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Distribution and Redistribution in Postindustrial Democracies

Published online by Cambridge University Press:  13 June 2011

David Bradley
Keystone Research Center
Evelyne Huber
University of North Carolina at Chapel Hill
Stephanie Moller
University of North Carolina at Chapel Hill
François Nielsen
University of North Carolina at Chapel Hill
John D. Stephens
University of North Carolina at Chapel Hill
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This article analyzes the processes of distribution and redistribution in postindustrial democracies. The authors combine a pooled time-series data base on welfare state effort and its determinants assembled by Huber, Ragin, and Stephens (1997) with data on income distribution assembled in the Luxembourg Income Survey (IJS) archive. In the case of the LIS data, the authors recalculate the microdata in order to remove the distorting influence of pensioners on pretax, pretransfer income distribution. They examine the determinants of two dependent variables: pretax, pretransfer income inequality and the proportional reduction in inequality from pre- to post—tax and transfer inequality. They test hypotheses derived from power resources theory against alternatives derived from the literature on the development of the welfare state and the determinants of income inequality, The results offer strong support for power resources theory, particularly in the case of reduction in inequality. Union density, unemployment, and percentage of female-headed households were the main determinants of pre—tax and transfer inequality (R2 = .64), while leftist government, directly and indirectly through its influence on the size of the welfare state, was found to be by far the strongest determinant of distribution (R2 = .81).

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Copyright © Trustees of Princeton University 2002

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38 Moene and Wallerstein (fn. 13) hypothesize the opposite relationship for certain insurance types of social spending, but because such spending is income related, it is less likely to be redistributive. Since our dependent variable is redistribution, we hypothesize a positive relationship between pre-tax and transfer inequality and redistribution.

39 Note that our dependent variable is household income and includes the households of the unemployed. Thus, the inverse relationship between wage dispersion and unemployment noted by Adrian Wood and Gosta Esping-Anderson would not be expected in our data; see Wood, , North-South Trade, Employment, and Inequality (Oxford: Oxford University Press, 1994)Google Scholar; and Esping-Anderson, , “Postindustrial Cleavage Structures: A Comparison of Evolving Patterns of Social Stratification in Germany, Sweden, and the United States,” in Grusky, David B., ed., Social Stratification in Sociological Perspective, 2d ed. (Boulder, Colo.: Westview Press, 2001)Google Scholar. They explain this inverse relationship with the argument that in countries offering high unemployment benefits, unemployed workers will be more likely to prefer unemployment (with attractive benefits) rather than accept low-paying jobs, while in countries with few benefits workers have no choice but to accept these low-paying jobs.

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63 OECD (fn. 62).

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65 To take one example, Mitchell (fn.17) calculates that taxes and transfers reduce inequality among the population of surveyed Swedes in 1981 by 53 percent, whereas our calculations for the population aged 25–59 show a 34 percent reduction in equality.

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69 The Alderson and Nielsen (fn. 40) results suggest that we should also include the percentage of the population in agriculture as an independent variable. We did test this hypothesis but it did not have the hypothesized effect in our data, which do not reach as far back in time as their data. The agricultural section is very small in all of our countries by this point in time (mean = 5 percent).

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78 These data were made available to us by Torben Iversen.

79 In married-couple households with females listed as the head of the household, LIS recoded the data to have married-couple households always headed by a male.

80 The grouping in this table is based on the character of the welfare state regime, not on political incumbency. The grouping here has no impact on the regressions, where we measure political incumbency as explained in the text.

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89 Even a measure of the progressivity of taxes and transfers would not capture the entire redistrib-utive effect of social democratic governments because of limitations in our dependent variable. Our dependent variable measures only income and not the value of free or subsidized public services. Social democratic governments have expanded a variety of public services, from public health care, child care, and elderly care to training and retraining, access to which is either universal and free or to be paid for according to income. With the partial exception of health care, Christian democratic governments have preferred private delivery of such services—to the extent that the state became involved in supporting them at all—and payments according to insurance principles, which has a less redistributive effect.

90 Huber and Stephens (fn. 7).

91 The total effects of Christian democracy and social democracy are very similar to the results one gets if one drops Taxes and Transfers from equation 3 in Table 4. The standardized coefficients for social democracy and Christian democracy are .74 and —.18, respectively. The latter coefficient is not significant.

92 Van Kersbergen (fn.28).

93 See also Alderson and Nielsen (fn. 40).

94 Huber and Stephens (fn. 7), chap. 5.

95 Huber and Stephens (fn. 7); and Swank (fn. 7).

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102 Huber and Stephens (fn. 7).