Labour Market Institutions and the Personal Distribution of Income in the OECD

exogenous variable. The first two columns consider the entire sample, controlling for country and year
effects, while the 3^rd and 4^th column restrict the sample to 6 countries for which we have longer series of
income inequality (US, UK, Germany, Sweden Italy and Canada). The two types of capital have the
strongest correlations with income inequality, with the overall impact being negative for capital equipment
and positive for human capital.²⁵ Two labour market institutions, union density and unemployment
benefit, negatively affect income inequality and have effects of comparable magnitude, while the minimum
wage has a marginally significant, but still negative, effect. Finally, the tax wedge, which probably works as
a proxy of the welfare state size, also exhibits a strong and negative correlation with income inequality.

Table 7 — Determinants of personal income inequality — reduced form — OLS

Robust normalized beta coefficients - * significant at 10%; ** significant at 5%; *** significant at 1%

Controls for changes in definitions and oil price included.

4. Conclusions

The recent literature on the determinants of personal income inequality has highlighted the role of a
number of factors, including output levels, globalisation, educational attainment, and political stability.
Many of these variables help us understand distributional differences in a large cross-section of countries,
but have little explanatory power when trying to understand differences across the rather similar OECD
economies or variations over time. In this paper we have argued that labour market institutions have
played an essential role in explaining differences in inequality within the OECD.

Our analysis highlights the different channels through which labour market institutions affect
distribution. In particular, these institutions affect simultaneously relative wages, the labour share, and the
unemployment rate, all of which then have an impact on the distribution of personal incomes. Because

²⁵ Barro (2000) finds a negative correlation between inequality and secondary school enrolment and a positive
correlation with tertiary enrolment; these findings are difficult to compare with ours, since we have a stock measure,
combining three levels of educational attainment.

27

<<   <   25   26   27   28   29   30   31   >   >>