Identification and Estimation of Average Partial Effects in "Irregular" Correlated Random Coefficient Panel Data Models

Econometrica ◽  
2012 ◽  
Vol 80 (5) ◽  
pp. 2105-2152 ◽  
2015 ◽  
Vol 188 (2) ◽  
pp. 421-434 ◽  
Author(s):  
Yichen Gao ◽  
Cong Li ◽  
Zhongwen Liang

2021 ◽  
Author(s):  
Jason Abrevaya ◽  
Yu-Chin Hsu

Summary Nonlinearity and heterogeneity are known to cause difficulties in estimating and interpreting partial effects. This paper provides a systematic characterization of the various partial effects in nonlinear panel data models that might be of interest to empirical researchers. The interpretation of the partial effects depends upon (i) whether the distribution of unobserved heterogeneity is treated as fixed or allowed to vary with covariates, and (ii) whether one is interested in particular covariate values or an average over such values. The characterization covers partial-effects concepts already in the literature but also includes new concepts for partial effects. A simple panel probit design highlights that the different partial effects can be quantitatively very different.


2016 ◽  
Vol 44 (9) ◽  
pp. 1543-1559 ◽  
Author(s):  
Fang Liu ◽  
Peng Zhang ◽  
Ibrahim Erkan ◽  
Dylan S. Small

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