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Constructing a real-time coincident recession index: an application to the Peruvian economy

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  • Mendoza, Liu

    (Universidad Peruana de Ciencias Aplicadas)

  • Morales, Daniel

    (Rimac Seguros)

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    Abstract

    In everyday macroeconomic analysis, businessmen and policymakers monitor many variables in order to assess the current situation of a country’s business cycle. However, making this assessment is extremely difficult, especially on the verge of recessions: does a drop in one or more of these series reveal the beginning of a recession? Or is it a signal of a temporal deceleration? To answer these questions we have constructed a monthly probabilistic coincident index to detect how close we are of a recession in the Peruvian economy using a non-linear Markov-switching model. In the construction of this index, we have explored the informational content of tendency surveys and international economic variables. We find that the index detected with promptness and reliability the recent recession period associated with the international financial crisis even in real-time analysis. However, since it has been developed with information comprising eight years due to limited data availability, its future recession detection capability has yet to endure the test of time.

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    Bibliographic Info

    Paper provided by Banco Central de Reserva del Perú in its series Working Papers with number 2012-020.

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    Date of creation: Nov 2012
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    Handle: RePEc:rbp:wpaper:2012-020

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    Related research

    Keywords: business cycles; Markov-switching models; recession index; business tendency surveys;

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    References

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    1. Gabriel Rodríguez, 2010. "Application of Three Non-Linear Econometric Approaches to Identify Business Cycles in Peru," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing,CIRET, vol. 2010(2), pages 1-25.
    2. Carrera Cesar, 2012. "Estimating Information Rigidity Using Firms' Survey Data," The B.E. Journal of Macroeconomics, De Gruyter, vol. 12(1), pages 1-34, June.
    3. Etter, Richard & Graff, Michael, 2011. "A composite leading indicator for the Peruvian economy based on the BCRP's monthly business tendency surveys," Working Papers 2011-006, Banco Central de Reserva del Perú.
    4. Hansen, Bruce E, 1992. "The Likelihood Ratio Test under Nonstandard Conditions: Testing the Markov Switching Model of GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages S61-82, Suppl. De.
    5. Hwee Kwan Chow & Keen Meng Choy, 2009. "Analyzing and Forecasting Business Cycles in a Small Open Economy : A Dynamic Factor Model for Singapore," Macroeconomics Working Papers 22074, East Asian Bureau of Economic Research.
    6. Maximo Camacho & Gabriel Perez-Quiros & Pilar Poncela, 2010. "Green shoots in the euro area. A real time measure," Banco de Espa�a Working Papers 1026, Banco de Espa�a.
    7. Javier Escobal & Javier Torres, 2002. "Un Sistema de Indicadores Líderes del Nivel de Actividad para la Economía Peruana," Documentos de Investigación dt39, Grupo de Análisis para el Desarrollo (GRADE).
    8. Jacques Anas & Laurent Ferrara, 2004. "Detecting Cyclical Turning Points: The ABCD Approach and Two Probabilistic Indicators," Journal of Business Cycle Measurement and Analysis, OECD Publishing,CIRET, vol. 2004(2), pages 193-225.
    9. Benoit Bellone & David Saint-Martin, 2004. "Detecting Turning Points with Many Predictors through Hidden Markov Models," Econometrics 0407001, EconWPA.
    10. Harding, Don & Pagan, Adrian, 2003. "A comparison of two business cycle dating methods," Journal of Economic Dynamics and Control, Elsevier, vol. 27(9), pages 1681-1690, July.
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