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Indicadores Sintéticos para la Proyección de Imacec en Chile

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  • Gonzalo Calvo
  • Miguel Ricaurte

Abstract

This paper studies the informational content of synthetic indicators of economic activity for projecting the monthly index of economic activity (Imacec) for Chile. Comparing them to the Urrutia-Sánchez (2008) model, which employs energy production, and calendar and seasonal components to forecast the Imacec, models employing synthetic leading indicators and financial conditions indicators are competitive in terms of the MSFE. Moreover, we show that combinations of different forecasting strategies with small bias present improvements in terms of the MSFE with respect to individual models. We also show that, due to their inertial behavior, projections with synthetic indicators display errors that last for many periods after an exogenous event (such as an earthquake). Specifications with variables that quickly adjust to economic activity, such as energy consumption, do not have this problem.

Suggested Citation

  • Gonzalo Calvo & Miguel Ricaurte, 2012. "Indicadores Sintéticos para la Proyección de Imacec en Chile," Working Papers Central Bank of Chile 656, Central Bank of Chile.
    • Handle: RePEc:chb:bcchwp:656
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    File URL: https://www.bcentral.cl/documents/33528/133326/DTBC_656.pdf
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    References listed on IDEAS

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    1. Raffaella Giacomini & Halbert White, 2006. "Tests of Conditional Predictive Ability," Econometrica, Econometric Society, vol. 74(6), pages 1545-1578, November.
    2. Michael Pedersen, 2009. "Un indicador líder compuesto para la actividad económica en Chile," Monetaria, CEMLA, vol. 0(2), pages 181-208, abril-jun.
    3. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    4. Luis Ceballos S. & Mario González F., 2012. "Indicador de Condiciones Económicas," Notas de Investigación Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 15(1), pages 105-117, April.
    5. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    6. Marcela Urrutia A. & Andrea Sánchez Y., 2008. "Generación de Energía Eléctrica en un Modelo para Proyectar el IMACEC," Notas de Investigación Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 11(2), pages 99-108, August.
    7. G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.
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    Cited by:

    1. Nicolás Chanut & Mario Marcel C. & Carlos A. Medel V., 2019. "Can economic perception surveys improve macroeconomic forecasting in Chile?," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 22(3), pages 034-097, December.
    2. Fernando Faure & Carlos A. Medel, 2020. "Does the Exposure to the Business Cycle Improve Consumer Perceptions for Forecasting? Microdata Evidence from Chile," Working Papers Central Bank of Chile 888, Central Bank of Chile.
    3. Luis Ceballos S. & Miguel Fuentes D. & Damián Romero C., 2013. "Efectos del Riesgo Financiero en Fuentes de Financiamiento de Empresas, Hogares y Bancos," Notas de Investigación Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 16(2), pages 134-148, August.

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