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MULTICOLLINEARITY IN REGRESSION MODELS WITH MULTIPLE DISTANCE MEASURES *
Author(s) -
Heikkila Eric
Publication year - 1988
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.1467-9787.1988.tb01087.x
Subject(s) - multicollinearity , econometrics , context (archaeology) , economic rent , regression analysis , regression , statistics , geography , mathematics , computer science , economics , archaeology , microeconomics
. In a polycentric urban context, several urban nodes may exert an influence over land rents. Where this is the case, regression analysis to explain land rents should employ distance variables corresponding to each of the urban nodes. However, these distance measures may be highly intercorrelated, thereby posing a problem of “spatial multicollinearity.” This paper demonstrates that problems arising from spatial multicollinearity can be avoided or substantially lessened by carefully selecting the geographic domain from which observations are drawn.