scholarly journals Differencing techniques in semi-parametric panel data varying coefficient models with fixed effects: a Monte Carlo study

2014 ◽  
Vol 30 (3) ◽  
pp. 885-906 ◽  
Author(s):  
Juan M. Rodriguez-Poo ◽  
Alexandra Soberón
Keyword(s):  
Monte Carlo ◽  
Panel Data ◽  
Fixed Effects ◽  
Monte Carlo Study ◽  
Varying Coefficient Models ◽  
Varying Coefficient

Fitting partially linear functional-coefficient panel-data models with Stata

2020 ◽  
Vol 20 (4) ◽  
pp. 976-998
Author(s):  
Kerui Du ◽  
Yonghui Zhang ◽  
Qiankun Zhou
Keyword(s):  
Monte Carlo ◽  
Panel Data ◽  
Fixed Effects ◽  
Linear Functional ◽  
Semiparametric Estimation ◽  
Data Models ◽  
Panel Data Models ◽  
Panel Models ◽  
Partially Linear ◽  
Functional Coefficient

In this article, we describe the implementation of fitting partially linear functional-coefficient panel models with fixed effects proposed by An, Hsiao, and Li [2016, Semiparametric estimation of partially linear varying coefficient panel data models in Essays in Honor of Aman Ullah ( Advances in Econometrics, Volume 36)] and Zhang and Zhou (Forthcoming, Econometric Reviews). Three new commands xtplfc, ivxtplfc, and xtdplfc are introduced and illustrated through Monte Carlo simulations to exemplify the effectiveness of these estimators.

scholarly journals Bias Corrections for Probit and Logit Models with Two-way Fixed Effects

2017 ◽  
Vol 17 (3) ◽  
pp. 517-545 ◽  
Author(s):  
Mario Cruz-Gonzalez ◽  
Iván Fernández-Val ◽  
Martin Weidner
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Panel Data ◽  
Fixed Effects ◽  
Two Dimensions ◽  
Panel Data Models ◽  
Logit Models ◽  
Unobserved Effects ◽  
Parameter Problem ◽  
Bias Corrections

In this article, we present the user-written commands probitfe and logitfe, which fit probit and logit panel-data models with individual and time unobserved effects. Fixed-effects panel-data methods that estimate the unobserved effects can be severely biased because of the incidental parameter problem (Neyman and Scott, 1948, Econometrica 16: 1–32). We tackle this problem using the analytical and jackknife bias corrections derived in Fernández-Val and Weidner (2016, Journal of Econometrics 192: 291–312) for panels where the two dimensions ( N and T) are moderately large. We illustrate the commands with an empirical application to international trade and a Monte Carlo simulation calibrated to this application.

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