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Non-Parametric Approach to Dynamic Time Series Discrete Choice Models

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Abstract

Dynamic discrete choice models are very important in applied research, frequently used in parametric contexts, and here we develop a non-parametric approach to such models. The main contribution of our work is generalization of the non-parametric quasi-likelihood method to the context that allows for time series models, and in particular with lags of the (discrete) dependent variable appearing among regressors. We show consistency and asymptotic normality of the estimator for such models and illustrate it with simulated and real data examples.

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  • Byeong U. Park & Léopold Simar & Valentin Zelenyuk, 2013. "Non-Parametric Approach to Dynamic Time Series Discrete Choice Models," CEPA Working Papers Series WP092013, School of Economics, University of Queensland, Australia.
    • Handle: RePEc:qld:uqcepa:91
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    File URL: https://economics.uq.edu.au/files/5142/WP092013.pdf
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