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Econometric Modeling as Information Aggregation

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Abstract

The information contained in the forecasts from two econometric models can be compared by regressing the actual change in the variable forecasted on the two forecasts of the change. We do such comparisons in this paper, where the forecasts are based only on information through the period prior to the first period of the forecast. If a model's forecast is statistically significant in such a regression, we conclude that the model captures information not in the other model whose forecast is also included in the regression. The models studied include the Fair model, vector autoregressive (VAR) models estimated by ordinary least squares, vector autoregressive models estimated with Litterman priors, and a new class of models, which we call "autoregressive components: (AC) models. The AC models divide GNP into components and estimate an autoregressive equation for each component. Our results show that the Fair model's forecasts contain information not in the forecasts of the VAR and AC models. The AC models contain no information not in the Fair model, which indicates that the Fair model uses all the useful information in the components. The VAR models contain information not in the Fair model for the four-quarter-ahead forecasts but not the one- quarter-ahead forecasts. The best AC model contains information not in the best VAR model, which indicates that there is useful information in the components that the VAR models are not using. The best VAR model contains information not in the best AC model for the four-quarter-ahead forecasts but not the one-quarter-ahead forecasts.

Suggested Citation

  • Ray C. Fair & Robert J. Shiller, 1987. "Econometric Modeling as Information Aggregation," Cowles Foundation Discussion Papers 833R, Cowles Foundation for Research in Economics, Yale University, revised Jan 1988.
  • Handle: RePEc:cwl:cwldpp:833r
    Note: CFP 754.
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    References listed on IDEAS

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    1. Cumby, Robert E. & Huizinga, John & Obstfeld, Maurice, 1983. "Two-step two-stage least squares estimation in models with rational expectations," Journal of Econometrics, Elsevier, vol. 21(3), pages 333-355, April.
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    3. Robert B. Litterman, 1984. "Forecasting with Bayesian vector autoregressions four years of experience," Staff Report 95, Federal Reserve Bank of Minneapolis.
    4. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 39(3), pages 106-135.
    5. P. C. B. Phillips & S. N. Durlauf, 1986. "Multiple Time Series Regression with Integrated Processes," Review of Economic Studies, Oxford University Press, vol. 53(4), pages 473-495.
    6. Fair, Ray C, 1978. "The Sensitivity of Fiscal Policy Effects to Assumptions about the Behavior of the Federal Reserve," Econometrica, Econometric Society, vol. 46(5), pages 1165-1179, September.
    7. Davidson, Russell & MacKinnon, James G, 1981. "Several Tests for Model Specification in the Presence of Alternative Hypotheses," Econometrica, Econometric Society, vol. 49(3), pages 781-793, May.
    8. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    9. Robert B. Litterman, 1979. "Techniques of forecasting using vector autoregressions," Working Papers 115, Federal Reserve Bank of Minneapolis.
    10. Yock Y. Chong & David F. Hendry, 1986. "Econometric Evaluation of Linear Macro-Economic Models," Review of Economic Studies, Oxford University Press, vol. 53(4), pages 671-690.
    11. Granger, C. W. J. & Newbold, Paul, 1986. "Forecasting Economic Time Series," Elsevier Monographs, Elsevier, edition 2, number 9780122951831 edited by Shell, Karl.
    12. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    13. Hendry, David F. & Richard, Jean-Francois, 1982. "On the formulation of empirical models in dynamic econometrics," Journal of Econometrics, Elsevier, vol. 20(1), pages 3-33, October.
    14. Mizon, Grayham E & Richard, Jean-Francois, 1986. "The Encompassing Principle and Its Application to Testing Non-nested Hypotheses," Econometrica, Econometric Society, vol. 54(3), pages 657-678, May.
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    Cited by:

    1. Robert J. Shiller, 1987. "Ultimate Sources of Aggregate Variability," Cowles Foundation Discussion Papers 816, Cowles Foundation for Research in Economics, Yale University.
    2. Ray C. Fair, 1987. "VAR Models as Structural Approximations," Cowles Foundation Discussion Papers 856R, Cowles Foundation for Research in Economics, Yale University, revised Mar 1989.
    3. Bentour, El Mostafa, 2015. "A ranking of VAR and structural models in forecasting," MPRA Paper 61502, University Library of Munich, Germany.

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