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GLS estimates of the regression coefficients using kernel regression and spectral methods are shown to be adaptive, in the sense of having the same asymptotic distribution, to the first order, as GLS estimates based on knowledge of the actual heteroskedasticity and serial correlation. A Monte Carlo experiment about the performance of our estimator is described.<\/jats:p>","DOI":"10.1017\/s0266466600012743","type":"journal-article","created":{"date-parts":[[2010,10,18]],"date-time":"2010-10-18T09:12:04Z","timestamp":1287393124000},"page":"161-187","source":"Crossref","is-referenced-by-count":11,"title":["Adaptive Estimation in Time Serise Regression Models With Heteroskedasticity of Unknown Form"],"prefix":"10.1017","volume":"8","author":[{"given":"Javier","family":"Hidalgo","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"56","published-online":{"date-parts":[[2010,10,18]]},"reference":[{"key":"S0266466600012743_ref016","unstructured":"16. Hidalgo J. Adaptive Estimation in Time Series Regression Models With Heteroscedasticity of Unknown Form. Preprint. 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