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Measuring Business Cycles with Business-Cycle Models

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  • Allan W. Gregory
  • Gregor W. Smith

Abstract

Business cycles may be defined or measured by parametrizing detrending filters to maximize the ability of a business-cycle model to match the moments of the remaining cycles. Thus a theory can be used to guide cycle measurement. We present two applications to U.S. postwar data. In the first application the cycles are measured with a standard, real business cycle model. In the second, they are measured using information on capacity utilization and unemployment rates. Simulation methods are used to describe the properties of the GMM estimators and to allow exact inference.

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File URL: http://qed.econ.queensu.ca/working_papers/papers/qed_wp_901.pdf
File Function: First version 1994
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Bibliographic Info

Paper provided by Queen's University, Department of Economics in its series Working Papers with number 901.

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Length: 21 pages
Date of creation: May 1994
Date of revision:
Handle: RePEc:qed:wpaper:901

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Keywords: business cycles; detrending;

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References

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  1. Timothy Cogley & James M. Nason, 1993. "Effects of the Hodrick-Prescott filter on trend and difference stationary time series: implications for business cycle research," Working Papers in Applied Economic Theory 93-01, Federal Reserve Bank of San Francisco.
  2. Andrews, Donald W K & McDermott, C John, 1995. "Nonlinear Econometric Models with Deterministically Trending Variables," Review of Economic Studies, Wiley Blackwell, vol. 62(3), pages 343-60, July.
  3. Eichenbaum, Martin & Hansen, Lars Peter, 1990. "Estimating Models with Intertemporal Substitution Using Aggregate Time Series Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 53-69, January.
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  7. Cogley, Timothy & Nason, James M, 1995. "Output Dynamics in Real-Business-Cycle Models," American Economic Review, American Economic Association, vol. 85(3), pages 492-511, June.
  8. Neusser, Klaus, 1991. "Testing the long-run implications of the neoclassical growth model," Journal of Monetary Economics, Elsevier, vol. 27(1), pages 3-37, February.
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  12. Lippi, Marco & Reichlin, Lucrezia, 1994. "Diffusion of Technical Change and the Decomposition of Output into Trend and Cycle," Review of Economic Studies, Wiley Blackwell, vol. 61(1), pages 19-30, January.
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  24. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
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Citations

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Cited by:
  1. Klaus Reiner Schenk-Hoppé, . "Economic Growth and Business Cycles: A Critical Comment on Detrending Time Series (Revised Version)," IEW - Working Papers 054, Institute for Empirical Research in Economics - University of Zurich.
  2. Butler, L, 1996. "The Bank of Canada's New Quarterly Porjection Model Part 4 : A Semi- Structural Method to Estimate Potential Output : Combining Economic Theory with a Time-Series Filter," Technical Reports 77, Bank of Canada.
  3. Yuriy Gorodnichenko & Serena Ng, 2009. "Estimation of DSGE Models When the Data are Persistent," NBER Working Papers 15187, National Bureau of Economic Research, Inc.

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