Equality, Participation, Transition: Essays in Honour of Branko Horvat

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Branko Milanović 59 an alternative data base, and I return to the discussion of other results using the Milanović data set. 21 Are our results, and in particular the role of STATE, perhaps driven by the presence of socialist countries and their high share of state-sector employment? Regression (2) is the same as regression (1) except that all socialist countries (7 from Eastern Europe, the Soviet Union, Algeria, China, and Cuba) are dropped. The values of the coefficients change but slightly: the coefficient of STATE becomes, in absolute terms, greater, rising from 0.22 to 0.29 (see also Figure 4.1a where the regression line becomes steeper when socialist countries are omitted) and the coefficient of TRANS becomes smaller (in absolute terms). Both income coefficients increase and their statistical significance rises. The R¯ 2 decreases from 0.7 to 0.63. Overall, the inclusion or exclusion of socialist countries makes little difference. The steeper relationship between STATE and GINI when socialist countries are omitted requires an explanation. It implies that decreases in inequality recorded by socialist countries are small compared with the huge size of the state sector in their economies. Indeed, even from the summary Table 4.1, it can be seen that while the difference in GINI between East European countries and, say, OECD countries is only some 6 Gini points, employment in the state sector is more than four times greater in Eastern Europe. Therefore, when socialist countries are dropped from the sample, a given increase in state-sector share produces larger decreases in GINI. Another issue is whether our STATE variable really adds something to the common practice of using a dummy variable for socialist countries in income distribution studies. We argued above that STATE is more general because it covers the whole spectrum of values from 0 to 100, and thus differentiates also between various capitalist (or even socialist) countries. In regression (3), I introduce both STATE and a socialist dummy variable (otherwise the regression is the same as 1). The regression coefficients are practically unchanged. Only the coefficient of STATE decreases somewhat (from 0.22 to 0.185) but remains highly significant. The dummy variable is statistically insignificant. We can reject the hypothesis that the dummy variable is statistically significant in presence of STATE. Would our results be affected by a somewhat different, narrower, definition of TRANS? In equation 4, I use the TRANS variable which is defined as the share of social cash transfers (pensions, family allowance, unemployment benefits, social assistance) in GDP. 22 The values of the coefficients and the significance levels are almost the same as in regression 1. The R¯ 2 increases to 0.74.
60 Determinants of Income Inequality Finally, do our results depend on the countries’ population structure? It is sometimes argued that the share of transfers in GDP depends largely on the population age structure: ‘older’ countries will tend (everything else being the same) to spend more because of higher pension and health expenditures needed for the other people. 23 In equation 5, I use the ‘old’ TRANS which includes both transfers in kind and cash to express it per equivalent adult, where the weight attached to the people under the age of 14 is 1/2. 24 The significance of the income variables now decreases somewhat, but the equation practically remains the same as regression 1 (except for the change in the value of 4 due to the scaling of TRANS). 25 4.4.3 Is Asia different? From Figure 4.3a, which displays residuals from regression (1), it emerges that in the case of Asian countries, the actual level of inequality is often smaller than predicted. Out of six countries whose actual inequality is 10 Gini points (about one-and-half standard deviations) and more below the predicted inequality, five are Asian (Bangladesh, India, Pakistan, South Korea and Taiwan). 26 Also, out of 17 Asian countries, in only four is the actual inequality higher than the predicted inequality. However, in African and Latin American economies, inequality seems to deviate upward from the predicted values. Several possible explanations for the contrast between Asia and other continents can be adduced. For example, more equal distribution of physical and human capital in Asian countries may result in lower market (pre-government involvement) inequality. Then, even if transfers are small, inequality in disposable income (that is, after transfers and taxes) will be less than in the countries in which the underlying market distribution of income is skewed. Take, for example, Taiwan and Uruguay, both probably the most highly educated and among the most developed countries in their respective regions. The per capita GDPs of these countries are very close ($6500 for Taiwan and $5800 for Uruguay). Uruguay’s share of state-sector workers is twice as high as Taiwan’s (21 vs. 10 per cent), and social transfers are greater (10.5 per cent of GDP vs. 8.1 per cent). Yet Taiwan’s Gini coefficient is 32 and Uruguay’s is 42. But the average number of years of education completed by the population over 25 years of age is 9.2 years for Taiwan and 7.8 years for Uruguay. The high importance of education in Taiwan is also reflected in the structure of social transfers: while total social transfers, in terms of GDP, are smaller in Taiwan, public education expenditures are three times as high: 4.6 per cent of GDP in
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Equality, Participation, Transition
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First published in Great Britain 20
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vi Contents 9 Self-Management, Empl
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List of Figures 02.1 First Law of O
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x Foreword institution most dear to
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Notes on the Contributors Ivo Bića
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xiv Notes on the Contributors membe
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xvi Notes on the Contributors done
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xviii Notes on the Contributors pri
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Introduction: Branko Horvat - Beyon
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xxii Introduction Dame (1978), Univ
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xxiv Introduction theory led him to
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xxvi Introduction though friendly,
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xxviii Introduction The second pape
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xxx Introduction disciplines such a
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Branko Horvat: Select Bibliography
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xxxiv Branko Horvat: Select Bibliog
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xxxvi Branko Horvat: Select Bibliog
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xxxviii Branko Horvat: Select Bibli
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2 Horvat’s Contributions to Econo
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Page 47 and 48: 8 Horvat’s Contributions to Econo
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Page 67 and 68: 28 Egalitarianism On Its Own Thomas
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Page 87 and 88: 4 Determinants of Cross-Country Inc
Page 89 and 90: 50 Determinants of Income Inequalit
Page 95 and 96: 56 GINI GINI 65 60 55 50 45 40 35 3
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Page 101 and 102: Table 4.2 The regressions: dependen
Page 119 and 120: 5 Illyrian Theories of Cooperative
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Page 137 and 138: EMPLOYEE RETURN ONLY PROFIT PROFIT
Page 139 and 140: 100 Employee Participation in Enter
Page 141 and 142: 7 Employee Involvement and the Mode
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110 Employee Involvement and the Mo
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8 Uneasy Symbiosis of a Market Econ
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120 Market Socialism in Yugoslavia
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146 Self-Management, Employee Owner
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Table 9.1 Methods of privatization
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10 Privatization and Enterprise Per
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164 Privatization: Evidence from Es
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11 Growth Theory and Transition Eco
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186 Growth Theory and Transition Ec
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202 Index economic growth - continu
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204 Index Horvat, Branko - continue
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206 Index neoclassical economics -
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208 Index ‘third way’, 88, 104
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Equality, Participation, Transition: Essays in Honour of Branko Horvat

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