scholarly journals The Exporter Productivity Premium Along the Productivity Distribution: First Evidence from a Quantile Regression Approach for Fixed Effects Panel Data Models

2010 ◽  
Author(s):  
David Powell ◽  
Joachim Wagner
Keyword(s):  
Panel Data ◽  
Quantile Regression ◽  
Fixed Effects ◽  
Data Models ◽  
Panel Data Models ◽  
Productivity Distribution ◽  
Regression Approach

Quantile regression for panel data models with fixed effects under random censoring

2019 ◽  
Vol 49 (18) ◽  
pp. 4430-4445
Author(s):  
Dai Xiaowen ◽  
Jin Libin ◽  
Tian Yuzhu ◽  
Tian Maozai ◽  
Tang Manlai
Keyword(s):  
Panel Data ◽  
Quantile Regression ◽  
Fixed Effects ◽  
Data Models ◽  
Panel Data Models ◽  
Random Censoring

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 TESTING HOMOGENEITY IN PANEL DATA MODELS WITH INTERACTIVE FIXED EFFECTS

2013 ◽  
Vol 29 (6) ◽  
pp. 1079-1135 ◽  
Author(s):  
Liangjun Su ◽  
Qihui Chen
Keyword(s):  
Panel Data ◽  
Fixed Effects ◽  
Data Models ◽  
Development Economic ◽  
Strong Mixing ◽  
Panel Data Models ◽  
Finite Sample ◽  
Test Statistic ◽  
Lm Test ◽  
Interactive Fixed Effects

This paper proposes a residual-based Lagrange Multiplier (LM) test for slope homogeneity in large-dimensional panel data models with interactive fixed effects. We first run the panel regression under the null to obtain the restricted residuals and then use them to construct our LM test statistic. We show that after being appropriately centered and scaled, our test statistic is asymptotically normally distributed under the null and a sequence of Pitman local alternatives. The asymptotic distributional theories are established under fairly general conditions that allow for both lagged dependent variables and conditional heteroskedasticity of unknown form by relying on the concept of conditional strong mixing. To improve the finite-sample performance of the test, we also propose a bootstrap procedure to obtain the bootstrap p-values and justify its validity. Monte Carlo simulations suggest that the test has correct size and satisfactory power. We apply our test to study the Organization for Economic Cooperation and Development economic growth model.

Estimating the Impact of Avian Flu on International Tourism Demand Using Panel Data

2009 ◽  
Vol 15 (3) ◽  
pp. 501-511 ◽  
Author(s):  
Hsiao-I Kuo ◽  
Chia-Lin Chang ◽  
Bing-Wen Huang ◽  
Chi-Chung Chen ◽  
Michael McAleer
Keyword(s):  
Panel Data ◽  
Pandemic Influenza ◽  
Fixed Effects ◽  
Data Models ◽  
International Tourism ◽  
Panel Data Models ◽  
Tourism Demand ◽  
Avian Flu ◽  
Potential Risks ◽  
The Impact

This paper investigates the impacts of avian flu on global and Asian tourism using panel data procedures. Both static and dynamic fixed effects panel data models are adopted to estimate the impacts of this infectious disease. The empirical results from static and dynamic fixed effects panel data models are consistent and indicate that the number of affected poultry outbreaks has significant impacts on the international tourism of global and Asian affected countries. The high mortality rate among humans, the potential of a global flu pandemic and some media frenzy with hype and speculation might adversely affect the images of these infected destinations as a safe tourist destination. Moreover, it was found that the average damage to Asian tourism was more serious, which might have been induced by an ineffective suppression in numerous Asian infected countries. In addition, Asia was the earliest affected region and the area infected most seriously by avian flu, both in humans and in poultry. Since the potential risks and damage arising from avian flu and the subsequent pandemic influenza are much greater than for previous diseases, the need to take necessary precautions in the event of an outbreak of avian flu and pandemic influenza warrants further attention and action in modelling and managing international tourism demand and risk.

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