{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T13:11:43Z","timestamp":1790687503845,"version":"4.1.0"},"reference-count":21,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2009,3,16]],"date-time":"2009-03-16T00:00:00Z","timestamp":1237161600000},"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":[[2009,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>In forecasting and regression analysis, it is often necessary to select predictors from a large feasible set. When the predictors have no natural ordering, an exhaustive evaluation of all possible combinations of the predictors can be computationally costly. This paper considers \u2018boosting\u2019 as a methodology of selecting the predictors in factor\u2010augmented autoregressions. As some of the predictors are being estimated, we propose a stopping rule for boosting to prevent the model from being overfitted with estimated predictors. We also consider two ways of handling lags of variables: a componentwise approach and a block\u2010wise approach. The best forecasting method will necessarily depend on the data\u2010generating process. Simulations show that for each data type there is one form of boosting that performs quite well. When applied to four key economic variables, some form of boosting is found to outperform the standard factor\u2010augmented forecasts and is far superior to an autoregressive forecast. Copyright \u00a9 2009 John Wiley &amp; Sons, Ltd.<\/jats:p>","DOI":"10.1002\/jae.1063","type":"journal-article","created":{"date-parts":[[2009,3,16]],"date-time":"2009-03-16T09:28:47Z","timestamp":1237195727000},"page":"607-629","source":"Crossref","is-referenced-by-count":127,"title":["Boosting diffusion indices"],"prefix":"10.1002","volume":"24","author":[{"given":"Jushan","family":"Bai","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Serena","family":"Ng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2009,4,27]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1111\/1468-0262.00392"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1111\/1468-0262.00273"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1468-0262.2006.00696.x"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2008.08.010"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4419-0320-4"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1214\/009053606000000092"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1214\/07-STS242"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1198\/016214503000125"},{"key":"e_1_2_8_10_1","doi-asserted-by":"crossref","unstructured":"DeMolC GiannoneD ReichlinL.2006.Forecasting using a large number of predictors: is Bayesian regression a valid alternative to principal components?ECB Working Paper 700.","DOI":"10.2139\/ssrn.947129"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1198\/016214504000002050"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1006\/inco.1995.1136"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1013203451"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1016218223"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1015957397"},{"key":"e_1_2_8_16_1","first-page":"471","article-title":"Boosting for high\u2010multivariate responses in high\u2010dimensional linear regression","volume":"16","author":"Lutz RW","year":"2006","journal-title":"Statistica Sinica"},{"key":"e_1_2_8_17_1","doi-asserted-by":"publisher","DOI":"10.2307\/2648877"},{"key":"e_1_2_8_18_1","doi-asserted-by":"crossref","unstructured":"RossetS.2005.Robust boosting and its relation to bagging. Mimeo IBM.","DOI":"10.1145\/1081870.1081900"},{"key":"e_1_2_8_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF00116037"},{"key":"e_1_2_8_20_1","doi-asserted-by":"publisher","DOI":"10.1198\/016214502388618960"},{"key":"e_1_2_8_21_1","unstructured":"TutzG BinderH.2005.Boosting ridge regression. Mimeo Universitat Munchen."},{"key":"e_1_2_8_22_1","doi-asserted-by":"publisher","DOI":"10.1214\/009053605000000255"}],"container-title":["Journal of Applied Econometrics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fjae.1063","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/jae.1063","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,17]],"date-time":"2023-10-17T19:52:04Z","timestamp":1697572324000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/jae.1063"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009,4,27]]},"references-count":21,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2009,6]]}},"alternative-id":["10.1002\/jae.1063"],"URL":"https:\/\/doi.org\/10.1002\/jae.1063","archive":["Portico"],"relation":{},"ISSN":["0883-7252","1099-1255"],"issn-type":[{"value":"0883-7252","type":"print"},{"value":"1099-1255","type":"electronic"}],"subject":[],"published":{"date-parts":[[2009,4,27]]}}}