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It is reported that the forecast using nondifferenced data tends to be more accurate than that using differenced data. This paper conducts simulations to compare root mean squared forecasting errors of the two competing forecasts. Simulation results indicate that forecasting using nondifferenced data performs better. The advantage of using nondifferenced data is more pronounced when a forecasting horizon is long and the number of factors is large. This paper applies the two competing forecasting methods to 68<jats:italic>I<\/jats:italic>(1) monthly US macroeconomic variables across a range of forecasting horizons and sampling periods. We also provide detailed forecasting analysis on US inflation and industrial production. We find that forecasts using nondifferenced data tend to outperform those using differenced data.<\/jats:p>","DOI":"10.1002\/jae.2777","type":"journal-article","created":{"date-parts":[[2020,5,29]],"date-time":"2020-05-29T10:13:49Z","timestamp":1590747229000},"page":"728-750","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Differencing versus nondifferencing in factor\u2010based forecasting"],"prefix":"10.1002","volume":"35","author":[{"given":"In","family":"Choi","sequence":"first","affiliation":[{"name":"Department of Economics Sogang University Seoul South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hanbat","family":"Jeong","sequence":"additional","affiliation":[{"name":"Department of Economics The Ohio State University Columbus Ohio United States"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2020,7,27]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmoneco.2006.04.006"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/for.957"},{"key":"e_1_2_8_4_1","first-page":"2","article-title":"Are Phillips curves useful for forecasting inflation?","volume":"25","author":"Atkeson A.","year":"2001","journal-title":"Federal Reserve Bank of Minneapolis Quarterly Review"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1111\/1468-0262.00392"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2003.10.022"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1468-0262.2006.00696.x"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1561\/0800000002"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2013.01.009"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.4337\/9780857931023.00017"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10182-006-0219-z"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1017\/S136510050705033X"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2015.02.010"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jspi.2016.10.003"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.1017\/S0266466600009932"},{"key":"e_1_2_8_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2014.06.016"},{"key":"e_1_2_8_17_1","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1080\/07350015.2000.10524869","article-title":"Unit\u2010root tests are useful for selecting forecasting models","volume":"18","author":"Diebold F. 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