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We consider least squares estimation of the regression parameters and establish asymptotic theories for estimators of both slope coefficients and the threshold parameter. Prediction intervals are also constructed for factor-augmented forecasts. Moreover, we develop a likelihood ratio statistic for tests on the threshold parameter and a sup-Wald test statistic for tests on the presence of threshold effects, respectively. Simulation results show that the proposed estimation method and testing procedures work very well in finite samples. Finally, we demonstrate the usefulness of the proposed model through an application to forecasting stock market returns.<\/jats:p>","DOI":"10.1093\/ectj\/utab011","type":"journal-article","created":{"date-parts":[[2021,4,6]],"date-time":"2021-04-06T23:45:51Z","timestamp":1617752751000},"page":"134-154","source":"Crossref","is-referenced-by-count":6,"title":["Factor-augmented forecasting regressions with threshold effects"],"prefix":"10.1093","volume":"25","author":[{"given":"Yayi","family":"Yan","sequence":"first","affiliation":[{"name":"Department of Econometrics and Business Statistics, Monash University , Wellington Road, Clayton, Melbourne, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tingting","family":"Cheng","sequence":"additional","affiliation":[{"name":"School of Finance, Nankai University , 38 Tongyan Road, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2021,4,6]]},"reference":[{"issue":"7","key":"2023010309111573500_bib1","doi-asserted-by":"crossref","first-page":"1013","DOI":"10.1002\/jae.2406","article-title":"What drives oil prices? 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