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Combination of Potential Output Estimates With a Bayesian Method

Author

Listed:
  • Alberto Vindas-Quesada

    (Department of Economic Research, Central Bank of Costa Rica)

  • Carlos Monge-Badilla

    (Department of Economic Research, Central Bank of Costa Rica)

Abstract

In this paper, we calculated the potential output for the Costa Rican economy. First, we applied several different methods to calculate this non-observable variable, such as the Beveridge-Nelson decomposition, Hodrick-Prescott filter, production function, Kalman filter, and SVAR. Then, we combined the results of these methods using Bayesian Model Averaging (BMA) and a Phillips curve. Finally, we obtained optimal weights for each estimated potential product and estimated an indicator of the potential output series. ***Resumen: En el documento se realizan distintas metodologías de estimación del producto potencial para la economía costarricense. Dentro de los métodos que se utilizan para estimar esta variable no observable, se pueden mencionar la descomposición Beveridge-Nelson, el filtro Hodrick Prescott, la función de producción, el filtro de Kalman y el VAR estructural (SVAR). Los resultados de estos modelos se promedian empleando el método de Ponderación bayesiana de modelos (Bayesian Model Averaging, BMA), por medio de una curva de Phillips, con el fin de determinar los pesos óptimos para la obtención de un único indicador de producto potencial.

Suggested Citation

  • Alberto Vindas-Quesada & Carlos Monge-Badilla, 2015. "Combination of Potential Output Estimates With a Bayesian Method," Documentos de Trabajo 1501, Banco Central de Costa Rica.
    • Handle: RePEc:apk:doctra:1501
    as

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    File URL: https://repositorioinvestigaciones.bccr.fi.cr/handle/20.500.12506/86
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    References listed on IDEAS

    as
    1. Kuttner, Kenneth N, 1994. "Estimating Potential Output as a Latent Variable," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 361-368, July.
    2. Beveridge, Stephen & Nelson, Charles R., 1981. "A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the `business cycle'," Journal of Monetary Economics, Elsevier, vol. 7(2), pages 151-174.
    3. Magnus, Jan R. & Powell, Owen & Prüfer, Patricia, 2010. "A comparison of two model averaging techniques with an application to growth empirics," Journal of Econometrics, Elsevier, vol. 154(2), pages 139-153, February.
    4. 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.
    5. Giuseppe De Luca & Jan R. Magnus, 2011. "Bayesian model averaging and weighted-average least squares: Equivariance, stability, and numerical issues," Stata Journal, StataCorp LLC, vol. 11(4), pages 518-544, December.
    6. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, vol. 79(4), pages 655-673, September.
    7. Watson, Mark W., 1986. "Univariate detrending methods with stochastic trends," Journal of Monetary Economics, Elsevier, vol. 18(1), pages 49-75, July.
    Full references (including those not matched with items on IDEAS)

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    Keywords

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    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E50 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - General

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