An Overview of Dependence in Cross-Section, Time-Series, and Panel Data

In this overview we present a summary of the contents of a collection of latest papers to deal with several aspects of dependence in time-series, cross-section and panels. These papers are collected in this special issue of Econometric Reviews. They include spatial models which usually account for dependence across geographic space as well as social interaction across individuals, see the papers by Baltagi et al. (2013), Liu and Lee (2013), and Drukker et al. (2013). Also factor models, popular in macroeconomics to account for dependence among countries, see the papers by Chudik and Pesaran (2013) and Huang (2013).1 Additionally, a poolability test for large dimensional semiparametric panel data models with cross-section dependence is proposed by Jin and Su (2013),2 and a tour de force on what lessons one learns from panel unit root tests and how deceptive inference can be under cross-section dependence is reviewed by Westerlund and Breitung (2013).

[1]  H. Kelejian,et al.  A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances , 1998 .

[2]  B. Baltagi,et al.  A Generalized Spatial Panel Data Model with Random Effects , 2009, SSRN Electronic Journal.

[3]  Harry H. Kelejian,et al.  A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model , 1999 .

[4]  M. Pesaran,et al.  Econometric Analysis of High Dimensional VARs Featuring a Dominant Unit , 2010, SSRN Electronic Journal.

[5]  Elisa Tosetti,et al.  Large Panels with Common Factors and Spatial Correlations , 2007, SSRN Electronic Journal.

[6]  Stephen G. Donald,et al.  Choosing the Number of Instruments , 2001 .

[7]  M. Pesaran,et al.  Testing for unit roots in heterogeneous panels , 2003 .

[8]  Liangjun Su,et al.  A Nonparametric Poolability Test for Panel Data Models with Cross Section Dependence , 2013 .

[9]  Mudit Kapoor,et al.  Panel data models with spatially correlated error components , 2007 .

[10]  M. Pesaran.  Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure , 2004, SSRN Electronic Journal.

[11]  David M. Drukker,et al.  On Two-Step Estimation of a Spatial Autoregressive Model with Autoregressive Disturbances and Endogenous Regressors , 2013 .

[12]  Xiao Huang.  Nonparametric Estimation in Large Panels with Cross-Sectional Dependence , 2013 .

[13]  M. Pesaran,et al.  Weak and Strong Cross-Section Dependence and Estimation of Large Panels , 2009, SSRN Electronic Journal.

[14]  Lung-Fei Lee,et al.  Two-Stage Least Squares Estimation of Spatial Autoregressive Models with Endogenous Regressors and Many Instruments , 2013 .

[15]  Badi H. Baltagi,et al.  Testing Panel Data Regression Models with Spatial Error Correlation , 2002 .

[16]  Tom Wansbeek,et al.  Cross-Sectional Dependence in Panel Data Analysis , 2012 .

[17]  J. Breitung,et al.  Lessons from a Decade of IPS and LLC , 2013 .

[18]  L. Anselin.  Spatial Econometrics: Methods and Models , 1988 .

[19]  Andrew T. Levin,et al.  Unit root tests in panel data: asymptotic and finite-sample properties , 2002 .