2019/08/16 by Zhentao Shi, Jingyi Huang, Shi, Zhentao +1 · 1 citation
Decision Sciences · Mathematics · #Advanced Causal Inference Techniques #Econometrics (econ.EM) #Efficiency Analysis Using DEA #FOS: Economics and business #Statistical Methods and Inference
paper · pdf · doi:10.48550/arxiv.1908.05894
openalex publication_date 2019/08/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Policy evaluation is central to economic data analysis, but economists mostly work with observational data in view of limited opportunities to carry out controlled experiments. In the potential outcome framework, the panel data approach (Hsiao, Ching and Wan, 2012) constructs the counterfactual by exploiting the correlation between cross-sectional units in panel data. The choice of cross-sectional control units, a key step in its implementation, is nevertheless unresolved in data-rich environment when many possible controls are at the researcher's disposal. We propose the forward selection method to choose control units, and establish validity of the post-selection inference. Our asymptotic framework allows the number of possible controls to grow much faster than the time dimension. The easy-to-implement algorithms and their theoretical guarantee extend the panel data approach to big data settings.