DECOMPOSE: Stata module to compute decompositions of wage differentials

Given the results from two regressions (one for each of two groups), decompose computes several decompositions of the outcome variable differential. The decompositions shows how much of the gap is due to differing endowments between the two groups, and how much is due to discrimination. Usually this is applied to wage differentials using Mincer type earnings equations.

The macro level effects of gender - (un)fair language in Polish

A recent analysis of more than 100 countries found that the extent to which their languages grammatically allowed for an asymmetric treatment of men and women correlated with socio-economic indices of gender inequality (Prewitt-Freilino, Caswell, & Laakso, 2012). In a set of four studies we examine whether the availability of feminine forms as indicated by the most recent dictionaries (1) predicts the actual percentage of women and gender wage gap for all professions registered in Poland; (2) predicts the longitudinal pattern of use of the occupational job-titles; (3) relates to social perception of the sample of 150 professions.

Standard Errors for the Blinder-Oaxaca Decomposition

The decomposition technique introduced by Blinder (1973) and Oaxaca (1973) is widely used to study outcome differences between groups. For example, the technique is commonly applied to the analysis of the gender wage gap. However, despite the procedure's frequent use, very little attention has been paid to the issue of estimating the sampling variances of the decomposition components. We therefore suggest an approach that introduces consistent variance estimators for several variants of the decomposition. The accuracy of the new estimators under ideal conditions is illustrated with the results of a Monte Carlo simulation. As a second check, the estimators are compared to bootstrap results obtained using real data. In contrast to previously proposed statistics, the new method takes into account the extra variation imposed by stochastic regressors.

JMPIERCE: Stata module to perform Juhn-Murphy-Pierce decomposition

jmpierce computes the decomposition of differences between two outcome distributions introduced by Juhn, Murphy and Pierce (1993). Examples are the decomposition of changes in the income distribution over time, the decomposition of male-female wage differentials, or the decomposition of wage inequality differences between countries. This routine was previously circulated as jmp.

New ruralities – old gender dynamics?: A reflection on high-value crop agriculture in the light of the feminisation debates

While a remarkable continuity in smallholder agricultural production has been identified, the shift from subsistence orientation towards more wage dependence appears in a different light when analysed under a gender perspective. "Feminisation" has been a catchphrase to characterise some of these processes; however, the debate has been subject to overgeneralisation, and can only inadequately grasp the gender dynamics in what has been referred to as "new ruralities". Illustrated for high-value crop production as an expression of agricultural transition in the Global South, this contribution offers a critical account of the feminisation thesis. Instead of discarding the notion of feminisation, it advocates a reassessment of its potential as a comprehensive framework against which empirical findings can be reflected. While conventional uses of the feminisation thesis have, in their great majority, come up with the conclusion that for women it can always only get worse, I propose a perspective which reveals gains and risks and how they are shared between men and women as they engage in new agricultural labour markets. This perspective rests on a methodology for case-based, comparative studies developed in this paper as a contribution for assessing the nature of agricultural transition and to investigate the qualitative change associated with new ruralities. A distinctive appreciation of the substance of agricultural change for different members of the rural society – namely men and women, but also different men, and different women – is the premise for overcoming barriers to shared development, and for framing effective governance in the context of global development.

SMITHWELCH: Stata module to compute trend decomposition of outcome differentials

smithwelch computes decompositions of differences in mean outcome differentials. Smith and Welch (1989) used such decomposition techniques in their analysis of the change in the black-white wage differential over time. An alternative application would be the decomposition of country differences in the male-female wage gap.

JMPIERCE2: Stata module to compute trend decomposition of outcome differentials

jmpierce2 computes the decomposition of differences in mean outcome differentials proposed by Juhn, Murphy and Pierce (1991). An example is the decomposition of the change of the black-white or the male-female wage differential over time or the decomposition of differences in the male-female wage differential between countries. This routine was previously circulated as jmp2.