{"title":"Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set","authors":"Yongchen Zhao","doi":"10.2139/ssrn.2839879","DOIUrl":null,"url":null,"abstract":"This paper considers the usefulness of diffusion indexes in identifying and predicting business cycle turning points in real time using a large data set from March 2005 to September 2014. We construct a monthly diffusion index, compare several smoothing and signal extraction methods, and evaluate predictions based on our index. We document the performance of diffusion-index-based forecasts and compare it against the performance of dynamic-factor-model-based forecasts. Our findings suggest that diffusion indexes remain relevant and effective in identifying turning points. In addition, we show that a diffusion index could outperform a dynamic factor model in identifying the onset of the 2008 recession in real time.","PeriodicalId":55850,"journal":{"name":"Journal of Business Cycle Research","volume":"47 1","pages":"1-21"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Business Cycle Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.2839879","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
引用次数: 3
Abstract
This paper considers the usefulness of diffusion indexes in identifying and predicting business cycle turning points in real time using a large data set from March 2005 to September 2014. We construct a monthly diffusion index, compare several smoothing and signal extraction methods, and evaluate predictions based on our index. We document the performance of diffusion-index-based forecasts and compare it against the performance of dynamic-factor-model-based forecasts. Our findings suggest that diffusion indexes remain relevant and effective in identifying turning points. In addition, we show that a diffusion index could outperform a dynamic factor model in identifying the onset of the 2008 recession in real time.
期刊介绍：
The Journal of Business Cycle Research promotes the exchange of knowledge and information on theoretical and empirical aspects of economic fluctuations. The range of topics encompasses the methods, analysis, measurement, modeling, monitoring, or forecasting of cyclical fluctuations including but not limited to: business cycles, financial cycles, credit cycles, price fluctuations, sectoral cycles, regional business cycles, international business cycles, the coordination and interaction of cycles, their implications for macroeconomic policy coordination, fiscal federalism and optimal currency areas, or the conduct of monetary policy; as well as statistical approaches to the development of short-term economic statistics and indicators; business tendency, investment, and consumer surveys; use of survey data or cyclical indicators for business cycle analysis.
The journal targets both theoretical and applied economists and econometricians in academic research on economic fluctuations, as well as researchers in central banks and other institutions engaged in economic forecasting and empirical modeling.
The Journal of Business Cycle Research is the successor to the OECD Journal: Journal of Business Cycle Measurement and Analysis which was published by the OECD and CIRET from 2004 to 2015.
Cited as: J Bus Cycle Res
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