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Employment Densities, Spatial Autocorrelation, and Subcenters in Large Metropolitan Areas
Author(s) -
McMillen Daniel P.
Publication year - 2004
Publication title -
journal of regional science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.171
H-Index - 79
eISSN - 1467-9787
pISSN - 0022-4146
DOI - 10.1111/j.0022-4146.2004.00335.x
Subject(s) - ordinary least squares , autocorrelation , spatial analysis , econometrics , metropolitan area , nonparametric statistics , statistics , lagrange multiplier , parametric statistics , mathematics , multiplier (economics) , geography , economics , mathematical optimization , archaeology , macroeconomics
Employment density functions are estimated for 62 large metropolitan areas. Estimated gradients are statistically significant for distance from the nearest subcenter as well as for distance from the traditional central business district. Lagrange Multiplier (LM) tests imply significant spatial autocorrelation under highly restrictive ordinary least squares (OLS) specifications. The LM test statistics fall dramatically when the models are estimated using flexible parametric and nonparametric methods. The results serve as a warning that functional form misspecification causes spatial autocorrelation.