Discussion Paper Series in Economics, Department of Economics, Norwegian School of Economics (NHH)
Computing the Jacobian in spatial models: an applied survey.
Abstract: Despite attempts to get around the Jacobian in fitting
spatial econometric models by using GMM and other approximations, it
remains a central problem for maximum likelihood estimation. In principle,
and for smaller data sets, the use of the eigenvalues of the spatial
weights matrix provides a very rapid and satisfactory resolution. For
somewhat larger problems, including those induced in spatial panel and
dyadic (network) problems, solving the eigenproblem is not as attractive,
and a number of alternatives have been proposed. This paper will survey
chosen alternatives, and comment on their relative usefulness.
Keywords: Spatial autoregression; Maximum likelihood estimation; Jacobian computation; Econometric software.; (follow links to similar papers)
JEL-Codes: C13; C21; C87; (follow links to similar papers)
30 pages, August 17, 2010
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