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Evaluating Multi-Step System Forecasts with Relatively Few Forecast-Error Observations

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  • David Hendry
  • Andrew B. Martinez

Abstract

Abstract: This paper develops a new approach for evaluating multi-step system forecasts with relatively few forecast-error observations. It extends Clements and Hendry (1993a) using Abadir et al.(2014) to generate "design-free" estimates of the general matrix of the forecast-error second-moment when there are relatively few forecast-error observations. Simulations show that the usefulness of alternative methods deteriorates when their assumptions are violated. The new approach compares well against these methods and provides correct forecast rankings.

Suggested Citation

  • David Hendry & Andrew B. Martinez, 2016. "Evaluating Multi-Step System Forecasts with Relatively Few Forecast-Error Observations," Economics Series Working Papers 784, University of Oxford, Department of Economics.
  • Handle: RePEc:oxf:wpaper:784
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    File URL: http://www.economics.ox.ac.uk/materials/papers/14425/paper-784.pdf
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    References listed on IDEAS

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    Cited by:

    1. repec:spr:jbuscr:v:12:y:2016:i:1:d:10.1007_s41549-016-0005-2 is not listed on IDEAS
    2. Jennifer L. Castle & Michael P. Clements & David F. Hendry, 2016. "An Overview of Forecasting Facing Breaks," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 3-23, September.
    3. Ericsson, Neil R., 2017. "Economic forecasting in theory and practice: An interview with David F. Hendry," International Journal of Forecasting, Elsevier, vol. 33(2), pages 523-542.
    4. Michael Clements, 2016. "Are Macro-Forecasters Essentially The Same? An Analysis of Disagreement, Accuracy and Efficiency," ICMA Centre Discussion Papers in Finance icma-dp2016-08, Henley Business School, Reading University.
    5. Håvard Hungnes, 2018. "Encompassing tests for evaluating multi-step system forecasts invariant to linear transformations," Discussion Papers 871, Statistics Norway, Research Department.

    More about this item

    Keywords

    Invariance; Forecast Evaluation; Forecast Error; Moment Matrices; MSFE; GFESM;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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