
The Kitagawa{Oaxaca{Blinder decomposition approach has been widely used to attribute group-level differences in an outcome to dierences in endowment, coefficients, and their interactions. The method has been implemented for Stata in the popular oaxaca command for cross-sectional analyses. In recent decades, however, research questions have been more often focused on the decomposition of group-based differences in change over time, for example, diverging income trajectories, as well as decomposition of change in differences between groups, for example, change in the gender pay gap over time. We review ve existing methods for the decomposition of changes in group means and contribute an extension that takes an interventionist perspective suitable for applications with a clear before{after comparison. These decompositions of levels and changes over time can be implemented using the xtoaxaca command, which works as a postestimation command for different regression commands in Stata. It is built to maximize flexibility in modeling and implements all decomposition techniques presented in this article.
panel data, st0640, longitudinal data, Research and Development/Tech Change/Emerging Technologies, decomposition, xtoaxaca, Oaxaca, Kitagawa, Blinder
panel data, st0640, longitudinal data, Research and Development/Tech Change/Emerging Technologies, decomposition, xtoaxaca, Oaxaca, Kitagawa, Blinder
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