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A Reduced Rank Regression Approach to Coincident and Leading Indexes Building

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Author Info
Cubadda, Gianluca ()

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Abstract

This paper proposes a reduced rank regression framework for constructing coincident and leading indexes. Based on a formal definition that requires that the first differences of the leading index are the best linear predictor of the first differences of the coincident index, it is shown that the notion of polynomial serial correlation common features can be used to build these composite variables. Concepts and methods are illustrated by an empirical investigation of the US business cycle indicators.

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Publisher Info
Paper provided by University of Molise, Dept. SEGeS in its series Economics & Statistics Discussion Papers with number esdp04022.

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Length: 28 pages
Date of creation: 24 Sep 2004
Date of revision:
Handle: RePEc:mol:ecsdps:esdp04022

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Related research
Keywords: Coincident and Leading Indexes; Polynomial Serial Correlation Common Feature; Reduced Rank Regression.;

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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; Dynamic Quantile Regressions

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Rebecca A Emerson & David Hendry, 1994. "An evaluation of forecasting using leading indicators," Economics Papers 5., Economics Group, Nuffield College, University of Oxford. [Downloadable!]
  2. Engle, Robert F & Kozicki, Sharon, 1993. "Testing for Common Features," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(4), pages 369-80, October.
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  3. Clive Granger & GAWON YOON, 2001. "Self-Generating Variables in a Cointegrated VAR Framework," University of California at San Diego, Economics Working Paper Series 2001-04, Department of Economics, UC San Diego. [Downloadable!]
  4. Hamilton, James D & Perez-Quiros, Gabriel, 1996. "What Do the Leading Indicators Lead?," Journal of Business, University of Chicago Press, vol. 69(1), pages 27-49, January. [Downloadable!] (restricted)
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  5. Wecker, William E, 1979. "Predicting the Turning Points of a Time Series," Journal of Business, University of Chicago Press, vol. 52(1), pages 35-50, January. [Downloadable!] (restricted)
  6. Proietti, Tommaso, 1997. "Short-Run Dynamics in Cointegrated Systems," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 59(3), pages 405-22, August.
  7. Gonzalo Camba-Mendez & George Kapetanios & Richard J. Smith & Martin Weale, 1999. "Tests of Rank in Reduced Rank Regression Models," NIESR Discussion Papers 150, National Institute of Economic and Social Research. [Downloadable!]
  8. Cubadda, Gianluca, 1999. "Common Cycles in Seasonal Non-stationary Time Series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(3), pages 273-91, May-June. [Downloadable!]
  9. Engle, Robert F & Kozicki, Sharon, 1993. "Testing for Common Features: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(4), pages 393-95, October.
  10. Maximo Camacho & Gabriel Perez-Quiros, 2002. "This is what the leading indicators lead," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(1), pages 61-80. [Downloadable!]
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  11. James H. Stock & Mark W. Watson, 1993. "A Procedure for Predicting Recessions with Leading Indicators: Econometric Issues and Recent Experience," NBER Chapters, in: Business Cycles, Indicators and Forecasting, pages 95-156 National Bureau of Economic Research, Inc. [Downloadable!]
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  12. Hecq, Alain & Palm, Franz C & Urbain, Jean-Pierre, 2000. " Permanent-Transitory Decomposition in VAR Models with Cointegration and Common Cycles," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 62(4), pages 511-32, September. [Downloadable!] (restricted)
  13. Anders Rahbek & Rocco Mosconi, 1999. "Cointegration rank inference with stationary regressors in VAR models," Econometrics Journal, Royal Economic Society, vol. 2(1), pages 76-91.
  14. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
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  15. Camba-Mendez, Gonzalo, et al, 2003. "Tests of Rank in Reduced Rank Regression Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 145-55, January.
  16. Cubadda, Gianluca & Hecq, Alain, 2001. "On non-contemporaneous short-run co-movements," Economics Letters, Elsevier, vol. 73(3), pages 389-397, December. [Downloadable!] (restricted)
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  1. Gianluca Cubadda, 2007. "A Unifying Framework for Analysing Common Cyclical Features in Cointegrated Time Series," CEIS Research Paper 102, Tor Vergata University, CEIS. [Downloadable!]
    Other versions:
  2. Marco Centoni & Gianluca Cubadda & Alain Hecq, 2008. "Common Shocks, Common Dynamics, and the International Business Cycle," CEIS Research Paper 106, Tor Vergata University, CEIS, revised 07 Jul 2008. [Downloadable!]
    Other versions:
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