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Semiparametric Estimation of Dynamic Binary Choice Panel Data Models

Fu Ouyang () and Thomas Tao Yang ()
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Fu Ouyang: School of Economics, University of Queensland
Thomas Tao Yang: Australian National University

No 626, Discussion Papers Series from University of Queensland, School of Economics

Abstract: We propose a new approach to the semiparametric analysis of panel data binary choice models with fixed effects and dynamics (lagged dependent variables). The model we consider has the same random utility framework as in Honor´e and Kyriazidou (2000). We demonstrate that, with additional serial dependence conditions on the process of deterministic utility and tail restrictions on the error distribution, the (point) identification of the model can proceed in two steps, and only requires matching the value of an index function of explanatory variables over time, as opposed to that of each explanatory variable. Our identification approach motivates an easily implementable, two-step maximum score (2SMS) procedure – producing estimators whose rates of convergence, in contrast to Honor´e and Kyriazidou’s (2000) methods, are independent of the model dimension. We then derive the asymptotic properties of the 2SMS procedure and propose bootstrap-based distributional approximations for inference. Monte Carlo evidence indicates that our procedure performs adequately in finite samples. We then apply the proposed estimators to study labor market dependence and the effects of health shocks, using data from the Household, Income and Labor Dynamics in Australia (HILDA) survey.

Keywords: Bundle choices; rank estimation; panel data; bootstrap. (search for similar items in EconPapers)
JEL-codes: C13 C14 C35 (search for similar items in EconPapers)
Date: 2020-04-29
New Economics Papers: this item is included in nep-dcm, nep-ore and nep-upt
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