identifies the determinants of employment and wages for both skilled and unskilled workers, and through
them of the wage differential, the labour share, and the unemployment rate. We start by estimating these
relationships. Denoting by θit the labour share, by ωit the relative wage, and by uit the
unemployment rate for country i in year t , our strategy will consist of estimating the following
relationships
θ,, = a + α1 ∙χit + aɔ∙ b,t + a ∙γit + a. ∙μ,7 + δ,. + λ, + ε,, (18)
it 0 1 it 2 it 3 it 4 it i t it
+ ++
ω,, = cr∣ + c↑ ∙ χ,t + c ∙ bit + C∙ Y⅛ + C ∙ μ⅛ + δ, + λt + ε,f (19)
it 0 1 it 2 it 3 it 4 it i t it
-±-
uit = dr. + d1 ∙ χit + d9 ∙ bit + d, ∙ γ,∙, + d ∣ ∙ μ,, + δ,∙ + λ, + ε,∙. (20)
it 0 1 it 2 it 3 it 4 it i t it
-++
1 .. Kit I 1 r ∙. 1 1 B Bit ■ ,1
where χit = logl ---------I denotes the log of capital per worker; bit =--- is the unemployment
Λ Hit + Lit ) wιt
benefit replacement rate; γit captures wage-push factors, and will be proxied by union membership rates
in the labour force and by the so-called Kaitz index ( the ratio between the minimum wage and the
median wage); and μit captures additional country specific factors, such as the oil price, educational
attainment, and the tax wedge, that have been included in previous analyses of either of these three
variables. The signs reported below the coefficients to be estimated indicate our theoretical expectations.
When we move to our variable of interest, the personal distribution of income, we cannot
proceed by direct estimation of equation (17). Our expression for the Gini coefficient, although an
identity, captures the main components of the distribution of income. Given the distribution of agents in
the economy, inequality depends on three factors, namely, the way in which total output is divided
between profits and wages, the distribution of wages within the labour force, and welfare provision as
captured by the unemployment benefit. If we had information on all the right-hand-side variables we
could simply decompose the Gini coefficient into its various components, and examine how much wage
inequality or the distribution of wealth contribute to overall income inequality. However, some of the
data required, such as the distribution of wealth or the number of employed individuals at each level of
education, are not available. Therefore we consider the estimation of the following relationship
Giniit =g0 +g1∙θit +g2∙ωit +g3∙uit +g4∙bit +δi +λt +defit +εit (21)
-+ +-
where the signs underlying the coefficient are in accordance with equation (17). We also control for
different definitions used to compute the Gini index (concerning the nature of the recipient unit and the
type of income taken into account) with the variable defit .
The coefficient g1 captures the relative contribution of the factor distribution of income to
personal income inequality, while g2 measures the contribution of the wage differential to overall
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