{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T02:57:26Z","timestamp":1768877846729,"version":"3.49.0"},"reference-count":34,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2017,4,9]],"date-time":"2017-04-09T00:00:00Z","timestamp":1491696000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J of Applied Econometrics"],"published-print":{"date-parts":[[2017,9]]},"abstract":"<jats:title>Summary<\/jats:title><jats:p>This paper provides consistent information criteria for the selection of forecasting models that use a subset of both the idiosyncratic and common factor components of a big dataset. This hybrid model approach has been explored by recent empirical studies to relax the strictness of pure factor\u2010augmented model approximations, but no formal model selection procedures have been developed. The main difference to previous factor\u2010augmented model selection procedures is that we must account for estimation error in the idiosyncratic component as well as the factors. Our main contribution is to show the conditions required for selection consistency of a class of information criteria that reflect this additional source of estimation error. We show that existing factor\u2010augmented model selection criteria are inconsistent in circumstances where <jats:italic>N<\/jats:italic> is of larger order than \n<jats:inline-graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"graphic\/jae2567-math-0001.png\" xlink:title=\"urn:x-wiley:jae:media:jae2567:jae2567-math-0001\"\/>, where <jats:italic>N<\/jats:italic> and <jats:italic>T<\/jats:italic> are the cross\u2010section and time series dimensions of the dataset respectively, and that the standard Bayesian information criterion is inconsistent regardless of the relationship between <jats:italic>N<\/jats:italic> and <jats:italic>T<\/jats:italic>. We therefore propose a new set of information criteria that guarantee selection consistency in the presence of estimated idiosyncratic components. The properties of these new criteria are explored through a Monte Carlo simulation study. The paper concludes with an empirical application to long\u2010horizon exchange rate forecasting using a recently proposed model with country\u2010specific idiosyncratic components from a panel of global exchange rates.<\/jats:p>","DOI":"10.1002\/jae.2567","type":"journal-article","created":{"date-parts":[[2017,4,10]],"date-time":"2017-04-10T01:26:37Z","timestamp":1491787597000},"page":"1087-1106","source":"Crossref","is-referenced-by-count":8,"title":["Model selection with estimated factors and idiosyncratic components"],"prefix":"10.1002","volume":"32","author":[{"given":"Jack","family":"Fosten","sequence":"first","affiliation":[{"name":"School of Economics University of East Anglia  Norwich UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2017,4,9]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1198\/073500106000000585"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1111\/1468-0262.00392"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1111\/1468-0262.00273"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1468-0262.2006.00696.x"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/jae.1063"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2005.01.027"},{"key":"e_1_2_9_8_1","doi-asserted-by":"crossref","unstructured":"Brownlees C. 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