Cross section dependence in panel data models 2011-2014

Pesaran, M. Hashem and Holly, Sean (2019). Cross section dependence in panel data models 2011-2014. [Data Collection]. Colchester, Essex: UK Data Archive. 10.5255/UKDA-SN-851454

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Data description (abstract)

Data collected based on secondary sources.
The use of panels where the number of time periods and cross section units varies across applications creates a number of challenges for statisticians and econometricians, as well as for economic theory where network interactions are of interest. One very common form of interaction is spatial. Closeness or geographical contiguity is observable and there is a well developed field of spatial econometrics that deals with these issues. When the interaction is unobservable it may be that there is a common factor at work-global warming, for example, or a world financial crisis with pervasive effects globally. But there can also be more local forms of interaction which in addition to spatial patterns could take place in more abstract spaces such as social or economic networks.These abstract interactions can be both strong and weak.
Strong interactions do not die away as the number of agents increases or as we move away from a 'neighbourhood'. Weak interactions do.This project will address these issues by developing econometric techniques for taking account of these interactions in a wide range of applications in economics.

Data creators:
Creator Name Affiliation ORCID (as URL)
Pesaran M. Hashem University of Southern California
Holly Sean University of Cambridge
Contributors:
Name Affiliation ORCID (as URL)
Smith L. Vanessa University of York
Sponsors: ESRC
Grant reference: ES/I031626/1
Topic classification: Housing and land use
Economics
Keywords: data, metropolitan areas, economic indicators
Project title: Cross Section Dependence in Panel Data Models: Analysis of Short T Panels and Tests of Weak and Strong Cross Section Dependence
Grant holders: M.Hashem Pesaran, Sean Holly
Project dates:
FromTo
1 October 201131 March 2014
Date published: 24 Sep 2014 16:24
Last modified: 19 Nov 2019 13:37

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