{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T20:25:58Z","timestamp":1777407958173,"version":"3.51.4"},"reference-count":0,"publisher":"Cambridge University Press (CUP)","issue":"4","license":[{"start":{"date-parts":[[2002,5,17]],"date-time":"2002-05-17T00:00:00Z","timestamp":1021593600000},"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":[[2002,8]]},"abstract":"<jats:p>Modern time series econometrics involves a diversity of models. \nIn addition to the more traditional vector autoregressive (VAR) \nand autoregressive moving average (ARMA) systems, cointegration \nand unit root models are in widespread use for macroeconomic \ndata, nonlinear and non-Gaussian models are popular for financial \ndata, and long memory models are becoming more common in both \nmacroeconomic and financial applications. Much econometric thought \nrelates to issues of estimation and hypothesis testing, and \nso, in the absence of a usable finite sample theory (as is the \ncase for the models just mentioned), an enormous amount of effort \nhas been given to developing adequate asymptotics for statistical \ninference. There is often a lag between the introduction of \na new model and the development of an asymptotic theory. In \nconsequence, applied econometricians sometimes have to estimate \ntime series models for which no asymptotic theory is available. \nFor instance, multivariate generalized autoregressive conditional \nheteroskedasticity (GARCH) models have been in use in empirical \nresearch for a while, and practitioners have been using asymptotic \nnormality of estimators in this model even though a theoretical \njustification is not available.<\/jats:p>","DOI":"10.1017\/s0266466602004103","type":"journal-article","created":{"date-parts":[[2002,11,14]],"date-time":"2002-11-14T17:02:47Z","timestamp":1037293367000},"page":"993-999","source":"Crossref","is-referenced-by-count":1,"title":["ASYMPTOTIC THEORY OF STATISTICAL INFERENCE FOR TIME \nSERIES"],"prefix":"10.1017","volume":"18","author":[{"given":"Offer","family":"Lieberman","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"56","published-online":{"date-parts":[[2002,5,17]]},"container-title":["Econometric Theory"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S0266466602004103","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,4,1]],"date-time":"2019-04-01T15:28:27Z","timestamp":1554132507000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S0266466602004103\/type\/journal_article"}},"subtitle":["by Masanobu Taniguchi and Yoshihide Kakizawa, Springer, \n2000"],"short-title":[],"issued":{"date-parts":[[2002,5,17]]},"references-count":0,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2002,8]]}},"alternative-id":["S0266466602004103"],"URL":"https:\/\/doi.org\/10.1017\/s0266466602004103","relation":{},"ISSN":["0266-4666","1469-4360"],"issn-type":[{"value":"0266-4666","type":"print"},{"value":"1469-4360","type":"electronic"}],"subject":[],"published":{"date-parts":[[2002,5,17]]}}}