Data on labour shares are from the OECD Stan Database. We use the standard definition of total
compensation per employee over value added, without any correction for the incomes of the self-
employed. This measure fits well our theoretical definition of the labour share, which comprises only the
income of employed individuals. The wage differential is proxied by the ratio between 1st and the 9th decile
of the earnings distributions (from OECD specific database).11 Standard datasets were used to obtain
information about on labour market institutions, educational attainments, and capital (see Appendix II for
details).
Table 1a reports some descriptive statistics for the main variables in our regressions. While the
potential sample size is 592 observations (16 countries × 37 years), many observations are missing, thus
reducing the available sample to 233 observations, among which the US, the UK, Germany, Sweden, Italy,
and Canada have the most observations. Table 1b reports the descriptive statistics of our entire dataset.
3.3. Determinants of labour market outcomes
Table 2 examines the determinants of the labour share and presents three alternative specifications. The
strongest impact on the labour share is exerted by the capital/labour ratio (as implied by our model),
independently from the specification adopted. In column 1 we find that the labour share is increasing in
union density rates. This effect persists when country fixed effects are taken into account (column 2) but
disappears when cyclical factors are properly accounted for using year fixed effects (column 3). The results
also capture the fact that when minimum wage legislation applies, employment of both skilled and
unskilled workers declines, leading to an increase in the wage share.12 Similarly, the unemployment
benefit also has a positive (but weakly significant) impact on the labour share. We include the price of oil
in national currency in order to capture exogenous shocks to raw materials prices (this variables also
captures the effect of competitive devaluations, and the J-effect on internal inflation).13 Lastly, we have
considered the potential role of the supply of skills. Time series of labour force composition by skills are
not available over a long enough time span, therefore we use proxies derived from measures of
educational attainment. The one reported in the text is the average years of education in the adult
population, but enrolment rates had a similar effect. Once country fixed effects are included, the
education variable displays a negative coefficient, suggesting that as the number of skilled individuals
increases, the unemployment rate of the skilled rises, reducing the incentives to shirk and hence allowing
firms to pay a lower skilled wage.
11 We experimented with both the relative difference and the more conventional measure based on percentile ratio,
using the latter alternative for better econometric performance.
12 Using the level of the minimum wage as an explanatory variable is problematic, it is missing for several countries
(Denmark, Finland, Germany, Italy, Norway, Sweden and UK for most of the sample period). In order not to loose
degrees of freedom, we have replaced the missing observation with a unitary value, which is cleared away with the
country fixed effect.
13 Unfortunately this variable alternates sign depending on whether or not time fixed effects are included. For this
reason, we will discard it as potential instrument.
15