that the informationadvantage of the local government (leading to better allocation efficiency of public spending relative to the central government)is more important in large (heterogeneous) countries than in small (homogeneous) countries. Moreover, Neyapti (2010) findsthat higher levels of ethnolinguistic fractionalization, better governance, and the presence of local elections5 lead to a lesspronounced deficit reducing impact of expenditure decentralization. Using revenue decentralization as the decentralization

5 Similarly, the presence of local elections yields a less pronounced deficit reducing impact of revenue decentralization.


proxy, different levels of ethnolinguistic fractionalization and better governance have no significant influence on the marginalimpact of decentralization on fiscal deficits.

Another line of research argues that a larger number of veto players in a decentralized country may lead to delayed fiscalconsolidation due to a war of attrition and may therefore increase fiscal deficits (Alesina and Drazen, 1991; Tsebelis, 1995). Theempirical evidence of the impact of veto players on the implementation of fiscal consolidation measures is mixed. Schaltegger andFeld (2009) show for Swiss cantons that centralization, rather than decentralization, impedes fiscal consolidation. The authorsargue that the Swiss type of fiscal decentralization leads to fiscal competition, which in turn strengthens fiscal disciplines. Theincrease in veto players due to fiscal decentralization seems to have no negative effect on fiscal consolidation in Switzerland. Themore decentralized cantons in Switzerland, the larger the likelihood of a successful fiscal consolidation. Contrary to these results,Baldacci et al. (2006) find weak empirical evidence that in emerging economies fiscal decentralization lowers the success ofreaching andmaintaining fiscal adjustments. That is, the effects of decentralization on fiscal sustainability can differ depending onthe stage of development.

3. Hypotheses

Several theoretical links between decentralization and fiscal deficit debts have been identified in the literature. Weargue that several aspects of decentralization may also have an impact on sovereign default risk since the sustainability ofpublic finances determines if sovereign borrowers pay back their debt. Based on the theoretical literature we develop fourhypotheses on the impact of different aspects of decentralization on sovereign default risk: 1) the common pool problemof decentralization; 2) intergovernmental transfers; 3) the presence of veto players; and 4) elections on subnationallevels.

A crucial characteristic of decentralization is that regional or local governments are, at least partly, autonomous tomake fiscal decisions on spending and/or taxing. While fiscal decentralization captures the de facto level ofdecentralization of fiscal decisions subnational governments make, for example the ratio of subnational expenditures tototal expenditures, political decentralization captures the de jure political rights of subnational governments to make fiscaldecisions, for example the right to borrow at the subnational level. Velasco (2000) shows that such a decentralized fiscalpolicymaking produces larger fiscal deficits and higher government debt than a policy framework where fiscal decisionsare made by a social planner. These results emerge, because the government's net assets, defined as the present value offuture government net income streams minus outstanding debts, are assumed to be the common property of all fiscalauthorities and each authority (the federal government and subnational governments) has access to this common poolresource. Consequently, the optimal behavior of each authority is to excessively utilize the common pool resource (netassets of government), which results in overborrowing.

The fact that the fiscal resources are regarded as a common pool resource is strongly related to the commitmentproblem of the federal government not to bail out subnational governments. Under the assumption that the federalgovernment aims to maximize social welfare in the federation, it cannot credibly rule out the commitment to bail outsubnational governments — and subnational governments anticipate this bailout commitment resulting in a moral hazardproblem. Bordignon et al. (2001) show in a theoretical model that it is socially optimal for the federal government toredistribute fiscal resources in such a manner, that every subnational region can provide the same amount of publicservices per capita. Therefore, a benevolent federal government cannot credibly exclude to bail out a subnationalgovernment ex ante. The subnational governments have incentives to undertax their regional resources and to overspendin order to call for additional fiscal transfer to close the fiscal gap. Bordignon et al. (2001) show that the timing of eventsdetermines whether undertaxing or overspending is chosen by the subnational government in order to attract fiscalassistance from the federal government. If the subnational government decides first on the tax rate and receives fiscaltransfers thereafter, undertaxing is likely. If the subnational government first decides on the size of expenditures,overspending is likely. The fiscal balance deteriorates in both cases.

Furthermore, the commitment problem of the federal government not to bail out holds even if the federal governmentdoes not maximize social welfare but maximizes its re-election probability (Goodspeed, 2002). In this case the federalgovernment also has the incentive to ensure an equal level of public good provision per voter in each subnational regionin order to maximize its expected votes. Due to the equalization condition, as Goodspeed (2002) argues in atwo-period-model, it is optimal for the federal government to increase the transfers to those subnational regions whichborrow. Hence, the borrowing costs of the subnational regions decline, because each region anticipates receiving transfersfrom the federal government and expects to pay back only a fraction of its initial borrowing. The model predicts thatsubnational governments are prone to overborrowing.

If investors anticipate that governments of decentralized economies are more likely to overborrow and, as a possibleconsequence, to default on sovereign debt, they will attach higher risk premiums to sovereign bonds of decentralized economies.

Hypothesis 1. Fiscal and political decentralization leads to overborrowing and bailout expectations thereby increasing sovereigndefault risk for decentralized countries.

While Hypothesis 1 captures the general idea that higher levels of decentralization increase sovereign default risk,Hypotheses 2 to 4 focus on specific elements of decentralization. Risk-sharing schemes in federations may lead to moral hazard


and a common pool problem, because then the individual local government does not internalize the costs of its policy actions tothe other local governments (Persson and Tabellini, 1996). This view is supported by Kohlscheen (2008), who shows that revenuesharing arrangements increase the demand for bailouts. Intergovernmental transfers are typically used to equalize subnationalrevenues between rich and poor regions and to share the risk of regional shocks. Thus the moral hazard problem induced bydecentralization per se (see Hypothesis 1) is even aggravated by the fact that in several decentralized countries the federalgovernment provides intergovernmental transfer to fund subnational governments. The literature on the flypaper-effect showsthat a one dollar increase in intergovernmental transfers leads to an expansion of local spending of more than one dollar, i.e. localgovernments tend to overspend when they are financed through intergovernmental transfers (see, e.g., Hines and Thaler, 1995, for anoverview). Furthermore, the dependence on intergovernmental transfers leads to the perception at the subnational government levelthat the responsibility for funding and hence, the responsibility for fiscal assistance if a subnational government is hit by a fiscal shock,moves more and more towards the federal government. Subnational governments perceive a larger probability of a bailout. Moreover,subnational governments have an incentive to produce fiscal deficits in order to receive intergovernmental transfers, i.e. they undertax oroverspend anticipating that fiscal gaps are financed by higher transfers (Weingast et al., 1981).

If investors anticipate that intergovernmental transfers increase the incentives of subnational governments to overborrow, they willattach higher risk premiums to the federal government's sovereign bonds since in the long run these transfersmay overtax the fiscal baseof the federal government.

Hypothesis 2. The more subnational governments depend on intergovernmental transfers the more severe the common poolproblem and the larger the sovereign default risk.

Decentralization may also impede fiscal consolidation in a way that Alesina and Drazen (1991) describe as war of attrition. In theirmodel, political actors agree on the necessity of fiscal consolidation but disagree on the distribution of the burden of fiscal consolidation.Eachpolitical actor delays fiscal consolidationhoping that other actors concede to bear a greater share of the burdenof fiscal consolidatione.g., governments consisting of large coalitions of politically diverse parties find it hard to agree on which voter blocks should bear theburden of tax increases or expenditure cuts. In decentralized countries a war of attrition can also occur in the vertical dimension, i.e.between the federal and the subnational government level or in the horizontal dimension, i.e. between the different subnationalgovernments or states.

Decentralization is mostly characterized by a constitutional representation of the states/regions that has to agree to all or certainlegislations. Tsebelis (1995) emphasizes that decentralization increases the number of institutional veto players, who can block theadoption of a policy, which leads to more difficulties in implementing and enforcing fiscal reforms or consolidation policies. If investorsanticipate that veto players may delay fiscal consolidations, they will attach higher risk premiums to sovereign bonds since delayedresolutions of unsustainable fiscal regimes may lead to debt crises and sovereign defaults.

Hypothesis 3. A higher number of veto players (e.g. the number of government levels) may lead to delayed or impeded fiscalconsolidations or reforms, thereby increasing sovereign default risk.

In addition to the issues discussed above, the adverse economic incentives of fiscal decentralization may also be related to localelections. Rodden (2002) argues that if a clear and transparent division of fiscal responsibilities of each government level exists,federalism must not necessarily worsen the fiscal discipline. Rodden (2002) shows empirically that subnational governmentswith a larger degree of autonomy (less dependence on intergovernmental transfers) have smaller fiscal deficits even when theyare free to borrow. He argues that voters and creditors of relatively autonomous regions view public debt as the liability of therespective region and therefore have an incentive to ensure a moderate level of debt. That is, voters would elect a localgovernment that prevents fiscal deficits. If regional voters are, however, aware of the possibility that the fiscal burden of theirregional public debts can be shifted to the entire federation in the long run, the common pool problem persists. In this case, voterswould elect politicians who excessively utilize the common pool resource (nationwide tax base) in favor of their region. That is,the impact of local elections on fiscal discipline and sovereign default risk depends crucially on whether voters regard the fiscalresources of the country as a common pool.

Hypothesis 4. When regional politicians are locally elected the effect on sovereign bonds is inconclusive.

4. Empirical analysis

4.1. Data

We use unbalanced panel data on up to 30 emerging markets in the period of 1993–2008.6 The definitions and data sources of thevariables included are reported in Tables 2 and 3.

In order tomeasure sovereigndefault risk in a country,weuse the yield spread betweendomestic sovereignbonds andU.S. treasuries.Assuming risk-neutral investors and risk-less U.S. sovereign bonds, this yield spread measures the expected loss associated with a

6 The following countries are included in the panel: Argentina, Brazil, Bulgaria, Chile, China, Colombia, Dominican Republic, Ecuador, Egypt, El Salvador,Georgia, Indonesia, Kazakhstan, Lebanon, Malaysia, Mexico, Pakistan, Panama, Peru, Philippines, Poland, Russia, South Africa, Sri Lanka, Tunisia, Turkey, Ukraine,Uruguay, Venezuela, and Vietnam.

Table 2Definitions and sources of decentralization variables.

Variable Definition Source

Fiscal decentralization variablesExpenditure Decentralization Subnational expenditures as %

of total government expendituresInternational Monetary Fund (IMF) (2010),own calculations

Revenue Decentralization Subnational revenues as %of total government revenues

IMF (2010), own calculations

Vertical Fiscal Balance Transfers received at subnational level as %of subnational expenditures

IMF (2010), own calculations

Political decentralization variablesFederalism Dummy = 1, if country is

classified as federal; 0 otherwiseElazar (1995)

Authority Do subnational governmentshave extensive taxing, spending,or regulatory authority?Dummy = 1, if yes; 0 otherwise

Beck et al. (2001)

Autonomy Are there autonomous regions?Dummy = 1, if yes; 0 otherwise

Beck et al. (2001)

Borrowing Autonomy Dummy = 1, if subnational levelin general is allowed to borrow;0 otherwise

World Bank (2010)

Legislation-1 Under constitution, subnationallegislatures have autonomy incertain specified areas(i.e. constitutional authority to legislate)not explicitly subject to central lawsDummy = 1, if yes; 0 otherwise

Fan et al. (2009)

Legislation-2 Under constitution, subnationalgovernments have residual powers(to legislate on areas not explicitlyassigned to other levels)Dummy = 1, if yes; 0 otherwise

Fan et al. (2009)

Election-1 Dummy = 1, if executive at secondlowest tier isdirectly elected or chosen by directlyelected assembly; 0 otherwise

Fan et al. (2009)

Election-2 Dummy = 1, if executive at bottomtier is directly elected or chosenby directly elected assembly;0 otherwise

Fan et al. (2009)

Tiers Number of tiers (including central government tier) Fan et al. (2009)


possible default of the domestic government. Ahigher sovereigndefault risk, i.e. a higher probability of default and/or loss givendefault, istherefore reflected by higher sovereign yield spreads at the capital market. Data on sovereign yield spreads is drawn from the EmergingMarket Bond Index (EMBI) provided by JPMorgan. Only U.S. dollar denominated sovereign bonds are included in the EMBI index, whichrules out exchange rate risk.7 Since our regression analysis is based on annual data, we use themean value of daily EMBI spreads for eachparticular year and country as the dependent variable.

In order to measure sovereign risk, we opt to use EMBI spreads (rather than sovereign default dummies) for several reasons. EMBIspreads indicate the development of sovereign default risk on a continuous basis,which enables us to study the relatively nuanced impactof decentralization. EMBI spreads are easily interpretable and comparable across countries, while using a sovereign default dummywould require us to define criteria of sovereign default. Moreover, EMBI spreads measure the cost of capital for the government and anempirical finding that EMBI spreads can be reduced by changing the level of decentralization may therefore be of political relevance.However, EMBI spreads are, of course, not an idealmeasure for sovereign default risk sincemarket perceptions about default riskmay notbe accurate and may be driven by contagion behavior. For example, Cottarelli et al. (2010) find that out of 36 cases where a country'sEMBI spread rose above 1000 basis points, only 7 cases of default occurred subsequently. However, although EMBI spreads may notpredict sovereign defaults perfectly, they are frequently used in the literature to measure sovereign risk and provide a relevant marketbased measure for the government's borrowing costs.

Fiscal decentralization is measured using three variables: Expenditure Decentralization, Revenue Decentralization and Vertical FiscalImbalance. Expenditure Decentralization aims tomeasure to what extent public expenditure is devolved to lower levels of government

7 The EMBI index includes Brady bonds, loans, and Eurobonds issued by the federal government with an average maturity of 12 years. The EMBI index averagesyield data from the most liquid bonds. The minimum size of a debt instrument to be included in the EMBI is $500 million, which guarantees that relatively liquidinstruments with reasonable prices are considered. The EMBI measures so-called stripped spreads, which are derived by subtracting collaterals from the observedmarket prices.

Table 3Definitions and sources of control variables.

Variable Definition Source

Arrears Principal arrears (public and publicly guaranteed)to Gross Domestic Product (GDP)

World Development Indicators(WDI)

Economic growth Year-over-year percentage change in GDP(in constant U.S. dollars)

WDI

External sovereign debt External debt stock(public and publicly guaranteed)to GDP

WDI

Current account balance Current account balance to totalforeign exchange reserves(including gold)

WDI

Exchange rate change Year-over-year percentage changein the local currency/U.S. dollar exchange rate;positive values indicate a depreciationof the local currency against the U.S. dollar

WDI

Investment ratio Gross fixed investment to GDP WDIU.S. interest rate 10-year U.S. treasury rate Department of the TreasuryVIX index Weighted average of the implied

volatilities of eight put and call optionswritten on the S&P 500 index

Chicago Board Options Exchange,Datastream

IMF program Dummy = 1, if IMF Standby Arrangementor IMF Extended Fund Facility Arrangementis in effect for at least 5 months in a particular year;0 otherwise

Dreher (2006b)

KOF index KOF Overall Globalization Index;higher values indicate higher level of economic,social and political globalization of a country

Dreher (2006a)

Polity score Indicator variable characterizing the political system;indicator ranges from +10 (strongly democratic)to −10 (strongly autocratic)

Polity IV Database

Presidential regime Dummy = 1, if political system is characterizedas a presidential regime; 0 otherwise

Database of Political Institutions

Parliamentary regime Dummy = 1, if political system is characterizedas a parliamentary regime; 0 otherwise`


Assembly elected regime Dummy = 1, if political system is characterizedas an assembly elected regime; 0 otherwise



by expressing subnational government expenditure (local and state/provincial level combined) as a share of total governmentexpenditures.

8 Ourdecentrand revreceive

Expenditure Decentralizationit ¼ExpSubit −TrFed;expensedit

ExpSubit þ ExpFedit −TrSub;expensedit −TrFed;expensedit

; ð1Þ

Expit is the government expenditures in country i in year t and the superscripts Sub and Fed denote the subnational and the
wherefederal government levels. At each government level the transfers to other government levels, Tritexpensed, are excluded in order toexclusively consider only the part of the expenditures that is spent for public goods at the respective level.8
Accordingly, Revenue Decentralizationmeasures subnational revenues as a share of total public revenues. For the calculation ofrevenue decentralization transfers from other levels of government are excluded. Vertical Fiscal Imbalance describes to whatextent subnational expenditures are financed by intergovernmental transfers.

Vertical Fiscal Imbalanceit ¼TrSub;receivedit

RevSubit

; ð2Þ

TritSub,received is the amount of transfers which the subnational level of country i in year t receives from the federal
where
government and Revit denotes the total revenues at the subnational level. This indicator measures the funding of decentralization.Each of the three fiscal decentralization variables is calculated based on the data drawn from the Government Finance

Statistics (GFS) of the International Monetary Fund. GFS data have several shortcomings, such as rather incomplete data forseveral countries and periods, and the fact that GFS data do not reveal information as to whether the subnational governmentdecides autonomously on the level and composition of its spending or whether it acts as a spending agency of the central

fiscal decentralization variables are calculated according to the definitions of the World Bank (http://www1.worldbank.org/publicsector/alization/fiscalindicators.htm#Formulas). By deducting fiscal transfers from other government levels we try to circumvent the problem that expendituresenues would partly be double counted at the level of government where expenditures and revenues actually occur and at the government level thator expend transfers.

http://www1.worldbank.org/publicsector/decentralization/fiscalindicators.htm#Formulas

http://www1.worldbank.org/publicsector/decentralization/fiscalindicators.htm#Formulas


government (Baskaran, 2010). However, GFS data are widely used in the literature to quantify the de facto level of fiscaldecentralization and (similar versions of) our decentralization variables have been applied in several papers on the impact ofdecentralization on fiscal deficits (see, for example, de Mello, 2000; Phlekanov and Singh, 2007; Baskaran, 2010; Neyapti, 2010).9

Inspecting the descriptive statistics of the fiscal decentralization variables (see Table 4) reveals that the variation in the fiscaldecentralization variables is mainly between the countries, but there is also a considerably degree of within variation in the data.Expenditure Decentralization and Revenue Decentralization are used to test Hypothesis 1. Vertical Fiscal Imbalance is used to testHypothesis 2. We expect a positive relationship between these fiscal decentralization measures and sovereign default risk. Themeans of sovereign yield spreads and the three fiscal decentralization variables are presented in Table 5.

We use several indicators to measure the different dimensions of political decentralization. Using these diverse measures weaim to characterize the political framework at the subnational government levels (e.g. are subnational governments locallyelected or not) and to describe to what extent they are allowed to act independently from the federal government. The followingpolitical decentralization variables are taken from the Database of Political Institutions (DPI). Autonomy indicates whether thecountry has autonomous or self-governing regions. The dummy variable Authority indicates whether subnational governmentshave authority over taxing, spending or legislative issues. Veto indicates the number of veto players in a political system, i.e. thenumber of political actors (e.g. chambers of the legislation) who are designated by the constitution to give their approval to newlegislations. The Veto variable is adjusted for the independence of the veto players, e.g. their respective party affiliations.10

The dummy variable Federalism is drawn from Elazar (1995) and indicates whether a country can be classified as a federationor not. The dummy variable Borrowing Autonomy is constructed using information from the World Bank and specifies whethersubnational governments are allowed to fund their expenditures through public borrowing.

Five variables on political decentralization are taken from Fan et al. (2009).11 The dummy variables Legislation-1 andLegislation-2 indicate whether subnational governments have autonomous legislation power in certain specified areas designatedby the constitution (Legislation-1) or whether subnational governments are allowed to legislate in areas not explicitly assigned toother levels of government (Legislation-2). The dummy variables Election-1 and Election-2 measure whether the executive at thesecond lowest government level (Election-1) or at the bottom government level (Election-2) is directly elected. Tiers counts thelevels of government starting with the federal government level.

Most of the political decentralization variables discussed (Autonomy, Legislation-1, Legislation-2, Federalism, SubnationalAuthority, Borrowing Autonomy) describe to what degree subnational governments can act autonomously from the federalgovernment and are used to test Hypothesis 1 in the political dimension of decentralization. A larger degree of political autonomyshould be related to higher sovereign default risk. Veto and Tiers are used to test Hypothesis 3, where we expect that a largernumber of veto players measured by Veto or Tiers lead to higher sovereign default risk. The variables indicating subnationalelections (Election-1 and Election-2) are used to test Hypothesis 4, where the expected impact on sovereign default risk isinconclusive.

We include several control variables which are frequently used in the literature as determinants of sovereign default risk. First,we include several macroeconomic control variables. Higher indebtedness of the government (measured by arrears on sovereigndebt and the level of external sovereign debt) is expected to increase sovereign default risk by reducing the government's abilityto repay its debt. Higher values of economic growth, the investment to GDP ratio, and the current account balance are expected toreduce sovereign default risk by improving the government's ability to collect taxes and to repay sovereign debt. We also accountfor the exchange rate change. We expect that a depreciation of the domestic currency against the U.S. dollar deteriorates thegovernment's ability to repay U.S. dollar denominated debt using domestic funds and thus increases sovereign default risk.

Moreover, we use two indicators to account for global risk factors. First, we use the U.S. interest rate to account for the globalrisk aversion of investors. Second, we use the VIX index in order to account for the riskiness of global financial markets.12 We

9 Some authors use modified versions of the definition used in this paper. For example, some studies use fiscal decentralization variables based on expendituresor revenues of particular subnational governments (such as for local or state/provincial governments only) as a robustness check (Neyapti, 2010). We considerrevenues and expenditures of all types of subnational governments as we believe that the common pool problem applies to all subnational governments.Moreover, Panizza (1999) and Neyapti (2010) argue that some public expenditures, such as social security and defense spending, can hardly be decentralized andshould, therefore, not be considered when calculating fiscal decentralization variables. However, historical GFS data do not cover these types of expenditures forall countries and periods. Due to reasons of comparability we therefore include defense spending and the budget of the social security system in the calculation ofour fiscal decentralization variables.10 The variable Veto is named Checks in the DPI. The definition of Veto is taken fromKeefer, 2009, (see p. 18)who provides an updated documentation of the variablesincluded in the DPI. The number of veto players is counted using the following approach: Veto equals one in countries where legislatures are not competitively elected.It is assumed that then only the executive possesses a check. If the legislature is competitively elected Veto is incremented by one if there is a chief executive. Veto isincremented by one if the chief executive is competitively elected. Veto is incremented by one if the opposition controls the legislature. In presidential systems, Veto isincremented by one for each chamber of the legislature unless the president's party has a majority in the lower house and a closed list system is in effect (implyingstronger presidential control of his/her party, and therefore of the legislature). Moreover, Veto is incremented by one in presidential systems for each party coded asallied with the president's party and which has an ideological (left–right–center) orientation closer to that of the main opposition party than to that of the president'sparty. In parliamentary systems, Veto is incremented by one for every party in the government coalition as long as the parties are needed tomaintain amajority and forevery party in the government coalition that has a position on economic issues (right–left–center) closer to the largest opposition party than to the party of theexecutive. In parliamentary systems, the primeminister's party is not counted as a check if there is a closed rule in place— the primeminister is presumed in this case tocontrol the party fully.11 The data was originally compiled by Treisman. A detailed description of the method used to create the variables can be found in Treisman (2002).12 The VIX is calculated as an average of the implied volatilities of eight put and call options written on the S&P 500 index. These implied volatilities are ameasure for the expected volatility of the S&P 500, which is interpreted as the riskiness of global financial markets in the future (see, for example, Hilscher andNosbusch, 2010).

Table 4Descriptive statistics.

Variable Mean Standard deviation Min Max Obs

Overall Between Within

Sovereign bond yield spread 584 817 472 681 47 6342 299Expenditure Decentralization 0.227 0.136 0.135 0.034 0.032 0.552 120Revenue Decentralization 0.160 0.112 0.151 0.025 0.033 0.552 115Vertical Fiscal Balance 0.468 0.203 0.171 0.074 0.103 1.049 106Arrears 0.43 1.54 0.77 1.27 0 16.78 299Economic growth 4.49 3.98 1.85 3.60 −11.03 18.29 299External sovereign debt 27.4 18.9 16.6 10.5 1.4 89.7 299Current account balance −10.1 59.4 45.6 50.3 −460.5 397.3 299Exchange rate change 20.4 136.8 33.8 131.0 −38.0 2239.0 299Investment ratio 20.9 5.8 5.2 3.2 11.0 43.1 299U.S. treasury rate 4.64 1.17 – 1.17 2.25 7.84 299VIX index 21.5 8.2 – 8.2 11.6 40.0 299KOF index 56.0 9.86 7.76 6.24 26.4 81.2 299Polity score 4.36 5.73 5.41 2.28 −9 10 299


expect that higher values lead to a higher risk premium international investors demand when buying emerging marketssovereign bonds, which, in turn, is expected to increase sovereign default risk.

We also include several political and institutional variables in our estimations. The degree of democracy (as opposed toautocracy) is measured using the polity score, where higher values indicate a higher degree of democracy. On the one hand,democratic regimes may reduce sovereign default risk as incompetent politicians may be voted out of office and waste of publicfunds may be prevented by checks and balances. On the other hand, autocratic regimes may be associated with lower sovereigndefault risk due to high political stability and high political power to introduce unpopular austerity programs. We also testwhether presidential, parliamentary and assembly elected regimes produce different levels of sovereign default risk. In order toaccount for institutional quality, we use the KOF Overall Globalization Index (see Dreher, 2006a) and expect that more globalizedcountries are associated with lower sovereign default risk. We also account for the presence of lending arrangements with theInternational Monetary Fund (IMF) using the dataset of Dreher (2006b). The effect of these lending arrangements on sovereign

Table 5Descriptive statistics by country.

Means of … Period coverage

Country Sovereign bond yield spread Expenditure decentralization Revenue decentralization Dummy Federalism

Argentina 1677 0.41 0.39 1 1993–2008Brazil 677 0.39 0.31 1 1994–2008Bulgaria 633 0.17 0.09 0 1994–2008Chile 147 0.13 0.08 0 1999–2008China 107 – 0.59 0 1994–2008Colombia 419 0.31 – 0 1997–1999Dominican Republic 591 – – 0 2001–2008Ecuador 1353 – – 0 1995–2008Egypt 196 – – 0 2001–2008El Salvador 307 0.06 0.04 0 2002–2008Georgia 1091 0.13 0.06 0 2008–2008Indonesia 324 – – 0 2004–2008Kazakhstan 582 0.43 0.28 0 2007–2008Lebanon 422 – – 0 2002–2008Malaysia 183 0.12 0.11 1 1996–2007Mexico 388 0.26 0.23 1 1993–2008Pakistan 629 – – 1 2001–2008Panama 344 – – 0 1996–2008Peru 410 0.25 0.06 0 1997–2008Philippines 402 – – 0 1997–2008Poland 221 0.26 0.17 0 1994–2008Russia 883 0.39 0.33 1 1997–2008South Africa 232 0.51 0.17 0 1994–2008Sri Lanka 887 – – 0 2007–2008Tunisia 182 – – 0 2002–2008Turkey 444 – – 0 1996–2008Ukraine 787 0.28 0.19 0 2000–2008Uruguay 487 – – 0 2001–2008Venezuela 875 – – 1 1993–2008Vietnam 273 – – 0 2005–2008All countries 521 0.227 0.160

Table 6Test of Hypothesis 1 with expenditure decentralization.

Dependent variable: sovereign bond yield spread (1)Pooled OLS

(2)Pooled OLS

(3)Pooled OLS

(4)Random effects

(5)Random effects

Expenditure Decentralization 1435⁎⁎

(2.606)1106⁎⁎

(2.283)1302⁎⁎

(2.483)1575⁎⁎⁎

(3.897)1083⁎⁎

(2.551)Arrears 301.7⁎⁎⁎

(5.850)286.3⁎⁎⁎

(5.399)283.4⁎⁎⁎

(5.375)274.3⁎⁎⁎

(8.506)250.0⁎⁎⁎

(10.44)Economic growth −29.78⁎

(−1.709)−28.81⁎

(−1.833)−19.43(−1.101)

−26.93⁎⁎⁎

(−2.900)−24.93⁎⁎⁎

(−2.854)External sovereign debt 15.12⁎⁎⁎

(2.633)21.67⁎⁎

(2.545)24.12⁎⁎⁎

(2.750)21.17⁎⁎⁎

(2.911)29.42⁎⁎⁎

(5.855)Current account balance 1.084

(1.072)1.060(0.994)

1.267(1.159)

1.031⁎

(1.880)(1.558)0.008

Exchange rate change 0.006(1.221)

0.009⁎

(1.824)0.004(0.650)

0.007(0.760)

0.008(0.986)

Investment ratio −2.928(−0.377)

4.213(0.426)

6.096(0.532)

4.124(0.354)

12.12(1.237)

U.S. treasury rate 19.12(0.592)

31.37(0.852)

71.66(1.314)

11.06(0.325)

18.15(0.541)

VIX index 11.72⁎⁎ 12.22⁎⁎⁎ 19.71⁎⁎⁎ 10.98⁎⁎ 11.06⁎⁎⁎

IMF program −26.65(−0.228)

−33.79(−0.241)

−122.9(−0.974)

−30.40(−0.320)

−34.21(−0.359)

KOF index −3.711(−0.721)

1.251(0.174)

0.558(0.0733)

−2.096(−0.301)

3.084(0.433)

Polity score −10.19(−0.875)

−18.85(−1.482)

−16.86(−1.366)

−3.291(−0.222)

−7.805(−0.510)

Presidential regime 450.7⁎⁎

(2.590)867.9⁎⁎

(2.318)905.5⁎⁎

(2.576)567.4⁎⁎⁎

(2.927)1223⁎⁎⁎

(4.409)Parliamentary regime 386.8⁎

(1.841)704.9⁎⁎

(2.014)816.4⁎⁎

(2.446)90.3⁎⁎

(2.209)816.0⁎⁎⁎

(4.296)Constant −521.8

(−1.043)−1587(−1.388)

−2093(−1.641)

−1019(−1.294)

−1060⁎

(−1.669)Region dummies – Yes Yes – YesTime dummies – – Yes – –

No. of observations 120 120 120 120 120No. of countries 15 15 15 15 15Adj. R² 0.876 0.881 0.889 0.891 0.898F-statistic 16.58⁎⁎⁎ 16.18⁎⁎⁎ 21.38⁎⁎⁎ 266.5⁎⁎⁎ 264.4⁎⁎⁎

Notes: The t-statistics in parentheses are calculated using heteroskedasticity robust standard errors clustered by country.⁎ Indicates significance at the 10% level.

⁎⁎ Indicates significance at the 5% level.⁎⁎⁎ Indicates significance at the 1% level.


default risk may be ambiguous. Such lending arrangements may help the domestic government to cope with liquidity constraints,but may also cause moral hazard and act as a signal of acute financial stress feeding expectations of sovereign default (Jorra,2012).

4.2. Methodology

In our empirical model, sovereign default risk, as indicated by the sovereign yield spread, is assumed to be a linearcombination of country-specific or United States-specific factors:

rit−rft ¼ Controlsitβ þ Decitβ þ εit ð3Þ

rit − rft denotes the observed EMBI spread in country i in year t; Decit denotes fiscal and political decentralization
wheremeasures; Controlsit denotes standard control variables; εit is the error term representing all unobserved factors that influencesovereign default risk.
Choosing an appropriate estimation method is, in our case, a tradeoff between omitted variables bias and measurement bias.One example of an omitted variable is the policy of theWorld Bank. The main task of theWorld Bank is to provide fiscal assistanceto developing countries. These actions are accompanied by actively supporting the implementation of decentralization, so thatthe policy of the World Bank clearly affects the probability of default and the extent of decentralization in these countries. Thepolicy of the World Bank can, however, hardly be quantified and therefore cannot be included as a control variable.

The measurement bias occurs, for example, because revenues and expenditures at different government levels are differentlyaffected by business cycles, so that the yearly variation in the fiscal decentralization variables (especially expendituredecentralization and revenue decentralization) is to some extent due to macroeconomic factors and not due to political decisionsto devolve more fiscal autonomy to the lower levels of governments. For example, a decentralized country may have a tax sharing

Table 7Test of Hypothesis 1 with revenue decentralization (pooled OLS).


(2)Pooled OLS

(3)Pooled OLS

(4)Random effects

(5)Random effects

Revenue Decentralization 2002⁎⁎⁎

(2.928)2322⁎⁎⁎

(3.282)2551⁎⁎⁎

(3.554)2002⁎⁎⁎

(5.114)2380⁎⁎⁎

(5.883)Arrears 289.7⁎⁎⁎

(5.931)240.5⁎⁎⁎

(4.556)233.4⁎⁎⁎

(4.486)289.7⁎⁎⁎

(5.931)227.5⁎⁎⁎

(8.334)Economic growth −29.59

(−1.574)−22.89(−1.596)

−20.57(−1.322)

−29.59(−1.574)

−21.20⁎⁎


(2.787)24.62⁎⁎⁎

(3.352)27.35⁎⁎⁎

(3.710)10.34⁎⁎⁎

(2.787)27.16⁎⁎⁎


(1.075)1.068(1.044)

1.180(1.206)

1.028(1.075)

0.859(1.530)


0.004(0.907)

−1.1E−04(−0.019)

0.001(0.190)

0.005(0.616)


11.14(1.135)

13.35(1.211)

−9.445(−1.163)

13.24(1.460)

U.S. treasury rate −10.38(−0.298)

−10.58(−0.298)

−0.514(−0.009)

−10.38(−0.298)

−10.13(−0.338)

VIX index 12.07⁎⁎⁎

(2.889)10.19⁎⁎⁎

(2.835)14.10⁎⁎

(2.578)12.07⁎⁎⁎

(2.889)9.763⁎⁎

(2.524)IMF program 34.97

(0.378)−14.82(−0.123)

−79.10(−0.792)

34.97(0.378)

−4.386(−0.048)

KOF index −13.88⁎⁎

(−2.431)−2.046(−0.298)

−4.897(−0.704)

−13.88⁎⁎

(−2.431)0.112(0.0164)

Polity score 12.28(0.868)

−2.193(−0.190)

4.334(0.360)

12.28(0.868)

−0.793(−0.058)

Presidential regime 307.1⁎⁎

(2.563)836.7⁎⁎⁎

(3.070)919.6⁎⁎⁎

(3.582)307.1⁎⁎

(2.563)940.3⁎⁎⁎

(4.385)Parliamentary regime 340.4⁎

(1.961)708.1⁎⁎

(2.622)840.9⁎⁎⁎

(3.230)340.4⁎⁎

(1.961)721.3⁎⁎⁎

(4.872)Constant 510.7

(1.653)−1578(−1.531)

−1701(−1.547)

510.7(1.165)

−1859⁎⁎

(−2.497)Region dummies – Yes Yes – YesTime dummies – – Yes – –

No. of observations 115 115 115 115 115No. of countries 15 15 15 15 15Adj. R2 0.885 0.892 0.905 0.904 0.918F-statistic 15.94⁎⁎⁎ 17.91⁎⁎⁎ 19.95⁎⁎⁎ 266.5⁎⁎⁎ 287.5⁎⁎⁎




regime where the federal government levies taxes that largely vary over the business cycle (such as income taxes) whereas thesubnational government levies taxes which are much less sensitive to business cycle fluctuations (such as mineral oil taxes). Inthe case of a boom (bust), federal government revenues will increase (decrease), while subnational government revenues changeat a much lower pace, which, in turn, leads to a reduction (increase) in the empirical measure of revenue decentralization.Nonetheless, fiscal decentralization variables are a goodmeasure to capture differences in decentralization between countries andthe variation in decentralization within one country in the medium run.

We could partly solve the omitted variable bias by conducting fixed effects estimations.13 The shortcoming of this approach isthat the measurement error is exacerbated, because the estimation of the coefficients is based solely on within variation. Sincedecentralization does only change gradually over time, focusing on within variation (and ignoring between variation) would notbe a suitable approach. Furthermore, this estimation method cannot be applied to our measures of political decentralization,which are mainly time invariant. We could deal with measurement bias by using the between estimator. Under the assumptionthat the measurement errors in the decentralization variables are not serially correlated from one year to another, the betweenestimator tends to minimize their importance due to averaging (Baltagi, 2005). There are however several shortcomings of thebetween estimator. First, we would have omitted variable bias, because we cannot control for unobserved fixed factors. Second,this approach is inefficient because we do not exploit the within information, which is related to real changes in decentralization.Moreover, our dataset covering 15–30 countries would be too small to produce reliable between estimates.

With this tradeoff between omitted variable bias and measurement bias in mind, we deal with these endogeneity problems intwo ways. First, we conduct random effects and pooled OLS estimations. Both approaches are more efficient than the between

13 This approach controls for time-invariant unobserved heterogeneity, but omitted variable bias that is triggered due to time-variant unobserved factors wouldstill be a problem.

Table 8Test of Hypothesis 1 with political decentralization variables (pooled OLS).

Sovereign bond yield spread (1) (2) (3) (4) (5) (6)

Dummy Federalism 152.6⁎⁎⁎

(2.918)Dummy Borrowing Autonomy 53.67

(0.532)Dummy Legislation-1 173.7⁎⁎⁎

(3.404)Dummy Legislation-2 206.0⁎⁎⁎

(3.675)Dummy Autonomy −65.36

(−0.828)Dummy Sub Authority 50.77

(0.571)Arrears 269.0⁎⁎⁎

(7.071)267.9⁎⁎⁎

(7.147)278.8⁎⁎⁎

(7.705)278.4⁎⁎⁎

(7.681)283.2⁎⁎⁎

(7.325)235.5⁎⁎⁎

(7.542)Economic growth −23.31⁎⁎

(−2.000)−27.87⁎⁎

(−2.192)−25.00⁎

(−1.737)−24.95⁎

(−1.728)−24.02⁎

(−1.950)−24.17⁎


(4.794)10.18⁎⁎⁎

(3.353)5.175⁎⁎⁎

(3.863)5.068⁎⁎⁎

(2.814)6.566⁎⁎⁎

(4.294)19.10⁎⁎⁎


(1.597)0.919⁎

(1.673)0.790(0.929)

0.926(1.165)

0.785(1.406)

0.413(1.200)

Exchange rate change 0.006⁎

(1.904)0.010⁎⁎⁎

(2.858)0.008⁎⁎

(2.036)0.007⁎

(1.924)0.008⁎

(1.866)0.014⁎⁎⁎

(3.204)Investment ratio 0.414

(0.0793)−0.718(−0.076)

−9.343(−1.559)

−4.850(−0.890)

−10.38(−1.550)

4.359(0.454)


32.29(0.890)

53.29(1.566)

73.03⁎⁎

(1.991)24.23(0.666)

−33.58(−0.854)


(2.917)15.10⁎⁎

(2.552)14.96⁎⁎⁎

(3.024)17.44⁎⁎

(2.568)14.85⁎⁎⁎

(3.010)7.159(1.105)

IMF program 199.0⁎⁎⁎

(3.897)170.4⁎⁎⁎

(2.857)261.2⁎⁎⁎

(4.023)281.7⁎⁎⁎

(4.395)149.9⁎⁎⁎

(2.933)260.3⁎⁎⁎

(3.552)KOF index −12.82⁎⁎⁎

(−2.805)−3.787(−0.581)

−0.584(−0.123)

0.0249(0.005)

−14.14⁎⁎⁎

(−3.197)−1.914(−0.292)


−34.58⁎⁎

(−2.529)−12.63⁎⁎

(−2.105)−5.909(−0.709)

2.680(0.424)

−76.95⁎⁎⁎

(−2.933)Presidential regime 107.3

(1.490)346.1⁎

(1.971)113.9(1.349)

69.69(0.722)

241.3⁎⁎⁎

(2.678)599.4⁎⁎⁎

(2.860)Parliamentary regime 112.7

(1.632)203.2(1.194)

59.17(0.788)

5.242(0.0497)

292.9⁎⁎⁎

(3.664)434.9⁎⁎

(2.251)Constant 599.8

(1.464)−280.5(−0.459)

−61.70(−0.147)

−386.5(−0.749)

724.2⁎

(1.958)−38.53(−0.0597)

Region dummies Yes Yes Yes Yes Yes YesTime dummies Yes Yes Yes Yes Yes YesNo. of observations 296 231 233 221 279 153No. of countries 30 22 22 22 29 14Adj. R2 0.720 0.728 0.763 0.766 0.715 0.806F-statistic 19.81⁎⁎⁎ 18.10⁎⁎⁎ 18.23⁎⁎⁎ 19.08⁎⁎⁎ 17.60⁎⁎⁎ 20.82⁎⁎⁎




estimator because within and between information means that more observations are used.14 Furthermore, the measurementerror is reduced – compared to the fixed effects estimation – because the estimates also rely on between variation. In order tocontrol for omitted time and regional fixed effects, we include year and region dummies.

Second, we conduct an instrumental variable (IV) estimation in order to deal with the endogeneity problems (measurementerror and omitted variable bias). The IV procedure produces a consistent estimator as long as valid instrument variables are foundfor the decentralization variables. The instrumental variable must be correlated with the explanatory variable for which it servesas an instrument (relevance condition). Moreover, the instrumental variable should be exogenous, i.e. it should have no partialeffect on sovereign yield spreads and it should be uncorrelated with the error term (exogeneity condition). Lagged values of theendogenous variable are often proposed and used as instruments. This is a valid approach as long as the errors are notautocorrelated. This assumption is seldom confirmed by the data and therefore IV estimation with lagged values does not solve

14 Random effects is in general more efficient than pooled OLS estimation, because it takes into account serial correlation. On the other hand, pooled OLS needsless restrictive assumptions.

Table 9Test of Hypothesis 1 with political decentralization variables (random effects).

Dependent variable: sovereign bond yield spread (1) (2) (3) (4) (5) (6)

Dummy Federalism 159.7(1.208)

Dummy Borrowing Autonomy 5.140(0.0230)

Dummy Legislation-1 217.6⁎⁎

(2.097)Dummy Legislation-2 153.2

(1.462)Dummy Autonomy −30.55

(−0.188)Dummy Sub Authority 87.18

(0.743)Arrears 247.5⁎⁎⁎

(13.26)232.4⁎⁎⁎

(10.81)273.0⁎⁎⁎

(14.82)266.3⁎⁎⁎

(12.65)251.5⁎⁎⁎

(13.07)226.4⁎⁎⁎

(10.09)Economic growth −24.92⁎⁎⁎

(−4.152)−26.30⁎⁎⁎

(−3.651)−31.75⁎⁎⁎

(−4.419)−30.47⁎⁎⁎

(−4.040)−24.72⁎⁎⁎

(−3.971)−30.40⁎⁎⁎


(4.618)20.10⁎⁎⁎

(5.109)8.458⁎⁎⁎

(2.618)11.29⁎⁎

(2.410)14.51⁎⁎⁎

(4.407)22.24⁎⁎⁎


(0.508)0.165(0.390)

0.418(0.761)

0.377(0.642)

0.114(0.292)

0.0528(0.107)


0.014(1.375)

0.010(1.082)

0.011(1.157)

0.012(1.352)

0.016(1.557)


−7.641(−0.717)

−12.50⁎

(−1.910)−9.663(−1.381)

−15.30⁎⁎

(−2.087)0.313(0.0322)

U.S. treasury rate −32.83(−1.293)

−45.60(−1.486)

7.094(0.251)

0.673(0.0212)

−30.78(−1.158)

−80.57⁎⁎

(−2.124)VIX index 10.41⁎⁎⁎

(3.497)9.619⁎⁎⁎

(2.615)11.12⁎⁎⁎

(3.214)11.22⁎⁎⁎

(3.081)11.52⁎⁎⁎

(3.631)4.985(1.041)

IMF program 276.4⁎⁎⁎

(4.872)265.4⁎⁎⁎

(3.782)278.8⁎⁎⁎

(4.051)275.6⁎⁎⁎

(3.887)256.0⁎⁎⁎

(4.366)279.1⁎⁎⁎

(3.439)KOF index −1.625

(−0.284)4.835(0.703)

−0.0735(−0.0134)

2.251(0.360)

−3.355(−0.540)

0.357(0.043)


−34.87⁎⁎

(−2.500)−15.47⁎

(−1.845)−19.10⁎

(−1.758)−12.01(−1.041)

−74.61⁎⁎⁎

(−2.855)Presidential regime 63.71

(0.500)202.9(0.780)

74.21(0.725)

100.3(0.850)

134.3(0.921)

520.9⁎⁎

(2.474)Parliamentary regime 267.1

(1.618)383.9⁎

(1.838)98.96(0.719)

206.2(1.078)

343.1⁎⁎

(2.092)462.7⁎⁎

(2.184)Constant 18.36

(0.0372)367.4(0.551)

223.9(0.500)

3.422(0.0070)

184.7(0.352)

17.06(0.0240)

Region dummies Yes Yes Yes Yes Yes YesNo. of observations 296 231 233 221 279 153No. of countries 30 22 22 22 29 14Adj. R2 0.906 0.895 0.917 0.923 0.900 0.947F-statistic 358.1⁎⁎⁎ 294.5⁎⁎⁎ 307.2⁎⁎⁎ 293.7⁎⁎⁎ 338.5⁎⁎⁎ 228.8⁎⁎⁎




the endogeneity problems because the exogeneity condition is violated. Thus, we refrain from using lagged values as instruments.The specific choice of instruments for the fiscal decentralization variables is discussed in Section 4.4.

4.3. Pooled OLS and random effects results

The results of the regression models testing the impact of fiscal decentralization on sovereign default risk are reported inTable 6 (reporting the results for expenditure decentralization) and Table 7 (reporting the results for revenue decentralization).15

The t-values are computed using robust standard errors clustered by country to control for possible serial correlation.The results show that for each specification, an increase in fiscal decentralization significantly increases sovereign default risk.

This relationship is also economically significant: For Expenditure Decentralization we find that a 10% increase in the share ofsubnational expenditures to total expenditures leads to an increase of the sovereign yield spread by 1.1–1.6%. For Revenue

15 All random effects estimations are conducted without including time dummies. When time dummies are included the number of countries is smaller than thenumber of explanatory variables and therefore between estimation cannot be conducted. But the between estimator is required to conduct random effectsestimation.

Table 10Test of Hypothesis 2.


(2)Pooled OLS

(3)Pooled OLS

(4)Random effects

(5)Random effects

Vertical Fiscal Imbalance 83.68(0.786)

56.77(0.496)

58.71(0.602)

238.2⁎⁎

(1.969)259.0⁎⁎

(2.074)Arrears 871.5⁎⁎⁎

(19.96)876.8⁎⁎⁎

(19.77)869.2⁎⁎⁎

(23.31)877.8⁎⁎⁎

(24.76)875.8⁎⁎⁎

(24.15)Economic growth −31.61⁎⁎⁎

(−3.428)−30.51⁎⁎⁎

(−3.322)−21.75⁎⁎⁎

(−2.780)−29.96⁎⁎⁎

(−7.674)−30.26⁎⁎⁎

(−7.703)External sovereign debt 2.320

(1.394)2.721(1.445)

3.549⁎

(1.828)5.995⁎⁎⁎

(2.582)6.152⁎⁎⁎

(2.611)Current account balance −0.705⁎⁎⁎

(−2.218)−0.688⁎⁎

(−2.005)−0.710⁎⁎

(−2.812)−0.211(−0.950)

−0.236(−1.051)

Exchange rate change 0.008⁎⁎⁎

(5.306)0.008⁎⁎⁎

(4.448)0.009⁎⁎⁎

(2.939)0.006⁎⁎

(1.968)0.006⁎⁎

(2.013)Investment ratio −5.510⁎

(−1.876)−3.817(−1.033)

−6.128(−1.595)

1.351(0.377)

1.165(0.319)


13.98(0.831)

1.603(0.0471)

5.873(0.413)

6.182(0.427)

VIX Index 9.683⁎⁎⁎

(4.994)9.358⁎⁎⁎

(4.532)11.26⁎⁎⁎

(3.355)8.269⁎⁎⁎

(5.315)8.294⁎⁎⁎

(5.318)IMF program 110.7

(1.552)112.0(1.507)

112.0(1.50)

58.82(1.387)

61.95(1.444)

KOF index −0.637(−0.219)

0.293(0.088)

0.823(0.221)

0.262(0.087)

0.0370(0.012)

Polity score −17.15⁎⁎⁎

(−3.302)−19.10⁎⁎⁎

(−2.757)−22.24⁎⁎⁎

(−2.842)−5.609(−0.892)

−3.628(−0.508)

Presidential regime 28.01(0.662)

85.56(1.015)

32.79(0.373)

47.21(0.538)

114.9(0.558)

Parliamentary regime −2.159(−0.0315)

55.04(0.716)

49.67(0.663)

−73.45(−0.591)

−70.42(−0.389)

Constant 238.0(1.066)

93.63(0.289)

63.07(0.157)

−57.51(−0.196)

−18.46(−0.0589)

Region dummies – Yes Yes – YesTime dummies – – Yes – –

No. of observations 106 106 106 106 106No. of countries 15 15 15 15 15Adj. R2 0.927 0.925 0.936 0.939 0.939F-statistic 672.8⁎⁎⁎ 640.9⁎⁎⁎ 111.09⁎⁎⁎ 300.3⁎⁎⁎ 300.9⁎⁎⁎




Decentralization, our regression results suggest that a 10% increase in the share of subnational revenues to total revenues leads toan increase of the sovereign yield spread by 2.0–2.5%. That is, sovereign bond investors take the extent of de facto fiscaldecentralization in emerging economies into account when evaluating sovereign default risk supporting Hypothesis 1. Our resultssuggest that sovereign bond investors anticipate that higher levels of fiscal decentralization may lead to a common pool problem,where subnational governments overborrow, anticipating that the federal government will bail them out. That is, moredecentralized countries are regarded to be riskier by sovereign bond investors and thus have to bear higher interest rate costs forsovereign debt. A possible policy implication from this result would be that a reduction in the fiscal autonomy of subnationalgovernments would significantly reduce the interest rate costs for the federal government.

The results of the regressions testing the impact of the various dimensions of political decentralization on sovereign defaultrisk are reported in Table 8 (reporting the pooled OLS regression results) and Table 9 (reporting the random effects regressionresults). For the political decentralization measures we also obtain evidence that supports Hypothesis 1. For the legislationmeasures (Legislation-1 and Legislation-2), indicating as to whether subnational governments have autonomous legislation powerdesignated by the constitution, we find a significantly positive impact on sovereign default risk for the pooled and random effectsestimations. The estimated coefficients indicate that countries with subnational legislation power face 1.7–2.1% higher yieldspreads than countries where legislature only exists at the level of the federal state. That is, if subnational governments havelegislator power, the federal government faces higher sovereign default risk since investors anticipate that the legislationautonomy may be used to pass laws that authorize the subnational government to overborrow (to overspend or undertax) at theexpense of the solvency of the federal government. The Borrowing Autonomy dummy has the expected positive coefficient but isinsignificant.16 For the Federalism and Autonomy dummies we get insignificant results. A possible explanation for this finding is

16 There is empirical evidence which can partly explain this result. Letelier (2011) report that Chilean municipalities are not allowed to borrow de jure, butactually they do borrow using arrears and leasing contracts. Thus, formal prohibition of subnational borrowing may not necessarily be effective.

Table 11Test of Hypothesis 3 (pooled OLS and random effects).


(2)Pooled OLS

(3)Random effects

(4)Random effects

Tiers 15.70(0.401)

42.39(0.451)

Veto 36.88⁎⁎

(2.002)22.99(0.981)

Arrears 288.9⁎⁎⁎

(7.349)280.5⁎⁎⁎

(7.374)253.6⁎⁎⁎

(13.14)256.5⁎⁎⁎


(−2.241)−23.94⁎

(−1.877)−25.59⁎⁎⁎

(−4.212)−25.45⁎⁎


(4.021)6.206⁎⁎⁎

(4.087)14.39⁎⁎⁎

(4.284)12.64⁎⁎⁎


(1.446)0.697(1.239)

0.202(0.533)

0.104(0.256)

Exchange rate change 0.008⁎⁎

(2.177)0.008⁎⁎

(1.975)0.012(1.328)

0.013(1.407)


−8.602(−1.263)

−9.568(−1.405)

−12.91⁎

(−1.786)U.S. treasury rate 12.42

(0.403)26.81(0.731)

−33.63(−1.314)

−26.26(−0.971)


(2.800)14.70⁎⁎⁎

(2.871)9.861⁎⁎⁎

(3.254)11.03⁎⁎⁎

(3.400)IMF program 183.1⁎⁎⁎

(3.500)199.6⁎⁎⁎

(4.088)276.8⁎⁎⁎

(4.868)292.0⁎⁎⁎

(5.050)KOF index −14.27⁎⁎⁎

(−2.992)−8.994⁎⁎

(−2.139)−2.674(−0.456)

0.111(0.0185)


−6.580(−1.039)

−20.42⁎

(−1.886)−15.49(−1.376)

Presidential regime 85.70(1.142)

– 5.916(0.045)

–

Parliamentary regime 165.0⁎

(2.372)– 265.6

(1.620)–

Constant 893.9⁎

(1.968)449.7(1.222)

−8.171(−0.012)

179.3(0.373)

Region dummies Yes Yes Yes YesTime dummies Yes Yes – –

No. of observations 292 278 292 278No. of countries 29 30 29 30Adj. R2 0.751 0.739 0.890 0.878F-statistic 17.38⁎⁎⁎ 17.45⁎⁎⁎ 355.6⁎⁎⁎ 332.2⁎⁎⁎

Notes: The t-statistics in parentheses are calculated using heteroskedasticity robust standard errors clustered by country. The presidential and parliamentaryregime dummies are excluded from the regressions considering the variable Veto, because the political regime is one important factor in calculating the number ofveto players as explained in Section 4.1.

⁎ Indicates significance at the 10% level.⁎⁎ Indicates significance at the 5% level.

⁎⁎⁎ Indicates significance at the 1% level.


that these proxies are rather crude measures of decentralization which also include, for example, subnational autonomy incultural and language issues and are thus not restricted to autonomous fiscal decision-making. The dummy Authority is alsoinsignificant. This result may be explained by the fact that although in some countries subnational governments have a certaindegree of autonomy in taxing or spending, this authority may significantly differ among countries, for example, on which taxes orexpenses subnational governments are allowed to decide. Moreover, this de jure dummy cannot represent the amount ofauthority in taxing and spending actually used by the subnational governments and thus our de facto fiscal decentralizationmeasures (expenditure and revenue decentralization) may be more relevant in this context.

Table 10 reports the regression results testing the impact of Vertical Fiscal Imbalance on sovereign default risk. For two out offive specifications we find that higher levels of Vertical Fiscal Imbalances increase sovereign default risk. This finding weaklyconfirms Hypothesis 2 that countries, where subnational governments are funded through intergovernmental transfers facehigher sovereign default risk. Investors seem to anticipate that the presence of intergovernmental transfers aggravates thegeneral moral hazard problem of decentralization by increasing the incentives to implement unsustainable fiscal policies at thesubnational level. A reasonable policy implication would be to rule out intergovernmental transfers in order to reduce sovereigndefault risk and thus interest rate costs for the federal government.

Table 11 reports the results for the regressions, testing the impact of the number of veto players (as indicated by Veto andTiers) on sovereign default risk. For the pooled OLS regressions we find that the presence of veto players increases sovereigndefault risk, while the effect is insignificant for the random effects specification and the specifications using the Tiers variable. Theresults provide weak evidence for Hypothesis 3, that a larger number of veto players in a decentralized political system may lead

Table 12Test of Hypothesis 4.


(2)Pooled OLS

(3)Random effects

(4)Random effects

Dummy Election-2 −112.4⁎

(−1.708)−2.205(−0.0142)

Dummy Election-1 73.12(1.234)

113.4(0.871)


(7.362)277.8⁎⁎⁎

(7.419)247.3⁎⁎⁎

(12.36)246.4⁎⁎⁎


(−2.002)−26.09⁎

(−1.937)−23.37⁎⁎⁎

(−3.734)−25.47⁎⁎⁎


(3.980)7.145⁎⁎⁎

(4.406)16.01⁎⁎⁎

(4.439)15.67⁎⁎⁎

(4.407)Current account balance 0.994⁎

(1.660)0.930(1.622)

0.252(0.639)

0.236(0.593)


0.007⁎

(1.727)0.012(1.289)

0.012(1.321)


−8.725(−1.265)

−14.15⁎

(−1.846)−15.89⁎⁎

(−2.111)U.S. treasury rate 28.84

(0.775)34.44(1.017)

−32.03(−1.181)

−28.70(−1.056)


(2.731)14.92⁎⁎⁎

(3.003)10.35⁎⁎⁎

(3.211)10.87⁎⁎⁎

(3.334)IMF program 175.7⁎⁎⁎

(3.339)151.8⁎⁎⁎

(2.686)246.8⁎⁎⁎

(4.149)254.7⁎⁎⁎

(4.165)KOF index −14.93⁎⁎⁎

(−3.260)−10.22⁎⁎

(−1.992)−2.459(−0.380)

−1.151(−0.181)


0.695(0.105)

−27.59⁎

(−1.781)−20.75(−1.562)

Presidential regime 157.0⁎

(1.825)271.9⁎⁎⁎

(3.325)191.5(1.169)

282.7⁎

(1.864)Parliamentary regime 215.3⁎⁎⁎

(2.681)337.9⁎⁎⁎

(4.005)404.2⁎⁎

(2.247)434.8⁎⁎

(2.535)Constant 756.1⁎

(1.920)374.3(0.765)

93.54(0.161)

229.7(0.404)

Region dummies Yes Yes Yes YesTime dummies Yes Yes – –

No. of observations 269 265 269 265No. of countries 27 27 27 27Adj. R2 0.724 0.722 0.893 0.897F-statistic 18.25⁎⁎⁎ 18.43⁎⁎⁎ 332.7⁎⁎⁎ 329.1⁎⁎⁎




to delayed fiscal consolidation. Investors may anticipate the risk that necessary tax increases or spending cuts may be blocked byveto players, which may lead to overborrowing thereby increasing sovereign yield spreads. Reducing the number or power ofveto players may thus help a country's ability to control public debt and to reduce the interest rate burden for the federalgovernment.

Table 12 reports the results for the regressions testing the impact of subnational elections (as indicated by Election-2 andElection-1) on sovereign default risk. We do not find a significant impact of local elections on sovereign default risk. Thus, ouranalysis cannot provide further evidence on the a priori unclear Hypothesis 4. As outlined in the Hypotheses section, the impact oflocal elections on sovereign default risk crucially depends on whether voters regard the fiscal resources of the country as acommon pool. If voters anticipate that subnational debt may be transferred to the federal government in the case of bailout, theywould elect opportunistic politicians realizing such a fiscal policy. If voters however regard subnational debt as a liability of thespecific region (ruling out bailouts), they would vote for politicians implementing a low fiscal deficit policy. Our results suggestthat sovereign bond investors are also ambiguous about the relevance of local elections.

4.4. Instrument variable estimation results and robustness checks

In order to account for possible endogeneity, we conduct instrumental variable (IV) estimations for the expenditure andrevenue decentralization regressions (see Tables 6 and 7) and the vertical fiscal imbalances regression (Table 10). The extent offiscal decentralization, i.e. Expenditure Decentralization and Revenue Decentralization, is instrumented by land area and populationsize. These variables are natural candidates for instruments in our case since larger countries tend to decentralize the provision ofpublic services (Arzaghi and Henderson, 2005). Moreover, these instruments should be uncorrelated with sovereign yield spreads

Table 13IV estimates of fiscal decentralization variables.

Dependent variable: sovereign bond yieldspread

(1) (2) (3) (4) (5) (6)

Expenditure Decentralization 1813⁎⁎

(1.883)2532⁎⁎

(2.475)Revenue Decentralization 2158⁎⁎

(2.407)2155⁎⁎⁎

(3.412)Vertical Fiscal Imbalance 1272⁎⁎

(2.390)−34.23(−0.0220)


(5.238)251.8⁎⁎⁎

(4.800)246.5⁎⁎⁎

(4.891)246.6⁎⁎⁎

(5.431)1100⁎⁎⁎

(9.794)842.9⁎⁎⁎

(2.733)Economic growth −18.50

(−1.226)−17.18(−1.198)

−20.54(−1.456)

−20.54(−1.454)

−26.01⁎⁎⁎

(−3.036)−19.78⁎⁎


(2.901)29.62⁎⁎⁎

(3.252)25.97⁎⁎⁎

(3.722)25.96⁎⁎⁎

(3.950)−4.996(−1.064)

7.243(0.542)

Current account balance 1.339(1.340)

1.440(1.348)

1.166(1.373)

1.166(1.380)

−0.400(−1.178)

−0.741⁎

(−1.759)Exchange rate change 0.001

(0.250)−0.001(−0.208)

0.002(0.267)

0.002(0.333)

0.005⁎

(1.838)0.009⁎

(1.885)Investment ratio 7.994

(0.838)10.66(1.072)

12.95(1.372)

12.94(1.349)

−16.10⁎⁎

(−2.095)−7.916(−0.572)


98.46⁎

(1.877)2.428(0.0492)

2.451(0.0489)

135.4⁎⁎

(1.969)−29.42(−0.199)


(3.665)25.28⁎⁎⁎

(3.478)13.70⁎⁎⁎

(2.852)13.70⁎⁎⁎

(2.986)19.84⁎⁎⁎

(3.720)9.235(1.561)

IMF program −178.4(−1.133)

−256.4(−1.593)

−70.81(−0.788)

−70.75(−0.826)

−124.8(−1.203)

9.495(0.0494)

KOF index 0.742(0.108)

1.001(0.133)

−4.358(−0.732)

−4.354(−0.726)

14.82⁎

(1.716)−1.040(−0.0541)


−10.08(−0.908)

−1.539(−0.135)

−1.584(−0.147)

−39.44⁎⁎⁎

(−3.197)−21.77(−0.954)

Presidential regime 887.1⁎⁎⁎

(3.109)861.3⁎⁎⁎

(3.094)882.8⁎⁎⁎

(3.671)882.5⁎⁎⁎

(3.787)−3.136(−0.0213)

−19.28(−0.207)

Parliamentary regime 846.0⁎⁎⁎

(2.810)887.6⁎⁎⁎

(2.989)769.0⁎⁎⁎

(2.877)768.5⁎⁎⁎

(3.262)152.4(1.502)

−0.997(−0.00760)

Constant −1513(−1.494)

−2266⁎⁎

(−1.982)−1569(−1.631)

−1568⁎

(−1.700)−1654⁎

(−1.769)604.3(0.313)

Endogenous explanatory variable ExpenditureDecentral.

ExpenditureDecentral.

RevenueDecentral.

RevenueDecentral.

Vertical FiscalImb.

Vertical FiscalImb.

Instrument Land area Population Land area Population Ethnic fraction. Linguisticfraction.

F-statistic instrument relevance 36.53⁎⁎⁎ 32.18⁎⁎⁎ 35.25⁎⁎⁎ 103.51⁎⁎⁎ 9.88⁎⁎⁎ 0.35Observations 120 120 115 115 106 99Countries 15 15 15 15 15 14Centered R-squared 0.887 0.877 0.909 0.909 0.848 0.941

Notes: The F-statistic of instrument relevance is an F-test of the significance of the instrument in the first-stage regression as proposed by Bound et al. (1995). Thet-statistics in parentheses are calculated using heteroskedasticity robust standard errors clustered by country.

⁎ Indicates significance at the 10% level.⁎⁎ Indicates significance at the 5% level.

⁎⁎⁎ Indicates significance at the 1% level.


since land and population size probably do not have an impact on the probability of sovereign debt default and are thus notcorrelated with the error term.

For the variable Vertical Fiscal Imbalance we use indices of ethnic and linguistic fractionalization as instruments. The literatureon civil conflicts shows that the probability of conflicts in a country depends on the heterogeneity of the population (Blimes,2006). The larger the ethnic heterogeneity, the higher the probability of civil conflicts in a country. Furthermore, Bakke andWibbels (2006) emphasize that intergovernmental transfers are important means for alleviating interregional conflict. Peace ismaintained as the federal government purchases the compliance of regions or population groups. Thus, the amount ofintergovernmental transfers (as indicated by vertical fiscal imbalances) should be positively correlated with the heterogeneity ofthe population. The heterogeneity of a population is empirically measured using ethnic and linguistic fractionalization. Bothindices of fractionalization are calculated as one minus the Herfindahl index of ethnolinguistic group shares. The indices can varybetween zero and one and reflect the probability that two randomly selected individuals of a population belong to different ethnicgroups (ethnic fractionalization) or to different linguistic groups (linguistic fractionalization). The data on fractionalization isprovided by Alesina et al. (2003).17 The composition/heterogeneity of a population is a persistent characteristic of a country

17 Neyapti (2010) shows in different interaction models that larger population size leads to a more pronounced deficit reducing effect of decentralization,whereas larger levels of ethnolinguistic fractionalization abates the effect.

Fig. 1. Marginal effect of expenditure decentralization on sovereign default risk conditional on financial market strength.


which depends on the specific history of the country and does not change in the short term. Our estimations cover 20 years andthus fractionalization can be regarded as exogenous.

Table 13 reports the results for the IV regressions, testing the impact of the fiscal decentralization measures (expenditure andrevenue decentralization) and the vertical fiscal imbalances on sovereign default risk. The results of the first-stage regressionsshow that the chosen instruments are relevant, i.e. they are highly correlated with the endogenous variables (see the F-statisticsin Table 13).18 The results for the second-stage regressions in Table 13 confirm the findings of our benchmark regressions inTables 6, 7, and 10. For each IV specification (except for specification 6), we find a highly significant positive impact of thedecentralization variables on sovereign default risk lending support for Hypotheses 1 and 2. Thus, sovereign bond investorsrealize that in decentralized emerging economies a common pool problem may arise and be aggravated by the presence ofintergovernmental transfers, increasing the risk of bailouts of subnational governments.

We estimate several alternative specifications in order to test for the robustness of our results. First, we re-estimate eachregression model including additional control variables.19 Second, in order to check whether our benchmark results are sensitiveto the combination of countries considered, we re-estimate each regression model dropping countries that belong to a commonregion in each specification. Third, in order to test whether the benchmark results are sensitive to the inclusion of particular years(for example, due to financial crises) we estimate each regression model dropping one year in each specification. Moreover, weuse the method of Hadi (1992, 1994) in order to detect outliers and exclude them from the data.20

Overall, results of the robustness tests (available upon request) confirm our benchmark findings suggesting that the linkbetween decentralization and sovereign default risk is not restricted to specific combinations of control variables, regions, oryears.

As a further robustness check, we tested whether the depth of the domestic public bond market affects the impact ofdecentralization on sovereign default risk. Previous studies use interaction models to analyze the marginal impact ofdecentralization on fiscal deficits or inflation depending on the quality of institutions and governance in a country. As outlinedin Section 2, Neyapti (2010) finds that population size, ethnolinguistic fractionalization, the presence of local elections, and thelevel of governance influence the size and significance of the marginal impact of fiscal decentralization on fiscal deficits. Neyapti

18 The exception is linguistic fractionalization which seems to be a weak instrument for vertical fiscal imbalances. The F-statistic in column (6) in Table 13 is farbelow 10 and as a rule of thumb an F-statistic less than 10 indicates a weak instrument. Stock and Yogo (2005) recently computed more accurate critical valuesfor the first-stage F-statistic. A value of the F-statistic below 16.38 (as in our case) indicates a weak instrument at the 5% significance level (see Table 5.4 in Stockand Yogo, 2005). Linguistic fractionalization is thus only slightly correlated with vertical fiscal imbalance and the results in column (6) should not be overstated.19 As additional control variables we add: GDP per capita in order to account for the level of economic development of a country; openness, measured as exportsplus imports over GDP, to account for the country's willingness to pay back debt; the TED spread, measuring the difference between the 3-month LIBOR interestrate on interbank loans and the 3-month U.S. Treasury bills, in order to account for liquidity conditions in the money market; and the redemption yield on theMerrill Lynch U.S. High Yield Index in order to account for risk aversion of international investors towards emerging market investments.20 Our results largely remain when excluding outliers. One notable exception are the regressions using vertical fiscal imbalances. For these cases, the outlier testsuggests that the results seem to be driven by outliers. Vertical fiscal imbalances become mostly insignificant at 10% significance level when excluding outliers.The results for other decentralization variables remain stable, except of some minor changes (dummy Sub Authority and dummy Borrowing allowed in Table 9become significant at 10% significance level, whereas dummy Legislation-2 in Table 8 becomes insignificant).

Fig. 2. Marginal effect of revenue decentralization on sovereign default risk conditional on financial market strength.


(2004) finds that revenue decentralization may significantly reduce inflation if accompanied by sufficient levels of central bankindependence and the presence of local elections.

We test whether the link between decentralization and sovereign default risk depends on the size of the public bond market.We would expect that a larger public bondmarket leads to a less pronounced impact of decentralization on sovereign default risk.A larger public bond market exhibits a higher demand for domestic public bonds, which makes it easier for the domesticgovernment to issue new public bonds if necessary. The risk of a (decentralization-induced) sovereign default is therefore lowerand investors may attach lower decentralization-induced risk premiums to domestic public bonds. In order to quantify the size ofthe public bondmarket we use the market capitalization of the domestic public bondmarket to GDP, taken from theWorld Bank'sFinancial Structure Database.

To estimate the marginal effect of decentralization on the sovereign yield spread conditional on the public bond marketcapitalization we use the following interaction model:

rit−rft ¼ β0 þ β1Decit þ β2DecitPublic Bondit þ β3Public Bondit þ∑βjControlsjit it þ εit : ð4Þ

The estimation results for the interaction models for revenue and expenditure decentralization are available upon request.Based on the estimation results, the marginal effect of revenue or expenditure decentralization on sovereign default riskconditional on the public bond to GDP ratio can be calculated according to Greene (2003, p. 123–124). The marginal effect of moreexpenditure or revenue decentralization on sovereign default risk, conditional on the public bond to GDP ratio; is illustrated inFigs. 1 and 2, respectively:

The results suggest that the marginal effect of expenditure and revenue decentralization on sovereign default risk in emergingeconomies declines for larger values of financial strength. That is, for relatively immature public bond markets with low levels ofpublic bond to GDP ratios, higher levels of decentralization increase sovereign default risk. For countries with large public bondmarkets, however, the link between decentralization and sovereign default risk becomes insignificant. This result suggests that bypromoting the growth of the domestic public bond market the government may reduce the adverse effect of decentralization onsovereign yield premiums in emerging economies.

The results for the control variables largely confirm the findings of previous papers. Robust evidence is found that higher levelsof economic growth and lower levels of external sovereign debt, arrears on sovereign debt, and the VIX index (reflecting stockmarket volatility) reduce sovereign default risk, while we do not find robust evidence for the current account balance, investment,the exchange rate, and the U.S. treasury rate. The results suggest that less democratic regimes (measured by a lower Polity score),countries with a parliamentary or presidential regime (as opposed to assembly elected regimes), as well as countries with a lowerinstitutional quality (as measured by a lower KOF Index of Globalization) suffer from higher levels of sovereign risk. Moreover,relatively weak evidence is found that the implementation of lending arrangements with the IMF increases sovereign default risklending support to the finding of Jorra (2012).

5. Conclusions

In this paper, we study whether bond investors anticipate the adverse incentives associated with the common pool problem ofdecentralization when pricing sovereign bonds. Using panel data on up to 30 emerging economies in the period 1993–2008 we

image of Fig.�2


find that higher levels of fiscal decentralization significantly increase sovereign default risk in emerging economies. That is,investors take the extent of de facto fiscal decentralization into account when estimating sovereign default risk. We also findevidence that higher levels of intergovernmental transfers aggravate the common pool problem of decentralization by providingincentives to implement unsustainable fiscal policies at the subnational level. Our results also suggest that higher levels ofpolitical decentralization increase sovereign default risk. Countries with an (partly) autonomous legislation at subnational levelsface higher sovereign yield spreads than countries with no subnational legislation suggesting that the degree of de jure fiscaldecentralization is also taken into account by investors. We find weak evidence that a larger number of veto players increasesovereign default risk, which suggests that impeded or delayed or impeded fiscal consolidations in a federation can lead tounsustainable debt levels and a higher risk of sovereign debt default. Overall, our findings of larger sovereign spreads in moredecentralized countries indicate that investors are aware of the common pool problem associated with decentralization indeveloping countries. Our results confirm that there is a problem with fiscal sustainability in decentralized countries. Publicbudgets are affected by decentralization in two ways. Decentralized countries do not only accumulate larger public debt due tounsustainable fiscal behavior at the subnational government level but also have to bear larger interest rates on their public debtdue to increased sovereign bond spreads.

Some implications for policymakers and investors may be derived from our results for developing countries. Our regressionresults suggest that sovereign yield spreads increase as the extent of decentralization increases. In order to reduce the interestrate costs of sovereign debt, (federal) governments may decide to reduce the de facto and/or de jure fiscal autonomy ofsubnational governments. Thus, reforms towards less decentralization are desirable from the viewpoint of the federalgovernment — but it may be difficult to implement these reforms when taking the incentives of subnational governments intoaccount. For investors, our results imply that decentralized countries are riskier in terms of yield spreads. Investors should thus beaware that sovereign bonds of developing countries decentralizing their fiscal and political decision-making may be attached tohigher yield spreads, suggesting losses for investors. Thus, efforts in increasing the degree of decentralization (particularly indeveloping countries) as advocated by theWorld Bankmay advance other aspects of the economy, but should be viewed criticallyby sovereign bond investors.

Acknowledgments

Wewant to thank participants of the 27th Annual Congress of the European Economic Association and the Brown Bag seminarat Technische Universitaet Dresden, two anonymous referees, and the editor for valuable comments. Stefan Eichler gratefullyacknowledges support from the Deutscher Akademischer Austauschdienst.

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