Electronic Resource
Oxford, UK
:
Blackwell Publishing Ltd
Journal of regional science
35 (1995), S. 0
ISSN:
1467-9787
Source:
Blackwell Publishing Journal Backfiles 1879-2005
Topics:
Geography
,
Economics
Notes:
. The problem of spatial autocorrelation has been ignored in selection-bias models estimated with spatial data. Spatial autocorrelation is a serious problem in these models because the heteroskedasticity with which it commonly is associated causes inconsistent parameter estimates in models with discrete dependent variables. This paper proposes estimators for commonly-employed spatial models with selection bias. A maximum-likelihood estimator is applied to data on land use and values in 1920s Chicago. Evidence of significant heteroskedasticity and selection bias is found.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1111/j.1467-9787.1995.tb01412.x
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