Bandwidth Selection For Spatial Hac And Other Robust Covariance Estimators
AbstractThis research note documents estimation procedures and results for an empirical investigation of the performance of the recently developed spatial, heteroskedasticity and autocorrelation consistent (HAC) covariance estimator calibrated with different kernel bandwidths. The empirical example is concerned with a hedonic price model for residential property values. The first bandwidth approach varies an a priori determined plug-in bandwidth criterion. The second method is a data driven cross-validation approach to determine the optimal neighborhood. The third approach uses a robust semivariogram to determine the range over which residuals are spatially correlated. Inference becomes more conservative as the plug-in bandwidth is increased. The data-driven approaches prove valuable because they are capable of identifying the optimal spatial range, which can subsequently be used to inform the choice of an appropriate bandwidth value. In our empirical example, pertaining to a standard spatial model and ditto dataset, the results of the data driven procedures can only be reconciled with relatively high plug-in values (n0.65 or n0.75). The results for the semivariogram and the cross-validation approaches are very similar which, given its computational simplicity, gives the semivariogram approach an edge over the more flexible cross-validation approach.
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Bibliographic InfoPaper provided by Purdue University, College of Agriculture, Department of Agricultural Economics in its series Working Papers with number 08-10.
Length: 25 pages
Date of creation: 2008
Date of revision:
spatial HAC; semivariogram; bandwidth; hedonic model;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
- R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-01-03 (All new papers)
- NEP-ECM-2009-01-03 (Econometrics)
- NEP-GEO-2009-01-03 (Economic Geography)
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