Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/185584 
Year of Publication: 
2018
Series/Report no.: 
Tinbergen Institute Discussion Paper No. TI 2018-065/III
Publisher: 
Tinbergen Institute, Amsterdam and Rotterdam
Abstract: 
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.
Subjects: 
Static and Dynamic Panel Data
Binary Response Models
Ordered Response Models
Semiparametric Identification
Partial Identification
JEL: 
C01
C33
C35
Document Type: 
Working Paper

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