Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/64735
Year of Publication: 
2009
Series/Report no.: 
cemmap working paper No. CWP05/09
Publisher: 
Centre for Microdata Methods and Practice (cemmap), London
Abstract: 
This paper gives identification and estimation results for marginal effects in nonlinear panel models. We find that linear fixed effects estimators are not consistent, due in part to marginal effects not being identified. We derive bounds for marginal effects and show that they can tighten rapidly as the number of time series observations grows. We also show in numerical calculations that the bounds may be very tight for small numbers of observations, suggesting they may be useful in practice. We propose two novel inference methods for parameters defined as solutions to linear and nonlinear programs such as marginal effects in multinomial choice models. We show that these methods produce uniformly valid confidence regions in large samples. We give an empirical illustration.
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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