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

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  • 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).

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  • 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
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    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. 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.
    4. Moneta, Fabio, 2003. "Does the yield spread predict recessions in the euro area?," Working Paper Series 294, European Central Bank.
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    Cited by:

    1. 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.
    2. 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).
    3. 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.
    4. Ozili, Peterson K, 2020. "Financial inclusion and business cycles," MPRA Paper 102054, University Library of Munich, Germany.
    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.

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