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  • We propose a strategy of retrospective causal inference in panel data settings where (1) there is a continuous outcome measured before and after a single binary treatment; (2) there exists a group of units exposed to treatment during a subset of periods (switch-treated) and group of units always exposed to treatment (always-treated), but no group that is never exposed to treatment; and (3) the elapsed treatment duration, z, differs across groups. The potential outcomes under treatment for the switch-treated in the pre-treatment period are missing and we impute these values via nuclear-norm regularized least squares using the observed (i.e, factual) outcomes. The imputed values can be interpreted as the counterfactual outcomes of the switch-treated had they been always-treated. Differencing the counterfactual outcomes from the factual outcomes can be interpreted as the effect of not having assigned treatment to the switch-treated in the pre-treatment period. A possible complication for our strategy arises when the evolution of the potential outcomes under treatment for the two groups might not be only influenced by calendar time, but also by z. The latter is particularly important if the treatment effect takes time before stabilizing in a new “steady state” equilibrium. We address this problem by weighting the loss function of the matrix completion estimator so that more weight is placed on the loss for factual outcomes with higher values of z. We apply the proposed strategy to study the impact of the visa policy of the Schengen Area on the labour market of border regions. We first aggregate over 2.2 million individual labour market decisions from the Eurostat Labour Force Survey to the region-level for regions always-treated and switch-treated by the policy during the period of 2004 to 2018. We then estimate the effect of not implementing the policy on the probability of working in any bordering region for switch-treated regions. Preliminary results indicate the share of the labour market working in bordering regions would have been about 0.5% larger had the switch-treated regions adopted the policy prior to 2008. (xsd:string)
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  • https://polmeth2020.org/event/causal-inference. (LFS) (xsd:string)
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  • 2020 (xsd:gyear)
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  • 2020 (xsd:gyear)
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  • english (xsd:string)
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  • Retrospective causal inference via matrix completion, with an evaluation of the effect of European integration on labour market outcomes (xsd:string)
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  • inproceedings (xsd:string)
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  • PolMeth XXXVII: A Virtual Conference (xsd:string)
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  • Bibsonomy (xsd:string)
  • In PolMeth XXXVII: A Virtual Conference, 1-36, 2020 (xsd:string)
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  • 14.-17.6.2020 (xsd:gyear)
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  • European Union Labour Force Survey (EU-LFS) (xsd:string)
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  • 2020 (xsd:string)
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  • LFS (xsd:string)
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  • 36 (xsd:string)
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