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Do Leading Indicators Lead Peaks More Than Troughs?

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  • Paap, Richard
  • Segers, Rene
  • van Dijk, Dick

Abstract

We develop a formal statistical approach to investigate the possibility that leading indicator variables have different lead times at business cycle peaks and troughs. For this purpose, we propose a novel Markov switching vector autoregressive model, where economic growth and leading indicators share a common Markov process determining the state, but such that their cycles are non-synchronous with the non-synchronicity varying across the different regimes. An empirical application to monthly US industrial production (IP) and The Conference Board's Composite Index of Leading Indicators (CLI) for the period 1959-2004 shows that on average the CLI leads IP by more than seven months at peaks, but only by three and a half months at troughs. In terms of timeliness, the CLI is therefore most useful for signalling oncoming recessions. Furthermore, we find that allowing for asymmetric lead times leads to improved real-time dating of business cycle peaks and troughs and more accurate forecasts of turning points and IP growth.

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File URL: http://pubs.amstat.org/doi/abs/10.1198/jbes.2009.07061
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Bibliographic Info

Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

Volume (Year): 27 (2009)
Issue (Month): 4 ()
Pages: 528-543

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Handle: RePEc:bes:jnlbes:v:27:i:4:y:2009:p:528-543

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References

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  1. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
  2. Daniel E. Sichel, 1992. "Inventories and the three phases of the business cycle," Working Paper Series / Economic Activity Section 128, Board of Governors of the Federal Reserve System (U.S.).
  3. 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.
  4. 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.
  5. Ana Maria Herrero & Elena Pesavento, 2003. "The Decline in U.S. Output Volatility: Structural Changes and Inventory Investment," Emory Economics 0301, Department of Economics, Emory University (Atlanta).
  6. Hans-Martin Krolzig & Michael Clements, 2000. "Business Cycle Asymmetries: Characterisation and Testing based on Markov-Switching Autoregressions," Economics Series Working Papers 2000-W32, University of Oxford, Department of Economics.
  7. Diebold & Rudebusch, . "Measuring Business Cycle: A Modern Perspective," Home Pages _061, University of Pennsylvania.
  8. Margaret M. McConnell & Gabriel Perez Quiros, 1998. "Output fluctuations in the United States: what has changed since the early 1980s?," Staff Reports 41, Federal Reserve Bank of New York.
  9. Paap, R. & van Dijk, H.K., 2002. "Bayes estimates of Markov trends in possibly cointegrated series: an application to US consumption and income," Econometric Institute Research Papers EI 2002-42, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  10. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
  11. Chib, Siddhartha, 1996. "Calculating posterior distributions and modal estimates in Markov mixture models," Journal of Econometrics, Elsevier, vol. 75(1), pages 79-97, November.
  12. McGuckin, Robert H. & Ozyildirim, Ataman & Zarnowitz, Victor, 2007. "A More Timely and Useful Index of Leading Indicators," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 110-120, January.
  13. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, December.
  14. Swanson, Norman R. & van Dijk, Dick, 2006. "Are Statistical Reporting Agencies Getting It Right? Data Rationality and Business Cycle Asymmetry," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 24-42, January.
  15. Filardo, Andrew J, 1994. "Business-Cycle Phases and Their Transitional Dynamics," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 299-308, July.
  16. Albert, James H & Chib, Siddhartha, 1993. "Bayes Inference via Gibbs Sampling of Autoregressive Time Series Subject to Markov Mean and Variance Shifts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 1-15, January.
  17. Chauvet, Marcelle, 1998. "An Econometric Characterization of Business Cycle Dynamics with Factor Structure and Regime Switching," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 969-96, November.
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Citations

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Cited by:
  1. Cem Cakmakli & Richard Paap & Dick van Dijk, 2012. "Measuring and Predicting Heterogeneous Recessions," Koç University-TUSIAD Economic Research Forum Working Papers 1206, Koc University-TUSIAD Economic Research Forum.
  2. Makram El-Shagi & Gregor von Schweinitz, 2012. "Qual VAR Revisited: Good Forecast, Bad Story," IWH Discussion Papers 12, Halle Institute for Economic Research.
  3. Shaun P Vahey & Elizabeth C Wakerly, 2013. "Moving towards probability forecasting," BIS Papers chapters, in: Bank for International Settlements (ed.), Globalisation and inflation dynamics in Asia and the Pacific, volume 70, pages 3-8 Bank for International Settlements.
  4. Sergey Smirnov, 2011. "Those Unpredictable Recessions," HSE Working papers WP BRP 02/EC/2011, National Research University Higher School of Economics.
  5. Camacho, Maximo, 2013. "Mixed-frequency VAR models with Markov-switching dynamics," Economics Letters, Elsevier, vol. 121(3), pages 369-373.
  6. Sylvia Kaufmann, 2008. "Dating and forecasting turning points by Bayesian clustering with dynamic structure: A suggestion with an application to Austrian data," Working Papers 144, Oesterreichische Nationalbank (Austrian Central Bank).
  7. Cem Cakmakli & Richard Paap & Dick van Dijk, 2011. "Measuring and Predicting Heterogeneous Recessions," Tinbergen Institute Discussion Papers 11-154/4, Tinbergen Institute, revised 15 Nov 2011.
  8. Rubén Hernández-Murillo & Michael T. Owyang & Margarita Rubio, 2013. "Clustered housing cycles," Working Papers 2013-021, Federal Reserve Bank of St. Louis.
    • Rubén Hernández-Murillo & Michael T Owyang & Margarita Rubio, 2013. "Clustered Housing Cycles," Discussion Papers 2013/02, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
  9. Jonas Dovern & Christina Ziegler, 2008. "Predicting Growth Rates and Recessions. Assessing U.S. Leading Indicators Under Real-Time Conditions," Kiel Working Papers 1397, Kiel Institute for the World Economy.

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