Locally Weighted Maximum Likelihood Estimation: Monte Carlo Evidence and an Application

Daniel McMillen () and John McDonald

Chapter 10 in Advances in Spatial Econometrics, 2004, pp 225-239 from Springer

Abstract: Abstract Even small cities have complicated spatial patterns that are difficult to model adequately with a small number of explanatory variables. Shopping centers, parks, lakes, and the like have local effects on variables such as housing prices, land values, and population density. Proximity to such sites can be included as explanatory variables, but the number of potential sites is large and some may be unknown beforehand. Coefficient estimates are biased when relevant sites are omitted, but are inefficient when unimportant ones are included. Moreover, functional forms are often complex for urban spatial patterns even in the absence of local peaks and valleys.

Keywords: Root Mean Square Error; South Side; Locally Weight; Monte Carlo Result; Density Zoning (search for similar items in EconPapers)
Date: 2004
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DOI: 10.1007/978-3-662-05617-2_10

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