TY - JOUR
T1 - Estimation and hypothesis testing for nonparametric hedonic house price functions
AU - McMillen, Daniel P
AU - Redfearn, Christian L.
PY - 2010/8
Y1 - 2010/8
N2 - In contrast to the rigid structure of standard parametric hedonic analysis, nonparametric estimators control for misspecified spatial effects while using highly flexible functional forms. Despite these advantages, nonparametric procedures are still not used extensively for spatial data analysis due to perceived difficulties associated with estimation and hypothesis testing. We demonstrate that nonparametric estimation is feasible for large datasets with many independent variables, offering statistical tests of individual covariates and tests of model specification. We show that fixed parameterization of distance to the nearest rapid transit line is a misspecification and that pricing of access to this amenity varies across neighborhoods within Chicago.
AB - In contrast to the rigid structure of standard parametric hedonic analysis, nonparametric estimators control for misspecified spatial effects while using highly flexible functional forms. Despite these advantages, nonparametric procedures are still not used extensively for spatial data analysis due to perceived difficulties associated with estimation and hypothesis testing. We demonstrate that nonparametric estimation is feasible for large datasets with many independent variables, offering statistical tests of individual covariates and tests of model specification. We show that fixed parameterization of distance to the nearest rapid transit line is a misspecification and that pricing of access to this amenity varies across neighborhoods within Chicago.
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U2 - 10.1111/j.1467-9787.2010.00664.x
DO - 10.1111/j.1467-9787.2010.00664.x
M3 - Article
AN - SCOPUS:76349090581
SN - 0022-4146
VL - 50
SP - 712
EP - 733
JO - Journal of Regional Science
JF - Journal of Regional Science
IS - 3
ER -