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«Department of Economics Working Paper Series Institutional Convergence: Exit or Voice? Joshua C. Hall Working Paper No. 15-40     This paper can be ...»

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Department of Economics

Working Paper Series

Institutional Convergence: Exit or


Joshua C. Hall

Working Paper No. 15-40



This paper can be found at the College of Business and Economics

Working Paper Series homepage:


Institutional Convergence: Exit or Voice?

Joshua C. Hall∗

West Virginia University

September 2015


There is a small but growing literature on the determinants of economic freedom.

In this paper I contribute to this literature in two ways. First, I empirically show that β-convergence in economic freedom occurred from 1980 to 2010. Countries with low levels of economic freedom in 1980 “catch up” at a rate of 0.7 percent a year on average, ceteris paribus. Second, I document the structural characteristics that contribute to this institutional convergence. My conditional convergence estimates suggest democratic institutions do not contribute to conditional convergence. Exitability, a variable that captures how easy it is for citizens to “vote with their feet” is related to the change in economic freedom from 1980 to 2010 in a statistically significant manner across all specifications. This provides some to the importance of “exit” versus “voice” with respect to the question of institutional change.

JEL Codes: O1, O43, P1, P48 Key Words: Convergence, Economic Freedom, Institutional Change, Democracy, Exit ∗ Department of Economics, College of Business and Economics, PO Box 6025, Morgantown WV 26506-6025; email: joshua.hall@mail.wvu.edu.

Acknowledgments: Hall would like to thank the John Templeton Foundation and the Free Market Institute at Texas Tech University for financial support. Matthew Brown also generously shared his data on exitability. Comments from Russell Sobel, Andrew Young, and Benjamin Powell were very helpful in revising the paper.

1 Introduction While the study of the institutions of economic freedom has a long history in economics going back at least to Adam Smith, the creation of the Economic Freedom of the World (EFW) index by Gwartney et al. (1996) has led a large number of economists to study the effect of economic freedom on social, political, and economic outcomes.1 Hall and Lawson (2014) provide an accounting of a subset of the literature using the EFW index. Focusing only on journals listed in the Social Science Citation Index, they find 402 articles citing the EFW index since 1996. Of those 402 articles, 198 are empirical papers using the EFW index as an explanatory variable. After reading and categorizing all the articles, Hall and Lawson (2014) find that fewer than 4% of the articles surveyed found economic freedom to be associated with a normatively “bad” outcome such as income inequality or obesity.2 The modal paper in the literature using the EFW index focuses on the relationship between economic freedom and growth. This literature almost uniformly shows that an institutional environment more consistent with economic freedom is conducive to long-term growth. An early paper by Gwartney et al. (1999) finds that a one unit change in the EFW index during the 1975-1985 period was associated with an 0.8 percentage point increase in a country’s long term growth rate. Looking at the 1990s and controlling for the effect that economic freedom has on the productivity of investment, Gwartney et al. (2006) find that a one unit change in the EFW index is associated with a 1.5 percentage point increase in growth. A critical survey of the literature by De Haan et al. (2006) finds strong evidence that increases in the EFW index stimulates growth. A 2011 meta-regression analysis by Efendic et al. (2011) finds similar results, Gwartney and Lawson (2003) provides a good overview of the theoretical foundations behind the construction of the EFW index.

Apergis et al. (2014) actually finds bi-directional causality between income inequality and economic freedom.

albeit with some suggestions for improvement within for scholars working in the area.

Other important recent works include Williamson and Mathers (2011), Rode and Coll (2012), and Young and Sheehan (2014).

If the institutions of economic freedom are associated with economic growth, then the next logical question is what causes countries to turn towards or away from market oriented institutions? What exactly are the determinants of economic freedom? While many have been discussed in the literature, a prominent determinant in the literature has been political freedom, or democratic institutions. An early paper in this literature is Dawson (1998), who finds that the level of economic freedom in 1990 is related to political freedom in 1975. Wu and Davis (1999), however, finds no effect of political freedom on economic freedom. More recent work by De Haan and Sturm (2003), Pitlik and Wirth (2003), Lundstr¨m (2005), and Rode and Coll (2012) find that political o freedom or democratic transitions lead to economic freedom. This finding is supported by papers by Dawson (2003), Vega-Gordillo and Alvarez-Arce (2003), and Aixal´ and a Fabro (2009) who present evidence that political freedom granger-causes economic freedom. Sobel and Coyne (2011) find that political and economic institutions are cointegrated and therefore move together through time within a country.3 The case for political freedom has also been backed by within-country case studies, such as the work of Beaulier and Subrick (2006) on Botswana.

Other long-run determinants of the institutions of economic freedom include the historical origins of a country’s laws (La Porta et al., 1999, 2008). Legal origin theory is based on the idea that the British common law created more effective constraints on the power of the executive than did French civil law or Scandinavian or Socialist legal origins (Du, 2010).4 Similarly, countries that are fractionalized in terms of ethnicity, Lawson and Clark (2010) find very few cases of countries with high levels of political freedom and economic freedom.

Nattinger and Hall (2012) find that the legal origins of U.S. states help explain their current levels religion, or language might have lower levels of economic freedom as it is harder for diverse individuals to agree on publicly-provided goods (Alesina et al., 2003). In a paper looking at the long-run determinants of growth, Easterly et al. (2006) find that ethnolinguistic fractionalization affects institutional quality, which in turn influences growth.

An important addition to this literature is the work of Brown (2014). Building off of the work of Diamond (1997) who briefly notes that the shape of Europe versus China could have influenced their institutional development. Europe, unlike China, is geographically indented and has more peninsulas and islands, which created natural barriers to population centralization and control. Brown (2014) links this literature to institutional competition, which requires the ability of citizens to “vote with their feet” (Tiebout, 1956). The closer and individual is in a country to a border, the closer they are to an alternative institutional environment. Brown (2014) creates a variable called ‘exitability” to capture this concept.5 Defined as the sum of land borders and coastline divided by total geographic area, his measure of the ‘exitability’ of a country is a long-run determinant of economic freedom in his empirical work.6 In this paper I add to this literature on the determinants of economic freedom by seeing how specific determinants contributed to institutional convergence from 1980 to

2010. This is an important question for four reasons. First, the question of income convergence across countries has interested economists since the seminal papers by of economic freedom.

In many ways, this variable and they thesis behind it is related to the work of Scott (2009). For more on the relationship between Scott (2009) and competition in governance, see Powell and Nair (2012) and Stringham and Miles (2012).

In addition to this literature on the deep determinants, there are a number of papers on how economic freedom responds to more short-run changes, such as in preferences (Crampton, 2002), foreign aid (Powell and Ryan, 2006; Young and Sheehan, 2014), immigration (Clark et al., 2014), ideas (Leeson et al., 2012), changes in nearby countries (Leeson et al., 2012), internet access (Sheehan and Young, 2014), and joining a monetary and fiscal union (Hall et al., 2011). While important, these are outside the scope of this paper, which focuses on initial conditions and time-invariant determinants such as exitability.

Barro and Sala-i-Martin (1992) and Sala-i-Martin (1996). Second, Knack and Keefer (1995), Knack (1996), and Keefer and Knack (1997) show that convergence depends on the quality of institutions. By better understanding the process of convergence in economic freedom across countries, scholars can better understand the causes of continued income differences across countries. Third, while many studies have documented how various determinants such as political freedom have influenced economic freedom, no studies have quantified how these determinants contribute to the speed at which countries with poor institutional quality catch up to those with good institutional quality.

Finally, my paper contributes to the literature on exit versus voice in determining the quality of institutions (Hirschman, 1978).

My paper proceeds as follows. In Section 2, I describe my data and empirical approach. Section 3 presents the empirical results and Section 4 concludes.

2 Empirical Approach and Data

In the growth literature there is a large body of work on the convergence of incomes across countries or regions (Barro and Sala-i-Martin, 1992; Mankiw et al., 1992). A large portion of this literature focuses on β-convergence. β-convergence is when the partial correlation between growth in income over some time period is negatively related to the initial level of income (Young et al., 2008). While there is a large body of literature on β-convergence in incomes, there is almost zero literature on β-convergence in economic freedom or institutions. A search for papers on institutional convergence yielded three working papers. The first paper, by Savoia and Sen (2012), looks for β-convergence across a number of different institutional measures, including Area 2 of the EFW report. In addition to not using the entire EFW index, the focus of their paper is just testing for convergence since they do not report coefficients for their conditional convergence regressions and employ largely time-invariant data using a panel approach. The second paper by Elert and Halvarsson (2012) does use the entire EFW index as its measure of institutions and finds evidence for convergence using a panel data approach. However, they do not control for any other determinants of the change in economic freedom other than the initial value of economic freedom and the change in economic freedom over the time period.7 Finally, a very recent paper by Boudreaux and Holcombe (2015) looks at institutional convergence for an unbalanced panel of countries from 1970 to 2010.

My measure of economic freedom is the Economic Freedom of the World (EFW) index by Gwartney et al. (2015). A widely used political economy indicator, the EFW

measures the economic freedom present in a country based on 42 variables in five areas:

size of government, legal system and property rights, sound money, freedom to trade internationally, and the regulation of business, credit, and labor. Each component is placed onto 0-10 scale and then aggregated to create a summary measure of economic freedom for the country as a whole. The index contains 157 countries in the most recent year (2013) and a smaller number of countries going back to 1970.8 I choose 1980 as my initial year instead of 1970 as the number of countries rated in 1980 is considerably higher than in 1970, especially for the chain-linked version of the index, which tries to adjust for changes in the components of the index over time. I only employ the chain-link measure of economic freedom in my analysis.

I test for convergence in institutional quality using the following equation:

–  –  –

where X1980 is a matrix of variables that might explain long-run determinants of Another similar recent paper is Heckelman (2015), who tests for σ-convergence in economic freedom.

The data is annual back to 2000 and at five-year intervals from 1970 to 2000.

the change in the natural log of economic freedom from 1980 to 2010. A negative sign on the parameter β implies that there is convergence in economic freedom. Conversely, a positive sign on β would imply divergence in economic freedom from 1980 to 2010 among this sample of countries. My choice of variables to include in the X matrix are motivated by the literature on the determinants of economic freedom discussed in the introduction. GDP per capita in 1980 in constant 2005 U.S. dollars was obtained from World Bank (2015). To capture the the quality of human capital in 1980, I include the average years of secondary schooling for the total population 25 and older in 1980 from Barro and Lee (2013). Descriptive statistics for all non-binary data used in the paper is presented in Table 1.

To see how the initial level of political institutions contributed to the change in economic freedom from 1980 to 2010, I include the level of political democracy in 1980 from Marshall et al. (2014). Widely used as a measure of democracy in a number of studies (Glaeser et al., 2004; Leeson and Dean, 2009), the measure ranges from total autocracy”) to +10 (“total democracy”). This variable captures political openness, the competitiveness of the political process, and constraints on the chief executive (Leeson and Dean, 2009). As an additional political institution variable I also include Checks from Beck et al. (2001). As created by Keefer and Stasavage (2003), Checks is trying to capture the number of veto players in government. This variable is based on whether the executive and legislature are controlled by different parties in a presidential system) or the number of parties in the government coalition (in parliamentary systems). The measure is also adjusted for political rules that make coalitions more cohesive. Countries with a higher score on Checks are expected to have higher economic freedom as the scope for collective activity is limited.

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