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Bootstrap inference under cross-sectional dependence

Conley, Timothy G.; Gonçalves, Sílvia; Kim, Min Seong; … - In: Quantitative Economics 14 (2023) 2, pp. 511-569

variables by the eigendecomposition of a bootstrap kernel. We prove the validity of our method for studentized and unstudentized …In this paper, we introduce a method of generating bootstrap samples with unknown patterns of cross …-sectional/spatial dependence, which we call the spatial dependent wild bootstrap. This method is a spatial counterpart to the wild dependent …

Persistent link: https://www.econbiz.de/10014536878

Bootstrap inference under cross-sectional dependence

Conley, Timothy G.; Gonçalves, Sílvia; Kim, Min Seong; … - In: Quantitative economics : QE ; journal of the … 14 (2023) 2, pp. 511-569

Persistent link: https://www.econbiz.de/10014308576

The welfare benefit of a home’s location: an empirical comparison of spatial and non-spatial model estimates

Koschinsky, Julia; Lozano-Gracia, Nancy; Piras, Gianfranco - In: Journal of Geographical Systems 14 (2012) 3, pp. 319-356

Persistent link: https://www.econbiz.de/10010867936

BANDWIDTH SELECTION FOR SPATIAL HAC AND OTHER ROBUST COVARIANCE ESTIMATORS

Lambert, Dayton M.; Florax, Raymond J.G.M.; Cho, Seong-Hoon - Department of Agricultural Economics, Purdue University - 2008

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...

Persistent link: https://www.econbiz.de/10005704661