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Nonparametric estimation of dynamic discrete choice models for time series data

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  • Park, Byeong U.
  • Simar, Léopold
  • Zelenyuk, Valentin

Abstract

The non-parametric quasi-likelihood method is generalized to the context of discrete choice models for time series data, where the dynamic aspect is modeled via lags of the discrete dependent variable appearing among regressors. Consistency and asymptotic normality of the estimator for such models in the general case is derived under the assumption of stationarity with strong mixing condition. Monte Carlo examples are used to illustrate performance of the proposed estimator relative to the fully parametric approach. Possible applications for the proposed estimator may include modeling and forecasting of probabilities of whether a subject would get a positive response to a treatment, whether in the next period an economy would enter a recession, or whether a stock market will go down or up, etc.

Suggested Citation

  • Park, Byeong U. & Simar, Léopold & Zelenyuk, Valentin, 2017. "Nonparametric estimation of dynamic discrete choice models for time series data," Computational Statistics & Data Analysis, Elsevier, vol. 108(C), pages 97-120.
  • Handle: RePEc:eee:csdana:v:108:y:2017:i:c:p:97-120
    DOI: 10.1016/j.csda.2016.10.024
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    Cited by:

    1. Byeong U. Park & Leopold Simar & Valentin Zelenyuk, 2017. "Revisiting Forecasting of Recessions via Dynamic Probit for Time Series by Kauppi and Saikkonen (2008)," CEPA Working Papers Series WP032017, School of Economics, University of Queensland, Australia.

    More about this item

    Keywords

    Nonparametric quasi-likelihood; Local-likelihood; Dynamic probit; Forecasting;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory

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