Large panel data models with cross-sectional dependence: a survey
Alexander Chudik and
M Pesaran ()
No 153, Globalization Institute Working Papers from Federal Reserve Bank of Dallas
This paper provides an overview of the recent literature on estimation and inference in large panel data models with cross-sectional dependence. It reviews panel data models with strictly exogenous regressors as well as dynamic models with weakly exogenous regressors. The paper begins with a review of the concepts of weak and strong cross-sectional dependence, and discusses the exponent of cross-sectional dependence that characterizes the different degrees of cross-sectional dependence. It considers a number of alternative estimators for static and dynamic panel data models, distinguishing between factor and spatial models of cross-sectional dependence. The paper also provides an overview of tests of independence and weak cross-sectional dependence.
JEL-codes: C31 C33 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-geo
Note: Published as: Chudik, Alexander and M. Hashem Pesaran (2015), "Large Panel Data Models with Cross-Sectional Dependence: A Survey," in The Oxford Handbook of Panel Data, ed. Badi H. Baltagi (New York: Oxford University Press), 3-45.
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (29) Track citations by RSS feed
Downloads: (external link)
Working Paper: Large Panel Data Models with Cross-Sectional Dependence: A Survey (2013)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:fip:feddgw:153
Ordering information: This working paper can be ordered from
Access Statistics for this paper
More papers in Globalization Institute Working Papers from Federal Reserve Bank of Dallas Contact information at EDIRC.
Bibliographic data for series maintained by Amy Chapman ().