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Improved forecasting with leading indicators: the principal covariate index

  • Heij, C.
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    We propose a new method of leading index construction that combines the need for data compression with the objective of forecasting. This so-called principal covariate index is constructed to forecast growth rates of the Composite Coincident Index. The forecast performance is compared with an alternative index based on principal components and with the Composite Leading Index of the Conference Board. The results show that the new index, which takes the forecast objective explicitly into account, provides significant gains over other single-index methods, both in terms of forecast accuracy and in terms of predicting recession probabilities.

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    File URL: http://repub.eur.nl/pub/10348/EI2007-23_paper.pdf
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    Paper provided by Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute in its series Econometric Institute Research Papers with number EI 2007-23.

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    Date of creation: 21 Jun 2007
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    Handle: RePEc:ems:eureir:10348
    Contact details of provider: Postal: Postbus 1738, 3000 DR Rotterdam
    Phone: 31 10 4081111
    Web page: http://www.eur.nl/ese

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    1. Ben S. Bernanke & Jean Boivin, 2001. "Monetary Policy in a Data-Rich Environment," NBER Working Papers 8379, National Bureau of Economic Research, Inc.
    2. Anindya Banerjee & Massimiliano Marcellino, 2003. "Are There Any Reliable Leading Indicators for U.S. Inflation and GDP Growth?," Working Papers 236, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    3. Issler, João Victor & Vahid, Farshid, 2003. "The missing link: Using the NBER recession indicator to construct coincident and leading indices of economic activity," Economics Working Papers (Ensaios Economicos da EPGE) 492, FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
    4. Mototsugu Shintani, 2003. "Nonlinear Forecasting Analysis Using Diffusion Indexes: An Application to Japan," Vanderbilt University Department of Economics Working Papers 0322, Vanderbilt University Department of Economics, revised Apr 2004.
    5. Andrea Carriero & Massimiliano Marcellino, 2007. "A Comparison of Methods for the Construction of Composite Coincident and Leading Indexes for the UK," Working Papers 590, Queen Mary University of London, School of Economics and Finance.
    6. Chauvet, Marcelle & Piger, Jeremy, 2008. "A Comparison of the Real-Time Performance of Business Cycle Dating Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 42-49, January.
    7. Jean Boivin & Serena Ng, 2003. "Are More Data Always Better for Factor Analysis?," NBER Working Papers 9829, National Bureau of Economic Research, Inc.
    8. Bair, Eric & Hastie, Trevor & Paul, Debashis & Tibshirani, Robert, 2006. "Prediction by Supervised Principal Components," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 119-137, March.
    9. Hamilton, James D & Perez-Quiros, Gabriel, 1996. "What Do the Leading Indicators Lead?," The Journal of Business, University of Chicago Press, vol. 69(1), pages 27-49, January.
    10. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2004. "Measuring the effects of monetary policy: a factor-augmented vector autoregressive (FAVAR) approach," Finance and Economics Discussion Series 2004-03, Board of Governors of the Federal Reserve System (U.S.).
    11. Charles L. Evans & Chin Te Liu & Genevieve Pham-Kanter, 2002. "The 2001 recession and the Chicago Fed National Index: identifying business cycle turning points," Economic Perspectives, Federal Reserve Bank of Chicago, issue Q III, pages 26-43.
    12. Jean Boivin & Serena Ng, 2005. "Understanding and Comparing Factor-Based Forecasts," International Journal of Central Banking, International Journal of Central Banking, vol. 1(3), December.
    13. Wesley Clair Mitchell & Arthur F. Burns, 1938. "Statistical Indicators of Cyclical Revivals," NBER Books, National Bureau of Economic Research, Inc, number mitc38-1, May.
    14. Lown, Cara & Morgan, Donald P., 2004. "The Credit Cycle and the Business Cycle: New Findings Using the Loan Officer Opinion Survey," SIFR Research Report Series 27, Institute for Financial Research.
    15. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
    16. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2003. "Do financial variables help forecasting inflation and real activity in the euro area?," Journal of Monetary Economics, Elsevier, vol. 50(6), pages 1243-1255, September.
    17. Marcelle Chauvet & James D. Hamilton, 2005. "Dating Business Cycle Turning Points," NBER Working Papers 11422, National Bureau of Economic Research, Inc.
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