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Policy Makers Priors and Inflation Density Forecasts

Author

Listed:
  • Marco Vega

    (LSE & Central Bank of Peru)

Abstract

This paper models an inflation forecast density framework that closely resembles actual policy makers behaviour regarding the determination of the modal point, the uncertainty and asymmetry in the inflation forecasts. The framework combines policy makers prior information about these parameters with a standard parametric density estimation technique using Bayesian theory. The combination crucially hinges on an information-theoretic utility function gains of the policy maker from performing the forecast exercise.

Suggested Citation

  • Marco Vega, 2004. "Policy Makers Priors and Inflation Density Forecasts," Econometrics 0403005, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpem:0403005
    Note: Type of Document - pdf; pages: 32
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    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/em/papers/0403/0403005.pdf
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    References listed on IDEAS

    as
    1. Neil R. Ericsson, 2001. "Forecast uncertainty in economic modeling," International Finance Discussion Papers 697, Board of Governors of the Federal Reserve System (U.S.).
    2. repec:sae:niesru:v:167:y::i:1:p:106-112 is not listed on IDEAS
    3. Kilian, Lutz & Manganelli, Simone, 2003. "The Central Banker as a Risk Manager: Quantifying and Forecasting Inflation Risks," CEPR Discussion Papers 3918, C.E.P.R. Discussion Papers.
    4. Wallis, Kenneth F., 2003. "Chi-squared tests of interval and density forecasts, and the Bank of England's fan charts," International Journal of Forecasting, Elsevier, vol. 19(2), pages 165-175.
    5. Christopher A. Sims, 2002. "The Role of Models and Probabilities in the Monetary Policy Process," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 33(2), pages 1-62.
    6. Anthony Tay & Kenneth F. Wallis, 2000. "Density Forecasting: A Survey," Econometric Society World Congress 2000 Contributed Papers 0370, Econometric Society.
    7. C. A. E. Goodhart, 2001. "The Inflation Forecast," National Institute Economic Review, National Institute of Economic and Social Research, vol. 175(1), pages 59-66, January.
    8. Svensson, Lars E. O., 1997. "Inflation forecast targeting: Implementing and monitoring inflation targets," European Economic Review, Elsevier, vol. 41(6), pages 1111-1146, June.
    9. Klaus Schmidt-Hebbel & Matías Tapia, 2002. "Monetary Policy Implementation and Results in Twenty Inflation-Targeting Countries," Working Papers Central Bank of Chile 166, Central Bank of Chile.
    10. Charles A. E. Goodhart, 2001. "Monetary transmission lags and the formulation of the policy decision on interest rates," Review, Federal Reserve Bank of St. Louis, vol. 83(Jul), pages 165-186.
    11. John Geweke, 1999. "Using simulation methods for bayesian econometric models: inference, development,and communication," Econometric Reviews, Taylor & Francis Journals, vol. 18(1), pages 1-73.
    12. Schmidt-Hebbel, Klaus & Tapia, Matias, 2002. "Inflation targeting in Chile," The North American Journal of Economics and Finance, Elsevier, vol. 13(2), pages 125-146, August.
    13. Svensson, Lars E. O., 1999. "Inflation targeting as a monetary policy rule," Journal of Monetary Economics, Elsevier, vol. 43(3), pages 607-654, June.
    14. Wallis, Kenneth F., 1999. "Asymmetric density forecasts of inflation and the Bank of England's fan chart," National Institute Economic Review, National Institute of Economic and Social Research, vol. 167, pages 106-112, January.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Juan Manuel Julio, 2005. "Implementacion, Uso e Interpretaci�n del FAN CHART," Borradores de Economia 2815, Banco de la Republica.
    2. Dong Jin Lee, 2009. "Testing Parameter Stability in Quantile Models: An Application to the U.S. Inflation Process," Working papers 2009-26, University of Connecticut, Department of Economics.
    3. Mihaela Bratu, 2011. "The Assessement Of Uncertainty In Predictions Determined By The Variables Aggregation," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 2(13), pages 1-31.
    4. Bratu Simionescu Mihaela, 2012. "Variables Aggregation-Source of Uncertainty in Forecasting," Scientific Annals of Economics and Business, Sciendo, vol. 59(2), pages 1-13, December.
    5. Juan Manuel Julio, 2005. "Implementación, Uso e Interpretación del "Fan Chart"," Borradores de Economia 346, Banco de la Republica de Colombia.
    6. Amparo Maset-Llaudes & Ana Mª Fuertes-Eugenio & Pilar Pardo-Forcadell, 2011. "Integrated Urban Regeneration: An Empirical Study Of The Normative Framework In Spanish Regions," ERSA conference papers ersa11p1781, European Regional Science Association.
    7. Mihaela Bratu, 2011. "Uncertainty of USA GDP Forecasts Determined by The Variables Aggregation," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 14(42), pages 25-46, December.

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    Keywords

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    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • 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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