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| Lambert, Dayton M.; Florax, Raymond J.G.M.; Cho, Seong-Hoon. |
| This 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... |
| Tipo: Working or Discussion Paper |
Palavras-chave: Spatial HAC; Semivariogram; Bandwidth; Hedonic model; Research Methods/ Statistical Methods; C13; C31; R21. |
| Ano: 2008 |
URL: http://purl.umn.edu/45964 |
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| Salgado-Ugarte, Isaias H.; Perez-Hernandez, Marco A.. |
| Variable bandwidth kernel density estimators increase the window width at low densities and decrease it where data concentrate. This represents an improvement over the fixed bandwidth kernel density estimators. In this article, we explore the use of one implementation of a variable kernel estimator in conjunction with several rules and procedures for bandwidth selection applied to several real datasets. The considered examples permit us to state that when working with tens or a few hundreds of data observations, least-squares cross-validation bandwidth rarely produces useful estimates; with thousands of observations, this problem can be surpassed. Optimal bandwidth and biased cross-validation (BCV), in general, oversmooth multimodal densities. The... |
| Tipo: Journal Article |
Palavras-chave: Kernel density estimation; Bandwidth; Cross validation; Multimodality test; Research Methods/ Statistical Methods. |
| Ano: 2003 |
URL: http://purl.umn.edu/116063 |
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