ISSUES IN SPATIAL DATA ANALYSIS
Version of Record online: 3 FEB 2010
© 2010, Wiley Periodicals, Inc.
Journal of Regional Science
Volume 50, Issue 1, pages 119–141, February 2010
How to Cite
McMillen, D. P. (2010), ISSUES IN SPATIAL DATA ANALYSIS. Journal of Regional Science, 50: 119–141. doi: 10.1111/j.1467-9787.2009.00656.x
- Issue online: 3 FEB 2010
- Version of Record online: 3 FEB 2010
- Received: April 2009; revised: August 2009; accepted: September 2009.
ABSTRACT Misspecified functional forms tend to produce biased estimates and spatially correlated errors. Imposing less structure than standard spatial lag models while being more amenable to large datasets, nonparametric and semiparametric methods offer significant advantages for spatial modeling. Fixed effect estimators have significant advantages when spatial effects are constant within well-defined zones, but their flexibility can produce variable, inefficient estimates while failing to account adequately for smooth spatial trends. Though estimators that are designed to measure treatment effects can potentially control for unobserved variables while eliminating the need to specify a functional form, they may be biased if the variables are not constant within discrete zones.