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

76 Determinants of Income Inequality
26 The only other one is Ghana.
27 The data come from the United Nations Development Program (1992).
28 Different formulations using INCOME and EDUC were tried; none dispenses
with the need for a dummy variable.
29 The ‘importance’ is measured by how much GINI is reduced owing to
changes in STATE and TRANS at various levels of income.
30 At some, possibly mythical, extremely low level of income, everyone would
be equally poor. But this is not true at the actual low levels of income
which we observe in our sample.
31 Annex Table 3, as well as Annex Tables 1 and 2 (referred to later in the text)
can be obtained from the author upon request.
32 Consumer subsidies and nomenklatura in-kind benefits are not included in
income. Including an estimate of the latter would make inequality greater
although not by a substantial amount. Using Matthews’s (1978) estimates
for the Soviet Union, and his own estimates for Eastern Europe, Morrisson
(1984) finds that including the monetized value of the nomenklatura benefits
raises the Gini coefficient by 3 to 4 Gini points (see Morrisson, 1984,
Table 2). As for consumer subsidies, they are overall income equalizers since
they were mostly concentrated on goods with low income elasticity of consumption,
like food. Two very careful studies that assessed the impact of
consumer subsidies in Poland (World Bank 1989) and Hungary (Kupa and
Fajth 1990) find that they reduce income inequality by about 2 Gini points.
Similar results were reported for Czechoslovakia (World Bank 1991). The
studies cover all consumer subsidies, including those that are neutral or
pro-rich, like housing, transportation or electricity subsidies. In conclusion,
it seems that the inclusion of consumer subsidies on top of the nomenklatura
perks would probably bring the Gini coefficient close to its reported
value. A more serious problem with income distribution data from socialist
countries exists in the case of the USSR, Bulgaria and Romania. The sampling
procedure in these countries was biased because the selection was
done, not at the place of residence, but at the work-place. The likelihood of
being selected was a function of employment status. There was, in addition,
informal pressure to select the 'average' households (both spouses working
in the state sector, two children and so on) – a kind of model ‘socialist’
household. Pensioners, students, housewives, the unemployed, vagrants
and so on were systematically undersampled. Although the surveys tries to
correct for this by, for example, adding on a quota of pensioners, their
numbers were still relatively few. The procedure led to ‘averaging out’ and
thus an underestimate of inequality. However, this bias was much less or
did not exist in other socialist countries, whose sampling procedures were
comparable to those in the West (see Atkinson and Micklewright 1992, and
Garner, Okrasa, Smeeding and Boyle Torrey 1993).
33 The distinction is, of course, somewhat artificial in the case of countries
with agricultural underemployment.
References
Ahluwalia, M. S. (1976) ‘Inequality, Poverty and Development’, Journal of
Development Economics, no. 3.