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Activity Number:
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164
- Social Statistics Speed Session
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Type:
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Contributed
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Date/Time:
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Tuesday, August 10, 2021 : 10:00 AM to 11:50 AM
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Sponsor:
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Social Statistics Section
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Abstract #317675
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Title:
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Retrospective Causal Inference via Matrix Completion, with an Evaluation of the Effect of European Integration on Cross-Border Employment
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Author(s):
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Jason Poulos* and Andrea Albanese and Andrea Mercatanti and Fan Li
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Companies:
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Duke University and SAMSI and Luxembourg Institute of Socio-Economic Research (LISER) and Bank of Italy and Duke University
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Keywords:
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Causal inference;
cross-border employment;
European integration;
matrix completion;
panel data
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Abstract:
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We propose a method of retrospective counterfactual imputation in panel data settings with later-treated and always-treated units, but no never-treated units. We use the observed outcomes to impute the counterfactual outcomes of the later-treated using a matrix completion estimator. We propose a novel propensity-score and elapsed-time weighting of the estimator's objective function to correct for differences in the observed covariate and unobserved fixed effects distributions, and elapsed time since treatment between groups. Our methodology is motivated by studying the effect of two milestones of European integration---the Free Movement of persons and the Schengen Agreement---on the share of cross-border workers in sending border regions. We apply the proposed method to the European Labour Force Survey (ELFS) data and provide evidence that opening the border almost doubled the probability of working beyond the border in Eastern European regions.
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Authors who are presenting talks have a * after their name.
