{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T15:32:09Z","timestamp":1759332729670},"reference-count":0,"publisher":"Cambridge University Press (CUP)","issue":"2","license":[{"start":{"date-parts":[[2001,3,3]],"date-time":"2001-03-03T00:00:00Z","timestamp":983577600000},"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":[[2001,4]]},"abstract":"<jats:p>This paper continues the work of Saikkonen (2001, \n<jats:italic>Econometric Theory<\/jats:italic> 17, 296\u2013326) and develops \nan asymptotic theory of statistical inference in cointegrated \nvector autoregressive models with nonlinear time trends \nin cointegrating relations and general nonlinear parameter \nrestrictions. Inference on parameters in cointegrating \nrelations and short-run dynamics is studied separately. \nIt is shown that Gaussian maximum likelihood estimators \nof parameters in cointegrating relations have mixed normal \nlimiting distributions and that related Wald, Lagrange \nmultiplier, and likelihood ratio tests for general nonlinear \nhypotheses have usual asymptotic chi-square distributions. \nThese results are shown to hold even if parameters in the \nshort-run dynamics are not identified. In that case suitable \nestimators of the information matrix have to be used to \njustify the application of Wald and Lagrange multiplier \ntests, whereas the likelihood ratio test is free of this \ndifficulty. Similar results are also obtained when inference \non parameters in the short-run dynamics is studied, although \nthen Gaussian maximum likelihood estimators have usual \nnormal limiting distributions. All results of the paper \nare proved without assuming existence of second partial \nderivatives of the likelihood function, and in some cases \neven differentiability with respect to nuisance parameters \nis not required.<\/jats:p>","DOI":"10.1017\/s0266466601172038","type":"journal-article","created":{"date-parts":[[2002,7,27]],"date-time":"2002-07-27T09:45:46Z","timestamp":1027763146000},"page":"327-356","source":"Crossref","is-referenced-by-count":10,"title":["STATISTICAL INFERENCE IN COINTEGRATED VECTOR AUTOREGRESSIVE \nMODELS WITH NONLINEAR TIME TRENDS IN COINTEGRATING RELATIONS"],"prefix":"10.1017","volume":"17","author":[{"given":"Pentti","family":"Saikkonen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"56","published-online":{"date-parts":[[2001,3,3]]},"container-title":["Econometric Theory"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S0266466601172038","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,4,8]],"date-time":"2019-04-08T15:29:08Z","timestamp":1554737348000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S0266466601172038\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2001,3,3]]},"references-count":0,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2001,4]]}},"alternative-id":["S0266466601172038"],"URL":"https:\/\/doi.org\/10.1017\/s0266466601172038","relation":{},"ISSN":["0266-4666","1469-4360"],"issn-type":[{"value":"0266-4666","type":"print"},{"value":"1469-4360","type":"electronic"}],"subject":[],"published":{"date-parts":[[2001,3,3]]}}}