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Extracting, Using and Analysing Cyclical Information

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Listed author(s):
  • Harding, Don
  • Pagan, Adrian

Abstract

Recent events suggest that the death of the business cycle has been exaggerated; the issue of how one learns about and monitors the business cycle remains centre stage. Advent of the Euro and the potential for tensions when sovereign nations subsume their monetary policy into a single response also makes monitoring the business cycle of particular interest for Euro area policy makers. In this paper we summarize recent research on three questions relating to cycles in economic activity --- how to extract cyclical information, how to analyse it, and how to enquire into what special difficulties might be encountered when using cyclical indicators. This survey focuses on our own research which we view as a formalization of some of the procedures developed by Burns and Mitchell at the NBER. However, defence of our position goes beyond continuity with the past and is based on the view that the way in which these investigators defined the business cycle is a very natural one that connects with the way policy makers and commentators discuss the cycle.

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File URL: https://mpra.ub.uni-muenchen.de/15/1/MPRA_paper_15.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 15.

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Date of creation: 15 Aug 2001
Handle: RePEc:pra:mprapa:15
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Keywords: Business cycle; growth cycle; synchronization; turning points;

Find related papers by JEL classification:

  • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
  • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
  • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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  1. Lawrence J. Christiano & Terry J. Fitzgerald, 1998. "The business cycle: it's still a puzzle," Economic Perspectives, Federal Reserve Bank of Chicago, issue Q IV, pages 56-83.
  2. Marianne Baxter & Robert G. King, 1999. "Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 575-593, November.
  3. Burnside, Craig, 1998. "Detrending and business cycle facts: A comment," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 513-532, May.
  4. Gruen, David & Pagan, Adrian & Thompson, Christopher, 1999. "The Phillips curve in Australia," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 223-258, October.
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  8. Alasdair Scott, 2000. "Stylised facts from output gap measures," Reserve Bank of New Zealand Discussion Paper Series DP2000/07, Reserve Bank of New Zealand.
  9. Hodrick, Robert J & Prescott, Edward C, 1997. "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
  10. Forni, Mario, et al, 2001. "Coincident and Leading Indicators for the Euro Area," Economic Journal, Royal Economic Society, vol. 111(471), pages 62-85, May.
  11. Gali, Jordi & Gertler, Mark & Lopez-Salido, J. David, 2001. "European inflation dynamics," European Economic Review, Elsevier, vol. 45(7), pages 1237-1270.
  12. Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(3), pages 231-247, July-Sept.
  13. Cashin, Paul & McDermott, C. John & Scott, Alasdair, 2002. "Booms and slumps in world commodity prices," Journal of Development Economics, Elsevier, vol. 69(1), pages 277-296, October.
  14. 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 357-384, March.
  15. Cogley, Timothy, 2001. "Alternative definitions of the business cycle and their implications for business cycle models: A reply to Torben Mark Pederson," Journal of Economic Dynamics and Control, Elsevier, vol. 25(8), pages 1103-1107, August.
  16. Fagan, Gabriel & Henry, Jérôme & Mestre, Ricardo, 2001. "An area-wide model (AWM) for the euro area," Working Paper Series 0042, European Central Bank.
  17. Harding, Don & Pagan, Adrian, 2002. "Dissecting the cycle: a methodological investigation," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 365-381, March.
  18. Don Harding & Adrian Pagan, 1999. "Knowing the Cycle," Melbourne Institute Working Paper Series wp1999n12, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
  19. Athanasopoulos, G. & Anderson, H.M. & Vahid, F., 2001. "Capturing the Shape of Business Cycles with Nonlinear Autoregressive Leading Indicator Models," Monash Econometrics and Business Statistics Working Papers 7/01, Monash University, Department of Econometrics and Business Statistics.
  20. Clements, Michael P & Krolzig, Hans-Martin, 2003. "Business Cycle Asymmetries: Characterization and Testing Based on Markov-Switching Autoregressions," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 196-211, January.
  21. Dungey, Mardi & Pagan, Adrian, 2000. "A Structural VAR Model of the Australian Economy," The Economic Record, The Economic Society of Australia, vol. 76(235), pages 321-342, December.
  22. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1, June.
  23. Clements, M.P. & Krolzig, H-M., 1999. "Business Cycle Asymmetries: Characterisationand Testing Based on Markov-Switching Autoregression," The Warwick Economics Research Paper Series (TWERPS) 522, University of Warwick, Department of Economics.
  24. Neftci, Salih N, 1984. "Are Economic Time Series Asymmetric over the Business Cycle?," Journal of Political Economy, University of Chicago Press, vol. 92(2), pages 307-328, April.
  25. Daniel M. Chin & John F. Geweke & Preston J. Miller, 2000. "Predicting turning points," Staff Report 267, Federal Reserve Bank of Minneapolis.
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