{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,9,10]],"date-time":"2023-09-10T21:42:03Z","timestamp":1694382123625},"reference-count":19,"publisher":"Cambridge University Press (CUP)","issue":"1","license":[{"start":{"date-parts":[[2009,2,11]],"date-time":"2009-02-11T00:00:00Z","timestamp":1234310400000},"content-version":"unspecified","delay-in-days":6557,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Econom. Theory"],"published-print":{"date-parts":[[1991,3]]},"abstract":"<jats:p>This paper deals with the problem of estimating the covariance matrix of the least-squares regression coefficients under heteroskedasticity and\/or autocorrelation of unknown form. We consider an estimator proposed by White [17] and give a relatively simple proof of its consistency. Our proof is based on more easily verifiable conditions than those of White. An alternative estimator with improved small sample properties is also presented.<\/jats:p>","DOI":"10.1017\/s0266466600004229","type":"journal-article","created":{"date-parts":[[2009,3,10]],"date-time":"2009-03-10T11:46:16Z","timestamp":1236685576000},"page":"22-45","source":"Crossref","is-referenced-by-count":15,"title":["Estimation of the Covariance Matrix of the Least-Squares Regression Coefficients When the Disturbance Covariance Matrix Is of Unknown Form"],"prefix":"10.1017","volume":"7","author":[{"given":"Robert W.","family":"Keener","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jan","family":"Kmenta","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Neville C.","family":"Weber","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"56","published-online":{"date-parts":[[2009,2,11]]},"reference":[{"key":"S0266466600004229_ref014","unstructured":"14 Robinson P.M. Automatic generalized least squares. Department of Economics, London School of Economics, London, 1988."},{"key":"S0266466600004229_ref012","first-page":"477","article-title":"Sufficient conditions of geometric mixing for polynomial autoregressive processes-applications to ARM A processes and to bilinear processes","volume":"305","author":"Mokkadem","year":"1987","journal-title":"Compte Rendu"},{"key":"S0266466600004229_ref011","doi-asserted-by":"publisher","DOI":"10.1016\/0304-4076(85)90158-7"},{"key":"S0266466600004229_ref009","volume-title":"Independent and Stationary Sequences of Random Variables","author":"Ibragimov","year":"1971"},{"key":"S0266466600004229_ref004","doi-asserted-by":"publisher","DOI":"10.2307\/1912156"},{"key":"S0266466600004229_ref008","doi-asserted-by":"publisher","DOI":"10.1080\/00401706.1977.10489550"},{"key":"S0266466600004229_ref016","doi-asserted-by":"publisher","DOI":"10.2307\/1912934"},{"key":"S0266466600004229_ref003","unstructured":"3. Calzolari G. & Panattoni L. . A simulation study on FIML covariance matrix. Centro Scientifico IBM, Pisa. Presented at the European Meeting of the Econometric Society, Madrid, 1984."},{"key":"S0266466600004229_ref015","doi-asserted-by":"publisher","DOI":"10.2307\/1911982"},{"key":"S0266466600004229_ref013","doi-asserted-by":"publisher","DOI":"10.2307\/1913610"},{"key":"S0266466600004229_ref010","unstructured":"10 Kool H. A note on consistent estimation of heteroskedasticity and autocorrelated covariance matrices. Department of Econometrics, Free University, Amsterdam, 1988."},{"key":"S0266466600004229_ref001","unstructured":"1. Andrews D.W.K. Heteroskedasticity and autocorrelation consistent cpvariance matrix estimation. 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