Models to date the business cycle: The Italian case
The problem of dating the business cycle has recently received many contributions, with a lot of proposed statistical methodologies, parametric and non-parametric. In general, these methods are not used in official dating, which is carried out by experts, who use their subjective evaluations of the state of economy. In this work we try to apply some statistical procedures to obtain an automatic dating of the Italian business cycle in the last 30 years, checking differences among various methodologies and with the ISAE chronology. The purpose of this exercise is to verify if purely statistical methods can reproduce the turning points detection proposed by economists, so that they could be fruitfully used in official dating. To this end parametric as well as non-parametric methods are employed. The analysis is carried out both aggregating results from single time series and directly in a multivariate framework. The different methods are also evaluated with respect to their ability to timely track (ex post) turning points.
If 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.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
References listed on IDEAS
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.:
- 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.
- Tom Doan, "undated". "BKFILTER: RATS procedure to implement band pass filter using Baxter-King method," Statistical Software Components RTS00026, Boston College 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.
- Artis, Michael J & Kontolemis, Zenon G & Osborn, Denise R, 1997. "Business Cycles for G7 and European Countries," The Journal of Business, University of Chicago Press, vol. 70(2), pages 249-279, April.
- Bruno, Giancarlo & Lupi, Claudio, 2003.
"Forecasting Industrial Production and the Early Detection of Turning Points,"
Economics & Statistics Discussion Papers
esdp03004, University of Molise, Dept. EGSeI.
- Giancarlo Bruno & Claudio Lupi, 2004. "Forecasting industrial production and the early detection of turning points," Empirical Economics, Springer, vol. 29(3), pages 647-671, 09.
- Giancarlo Bruno & Claudio Lupi, 2001. "Forecasting Industrial Production and the Early Detection of Turning Points," Econometrics 0110004, EconWPA.
- Bruno Giancarlo & Lupi Claudio, 2001. "Forecasting Industrial Production and the Early Detection of Turning POints," ISAE Working Papers 20, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
- Francis X. Diebold & Glenn D. Rudebusch, 1994.
"Measuring Business Cycles: A Modern Perspective,"
NBER Working Papers
4643, National Bureau of Economic Research, Inc.
- 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.
- Vincent, BODART & Konstantin, KHOLODILIN & Fati, SHADMAN-MEHTA, 2005. "Identifying and Forecasting the Turning Points of the Belgian Business Cycle with Regime-Switching and Logit Models," Discussion Papers (ECON - Département des Sciences Economiques) 2005006, Université catholique de Louvain, Département des Sciences Economiques.
- Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, April.
- Diebold, Francis X & Rudebusch, Glenn D, 1989.
"Scoring the Leading Indicators,"
The Journal of Business,
University of Chicago Press, vol. 62(3), pages 369-391, July.
- Gerhard Bry & Charlotte Boschan, 1971. "Foreword to "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs"," NBER Chapters, in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages -1 National Bureau of Economic Research, Inc.
- 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.
- Don Harding & Adrian Pagan, 2004.
"Synchronization of cycles,"
CAMA Working Papers
2004-03, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Edoardo Otranto, 2006. "Extracting a Common Cycle from Series with Different Frequency: An Application to the Italian Economy," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2005(3), pages 407-429.
- Altissimo, F. & Marchetti, D.J. & Oneto, G.P., 2000. "The Italian Business Cycle: Coincident and Leading Indicators and Some Stylized Facts," Papers 377, Banca Italia - Servizio di Studi.
- Filippo Altissimo & Domenico J. Marchetti & Gian Paolo Oneto, 2000. "The Italian Business Cycle; Coincident and Leading Indicators and Some Stylized Facts," Temi di discussione (Economic working papers) 377, Bank of Italy, Economic Research and International Relations Area.
- Garcia-Ferrer, Antonio & Bujosa-Brun, Marcos, 2000. "Forecasting OECD industrial turning points using unobserved components models with business survey data," International Journal of Forecasting, Elsevier, vol. 16(2), pages 207-227.
- Chang-Jin Kim & Charles R. Nelson, 1998. "Business Cycle Turning Points, A New Coincident Index, And Tests Of Duration Dependence Based On A Dynamic Factor Model With Regime Switching," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 188-201, May.
- Edoardo Otranto & Giampiero M. Gallo, 2001.
"A Nonparametric Bayesian Approach to Detect the Number of Regimes in Markov Switching Models,"
Econometrics Working Papers Archive
wp2001_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
- Edoardo Otranto & Giampiero Gallo, 2002. "A Nonparametric Bayesian Approach To Detect The Number Of Regimes In Markov Switching Models," Econometric Reviews, Taylor & Francis Journals, vol. 21(4), pages 477-496.
- Chow, Gregory C & Lin, An-loh, 1971.
"Best Linear Unbiased Interpolation, Distribution, and Extrapolation of Time Series by Related Series,"
The Review of Economics and Statistics,
MIT Press, vol. 53(4), pages 372-375, November.
- Litterman, Robert B, 1983. "A Random Walk, Markov Model for the Distribution of Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 169-173, April.
- Fernandez, Roque B, 1981. "A Methodological Note on the Estimation of Time Series," The Review of Economics and Statistics, MIT Press, vol. 63(3), pages 471-476, August.
- Tom Doan, "undated". "DISAGGREGATE: RATS procedure to implement general disaggregation (interpolation/distribution) procedure," Statistical Software Components RTS00050, Boston College Department of Economics.
- Tom Doan, "undated". "CHOWLIN: RATS procedure to distribute a series to a higher frequency using related series," Statistical Software Components RTS00036, Boston College Department of Economics.
- 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, April.
- Neftici, Salih N., 1982. "Optimal prediction of cyclical downturns," Journal of Economic Dynamics and Control, Elsevier, vol. 4(1), pages 225-241, November.
- 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.
When requesting a correction, please mention this item's handle: RePEc:eee:ecmode:v:25:y:2008:i:5:p:899-911. See general 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: (Dana Niculescu)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.