Common Correlated Effect Cross-Sectional Dependence Corrections for Non-Linear Conditional Mean Panel Models

2017 ◽  
Author(s):  
Sinem Hacioglu Hoke ◽  
George Kapetanios
Keyword(s):  
Cross Sectional ◽  
Conditional Mean ◽  
Panel Models ◽  
Non Linear ◽  
Cross Sectional Dependence

Extent Pursuit for Cross-Sectional Dependence in Large Panels

2019 ◽  
Author(s):  
Jiti Gao ◽  
Guangming Pan ◽  
Yanrong Yang ◽  
Bo Zhang
Keyword(s):  
Cross Sectional ◽  
Large Panels ◽  
Cross Sectional Dependence

scholarly journals A Review of Software for Spatial Econometrics in R

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1276
Author(s):  
Roger Bivand ◽  
Giovanni Millo ◽  
Gianfranco Piras
Keyword(s):  
Maximum Likelihood ◽  
Spatial Econometrics ◽  
Historical Perspective ◽  
Statistical Computing ◽  
Spatial Econometric ◽  
Cross Sectional ◽  
Panel Models ◽  
Econometric Software ◽  
Generalized Moments

The software for spatial econometrics available in the R system for statistical computing is reviewed. The methods are illustrated in a historical perspective, highlighting the main lines of development and employing historically relevant datasets in the examples. Estimators and tests for spatial cross-sectional and panel models based either on maximum likelihood or on generalized moments methods are presented. The paper is concluded reviewing some current active lines of research in spatial econometric software methods.

Nonparametric panel data regression with parametric cross-sectional dependence

2021 ◽  
Author(s):  
Alexandra Soberon ◽  
Juan M Rodriguez-Poo ◽  
Peter M Robinson
Keyword(s):  
Panel Data ◽  
Monte Carlo Study ◽  
Generalized Least Squares ◽  
Linear Estimator ◽  
Dependence Structure ◽  
Finite Sample ◽  
Cross Sectional ◽  
Panel Data Regression ◽  
Local Linear Estimator ◽  
Cross Sectional Dependence

Abstract In this paper, we consider efficiency improvement in a nonparametric panel data model with cross-sectional dependence. A Generalized Least Squares (GLS)-type estimator is proposed by taking into account this dependence structure. Parameterizing the cross-sectional dependence, a local linear estimator is shown to be dominated by this type of GLS estimator. Also, possible gains in terms of rate of convergence are studied. Asymptotically optimal bandwidth choice is justified. To assess the finite sample performance of the proposed estimators, a Monte Carlo study is carried out. Further, some empirical applications are conducted with the aim of analyzing the implications of the European Monetary Union for its member countries.

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