The prevention of wide income differentials was an important political objective in prereform Central and Eastern Europe. This objective was widely achieved, however, at the cost of a severe misallocation of resources and economic stagnation. In order to channel resources into more productive uses, many countries have introduced bold, market-oriented reforms aimed at correcting distorted relative prices. Coupled with sustained financial adjustment, these measures have contributed to a marked increase in economic efficiency, and most countries in transition have seen a turnaround in output. However, relative price changes inevitably bring about important distributional effects.1 Very few studies (for example, Stodder (1991)) have tried to estimate the welfare implications of the transition process; they suggest that the potential opportunity costs of rising inequality may be significant. This may be an important reason why some countries, particularly many countries of the former U.S.S.R., have moved rather cautiously in introducing market-oriented reforms.
In this paper, we examine the extent to which income differentials have widened in countries where bold policy measures have been introduced. The Baltic states are especially interesting cases. Following the dissolution of the former U.S.S.R., they embarked on ambitious stabilization and reform programs considerably earlier than other countries. These programs have proved very successful in stabilizing inflation at low levels and creating the necessary preconditions for sustained economic growth.2 In fact, living standards in these countries have started to recover so that they are widely regarded as model cases for a successful transition.
It is important to note that an intertemporal comparison of income differentials is restricted by various factors. Apart from the dubious quality of the Family Budget Surveys, especially in the prereform period, and the presentation of income data in grouped form, there is virtually no information on nonmonetary incomes. The comparison is further restricted by the limited range of consumer goods that was available. As is well-known, privileges played an important role in centrally planned economies. At the same time, however, queuing was an important egalitarian device. While we discuss these caveats in greater detail in this paper, we make no attempt to estimate the extent to which our results might be distorted by these phenomena. Similarly, we do not examine the extent to which the distribution of wealth has been affected by the transformation. With the elimination of the monetary overhang at the onset of this process, monetary assets were largely eroded by high inflation. However, there is very little information on how much wealth has been accumulated by different income groups since then. Presumably, privatization and the repatriation of land have played a particularly important role in the accumulation of wealth, and this will likely be reflected in future income streams.
With these caveats in mind, the rest of the paper is structured as follows. In Section I, we start by examining the distribution of income in the former U.S.S.R. in the prereform period. On the basis of various standard summary statistics of income inequality, we analyze in Section II the degree to which monetary income differentials have widened since then. In Section III, we examine the contributions to inequality of different components of income, whereby we pay particular attention to the distribution of earnings. In Section IV, we discuss the redistributive effects of social benefits and direct taxes, employing Kakwani’s (1995) progressivity index. In Section V, we summarize our findings and draw some conclusions.
Ackland, Robert, and Jane Falkingham, “Economic Transition and the Profile of Poverty in Kyrgyzstan,” in Household Welfare in Central Asia, ed. by Jane Falkingham and others (London: McMillan, 1996, forthcoming).
Ahmad, Ehtisham, “Poverty, Inequality, and Public Policy in Transition Economies,” Public Finance, Vol. 47 (Supplement, 1992), pp. 94–106.
Alexeev, Michael V., and Clifford G. Gaddy, “Income Distribution in the U.S.S.R. in the 1980s,” Review of Income and Wealth, Vol. 39 (March 1993), pp. 23–36.
Atkinson, Anthony B., and John Micklewright, Economic Transformation in Eastern Europe and the Distribution of Income (Cambridge and New York: Cambridge University Press, 1992).
Bergson, Abram, “Income Inequality under Soviet Socialism,” Journal of Economic Literature, Vol. 22 (September 1984), pp. 1052–99.
Blackwood, D.L., and R.G. Lynch, “The Measurement of Inequality and Poverty: A Policy Maker’s Guide to the Literature,” World Development, Vol. 22 (April 1994), pp. 567–78.
Cornelius, Peter K. (1995a), “Cash Benefits and Poverty Alleviation in an Economy in Transition: The Case of Lithuania,” Comparative Economic Studies, Vol. 37 (September 1995), pp. 49–69.
Cornelius, Peter K. (1995b), “Unemployment During Transition: The Experience in the Baltic Countries,” Communist Economies and Economic Transformation, Vol. 7 (December 1995), pp. 445–64.
Hansson, Ardo H., and Jeffrey D. Sachs, “Monetary Institutions: A Comparison of the Experience in the Baltics,” paper presented at Conference on Central Banks in Eastern Europe and the Newly Independent States, University of Chicago Law School, April 22–23, 1994.
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)| false Hansson, Ardo H., and Jeffrey D. Sachs, “Monetary Institutions: A Comparison of the Experience in the Baltics,”paper presented at Conference on Central Banks in Eastern Europe and the Newly Independent States, University of Chicago Law School, April 22–23, 1994.
International Monetary Fund, Fund-Supported Programs, Fiscal Policy, and Income Distribution, IMF Occasional Paper No. 46 (Washington: International Monetary Fund, September 1986).
International Monetary Fund, (1994a), Lithuania, IMF Economic Reviews, No. 6 (Washington: International Monetary Fund, August 1994).
International Monetary Fund, (1994b), Estonia, IMF Economic Reviews, No. 7 (Washington: International Monetary Fund, August 1994).
International Monetary Fund, (1994c), Latvia, IMF Economic Reviews, No. 10 (Washington: International Monetary Fund, November 1994).
International Monetary Fund, “Social Safety Nets for Economic Transition: Options and Recent Experiences,” IMF Paper on Policy Analysis and Assessment 95/3 (Washington: International Monetary Fund, February 1995).
Johnson, Omotunde, and Joanne Salop, “Distributional Aspects of Stabilization Programs in Developing Countries,” Staff Papers, International Monetary Fund, Vol. 27 (March 1980), pp. 1–23.
Kakwani, Nanak C , “Income Inequality, Welfare, and Poverty: An Illustration Using Ukrainian Data,” World Bank Policy Research Working Paper No. 1411 (Washington: World Bank, January 1995).
Kakwani, Nanak C , and N. Podder, “Efficient Estimation of the Lorenz Curve and Associated Inequality Measures from Grouped Observations,” Econometrica, Vol. 44 (January 1976), pp. 137–48.
Milanovic, Branko, “Determinants of Cross-Country Income Inequality: An ‘Augmented’ Kuznets’ Hypothesis,” World Bank Policy Research Working Paper No. 1246 (Washington: World Bank, January 1994).
Milanovic, Branko, “Poverty, Inequality and Social Policy in Transition Economies,” World Bank Policy Research Working Paper No. 1530 (Washington: World Bank, 1995).
Morrisson, Christian, “Income Distribution in East European and Western Countries,” Journal of Comparative Economics, Vol. 8 (June 1984), pp. 121–38.
Saavalainen, Tapio O., “Stabilization in the Baltic Countries: Early Experience,” in Road Maps of the Transition: The Baltics, the Czech Republic, Hungary, and Russia, IMF Occasional Paper No. 127, by Biswajit Banerjee and others (Washington: International Monetary Fund, September 1995).
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)| false Saavalainen, Tapio O., “Stabilization in the Baltic Countries: Early Experience,”in Road Maps of the Transition: The Baltics, the Czech Republic, Hungary, and Russia, IMF Occasional Paper No. 127, by ( Biswajit Banerjeeand others Washington: International Monetary Fund, September 1995).
Sen, Amartya K., “Informational Bases of Alternative Welfare Approaches: Aggregation and Income Distribution,” Journal of Public Economics, Vol. 3 (November 1974), pp. 387–403.
Stodder, James, “Equity-Efficiency Preferences in Poland and the Soviet Union: Order Reversals under the Atkinson Index,” Review of Income and Wealth, Vol. 37 (September 1991), pp. 287–99.
Tarn, Mo-Yin S., and Renze Zhang, “Ranking Income Distributions: The Tradeoff between Efficiency and Equality,” Economica, Vol. 63 (May 1996), pp. 239–52.
Villasefior, Jose A., and Barry C. Arnold, “Elliptical Lorenz Curves,” Journal of Econometrics, Vol. 40 (February 1989), pp. 327–38.
Wiles, Peter J.D., and Stefan Markowski, “Income Distribution under Communism and Capitalism,” Part 1, Soviet Studies, Vol. 22 (January 1971), pp. 344–69; Part 2, Soviet Studies, Vol. 22 (April 1971), pp. 487–511.
Peter K. Cornelius, who holds a doctorate from the University of Göttingen, was the IMF’s Resident Representative in Lithuania when the paper was written. He is a Senior Economist in the European II Department. At the time of writing, Beatrice S. Weder, who received her Ph.D. from the University of Basle, was an Economist in the Fiscal Affairs Department. Currently, she is an Assistant Professor at the University of Basle. This paper has benefited from helpful comments by Julian Berengaut, Jeffrey M. Davis, Sanjeev Gupta, Adalbert Knobl, Vincent Koen, John Odling-Smee, Caroline Van Rijckeghem, and Jeromin Zettelmeyer. Valuable research assistance has been provided by Linda Galantin and Ingrida Grivaciauskaite.
While the liberalization of prices (including factor prices) has probably the most direct impact on the dispersion of income, there are, of course, numerous other channels through which the distribution of income can be affected. These channels include, inter alia, tax and expenditure policies, monetary and exchange rate policies, and trade policies. For a discussion of these channels and the conceptual problems involved in measuring the effects of certain policies on income distribution, see, for example, Johnson and Salop (1980) and International Monetary Fund (1986).
For a review of these programs, see, for example, Hansson and Sachs (1994), Lainela and Sutela (1994), and Saavalainen (1995). On individual country experiences, see International Monetary Fund (1994a, 1994b, and 1994c).
Various approaches have been taken to estimate Lorenz curves from grouped observations (for example, Kakwani and Podder (1976), and Villasenor and Arnold (1989)). However, these approaches do not always work well. Certain groupings of the data can yield distorted estimates.
However, this result should be regarded with caution; it is well-known that an unambiguous ranking of income distributions across countries requires that the Lorenz curves do not intersect. Otherwise, alternative income distributions might rank differently, depending on the precise shape of the households’ common utility function.
These results are in line with those derived by Kakwani (1995), who estimated a separate, continuously differentiable function fitting the data points.
The decile ratios reported in Table 1 refer to the ratio of gross income at the top decile relative to the median (P90) over the gross income at the bottom decile relative to the median (P10).
Notwithstanding these improvements of the household surveys, a number of important problems still remain. See Cornelius (1995a).
The egalitarian effect of queuing was probably largest in the lower and middle range of the income distribution. In contrast, such privileges as access to special shops and preferential treatment in ordinary shops, restaurants, or cafeterias, as well as privileges in connection with foreign currency, housing, official cars, and hospital and holiday resort facilities, benefited mainly people at the upper end of the distribution, estimated at 0.2-0.3 percent of the total population. According to Morrisson (1984), whose estimates were based on rather generous assumptions about the value of such benefits, the prereform Gini coefficients in various Central and Eastern European economies could have been distorted downward by a maximum of 3-4 percentage points.
This supposition seems especially likely in the case of Latvia, where according to the household surveys the mean income per month per head amounted to only $36 in 1994—compared with an average monthly wage of nearly $200.
However, according to a representative multipurpose poverty survey conducted in the Kyrgyz Republic in the fall of 1993, the actual increase in the dispersion of income seems to have been much larger than suggested by official data. Based on this survey, a Gini coefficient of 0.678 was estimated, implying that the distribution had widened by 37 Gini points. For details, see Ackland and Falkingham (forthcoming, 1996).
Based on data from the 1980s, Milanovic (1994) has estimated the average Gini coefficient for the OECD at 0.312.
Recently, this approach was used by Kakwani (1995) to analyze Ukrainian income data.
In Estonia, the percentage of earnings in the lowest decile relative to the median (P10) amounted to 53.7 percent in 1989. Earnings in the top decile relative to the median (P90) were estimated at 172.8 percent. In Latvia, these ratios were estimated at 53.5 percent and 173.6 percent, respectively; in Lithuania, they were estimated at 53.9 percent and 178.7 percent, respectively (Atkinson and Micklewright (1992, Table UE 6)). Earnings in the Baltic countries have been far more dispersed than in other former centrally planned economies. Atkinson and Micklewright (1992, p. 80), for example, report decile ratios of 2.5, 2.6, and 2.8 for former Czechoslovakia, Hungary, and Poland, respectively.
Whereas the Baltic states moved rapidly in liberalizing prices of goods and services, authorities in those countries initially continued to intervene in the labor market. In order to deal with a sharp deterioration in their terms of trade and to break the momentum of inflation expectations, the authorities in Estonia and Latvia imposed a tax on excessive wage increases in the state sector in 1992, while Lithuania implemented a statutory incomes policy. These wage controls have contributed to a significant adjustment in real incomes, which was regarded as indispensable in light of the severe supply shock caused by the sharp rise in imported energy prices (Cornelius (1995b)). Consequently, the wage controls, which inevitably had important distortionary effects, were converted into voluntary guidelines in early 1993.
A similar value (–0.3), for example, has been estimated by Kakwani (1995, Table 10) for Ukraine.
Cornelius (1995a) estimated that cash benefits in Lithuania have reduced the poverty gap by only about 1 percentage point. With perfect targeting of the poor, a three-and-a-half-times larger reduction could have been achieved. However, as Ahmad (1992) argues, detailed means testing is likely to be administratively cumbersome, so that the actual impact of social assistance reforms would probably be considerably smaller.
In 1992, the average expenditure for social security and welfare in a sample of 19 high-income countries was about 12 percent of GDP; the corresponding figure in a sample of 29 middle-income countries was about 5 percent of GDP (International Monetary Fund (1994d)).
For a discussion of reform options for the social safety net in transition economies, see International Monetary Fund (1995).
Ceteris paribus, the distribution of disposable income becomes more equal with higher average tax rates. However, as the average tax rate may be changed without changing the tax elasticity or the tax progressivity, the comparison of the pretax and posttax Lorenz curves as a measure of the redistributive effects of direct taxes should be regarded with considerable caution.