Seasonality, Forecast Extensions and Business Cycle Uncertainty
AbstractSeasonality is one of the most important features of economic time series. The possibility to abstract from seasonality for the assessment of economic conditions is a widely debated issue. In this paper we propose a strategy for assessing the role of seasonal adjustment on business cycle measurement. In particular, we provide a method for quantifying the contribution to the unreliability of the estimated cycles extracted by popular filters, such as Baxter and King and Hodrick-Prescott. The main conclusion is that the contribution is larger around the turning points of the series and at the extremes of the sample period; moreover, it much more sizeable for highpass filters, like the Hodrick-Prescott filter, which retain to a great extent the high frequency fluctuations in a time series, the latter being the ones that are more affected by seasonal adjustment. If a bandpass component is considered, the effect has reduced size. Finally, we discuss the role of forecast extensions and the prediction of the cycle. For the time series of industrial production considered in the illustration, it is not possible to provide a reliable estimate of the cycle at the end of the sample.
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 University Library of Munich, Germany in its series MPRA Paper with number 20868.
Date of creation: 21 Feb 2010
Date of revision:
Linear filters; Unobserved Components; Seasonal Adjustment; Reliability.;
Other versions of this item:
- Tommaso Proietti, 2012. "Seasonality, Forecast Extensions And Business Cycle Uncertainty," Journal of Economic Surveys, Wiley Blackwell, Wiley Blackwell, vol. 26(4), pages 555-569, 09.
- 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 &bull Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-03-06 (All new papers)
- NEP-ECM-2010-03-06 (Econometrics)
- NEP-FOR-2010-03-06 (Forecasting)
- NEP-MAC-2010-03-06 (Macroeconomics)
- NEP-ORE-2010-03-06 (Operations Research)
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.:
- J. Durbin, 2002. "A simple and efficient simulation smoother for state space time series analysis," Biometrika, Biometrika Trust, Biometrika Trust, vol. 89(3), pages 603-616, August.
- Durbin, James & Koopman, Siem Jan, 2001.
"Time Series Analysis by State Space Methods,"
OUP Catalogue, Oxford University Press,
Oxford University Press, number 9780198523543, October.
- Tom Doan, . "SEASONALDLM: RATS procedure to create the matrices for the seasonal component of a DLM," Statistical Software Components RTS00251, Boston College Department of Economics.
- William R. Bell & Donald E. K. Martin, 2004. "Computation of asymmetric signal extraction filters and mean squared error for ARIMA component models," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(4), pages 603-623, 07.
- 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.
- 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, Royal Economic Society, vol. 2(1), pages 107-160.
- Koopman, S.J.M. & Shephard, N. & Doornik, J.A., 1998. "Statistical Algorithms for Models in State Space Using SsfPack 2.2," Discussion Paper, Tilburg University, Center for Economic Research 1998-141, Tilburg University, Center for Economic Research.
- Regina Kaiser & Agustín Maravall, 2004.
"Combining filter design with model based filtering (with an application to business cycle estimation),"
Banco de Espaï¿½a Working Papers
0417, Banco de Espa�a.
- Kaiser, Regina & Maravall, Agustin, 2005. "Combining filter design with model-based filtering (with an application to business-cycle estimation)," International Journal of Forecasting, Elsevier, Elsevier, vol. 21(4), pages 691-710.
- King, Robert G. & Rebelo, Sergio T., 1993.
"Low frequency filtering and real business cycles,"
Journal of Economic Dynamics and Control, Elsevier,
Elsevier, vol. 17(1-2), pages 207-231.
- Morten O. Ravn & Harald Uhlig, 2002. "On adjusting the Hodrick-Prescott filter for the frequency of observations," The Review of Economics and Statistics, MIT Press, vol. 84(2), pages 371-375.
- [Reference to Proietti], Tommaso, 2000. "Comparing seasonal components for structural time series models," International Journal of Forecasting, Elsevier, Elsevier, vol. 16(2), pages 247-260.
- Pollock, D. S. G., 2000. "Trend estimation and de-trending via rational square-wave filters," Journal of Econometrics, Elsevier, Elsevier, vol. 99(2), pages 317-334, December.
- Pollock, D. S. G., 2003. "Improved frequency selective filters," Computational Statistics & Data Analysis, Elsevier, Elsevier, vol. 42(3), pages 279-297, March.
- Bell, William R & Hillmer, Steven C, 1984. "Issues Involved with the Seasonal Adjustment of Economic Time Series," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 2(4), pages 291-320, October.
Blog mentionsAs found by EconAcademics.org, the blog aggregator for Economics research:reading lists or Wikipedia pages:Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ekkehart Schlicht).
If references are entirely missing, you can add them using this form.