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

58 Determinants of Income Inequality
RESID
20
10
0
–10
–20
0 5000 10000 15000 20000
PPP
Figure 4.2 Residuals from equation 1.0 as a function of INCOME
PPPGDP per capita in 1988 dollars of equal purchasing power parity.
RESIDresiduals from equation 1.0.
which had become available since the first draft of this study was
completed. The Deininger–Squire data set is an unbalanced panel of
inequality measures for 101 countries covering the period from the
1950s onward. Unfortunately for my purpose, it combines both
income and expenditure inequality measures: for a number of countries,
only the distribution of expenditures is available. 18 For each of the
80 countries in my sample, I have selected from the Deininger–Squire
data base, the Gini coefficient and the quintile ratio 19 based on income
(or if unavailable, expenditures) from the mid-1980s. The sample size
declines to 70 due to the fact that 10 countries from my data set are
not included in the Deininger–Squire set. Equation 1 is then rerun first,
over the Gini coefficients from the Deininger–Squire data set (equation
1A), and then over the quintile ratios from the same set (equation 1B).
The signs of all the coefficients are the same as predicted and as in
equation 1. All coefficients except the one for TRANS remain statistically
highly significant, and their values (except for TRANS) change
very little (compare, for example, equations 1 and 1A in Table 4.2). 20
The R¯2 decreases from 0.7 to 0.42, and the constant term becomes
significant at 5 per cent level. The results seem robust to the use of