Working papers, Department of Economics, WU (Wirtschaftsuniversität Wien)
Manfred M. Fischer
Model uncertainty in matrix exponential spatial growth regression models
() and Philipp Piribauer
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.
Keywords: model comparison, model uncertainty, spatial Durbin matrix exponential growth models, spatial weight structures, European regions; (follow links to similar papers)
JEL-Codes: C11,; C21,; C52,; O47,; O52,; R11; (follow links to similar papers)
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