A nonparametric Bayesian approach for counterfactual prediction with an application to the Japanese private nursing home market

This paper proposes a new inferential framework for structural econometric models using a nonparametric Bayesian approach. Although estimation methods based on moment conditions can employ a flexible estimation without distributional assumptions, they have difficulty conducting a prediction analysis. I propose a nonparametric Bayesian methodology for an estimation and prediction analysis. My methodology is applied to an empirical analysis of the Japanese private nursing home market. This market has a sticky economic circumstance, and my prediction simulates an intervention that removes this circumstance. The prediction result implies that the outdated circumstance in this market is harmful for consumers today.