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

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  • Sugawara, Shinya

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 The prediction result implies that the outdated circumstance in this market is harmful for consumers today.

Suggested Citation

  • Sugawara, Shinya, 2012. "A nonparametric Bayesian approach for counterfactual prediction with an application to the Japanese private nursing home market," MPRA Paper 42154, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:42154
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    References listed on IDEAS

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    More about this item

    Keywords

    Nonparametric Bayes; Nonlinear simultaneous equation model; Prediction; Industrial organization; Nursing home; Long-term care in Japan;
    All these keywords.

    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

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