High Dimensional Discrete Choice Models With Interactive Fixed Effects Applied to Causal Inference
含交互固定效应的高维离散选择模型及其因果推断应用
ABSTRACT We propose a two‐step procedure to estimate a high dimensional discrete choice panel with interactive fixed effects where the initial and final estimators are obtained via a nuclear‐norm regularized (NNR) maximum likelihood estimation and post‐NNR iterated estimation, respectively. We apply the method to make counterfactual predictions of choice probabilities. Simulations demonstrate nice finite sample performance in estimation and tests. An illustrative application…