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Nowcasting Peruvian GDP using Leading Indicators and Bayesian Variable Selection

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  • Pérez, Fernando

    (Banco Central de Reserva del Perú)

Abstract

There exists a large set of leading indicators that are directly related with GDP growth. However, it is often very difficult to select which of these indicators can be used in order to choose the best shortterm forecasting (nowcasting) model. In addition, it may be the case that more than one model can do this job accurately. Therefore, it would be convenient to average these potentially non-nested models. Following Scott and Varian (2015), we estimate a Structural State Space model through Gibbs Sampling and a spike-slab prior in order to perform the Stochastic Search Variable Selection (SSVS) method. Posterior simulations can be used to then compute the inclusion probability of each variable for the whole set of models considered. In-sample GDP estimates are very precise, taking into account the large set of regressors considered for the estimation. Data comes from the BCRPs database plus other additional sources.

Suggested Citation

  • Pérez, Fernando, 2018. "Nowcasting Peruvian GDP using Leading Indicators and Bayesian Variable Selection," Working Papers 2018-010, Banco Central de Reserva del Perú.
  • Handle: RePEc:rbp:wpaper:2018-010
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    References listed on IDEAS

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    1. Tiago M. Fragoso & Wesley Bertoli & Francisco Louzada, 2018. "Bayesian Model Averaging: A Systematic Review and Conceptual Classification," International Statistical Review, International Statistical Institute, vol. 86(1), pages 1-28, April.
    2. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
    3. Bragoli, Daniela, 2017. "Now-casting the Japanese economy," International Journal of Forecasting, Elsevier, vol. 33(2), pages 390-402.
    4. Daniela Bragoli & Luca Metelli & Michele Modugno, 2015. "The importance of updating: Evidence from a Brazilian nowcasting model," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2015(1), pages 5-22.
    5. Martin D. D. Evans, 2005. "Where Are We Now? Real-Time Estimates of the Macroeconomy," International Journal of Central Banking, International Journal of Central Banking, vol. 1(2), September.
    6. Bańbura, Marta & Giannone, Domenico & Modugno, Michele & Reichlin, Lucrezia, 2013. "Now-Casting and the Real-Time Data Flow," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.),Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 195-237, Elsevier.
    7. Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 615-643, August.
    8. Daniela Bragoli & Jack Fosten, 2018. "Nowcasting Indian GDP," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(2), pages 259-282, April.
    9. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2005. "Nowcasting GDP and Inflation: The Real Time Informational Content of Macroeconomic Data Releases," CEPR Discussion Papers 5178, C.E.P.R. Discussion Papers.
    10. 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).
    11. Ochoa, Enrique & Lladó, Jorge, 2003. "Modelos de indicadores líderes de actividad económica para el Perú," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 10.
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    More about this item

    Keywords

    Nowcasting; Gibbs Sampling; Variable Selection; Model Averaging;

    JEL classification:

    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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