Measuring Asymmetric Stochastic Cycle Components in U.S. Macroeconomic Time Series
AbstractTo gain insights in the current status of the economy, macroeconomic time series are often decomposed into trend, cycle and irregular components. This can be done by nonparametric band-pass filtering methods in the frequency domain or by model-based decompositions based on autoregressive moving average models or unobserved components time series models. In this paper we consider the latter and extend the model to allow for asymmetric cycles. In theoretical and empirical studies, the asymmetry of cyclical behavior is often discussed and considered for series such as unemployment and gross domestic product (GDP). The number of attempts to model asymmetric cycles is limited and it is regarded as intricate and nonstandard. In this paper we show that a limited modification of the standard cycle component leads to a flexible device for asymmetric cycles. The presence of asymmetry can be tested using classical likelihood based test statistics. The trend-cycle de! composition model is applied to three key U.S. macroeconomic time series. It is found that cyclical asymmetry is a prominent salient feature in the U.S. economy.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 05-081/4.
Date of creation: 15 Aug 2005
Date of revision:
Contact details of provider:
Web page: http://www.tinbergen.nl
Asymmetric business cycles; Unobserved Components; Nonlinear state space models; Monte Carlo likelihood; Importance sampling;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
This paper has been announced in the following NEP Reports:
- NEP-ALL-2006-01-24 (All new papers)
- NEP-ECM-2006-01-24 (Econometrics)
- NEP-ETS-2006-01-24 (Econometric Time Series)
- NEP-MAC-2006-01-24 (Macroeconomics)
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.:
- Robert J. Hodrick & Edward Prescott, 1981.
"Post-War U.S. Business Cycles: An Empirical Investigation,"
451, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
- 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.
- Pesaran, M. Hashem & Potter, Simon M., 1997.
"A floor and ceiling model of US output,"
Journal of Economic Dynamics and Control,
Elsevier, vol. 21(4-5), pages 661-695, May.
- Neil Shephard & Siem Jan Koopman, 2002.
"Testing the assumptions behind the use of importance sampling,"
Economics Series Working Papers
2002-W17, University of Oxford, Department of Economics.
- Siem Jan Koopman & Neil Shephard, 2002. "Testing the Assumptions Behind the Use of Importance Sampling," Economics Papers 2002-W17, Economics Group, Nuffield College, University of Oxford.
- Koopman, S.J.M. & Shephard, N. & Doornik, J.A., 1998.
"Statistical Algorithms for Models in State Space Using SsfPack 2.2,"
1998-141, Tilburg University, Center for Economic Research.
- Siem Jan Koopman & Neil Shephard & Jurgen A. Doornik, 1999. "Statistical algorithms for models in state space using SsfPack 2.2," Econometrics Journal, Royal Economic Society, vol. 2(1), pages 107-160.
- Neil Shephard & Jurgen Doornik & Siem Jan Koopman, 1998. "Statistical algorithms for models in state space using SsfPack 2.2," Economics Series Working Papers 1998-W06, University of Oxford, Department of Economics.
- 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.
- Shephard, N. & Pitt, M.K., 1995.
"Likelihood Analysis of Non-Gaussian Parameter-Driven Models,"
108, Economics Group, Nuffield College, University of Oxford.
- Neil Shephard & Michael K Pitt, 1995. "Likelihood analysis of non-Gaussian parameter driven models," Economics Papers 15 & 108., Economics Group, Nuffield College, University of Oxford.
- Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-39, November.
- Lawrence J. Christiano & Terry J. Fitzgerald, 1999.
"The Band pass filter,"
9906, Federal Reserve Bank of Cleveland.
- McQueen, Grant & Thorley, Steven, 1993. "Asymmetric business cycle turning points," Journal of Monetary Economics, Elsevier, vol. 31(3), pages 341-362, June.
- Sichel, Daniel E, 1993.
"Business Cycle Asymmetry: A Deeper Look,"
Western Economic Association International, vol. 31(2), pages 224-36, April.
- Daniel E. Sichel, 1989. "Business cycle asymmetry: a deeper look," Working Paper Series / Economic Activity Section 93, Board of Governors of the Federal Reserve System (U.S.).
- Sichel, D.E., 1988. "Business Cycle Asymmetry: A Deeper Look," Papers 85, Princeton, Department of Economics - Financial Research Center.
- Beaudry, Paul & Koop, Gary, 1993. "Do recessions permanently change output?," Journal of Monetary Economics, Elsevier, vol. 31(2), pages 149-163, April.
- Acemoglu, Daron & Scott, Andrew, 1997.
"Asymmetric business cycles: Theory and time-series evidence,"
Journal of Monetary Economics,
Elsevier, vol. 40(3), pages 501-533, December.
- Scott, A. & Acemoglu, D., 1995. "Asymmetric Business Cycles: Theory and Time-series Evidence," Economics Series Working Papers 99173, University of Oxford, Department of Economics.
- Falk, Barry, 1986.
"Further Evidence on the Asymmetric Behavior of Economic Time Series over the Business Cycle,"
Journal of Political Economy,
University of Chicago Press, vol. 94(5), pages 1096-1109, October.
- Falk, Barry L., 1986. "Further Evidence on the Asymmetric Behavior of Economic Time Series over the Business Cycle," Staff General Research Papers 11097, Iowa State University, Department of Economics.
- Marianne Baxter & Robert G. King, 1995.
"Measuring Business Cycles Approximate Band-Pass Filters for Economic Time Series,"
NBER Working Papers
5022, National Bureau of Economic Research, Inc.
- 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.
- Luginbuhl, Rob & de Vos, Aart, 1999. "Bayesian Analysis of an Unobserved-Component Time Series Model of GDP with Markov-Switching and Time-Varying Growths," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(4), pages 456-65, October.
- S. J. Koopman & J. Durbin, 2003. "Filtering and smoothing of state vector for diffuse state-space models," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(1), pages 85-98, 01.
- Tanizaki, Hisashi & Mariano, Roberto S., 1998. "Nonlinear and non-Gaussian state-space modeling with Monte Carlo simulations," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 263-290.
- Harvey, A.C. & Trimbur, T.M., 2001.
"General Model-based Filters for Extracting Cycles and Trends in Economic Time Series,"
Cambridge Working Papers in Economics
0113, Faculty of Economics, University of Cambridge.
- Andrew C. Harvey & Thomas M. Trimbur, 2003. "General Model-Based Filters for Extracting Cycles and Trends in Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 244-255, May.
- 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 231-47, July-Sept.
- J. Durbin, 2002. "A simple and efficient simulation smoother for state space time series analysis," Biometrika, Biometrika Trust, vol. 89(3), pages 603-616, August.
- Francisco A. Gallego & Christian A. Johnson, 2003.
"Building Confidence Intervals for the Band-Pass and Hodrick-Prescott Filters: An Application Using Bootstrapping,"
Working Papers Central Bank of Chile
202, Central Bank of Chile.
- Christian A. Johnson & Francisco A. Gallego, 2003. "Building Confidence Intervals for the Band-Pas and Hodrick-Prescott Filters: An Application using Bootstrapping," Computing in Economics and Finance 2003 15, Society for Computational Economics.
- Simon M. Potter, 1993.
"A Nonlinear Approach to U.S. GNP,"
UCLA Economics Working Papers
693, UCLA Department of Economics.
- Clark, Peter K., 1989. "Trend reversion in real output and unemployment," Journal of Econometrics, Elsevier, vol. 40(1), pages 15-32, January.
- 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 307-28, April.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Antoine Maartens (+31 626 - 160 892)).
If references are entirely missing, you can add them using this form.