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Heteroscedasticity resistant robust covariance matrix estimator
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SYSNO ASEP 0365723 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Ostatní články Title Heteroscedasticity resistant robust covariance matrix estimator Author(s) Víšek, Jan Ámos (UTIA-B) ORCID Number of authors 1 Source Title Bulletin of the Czech Econometric Society - ISSN 1212-074X
Roč. 17, č. 27 (2010), s. 33-49Number of pages 17 s. Language eng - English Country CZ - Czech Republic Keywords Regression ; Covariance matrix ; Heteroscedasticity ; Resistant Subject RIV BB - Applied Statistics, Operational Research CEZ AV0Z10750506 - UTIA-B (2005-2011) Annotation It is straightforward that breaking the orthogonality condition implies biased and inconsistent estimates by means of the ordinary least squares. If moreover, the data are contaminated it may significantly worsen the data processing, even if it is performed by instrumental variables or the (scaled) total least squares. That is why the method of instrumental weighted variables based of weighting down order statistics of squared residuals was proposed. The main underlying idea of this method is recalled and discussed. Then it is also recalled that neglecting heteroscedasticity may end up in significantly wrong specification and identification of regression model, just due to wrong evaluation of significance of the explanatory variables. So, if the test of heteroscedasticity rejects the hypothesis of homoscedasticity, we need an estimator of covariance matrix resistant to heteroscedasticity. The proposal of such an estimator is the main result of the paper. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2012
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