{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T22:14:23Z","timestamp":1790201663937,"version":"4.1.0"},"reference-count":0,"publisher":"Cambridge University Press (CUP)","issue":"5","license":[{"start":{"date-parts":[[2002,7,17]],"date-time":"2002-07-17T00:00:00Z","timestamp":1026864000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Econom. Theory"],"published-print":{"date-parts":[[2002,10]]},"abstract":"<jats:p>The problem of statistical inference for the mean of a time \nseries with possibly heavy tails is considered. We first show \nthat the self-normalized sample mean has a well-defined asymptotic \ndistribution. Subsampling theory is then used to develop \nasymptotically correct confidence intervals for the mean \n<jats:italic>without<\/jats:italic> knowledge (or explicit estimation) either of \nthe dependence characteristics, or of the tail index. Using \na symmetrization technique, we also construct a distribution \nestimator that combines robustness and accuracy: it is higher-order \naccurate in the regular case, while remaining consistent in \nthe heavy tailed case. Some finite-sample simulations confirm \nthe practicality of the proposed methods.<\/jats:p>","DOI":"10.1017\/s026646660218501x","type":"journal-article","created":{"date-parts":[[2003,10,16]],"date-time":"2003-10-16T06:06:57Z","timestamp":1066284417000},"page":"1019-1039","source":"Crossref","is-referenced-by-count":17,"title":["ROBUST INFERENCE FOR THE MEAN IN THE PRESENCE OF SERIAL \nCORRELATION AND HEAVY-TAILED DISTRIBUTIONS"],"prefix":"10.1017","volume":"18","author":[{"given":"Tucker","family":"McElroy","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dimitris N.","family":"Politis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"56","published-online":{"date-parts":[[2002,7,17]]},"container-title":["Econometric Theory"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S026646660218501X","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,6]],"date-time":"2019-05-06T20:32:50Z","timestamp":1557174770000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S026646660218501X\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2002,7,17]]},"references-count":0,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2002,10]]}},"alternative-id":["S026646660218501X"],"URL":"https:\/\/doi.org\/10.1017\/s026646660218501x","relation":{},"ISSN":["0266-4666","1469-4360"],"issn-type":[{"value":"0266-4666","type":"print"},{"value":"1469-4360","type":"electronic"}],"subject":[],"published":{"date-parts":[[2002,7,17]]}}}