«Department of Economics Working Paper Series Institutional Convergence: Exit or Voice? Joshua C. Hall Working Paper No. 15-40 This paper can be ...»
To test whether the threat of exit plays an important role in explaining convergence in economic freedom over this period I include Exitability from Brown (2014). As
discussed in the introduction, this variable is deﬁned as the “sum of land borders and coastline divided by total geographic area” (Brown, 2014, p. 110). A country’s Exitability score is higher when the length of its border and coastline to its total area is greater. So countries with irregular borders, like Denmark and Panama have relatively high scores (0.17 and 0.039 respectively). A country like Chad with a large land mass and smooth borders has a low score of 0.004.
Between exitability and democracy, we have the ability to test how these structural characteristics contribute to conditional convergence in economic freedom from 1980-2010. Do countries that were similar in terms of democracy in 1980 converge faster than countries that were similar in terms of exit? The coeﬃcient estimates on Democracy and Exitability should be able to shed some light on this question. The ﬁnal variables included in my regressions to explain β-convergence in economic freedom across countries are variables representing legal origins (La Porta et al., 1999, 2008) and ethnic, religious, and linguistic fractionalization (Alesina et al., 2003).
3 Empirical Results
Column (1) of Table 2 presents the unconditional convergence estimates over the 1980 to 2010 period for the EFW index. The negative and statistically signiﬁcant coeﬃcient on 1980 EFW demonstrates that economic freedom has been converging since 1980. To put these estimates in context, consider that Argentina had a score in the EFW index in 1980 of 3.96. According to the unconditional convergence estimates in column (1), the expected annual growth in economic freedom will be 0.0329 − 0.00450 × 3.96 = 0.015 percentage points. This implies that over the 30-year period, economic freedom in Argentina would reach an EFW score of 3.96 × e30×0.015 = 6.21 if it were converging at the average rate. In reality, Argentina had an EFW score of 5.86 in 2010.
Convergence not only means that countries that begin the period with low levels of economic freedom “catch up,” but also that some countries that begin the period with a high level of economic freedom might stagnate institutionally or decline. Once you have eliminated conscription, for example, there is no way to get freer on that component of the EFW. Consider the United States, which began 1980 with an EFW score of 7.92. Again using the estimates from column (1) the expected annualized growth rate in economic freedom for the United States will be 0.0329−0.00450×7.92 = −0.0027 percentage points. After 30 years, this would predict that an EFW score of
7.92 × e30×−0.0027 = 7.29. In reality, the United States had a chain-link EFW score of
7.76 in 2010.
Clearly, it is necessary to look at institutional convergence conditional on other factors such as initial GDP levels and human capital levels. Columns (2) and (3) from Table 2 introduce both of these variables. The natural log of 1980 GDP per capita is positively related to the speed of economic freedom convergence in Column (2) but its statistical signiﬁcance disappears once 1980 Education is introduced in Column (3), with years of secondary education of those over 25 (in 1980) being statistically signiﬁcant at the one percent level. The coeﬃcient on 1980 EFW in Column (3) suggests that a country with a low initial EFW will close the institutional gap with countries at the top of the economic freedom rankings like Hong Kong and Singapore at a rate of 0.5 percent annually, other things being equal.
What about Democracy and Exitability? Table 3 introduces Democracy, Checks, and Exitability one at a time. Democracy as measured by the Polity IV data is not statistically signiﬁcant in any of the speciﬁcations. The same is also true for Checks.
Exitability, however, is positively related to institutional convergence in Column (3) of Table 3. This implies that countries with more uneven borders or longer borders relative to their total area converged more than other countries conditional on initial levels of economic freedom. Other important things to note are that 1980 Education retains its signiﬁcance with the inclusion of these additional variables. Once more
similar countries are taken into account in these conditional convergence speciﬁcations, it is not surprising that the estimated β becomes larger since institutional convergence should be faster for countries that are similar in important structural ways, like having the same degree of Exitability.
In Table 4 we test the robustness of the ﬁndings of Table 3 by including measures of ethnic, language, and religious fractionalization. None of these variables contribute to the convergence of economic freedom over the 1980 to 2010 period in a statistically signiﬁcant manner. Most importantly, however, Exitability retains its statistical significance across all three columns, as does 1980 Education. The estimate of β in column (3) of Table 4 is -0.00648, suggesting that a country with a low EFW score in 1980 will erode the economic freedom gap at a rate of 0.648 percent a year.
Countries fundamentally change their legal systems infrequently, usually as the result of colonization or initial settlement. Table 5 introduces legal origins. Column (1) introduces a dummy variable equal to one if the country follows the British common law tradition. While the sign on this variable is positive, as expected, it is not statistically signiﬁcant. Similarly, when the French legal origin binary variable is introduced in column (2), the sign is negative as expected but statistically insigniﬁcant as well.
Socialist legal origins are introduced in column (3). The variable not only is statistically insigniﬁcant, it has the wrong sign (i.e., is positively related to the change in the natural log of economic freedom from 1980 to 2010.
In terms of our primary variables of interest, Democracy and Exitability, both retain the same conclusion once legal origins are introduced. While the sign on Democracy is now negative, it is statistically indistinguishable from zero. Exitability, on the other hand remains statistically signiﬁcant even with the inclusion of a large number of covariates and the number of countries falling to 81. The same is also true of 1980 Education, which also retains its positive and signiﬁcant relationship with the change
There is a small but growing literature on the determinants of economic freedom. In this paper I have contributed to this literature in two ways. First, I have empirically shown that β-convergence in economic freedom occurred from 1980 to 2010. Countries that started 1980 with low levels of economic freedom are converging on those at the top of the EFW ranking, albeit at a slow rate. Second, I have documented the initial conditions that have contributed to this institutional convergence. For example, countries where individuals 25 years of age and older had more years of secondary schooling in 1980 saw stronger convergence, other things being equal.
Most interestingly, I ﬁnd no evidence of stronger convergence among countries with similar levels of democracy. Exitability, a variable created by Brown (2014) to capture 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 indirect evidence to the importance of “exit” versus “voice” with respect to the question of institutional reform.
The results here suggest several other avenues for future research. First, Exitability is likely to be stronger within a country rather than across countries given the importance of passport controls and immigration restrictions. This suggest that areas within a country with greater Exitability are likely to have higher levels of economic freedom, ceteris paribus. This would be extremely easy to test with any of the subregional economic freedom indices, such as Stansel et al. (2014). This would ﬁt in well with the literature on economic freedom and migration (Ashby, 2007; Cebula et al., 2015). Second, across countries there have been found many determinants of economic freedom that change considerably over a thirty-year period, such as joining ﬁscal or monetary unions (Hall et al., 2011), ﬁnancial crises Rode and Coll (2012), populism (Rode and Revuelta, 2015), or human rights violations (Carden and Lawson, 2010).
The eﬀect of these variables on β-convergence of economic freedom could be analyzed in a panel data format. Finally, β-convergence of economic freedom across U.S. states could estimated to see if states were converging or diverging in terms of institutional quality since 1980.
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