Issues in spatial data analysis

Daniel P. McMillen

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)119-141
Number of pages23
JournalJournal of Regional Science
Volume50
Issue number1
DOIs
StatePublished - Feb 2010

ASJC Scopus subject areas

  • Development
  • Environmental Science (miscellaneous)

Fingerprint

Dive into the research topics of 'Issues in spatial data analysis'. Together they form a unique fingerprint.

Cite this