Semiparametric Identification in Panel Data Discrete Response Models
No 18-065/III, Tinbergen Institute Discussion Papers from Tinbergen Institute
This paper studies semiparametric identification in linear index discrete response panel data models with fixed effects. Departing from the classic binary response static panel data model, this paper examines identification in the binary response dynamic panel data model and the ordered response static panel data model. It is shown that under mild distributional assumptions on the fixed effect and the time-varying unobservables, point-identification fails but informative bounds on the regression coefficients can still be derived. Partial identification is achieved by eliminating the fixed effect and discovering features of the distribution of the unobservable time-varying components that do not depend on the unobserved heterogeneity. Numerical analyses illustrate how the identified set changes as the support of the explanatory variables varies.
Keywords: Static and Dynamic Panel Data; Binary Response Models; Ordered Response Models; Semiparametric Identification; Partial Identification (search for similar items in EconPapers)
JEL-codes: C01 C33 C35 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:tin:wpaper:20180065
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