Model uncertainty in matrix exponential spatial growth regression models

Manfred M. Fischer, Philipp Piribauer

Publication: Working/Discussion PaperWU Working Paper

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Abstract

This paper considers the problem of model uncertainty associated with variable selection and specification of the spatial weight matrix in spatial growth regression models in general and growth regression models based on the matrix exponential spatial specification in particular. A natural solution, supported by formal probabilistic reasoning, is the use of Bayesian model averaging which assigns probabilities on the model space and deals with model uncertainty by mixing over models, using the posterior model probabilities as weights. This paper proposes to adopt Bayesian information criterion model weights since they have computational advantages over fully Bayesian model weights. The approach is illustrated for both identifying model covariates and unveiling spatial structures present in pan-European growth data.
Original languageEnglish
Place of PublicationVienna
PublisherWU Vienna University of Economics and Business
Publication statusPublished - 1 Oct 2013

Publication series

NameDepartment of Economics Working Paper Series
No.158

WU Working Paper Series

  • Department of Economics Working Paper Series

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