Appendix I. Sample, Data Definition, and Sources
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For valuable comments and suggestions, I am grateful to David Owen, Erik De Vrijer, Peter Winglee, and participants in the seminar held at the International Monetary Fund (IMF). Thanks also to Michael Landesmann for useful comments on an earlier version of this paper. Susanne Winkler provided superb research assistance. The views expressed are those of the author and should not be interpreted as those of the IMF. Responsibility for any errors of fact or judgment that remain in this paper rests entirely with the author.
The CIS region includes Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, the Kyrgyz Republic, Moldova, Mongolia, Russia, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan. Mongolia, which is not a member of the CIS, is included in this group for reasons of geography and similarities in economic structure.
Examples of regional conflicts include the war over Nagorno-Karabakh between Armenia and Azerbaijan (1990–94), secessionist pressures in Georgia and Moldova, and the civil war in Tajikistan (1991–97).
The EBRD market reform index ranges from 1 to 4.3, where 1 represents conditions before reform in a centrally planned economy with dominant state ownership of the means of production, and 4.3 indicates that the country’s structural characteristics are comparable to those prevailing on average in market economies.
Turkmenistan is excluded from the transition sample due to its poor quality of national accounts statistics.
There are two main estimation procedures for panel data, fixed, and random effects. In this paper, the fixed effect method is more appropriate. First, the main interest is in measuring differences between countries. Second, in small samples (relatively shorter time span there may be practical problems preventing parameter estimation when the random effect model is applied; this is not the case with the fixed effect model. Also the Hausman specification test confirmed that the fixed effect model is the more appropriate technique for the data used in this paper.
Based on Monte Carlo simulations, Hauk and Wacziarg (2004) argue that taking account of all the advantages and limitations of the different estimation procedures, the cross-section OLS estimator that averages data over longer periods might be the most efficient.
A high rate of inflation is harmful to growth because it raises the cost of borrowing and thus lowers the rate of capital investment. At the same time, highly variable inflation make it difficult and costly to forecast accurately costs and profits and hence investors and entrepreneurs may be reluctant to undertake new projects. Likewise, given that financial resources in the form of domestic savings and loans are limited, a larger fiscal deficit will mean that more of those limited resources must be devoted to financing the budget defect. Fewer resources will thus be available for private sector investment.
The reform indices are not perfect and their assessment is sometimes influenced by the observed macroeconomic performance, which raises the problem of possible endogeneity.
Wage income earned abroad has become a sizeable component in the balance of payments of several CIS and south-east European economies. Income earned abroad by short-term workers (residents for less than a year) appears in the balance of payments as workers’ compensation under the income account while income earned abroad by migrants (foreign residence for over a year) appears as workers’ remittances under the current account private transfers.
The EBRD reform score and investment are highly correlated with institutional quality and are not used in the same regression equations.
The unfavorable external environment in 1980–82, is reflected in higher international interest rates, higher oil prices, and growth slowdown in industrial countries.
Beck and Laeven, 2006, show that countries that had been longer under socialist government and rely more on natural resources experienced less institution building during the transition process. This finding is robust to using different indicators of institutions building and controlling for other factors that might be associated with institution building.
Easterly and Levine (1997) have shown that per capita GDP growth is inversely related to ethno-linguistic fractionalization in a large sample of countries. In particular, they argued that much of Africa’s growth failure is due to ethnic conflict, partly as a result of absurd borders left by former colonizers. Alesina and others (2003) conclude that ethnic and linguistic fractionalization variables, more so than religious ones, are likely to be important determinants of economic success, both in terms of output and quality of institutions.