Appendix II: Data sources
Data on income inequality are obtained from two alternative sources: the variable gini1 is obtained from
Brandolini 2003, whereas the variable GINI2 is derived Deininger and Squire 1996 (downloaded on
22/10/1998), by selecting “high quality data” only. In both cases we have controlled for the type of
income (“gross”, “disposable” or “net”) and the type of recipient (“household”, “household equivalent”
or “person equivalent”). As it can be seen by the figure Erreur ! Source du renvoi introuvable. below,
the two indices provide very similar information for Italy, United Kingdom and United States, whereas
diverging for others countries (especially for Nordic countries).
Data on labour shares are obtained from the OECD-Stan dataset, reconstructed backward to the 60’s
from the Research Group at the Bank of France, and made available to us by Emilie Daudey (see Daudey,
2004). They are defined as the ratio between “compensation per employees” and “gross domestic product
(income approach)”, at current prices, for the entire economy. The data can be corrected in order to
include the self-employed (see Gollin, 2002). The most common adjusted measure of the labour share is
obtained by assigning to the self-employed the average earnings of employees. Since we do not find this
assumption very convincing, we stick to the simple labour share. Results with corrected labour share are
available upon request.
Data on unemployment rates are from Nickell and Nunziata 2001, whereas the replacement rate of the
unemployment subsidy is obtained on a biannual base by OECD 2002 (and then replicated for the
missing years). The wage differential is computed as the ratio between the 9th and 1st earnings decile, on
data on earnings distribution from OECD (Trends in earning dispersion database). The Kaitz index
(minimum to median wage) is obtained from OECD (Minimum wage database). For countries were
minimum wages are non-existent (for example for they are replaced by national contract, this variable has
been set equal to unity (Denmark, Finland, Germany, Italy, Norway, Sweden and UK for most of the
sample period). Data on union density (ratio between union membership and active dependent
employment) are from .
The capital stock is derived from the Penn World Tables, Mark 5.6 (see Summer and Heston 1991). Since
data on labour force composition by skills are not available over a long time span, we relied on two
potential proxies derived from educational attainment, i.e. measures of human capital. In the text we have
used the average years of education in the adult population, obtainable from Cohen and Soto 2001.26 The
oil price in national currency is computed from IMF Financial Statistics. Finally, the tax wedge measure is
obtained from Nickell and Nunziata 2001.
26 The alternative measure is given by the population share with “at least some secondary schooling”. Since these
two measures are collinear (correlation coefficient is 0.84), we have chosen the one with the stronger statistical
significance.
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