published in: Review of Economics and Statistics, 2008, 90 (2), 290-299
In this paper I present a methodology that uses matching comparisons to explain gender
differences in wages. The approach emphasizes gender differences in the supports of the
distributions of observable characteristics and provides useful insights about the distribution
of the unexplained gender differences in pay. The proposed methodology, a non-parametric
alternative to the Blinder-Oaxaca (BO) wage gap decomposition, does not require the
estimation of earnings equations. It breaks down the gap into four additive elements, two of
which are analogous to the elements of the BO decomposition (but computed only over the
common support of the distributions of characteristics), while the other two account for
differences in the supports. Using data for Peru in the period 1986-2000, I found that this
problem of non-comparability accounts for 23% and 30% of the male and female working
populations respectively. The matching methodology allows us to quantify the effect of
explicitly recognizing these differences in the supports. In this way, the 45% gender wage
gap in Peru is decomposed as: 11% explained by differences in the supports, 6% explained
by differences in the distributions of individual characteristics and the remaining 28% cannot
be explained by differences in observable individuals’ characteristics. Approximately half of
the latter is due to unexplained differences in the highest quintile of the wage distribution.
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