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

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Branko Milanović 53 of the countries, the data used, and their sources are given in Annex Tables 1–4 and are available from the author on request. The explanatory variables are the following: INCOMEthe country’s purchasing power 1988 GDP per capita (in thousands of 1988 international dollars); STATEthe percentage of economically active population who work in the state sector (inclusive of government administration); and TRANSthe percentage share of cash and in-kind social transfers (pensions, maternity and family allowances, temporary sick pay, unemployment compensations, education, and health) in the country’s GDP. The dependent variable is the Gini coefficient of disposable income (GINI) 7 expressed for convenience in percentages: Gini coefficient of 30 (instead of 0.3). 8 Two points need to be clarified. An apparent inconsistency may be detected between the inclusion of in-kind transfers like education and health in the TRANS variable, and disposable income inequality (which excludes public in-kind transfers) in the GINI variable. The rationale for this is that transfers in kind over the period with which we are concerned here reflect their long-term importance in the country’s GDP, and that the same or similar level of past spendings on health and education affect the recorded inequality in the mid-1980’s. In other words, while current health and education spending may not have much to do with current inequality, a higher level of such past spending will tend to depress current inequality (for example, more widely spread public education may reduce wage differences). However, one might wonder if that is indeed the case and prefer a more narrow definition of transfers where TRANS includes only current cash transfers: I shall use such a formulation too. 9 Secondly, the analysis is conducted in per capita terms rather than in terms of equivalent consumption units. There are several reasons for this. There are practical ones, because most of the income distribution data for non-OECD countries are expressed in per capita terms. There are also more substantive reasons for using the per capita measure. First, if we require that GINI be reported in equivalent units, should we not require the same for GDP? Second, and the more compelling reason, is that the very idea of equivalency units is country-dependent (or rather, price-structure dependent). If rents, for example, are subsidized, then economies of scale are much less important than if they are not; if education is private, the cost of children is much higher than if education is public and free. 10 In consequence, the use of per capita measures has both practical and substantive advantages.
54 Determinants of Income Inequality Table 4.1 Summary statistics for the five regions Region GINI STATE TRANS INCOME Number of countries OECD 31.2 21.2 22.6 12501 22 E. Europe 24.8 90.0 17.2 6234 8 Africa 52.3 11.3 5.7 1778 16 Asia 41.0 12.6 6.8 4851 17 L. America 49.2 19.3 7.6 4156 17 All the statistics are unweighted averages. Definition of the variables: GINI: Gini coefficient of disposable income for OECD and socialist economies; Gini coefficient of gross income for Africa, Asia and Latin America. Gini coefficients are expressed in per cent. STATE: Share of state-sector workers (general government and state-owned enterprises) in total labour force. TRANS: Share of cash and in-kind social transfers in GDP, in per cent. INCOME: Purchasing power GDP in international dollars for 1988. 4.4.2 Empirical analysis Table 4.1 gives summary statistics for the five regions. The most important conclusions are the following. In terms of income inequality, the five regions have distinctly different averages: inequality is highest in Africa (Gini of 52), closely followed by Latin America (49), then Asia (41), OECD countries (31), while the European socialist economies are the most equal (25). Eastern Europe and the former Soviet Union have a much larger share of state-sector employment than does any other region (90 per cent); the African and Asian samples have the lowest share (11 to 12 per cent of the labour force). The size of social transfers is much greater in OECD and socialist countries than elsewhere. Figures 4.1a–4.1c display the relationship between GINI and the three explanatory variables. We test first equation (1.0). The income variable is quadratic, since we test for the existence of an inverted U-shaped relationship. 3 and 4 are expected to have negative signs. 11 The observations in all the regressions are arranged in GINI 0 1 ln(INCOME) 2[ln(INCOME)] 2 3 STATE 4TRANS (1.0)
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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
Page 41 and 42: 2 Horvat’s Contributions to Econo
Page 49 and 50: 10 Horvat’s Contributions to Econ
Page 55 and 56: 2 Individual Initiative, Entry and
Page 67 and 68: 28 Egalitarianism On Its Own Thomas
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104 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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