Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/189742 
Year of Publication: 
2017
Series/Report no.: 
cemmap working paper No. CWP31/17
Publisher: 
Centre for Microdata Methods and Practice (cemmap), London
Abstract: 
In nonlinear panel models with fixed effects and fixed-T, the incidental parameter problem poses identification difficulties for structural parameters and partial effects. Existing solutions are model-specific, likelihood-based, impose time homogeneity, or restrict the distribution of unobserved heterogeneity. We provide new identification results for the large class of Fixed Effects Linear Transformation (FELT) models with unknown, time-varying, weakly mono- tone transformation functions. Our results accommodate continuous and discrete outcomes and covariates, require only two time periods and no parametric distributional assumptions. First, we provide a systematic solution to the incidental parameter problem in FELT via binarization, which transforms FELT into many binary choice models. Second, we identify the distribution of counter- factual outcomes and a menu of time-varying partial effects. Third, we obtain new results for nonlinear difference-in-differences with discrete and censored outcomes, and for FELT with random coefficients. Finally, we propose rank- and likelihood-based estimators that achieve Í n rate of convergence.
Subjects: 
panel data
fixed effects
incidental parameter
time-varying transformation model
partial effects
random coefficients
nonlinear difference-in-differences
JEL: 
C14
C23
C41
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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