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

Shinya Sugawara ()

MPRA Paper from University Library of Munich, Germany

Abstract: 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 The prediction result implies that the outdated circumstance in this market is harmful for consumers today.

Keywords: Nonparametric Bayes; Nonlinear simultaneous equation model; Prediction; Industrial organization; Nursing home; Long-term care in Japan (search for similar items in EconPapers)
JEL-codes: C11 J14 L11 (search for similar items in EconPapers)
Date: 2012-10-23
New Economics Papers: this item is included in nep-ecm, nep-for and nep-hea
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