Oaxaca-Blinder Type Counterfactual Decomposition Methods for Duration Outcomes

Oaxaca-Blinder Type Counterfactual Decomposition Methods for Duration Outcomes. Andrés Felipe García-Suaza
Abstract: Existing inference procedures to perform counterfactual decomposition of the difference between distributional features, applicable when data is fully observed, are not suitable for censored outcomes. This may explain the lack of decomposition exercises for variables related to duration outcomes, typically observed under right censoring. We propose two decomposition methods that consider the presence of this kind of censoring. First, under suitable restrictions on the censoring mechanism, we provide an Oaxaca-Blinder type decomposition method of the mean in a nonparametric context. Consistent estimation of the decomposition components is based on a prior estimator of the joint distribution of duration and covariates. Secondly, we consider a method that makes possible to decompose other distributional features, such as the median or the Gini coefficient. To do so, weaker assumptions on the censoring nature are needed, but it is required to introduce restrictions on the functional form of the conditional distribution of duration given covariates. We provide formal justification for asymptotic inference and study the finite sample performance through Monte Carlo experiments. Finally, we apply the proposed methodology to the analysis of unemployment duration gaps in Spain. This study suggests that factors beyond the workers. socioeconomic characteristics play a relevant role in explaining the difference between several unemployment duration distribution features such as the mean, the probability of being long term unemployed and the Gini coefficient. Universidad EAFIT. Abril 26 de 2017

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