IDEAS home Printed from https://ideas.repec.org/a/taf/applec/v41y2009i18p2309-2322.html
   My bibliography  Save this article

Economic activity and recession probabilities: information content and predictive power of the term spread in Italy

Author

Listed:
  • Marianna Brunetti
  • Costanza Torricelli

Abstract

The aim of the present article is to examine the information content of the Italian term spread as for real economic growth rates and recession probabilities and to test its predictive power in forecasting regime probabilities. To this end the relationship between the term spread and economic growth rates is modelled as a nonlinear one and specifically the Logistic Smooth Transition model is used, while a probit model is implemented to forecast recession probabilities. Specific to this article is the use of the OECD business cycle chronology, which was never used before to this end for the Italian case. Overall evidence supports the informative content of the spread in Italy over the whole period (1984-2005) although results are more satisfactory as from 1992. In particular, recession forecasts are generally better than those obtained with other chronologies previously adopted for the Italian case (ISAE and ECRI).

Suggested Citation

  • Marianna Brunetti & Costanza Torricelli, 2009. "Economic activity and recession probabilities: information content and predictive power of the term spread in Italy," Applied Economics, Taylor & Francis Journals, vol. 41(18), pages 2309-2322.
    • Handle: RePEc:taf:applec:v:41:y:2009:i:18:p:2309-2322
    DOI: 10.1080/00036840701222512
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/00036840701222512
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00036840701222512?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Oleg Korenok & Bruce Mizrach, 2004. "The Microeconomics of Macroeconomic Asymmetries: Sectoral Driving Forces and Firm Level Characteristics," Computing in Economics and Finance 2004 266, Society for Computational Economics.
    2. Giancarlo Bruno & Edoardo Otranto, 2003. "Dating the Italian Business Cycle: A Comparison of Procedures," Econometrics 0312003, University Library of Munich, Germany.
    3. Moneta, Fabio, 2003. "Does the yield spread predict recessions in the euro area?," Working Paper Series 294, European Central Bank.
    4. Filippo Altissimo & Domenico J. Marchetti & Gian Paolo Oneto, 2000. "The Italian Business Cycle: Coincident and Leading Indicators and Some Stylized Facts," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 59(2), pages 147-220, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Peterson K. Ozili, 2020. "Financial inclusion and business cycles," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 13(2), pages 180-199, August.
    2. Marianna Brunetti & Costanza Torricelli, 2007. "The role of demographic variables in explaining financial returns in Italy," Heterogeneity and monetary policy 0701, Universita di Modena e Reggio Emilia, Dipartimento di Economia Politica.
    3. Ye, Zhen & Zhang, Fangzhu & Coffman, D’Maris & Xia, Senmao & Wang, Zhifeng & Zhu, Zhonghua, 2022. "China’s urban construction investment bond: Contextualising a financial tool for local government," Land Use Policy, Elsevier, vol. 112(C).
    4. Novella Maugeri, 2014. "Some Pitfalls in Smooth Transition Models Estimation: A Monte Carlo Study," Computational Economics, Springer;Society for Computational Economics, vol. 44(3), pages 339-378, October.
    5. Lili Hao & Eric C.Y. Ng, 2011. "Predicting Canadian recessions using dynamic probit modelling approaches," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 44(4), pages 1297-1330, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Edoardo Otranto, 2005. "Extraction of Common Signal from Series with Different Frequency," Econometrics 0502011, University Library of Munich, Germany.
    2. Stefano Fachin & Andrea Gavosto, 2010. "Trends of labour productivity in Italy: a study with panel co‐integration methods," International Journal of Manpower, Emerald Group Publishing Limited, vol. 31(7), pages 755-769, October.
    3. Libero Monteforte & Valentina Raponi, 2019. "Short‐term forecasts of economic activity: Are fortnightly factors useful?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(3), pages 207-221, April.
    4. Sergey V. Smirnov & Nikolay V. Kondrashov & Anna V. Petronevich, 2017. "Dating Cyclical Turning Points for Russia: Formal Methods and Informal Choices," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 13(1), pages 53-73, May.
    5. Fabio H. Nieto & Luis Fernando Melo, 2001. "About a Coincident Index for the State of the Economy," Borradores de Economia 1938, Banco de la Republica.
    6. Christophe Blot & Grégory Levieuge, 2008. "Are MCIs Good Indicators of Economic Activity ? Evidence from the G7 Countries," Working Papers hal-00973056, HAL.
    7. Francesco Daveri & Cecilia Jona-Lasinio, 2005. "Italy's Decline: Getting the Facts Right," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 64(4), pages 365-410, December.
    8. Nada Kulendran & Kevin K.F. Wong, 2009. "Predicting Quarterly Hong Kong Tourism Demand Growth Rates, Directional Changes and Turning Points with Composite Leading Indicators," Tourism Economics, , vol. 15(2), pages 307-322, June.
    9. Luis Fernando Melo & Fabio Nieto & Mario Ramos, 2003. "A Leading Index for the Colombian Economic Activity," Borradores de Economia 243, Banco de la Republica de Colombia.
    10. Silvia Palasca & Elisabeta Jaba, 2014. "Leading and Lagging Indicators Of the Economic Crisis," Romanian Statistical Review, Romanian Statistical Review, vol. 62(3), pages 31-47, September.
    11. Fachin, Stefano & Gavosto, Andrea, 2007. "The decline in Italian productivity: a study in estimation of long-Run trends in Total Factor Productivity with panel cointegration methods," MPRA Paper 3112, University Library of Munich, Germany.
    12. Soh, Ann-Ni, 2020. "A Review on the Leading Indicator Approach towards Economic Forecasting," MPRA Paper 103854, University Library of Munich, Germany.
    13. Ataman Ozyildirim & Brian Schaitkin & Victor Zarnowitz, 2010. "Business cycles in the euro area defined with coincident economic indicators and predicted with leading economic indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 6-28.
    14. Mario Quagliariello, 2007. "Banks' riskiness over the business cycle: a panel analysis on Italian intermediaries," Applied Financial Economics, Taylor & Francis Journals, vol. 17(2), pages 119-138.
    15. Luis Fernando Melo & Fabio H. Nieto & Carlos Esteban Posada & Yanneth Rocío Betancourt, 2001. "Un Índice Coincidente para la Actividad Económica Colombiana," Borradores de Economia 3678, Banco de la Republica.
    16. Melvin Muzi Khomo & Meshach Jesse Aziakpono, 2007. "Forecasting Recession In South Africa: A Comparison Of The Yield Curve And Other Economic Indicators," South African Journal of Economics, Economic Society of South Africa, vol. 75(2), pages 194-212, June.
    17. G. Bruno & L. Crosilla & P. Margani, 2019. "Inspecting the Relationship Between Business Confidence and Industrial Production: Evidence on Italian Survey Data," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 15(1), pages 1-24, April.
    18. Alberto Baffigi & Roberto Golinelli & Giuseppe Parigi, 2002. "Real-time GDP forecasting in the euro area," Temi di discussione (Economic working papers) 456, Bank of Italy, Economic Research and International Relations Area.
    19. Antonio Bassanetti & Michele Caivano & Alberto Locarno, 2010. "Modelling Italian potential output and the output gap," Temi di discussione (Economic working papers) 771, Bank of Italy, Economic Research and International Relations Area.
    20. Nissilä, Wilma, 2020. "Probit based time series models in recession forecasting – A survey with an empirical illustration for Finland," BoF Economics Review 7/2020, Bank of Finland.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:applec:v:41:y:2009:i:18:p:2309-2322. See general information about how to correct material in RePEc.

    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 CitEc recognized a bibliographic reference but did not link an item in RePEc 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 RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEC20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.