Series editor(s): Thomas B. Fomby, R. Carter Hill, Ivan Jeliazkov, Juan Carlos Escanciano, Eric Hillebrand
Subject Area: Economics
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|Title:||SPATIAL LAGS AND SPATIAL ERRORS REVISITED: SOME MONTE CARLO EVIDENCE|
|Volume:||18 Editor(s): James P. Lesage and R. Kelley Pace ISBN: 978-0-76231-148-4 eISBN: 978-1-84950-301-3|
|Citation:||Robin Dubin (2004), SPATIAL LAGS AND SPATIAL ERRORS REVISITED: SOME MONTE CARLO EVIDENCE, in James P. Lesage and R. Kelley Pace (ed.) Spatial and Spatiotemporal Econometrics (Advances in Econometrics, Volume 18), Emerald Group Publishing Limited, pp.75-98|
|DOI:||10.1016/S0731-9053(04)18002-X (Permanent URL)|
|Publisher:||Emerald Group Publishing Limited|
|Article type:||Chapter Item|
There are two schools of thought for modeling spatial dependence: lattice models and geostatistical models. In the former, a weight matrix is used to model the connectedness of the population, while in the latter, the spatial correlations are directly modeled as a function of separation distance. By combining the two approaches, the above estimation problem can be solved. Furthermore, since the geostatistical approach will be used to model the spatial error, the technique of Kriging can be used to improve the predictive ability of the model.
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