A nonparametric Bayesian approach for counterfactual prediction with an application to the Japanese private nursing home market
AbstractThis 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 The prediction result implies that the outdated circumstance in this market is harmful for consumers today.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 42154.
Date of creation: 23 Oct 2012
Date of revision:
Nonparametric Bayes; Nonlinear simultaneous equation model; Prediction; Industrial organization; Nursing home; Long-term care in Japan;
Find related papers by JEL classification:
- J14 - Labor and Demographic Economics - - Demographic Economics - - - Economics of the Elderly; Economics of the Handicapped; Non-Labor Market Discrimination
- L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-11-03 (All new papers)
- NEP-ECM-2012-11-03 (Econometrics)
- NEP-FOR-2012-11-03 (Forecasting)
- NEP-HEA-2012-11-03 (Health Economics)
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