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Modelling multi-period inflation uncertainty using a panel of density forecasts

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  • Fushang Liu

    (Department of Economics, University at Albany, SUNY Albany, NY 12222, USA)

  • Kajal Lahiri

    (Department of Economics, University at Albany, SUNY Albany, NY 12222, USA)

Abstract

This paper examines the determinants of inflation forecast uncertainty using a panel of density forecasts from the Survey of Professional Forecasters (SPF). Based on a dynamic heterogeneous panel data model, we find that the persistence in forecast uncertainty is much less than what the aggregate time series data would suggest. In addition, the strong link between past forecast errors and current forecast uncertainty, as often noted in the ARCH literature, is largely lost in a multi-period context with varying forecast horizons. We propose a novel way of estimating 'news' and its variance using the Kullback-Leibler information, and show that the latter is an important determinant of forecast uncertainty. Our evidence suggests a strong relationship of forecast uncertainty with level of inflation, but not with forecaster discord or with the volatility of a number of other macroeconomic indicators. Copyright © 2006 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/jae.880
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Bibliographic Info

Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 21 (2006)
Issue (Month): 8 ()
Pages: 1199-1219

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Handle: RePEc:jae:japmet:v:21:y:2006:i:8:p:1199-1219

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Citations

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Cited by:
  1. Stefania D'Amico & Athanasios Orphanides, 2008. "Uncertainty and disagreement in economic forecasting," Finance and Economics Discussion Series 2008-56, Board of Governors of the Federal Reserve System (U.S.).
  2. Carrera, César, 2012. "Estimating Information Rigidity using Firms’ Survey Data," Working Papers 2012-004, Banco Central de Reserva del Perú.
  3. Kajal Lahiri & Fushang Liu, 2009. "On the Use of Density Forecasts to Identify Asymmetry in Forecasters' Loss Functions," Discussion Papers 09-03, University at Albany, SUNY, Department of Economics.
  4. Badi H. Baltagi, 2008. "Forecasting with panel data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 153-173.
  5. Wojciech Charemza & Carlos Diaz & Svetlana Makarova, 2014. "Term Structure Of Inflation Forecast Uncertainties And Skew Normal Distributions," Discussion Papers in Economics 14/01, Department of Economics, University of Leicester.
  6. Kajal Lahiri & Xuguang Sheng, 2008. "Measuring Forecast Uncertainty by Disagreement: The Missing Link," Ifo Working Paper Series Ifo Working Paper No. 60, Ifo Institute for Economic Research at the University of Munich.
  7. Halina Kowalczyk & Tomasz Lyziak & Ewa Stanisławska, 2013. "A new approach to probabilistic surveys of professional forecasters and its application in the monetary policy context," National Bank of Poland Working Papers 142, National Bank of Poland, Economic Institute.
  8. Wojciech Charemza & Carlos Diaz Vela & Svetlana Makarova, 2013. "Inflation fan charts, monetary policy and skew normal distribution," Discussion Papers in Economics 13/06, Department of Economics, University of Leicester.
  9. Knüppel, Malte, 2014. "Efficient estimation of forecast uncertainty based on recent forecast errors," International Journal of Forecasting, Elsevier, vol. 30(2), pages 257-267.

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