{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T00:32:38Z","timestamp":1793147558481,"version":"4.5.0"},"reference-count":0,"publisher":"Cambridge University Press (CUP)","issue":"6","license":[{"start":{"date-parts":[[2001,12,1]],"date-time":"2001-12-01T00:00:00Z","timestamp":1007164800000},"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":[[2001,12]]},"abstract":"<jats:p>This paper, along with the companion paper Forni, Hallin, Lippi, \nand Reichlin (2000, <jats:italic>Review of Economics and Statistics<\/jats:italic> \n82, 540\u2013554), introduces a new model\u2014the <jats:italic>generalized \ndynamic factor model<\/jats:italic>\u2014for the empirical analysis of financial \nand macroeconomic data sets characterized by a large number of observations \nboth cross section and over time. This model provides a generalization \nof the static approximate factor model of Chamberlain (1983, \n<jats:italic>Econometrica<\/jats:italic> 51, 1181\u20131304) and Chamberlain and \nRothschild (1983, <jats:italic>Econometrica<\/jats:italic> 51, 1305\u20131324) \nby allowing serial correlation within and across individual \nprocesses and of the dynamic factor model of Sargent and Sims \n(1977, in C.A. Sims (ed.), <jats:italic>New Methods in Business Cycle \nResearch<\/jats:italic>, pp. 45\u2013109) and Geweke (1977, in D.J. Aigner \n&amp; A.S. Goldberger (eds.), <jats:italic>Latent Variables in \nSocio-Economic Models<\/jats:italic>, pp. 365\u2013383) by allowing for \nnonorthogonal idiosyncratic terms. Whereas the companion paper \nconcentrates on identification and estimation, here we give \na full characterization of the generalized dynamic factor model \nin terms of observable spectral density matrices, thus laying \na firm basis for empirical implementation of the model. Moreover, \nthe common factors are obtained as limits of linear combinations \nof dynamic principal components. Thus the paper reconciles two \nseemingly unrelated statistical constructions.<\/jats:p>","DOI":"10.1017\/s0266466601176048","type":"journal-article","created":{"date-parts":[[2019,9,2]],"date-time":"2019-09-02T12:16:40Z","timestamp":1567426600000},"page":"1113-1141","source":"Crossref","is-referenced-by-count":239,"title":["THE GENERALIZED DYNAMIC FACTOR MODEL: REPRESENTATION THEORY"],"prefix":"10.1017","volume":"17","author":[{"given":"Mario","family":"Forni","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marco","family":"Lippi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"56","published-online":{"date-parts":[[2001,12,1]]},"container-title":["Econometric Theory"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S0266466601176048","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,2]],"date-time":"2019-09-02T12:16:41Z","timestamp":1567426601000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S0266466601176048\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2001,12]]},"references-count":0,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2001,12]]}},"alternative-id":["S0266466601176048"],"URL":"https:\/\/doi.org\/10.1017\/s0266466601176048","relation":{},"ISSN":["0266-4666","1469-4360"],"issn-type":[{"value":"0266-4666","type":"print"},{"value":"1469-4360","type":"electronic"}],"subject":[],"published":{"date-parts":[[2001,12]]}}}