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Diffusion Indexes

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Author Info
James H. Stock
Mark W. Watson

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Abstract

This paper considers forecasting a single time series using more predictors than there are time series observations. The approach is to construct a relatively few indexes, akin to diffusion indexes, which are weighted averages of the predictors, using an approximate dynamic factor model. Estimation is discussed for balanced and unbalanced panels. The estimated dynamic factors are (uniformly) consistent, even in the presence of time varying parameters and/or data contamination, and forecasts based on the estimated factors are efficient. In an application to forecasting U.S. inflation and industrial production using 224 monthly time series, these forecasts outperform various state-of-the-art benchmark models.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 6702.

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Date of creation: Aug 1998
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Publication status: published as Stock, James H. and Mark W. Watson. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business and Economic Statistics, 2002, v20(2,Apr), 147-162.
Handle: RePEc:nbr:nberwo:6702

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Find related papers by JEL classification:
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models
E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation

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  1. Forni, Mario & Reichlin, Lucrezia, 1997. "National Policies and Local Economies: Europe and the United States," CEPR Discussion Papers 1632, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
  2. Forni, Mario & Reichlin, Lucrezia, 1995. "Let's Get Real: A Dynamic Factor Analytical Approach to Disaggregated Business Cycle," CEPR Discussion Papers 1244, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
  3. Forni, Mario & Reichlin, Lucrezia, 1996. "Dynamic Common Factors in Large Cross-Sections," Empirical Economics, Springer, vol. 21(1), pages 27-42.
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  4. Gordon, Robert J, 1997. "The Time-Varying NAIRU and Its Implications for Economic Policy," Journal of Economic Perspectives, American Economic Association, vol. 11(1), pages 11-32, Winter. [Downloadable!] (restricted)
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  5. Bekker, Paul & Dobbelstein, Pascal & Wansbeek, Tom, 1996. "The APT Model as Reduced-Rank Regression," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(2), pages 199-202, April.
  6. Jeffrey C. Fuhrer, 1995. "The Phillips curve is alive and well," New England Economic Review, Federal Reserve Bank of Boston, issue Mar, pages 41-56. [Downloadable!]
  7. Geweke, John & Zhou, Guofu, 1996. "Measuring the Pricing Error of the Arbitrage Pricing Theory," Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 9(2), pages 557-87. [Downloadable!] (restricted)
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  8. Staiger, Douglas & Stock, James H & Watson, Mark W, 1997. "The NAIRU, Unemployment and Monetary Policy," Journal of Economic Perspectives, American Economic Association, vol. 11(1), pages 33-49, Winter. [Downloadable!] (restricted)
  9. Thomas J. Sargent & Christopher A. Sims, 1977. "Business cycle modeling without pretending to have too much a priori economic theory," Working Papers 55, Federal Reserve Bank of Minneapolis. [Downloadable!]
  10. D Quah & T Sargent, 1993. "A Dynamic Index Model for Large Cross Sections," CEP Discussion Papers 0132, Centre for Economic Performance, LSE.
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  11. Connor, Gregory & Korajczyk, Robert A, 1993. " A Test for the Number of Factors in an Approximate Factor Model," Journal of Finance, American Finance Association, vol. 48(4), pages 1263-91, September. [Downloadable!] (restricted)
  12. Sargent, Thomas J, 1989. "Two Models of Measurements and the Investment Accelerator," Journal of Political Economy, University of Chicago Press, vol. 97(2), pages 251-87, April. [Downloadable!] (restricted)
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