Regulation and government debt


Government debt is large in most developed countries, and while budget deficits may reflect short-term attempts to kick-start the economy in times of crisis by means of fiscal stimulus, the longer-term consequences may be detrimental to investment and growth. Those negative consequences make it important to identify factors that are associated with public debt. While previous studies have related government debt to economic and political variables, they have not incorporated the degree to which the economy is regulated. Using a measure of regulatory freedom (absence of detailed regulation of labor, business and credit) from the Economic Freedom of the World index, we conduct an empirical analysis covering up to 67 countries during the period 1975–2010. The main finding is that regulatory freedom, especially with respect to credit availability, reduces debt accumulation. The effect is more pronounced when the political system is fractionalized and characterized by strong veto players, indicating policy stability and credibility, and when governments have right-wing ideologies.

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  1. 1.

    Debt is also relevant when considering other long-term goals, e.g., inflation, employment, intergenerational equity and fiscal sustainability (Auerbach 2008).

  2. 2.

    Indeed, Reinhardt and Rogoff (2010) find that the debt–growth relationship is quite weak at “normal” debt ratios, but that very high debt ratios (above 90% of GDP) tend to reduce growth sharply, from 3% to 1.7% over the two-century period they study, but even more, from 3 to − 0.1% in the post-war sample. The estimates were criticized by Herndon et al. (2014), who find smaller negative effects of high debt and no particular threshold at 90%, but Reinhart et al. (2012) provide some further support for the previous findings. See also Eberhardt and Presbitero (2015) for further evidence of a negative relationship, but with no common threshold across countries; cf. Égert (2015).

  3. 3.

    High debt levels also make it more difficult for stimulus to be effective: see Nickel and Tudyka (2014).

  4. 4.

    Political business cycles could provide a further explanatory mechanism for debt accumulation, if voters reward expansionary fiscal policy and punish more restrictive policy. However, Alesina and Passalacqua (2015, p. 18) write that such cycles “cannot be the main explanation for large and long-lasting accumulation of public debt”.

  5. 5.

    In Sect. 4.4, we provide an explorative empirical analysis to see whether some of these four possibilities can be shown to function as actual channels between regulation and debt.

  6. 6.

    This exposition concerns democracies. For non-democratic settings, voters and the legislature are not relevant as such—authoritarian regimes often have legislatures that have only nominal power, and if there are voters, they do not de facto have alternatives to vote for.

  7. 7.

    We here follow the general approach of Peltzman (1976). However, the public choice literature has documented a number of mechanisms by which politicians’ stated ideological preferences could be either distorted or reversed entirely: Hillman (2009) and Holcombe (2016) provide compendia of such mechanisms.

  8. 8.

    The Initiative on Global Markets (IGM) Economic Experts Panel leaned towards the Keynesian position in 2014 (IGM 2014). When asked whether the benefits of US stimulus efforts would end up exceeding their costs, 20% strongly agreed, 36% agreed, 23% were uncertain and 5% disagreed. Even stronger agreement with Keynesian ideas was found in a large survey of economists some decades earlier (Frey et al. 1984).

  9. 9.

    A number of studies link stricter regulation to less adaptability and dynamism. For example, Alesina et al. (2005) show that regulatory reform of product markets in OECD countries is associated with an increase in investment. Djankov et al. (2006), Jalilian et al. (2007) and Justesen (2008) find that countries with fewer regulatory restrictions grow more rapidly. Haltiwanger et al. (2014) find strong and robust evidence that stringent hiring and firing regulations tend to reduce the pace of job reallocation. Bjørnskov (2016) shows that countries with more-regulated markets tend to experience substantially longer and deeper economic crises.

  10. 10.

    In a very general way, Alchian (1950) describes how adaptability is a central feature of economic development. Feldman (2009) documents how labor–market regulations tend to affect unemployment, which, in certain situations, gives rise to an inclination to increase public spending.

  11. 11.

    Including a lagged dependent variable is equivalent to estimating changes in debt levels during five-year periods. Empirically, using the change as either a left-hand side variable or the level is the same as long as both specifications include a lagged dependent variable. The only real difference is the estimated coefficient on the lagged dependent variable.

  12. 12.

    The results that follow are robust to applying either a standard random-effects estimator or adding country fixed effects. We do both, but prefer an OLS estimator with panel-corrected standard errors, as the use of fixed effects more clearly identifies short- to medium-term relations. We note that our choice in the present context produces the most conservative estimates.

  13. 13.

    Estimating the association between our control variables and regulation, and using the latter as the dependent variable, illustrates the potential problems. Regulation is strongly associated with both veto player strength, proportional voting, presidential democracy and government ideology. Not including those characteristics in the specification must give rise to omitted-variable bias in our main estimate.

  14. 14.

    Inspired by Gørgens et al. (2005), we have also tried nonlinear modeling, but it did not produce evidence of curvilinear effects. Including a squared regulation term yields a worse fit and no statistical significance. Furthermore, categorizing the regulatory freedom variable in four equal categories suggests that the effects are approximately linear.

  15. 15.

    We also tried including four additional indicators of economic freedom, indicators that together with regulatory freedom constitute the Economic Freedom of the World index (Gwartney et al. 2016). As can be seen in Table A3 in the Appendix, the four are not related to the debt ratio in a statistically significant way.

  16. 16.

    We also tested whether an ideological change in government within each 5-year period is related to debt. We find that a dummy variable indicating such change is statistically nonsignificant and that its inclusion does not affect any of our main findings.

  17. 17.

    The standard solution is an instrumental variables (IV) approach, but the most obvious candidates as identified in previous studies—ideological differences and legal origins—are also candidates for direct influences. We have been unable to find any other theoretically valid variables that solve the identification problem, and therefore cannot undertake any IV estimates.

  18. 18.

    Figures 3, 4 and 5 have been produced using the delta method (Brambor et al. 2006). They cover the full sample.

  19. 19.

    We suggest that this finding can be explained by the fact that left- and right-wing governments can impose different types of regulation (Potrafke 2010; Bjørnskov and Potrafke 2012, 2013).

  20. 20.

    However, the interaction with ideology loses significance in the fixed-effect estimates.

  21. 21.

    This is a way of recognizing that the regulatory environment is a complex one, and that any aggregation is bound to hide a great deal of heterogeneity, e.g., in terms of what the effects on some outcome variable may be. The point estimates we produce are to be seen as “net effects” of all the components of a particular index, where both sizes and signs can vary between those variables.

  22. 22.

    As in Aghion et al. (2010) and Pitlik and Kouba (2015), these measures all derive from the most recent waves of the World Values Survey and the European Values Study. When a country is included in both surveys, we take the average.


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The authors wish to thank Niklas Potrafke and participants at the 2016 Conference of the Italian Society of Law and Economics in Torino, especially Enrico Colombatto, the 2017 Research Workshop of the Institute for Research in Economic and Fiscal Issues (IREF) in Manchester, the 2017 Conference of the European Association of Law and Economics in London and the 2018 conference “The Importance of Janos Kornai’s Research for Understanding the Changing Role of the State in the Economy” at Corvinus University in Budapest for valuable comments and suggestions. Olga Pugatšova provided excellent research assistance. Financial support from the Swedish Research Council (Grant 2103-734, Berggren), Torsten Söderberg Foundation (Grant E1-14, Berggren), the Czech Science Foundation (GA ČR) (Grant 16-19934S, Berggren) and the Institute for Research in Economic and Fiscal Issues (IREF) is gratefully acknowledged.

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Correspondence to Niclas Berggren.

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See Tables 5, 6, 7 and 8.

Table 5 Definitions of variables
Table 6 The countries included in the study
Table 7 Debt ratio predictors, including all five areas of the Economic Freedom Index
Table 8 Additional tests

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Berggren, N., Bjørnskov, C. Regulation and government debt. Public Choice 178, 153–178 (2019).

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  • Debt
  • Economic freedom
  • Regulation
  • Markets
  • Stimulus
  • Keynesianism

JEL Classification

  • E02
  • H63