inequality. In the highly simplified framework with workers and capitalists, g1 could be interpreted as a
measure of the between-group inequality, where groups are to be defined in accordance to their position
in the production process, while the coefficients g2 , g3 , and g4 can be interpreted as the contribution of
inequality within the group of workers.
Equation (21) cannot be directly estimated, since some variables are potentially endogenous and
could be correlated with unobservable and/or unmeasured variables (such as the degree of risk-aversion
or the level of skilled and unskilled employment) that may also affect personal income inequality through
other channels. In order two obtain an unbiased estimate of the impact of the functional distribution of
income onto the personal distribution (coefficient g1 ), as well as assessing the contribution of earnings
inequality (coefficients g2 and g3 ), we will follow two strategies. One consists in estimating the
simultaneous equation system given by equations (18), (19), (20) and (21), through three-stage least
squares methods. The alternative is to instrument the potentially endogenous variables. Using the
estimates obtained from equations (18), (19) and (20), we can then estimate equation (21) as
Giniit = g о + g ι∙θ (χ it, bn, γ it )+g 2 ∙ω (χ it, b,t, γ it )+g ɜ-u(χ it, b,t, γ it )+g 4 ∙ bt+ δ i +λ t+ df + ε it (22)
-+ +-
Since we are also interested in assessing the overall impact of labour market institutions on
income inequality, we will estimate as well the reduced form equation obtained when we replace (18)-(20)
into equation (21), which yields
Giniit =h0+h1∙χit+h2∙bit+h3∙γit+δi+λt+defit+εit (23)
±±±
The reduced form equation shows that the overall effect of labour market institutions is ambiguous.
Stronger unions tend to increase the labour share and compress the wage distribution, both of which
reduce inequality. However, they also increase the unemployment rate, which raises the Gini coefficient.
An increase in the unemployment benefit raises both the labour share and unemployment, and these
changes have opposite effects on inequality. Lastly, a higher capital-labour ratio unambiguously reduces
inequality as it simultaneously increases the labour share and lowers both the unemployment rate and the
relative wage.
3.2. The data
Our data cover 16 OECD countries over the period 1960-96. Details on the data and their sources are
provided in Appendix II. As is well known, the data on income inequality are problematic and
international comparisons difficult (see Atkinson and Brandolini, 2001). For this reason we use two
different sources for our income inequality measure: one measure is obtained from Brandolini (2003), who
collected comparable measures of income inequality for several OECD countries; the other measure is
obtained from Deininger and Squire (1996), which has become the standard dataset for empirical studies
of income inequality. Brandolini (2003) provides detailed information on the way in which data were
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