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Are Forecast Updates Progressive?

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Abstract

Macro-economic forecasts typically involve both a model component, which is replicable, as well as intuition, which is non-replicable. Intuition is expert knowledge possessed by a forecaster. If forecast updates are progressive, forecast updates should become more accurate, on average, as the actual value is approached. Otherwise, forecast updates would be neutral. The paper proposes a methodology to test whether forecast updates are progressive and whether econometric models are useful in updating forecasts. The data set for the empirical analysis are for Taiwan, where we have three decades of quarterly data available of forecasts and updates of the inflation rate and real GDP growth rate. The actual series for both the inflation rate and the real GDP growth rate are always released by the government one quarter after the release of the revised forecast, and the actual values are not revised after they have been released. Our empirical results suggest that the forecast updates for Taiwan are progressive, and can be explained predominantly by intuition. Additionally, the one-, two- and three-quarter forecast errors are predictable using publicly available information for both the inflation rate and real GDP growth rate, which suggests that the forecasts can be improved.

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  • Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2010. "Are Forecast Updates Progressive?," Working Papers in Economics 10/12, University of Canterbury, Department of Economics and Finance.
  • Handle: RePEc:cbt:econwp:10/12
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    File URL: https://repec.canterbury.ac.nz/cbt/econwp/1012.pdf
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    1. Mcleer, M. & Mckenzie, C.R., 1989. "When Are Two Step Estimators Efficient?," Papers 179, Australian National University - Department of Economics.
    2. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, vol. 105(1), pages 85-110, November.
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    6. MICHAEL McALEER, 1992. "Efficient Estimation: The Rao‐Zyskind Condition, Kruskal's Theorem and Ordinary Least Squares," The Economic Record, The Economic Society of Australia, vol. 68(1), pages 65-72, March.
    7. Oxley, Les & McAleer, Michael, 1993. "Econometric Issues in Macroeconomic Models with Generated Regressors," Journal of Economic Surveys, Wiley Blackwell, vol. 7(1), pages 1-40.
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    9. Bunn, Derek W. & Salo, Ahti A., 1996. "Adjustment of forecasts with model consistent expectations," International Journal of Forecasting, Elsevier, vol. 12(1), pages 163-170, March.
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    1. What Have You Been Reading?
      by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2013-06-12 00:47:00

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    Cited by:

    1. Michael McAleer & Felix Chan & Les Oxley, 2013. "Modeling and Simulation: An Overview," Working Papers in Economics 13/18, University of Canterbury, Department of Economics and Finance.

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    More about this item

    Keywords

    Macro-economic forecasts; econometric models; intuition; initial forecast; primary forecast; revised forecast; actual value; progressive forecast updates; forecast errors;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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