EconPapers    
Economics at your fingertips  
 

The Performance of Diagnostic Tests for Spatial Dependence in Linear Regression Models: A Meta-Analysis of Simulation Studies

Raymond Florax and Thomas Graaff ()

Chapter 2 in Advances in Spatial Econometrics, 2004, pp 29-65 from Springer

Abstract: Abstract One of the reasons for A.D. Cliff and J.K. Ord’s 1973 book “Spatial Autocorrelation” achieving the status of a seminal work on spatial statistics and econometrics lies in their careful and lucid treatment of the autocorrelation problem in spatial data series. Cliff and Ord present test statistics for univariate spatial series of categorical (nominal and ordinal) and continuous (interval or ratio scale) data. They extend the use of autocorrelation statistics, specifically Moran’s I (Moran, 1948), to the analysis of regression residuals (see also Cliff and Ord, 1972). The detection of spatial autocorrelation among regression residuals implies either a nonlinear relationship between the dependent and independent variables, the omission of one or more spatially correlated regressors, or the appropriateness of an autoregressive error structure. Ignoring the presence of spatial autocorrelation among the population errors causes ordinary least squares (OLS) to be a biased variance estimator and an inefficient regression coefficient estimator. Anselin (1988b) shows that erroneously omitting the spatially lagged dependent variable from the set of explanatory variables causes the OLS estimator to be biased and inconsistent. Cliff and Ord (1981, p. 197) therefore urge the applied researcher to always apply “some check for autocorrelation,” and take remedial action when necessary.

Keywords: Lagrange Multiplier; Ordinary Little Square; Spatial Autocorrelation; Spatial Dependence; Spatial Error (search for similar items in EconPapers)
Date: 2004
References: Add references at CitEc
Citations: View citations in EconPapers (39)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:adspcp:978-3-662-05617-2_2

Ordering information: This item can be ordered from
http://www.springer.com/9783662056172

DOI: 10.1007/978-3-662-05617-2_2

Access Statistics for this chapter

More chapters in Advances in Spatial Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-23
Handle: RePEc:spr:adspcp:978-3-662-05617-2_2