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A framework for economic forecasting

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Author Info
Neil R. Ericsson
Jaime Marquez

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Abstract

This paper proposes a tripartite framework of design, evaluation, and post-evaluation analysis for generating and interpreting economic forecasts. This framework's value is illustrated by re-examining mean square forecast errors from dynamic models and nonlinearity biases from empirical forecasts of U.S. external trade. Previous studies have examined properties such as nonlinearity bias and the possible nonmonotonicity and nonexistence of mean square forecast errors in isolation from other aspects of the forecasting process, resulting in inefficient forecasting techniques and seemingly puzzling phenomena. The framework developed reveals how each such property follows from systematically integrating all aspects of the forecasting process.

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Paper provided by Board of Governors of the Federal Reserve System (U.S.) in its series International Finance Discussion Papers with number 626.

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Date of creation: 1998
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Handle: RePEc:fip:fedgif:626

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Keywords: Forecasting;

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  1. Beach, Charles M & MacKinnon, James G, 1978. "A Maximum Likelihood Procedure for Regression with Autocorrelated Errors," Econometrica, Econometric Society, vol. 46(1), pages 51-58, January. [Downloadable!] (restricted)
  2. Bianchi, Carlo & Calzolari, Giorgio & Brillet, Jean-Louis, 1987. "Measuring forecast uncertainty : A review with evaluation based on a macro model of the French economy," International Journal of Forecasting, Elsevier, vol. 3(2), pages 211-227. [Downloadable!] (restricted)
  3. Calzolari, Giorgio, 1987. "Forecast Variance in Dynamic Simulation of Simultaneous Equation Models," Econometrica, Econometric Society, vol. 55(6), pages 1473-76, November. [Downloadable!] (restricted)
  4. Calzolari, Giorgio, 1979. "Antithetic variates to estimate the simulation bias in non-linear models," Economics Letters, Elsevier, vol. 4(4), pages 323-328. [Downloadable!] (restricted)
  5. Baillie, Richard T, 1981. "Prediction from the Dynamic Simultaneous Equation Model with Vector Autoregressive Errors," Econometrica, Econometric Society, vol. 49(5), pages 1331-37, September. [Downloadable!] (restricted)
  6. Calzolari, Giorgio, 1981. "A Note on the Variance of Ex-Post Forecasts in Econometric Models," Econometrica, Econometric Society, vol. 49(6), pages 1593-95, November. [Downloadable!] (restricted)
  7. Calzolari, Giorgio & Sterbenz, Frederic P, 1986. "Control Variates to Estimate the Reduced Form Variances in Econometric Models," Econometrica, Econometric Society, vol. 54(6), pages 1483-90, November. [Downloadable!] (restricted)
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(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  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.). [Downloadable!]
  2. Guillaume Chevillon, 2005. "Direct multi-step estimation and forecasting," Documents de Travail de l'OFCE 2005-10, Observatoire Francais des Conjonctures Economiques (OFCE). [Downloadable!]
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  3. Daniel J. Wilson, 2001. "Embodying embodiment in a structural, macroeconomic input-output model," Working Papers in Applied Economic Theory 2001-18, Federal Reserve Bank of San Francisco. [Downloadable!]
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  4. John Galbraith, 1999. "Content Horizons for Forecasts of Economic Time Series," CIRANO Working Papers 99s-17, CIRANO. [Downloadable!]
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  5. Neil R. Ericsson, 2000. "Predictable uncertainty in economic forecasting," International Finance Discussion Papers 695, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
  6. Jenny Li & Peter Winker, 2003. "Time Series Simulation with Quasi Monte Carlo Methods," Computational Economics, Springer, vol. 21(1), pages 23-43, February. [Downloadable!] (restricted)
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