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The Forecasting Accuracy of Regional Bayesian VAR Models with Alternative National Variable Choices

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  • Gary L. Shoesmith

    (Babcock Graduate School of Management, Wake Forest University, Winston-Salem, North Carolina 27109 USA)

Abstract

The forecasting accuracy of vector autoregressive (VAR) and Bayesian VAR (BVAR) versions of five different regional models are compared for three states. Two base models for each state consist of three national variables and three state variables. Three misspecified models are then constructed by substituting or adding a simulated (random) national variable to the base models. Forecasting accuracy is measured by each model's ability to forecast the three state variables one, four, and eight quarters ahead. Inclusion of the random variable generally reduces the forecasting accuracy of unrestricted VAR models. The BVAR technique is superior to the VAR approach in terms of forecasting accuracy but, more important, is largely insensitive to the choice of national variables, even when the misspecified national variable is included.

Suggested Citation

  • Gary L. Shoesmith, 1990. "The Forecasting Accuracy of Regional Bayesian VAR Models with Alternative National Variable Choices," International Regional Science Review, , vol. 13(3), pages 257-269, December.
    • Handle: RePEc:sae:inrsre:v:13:y:1990:i:3:p:257-269
    DOI: 10.1177/016001769001300304
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    References listed on IDEAS

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    1. Richard M. Todd, 1984. "Improving economic forecasting with Bayesian vector autoregression," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 8(Fall).
    2. Christopher A. Sims, 1986. "Are forecasting models usable for policy analysis?," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 10(Win), pages 2-16.
    3. Terrence Kinal & Jonathan Ratner, 1986. "A VAR Forecasting Model of a Regional Economy: Its Construction and Comparative Accuracy," International Regional Science Review, , vol. 10(2), pages 113-126, August.
    4. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    5. Robert B. Litterman, 1984. "Forecasting and policy analysis with Bayesian vector autoregression models," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 8(Fall).
    6. McNees, Stephen K., 1986. "Forecasting accuracy of alternative techniques: A comparison of US macroeconomic forecasts, with comment : Stephen K. McNees, with comment, Journal of Business and Economic Statistics 4 (1986) 5-23," International Journal of Forecasting, Elsevier, vol. 2(4), pages 497-498.
    7. McNees, Stephen K, 1986. "Forecasting Accuracy of Alternative Techniques: A Comparison of U.S. Macroeconomic Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 5-15, January.
    8. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    9. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
    10. James G. Hoehn, 1984. "A regional economic forecasting procedure applied to Texas," Working Papers (Old Series) 8402, Federal Reserve Bank of Cleveland.
    11. Roy H. Webb, 1984. "Vector autoregressions as a tool for forecast evaluations," Economic Review, Federal Reserve Bank of Richmond, vol. 70(Jan), pages 3-11.
    12. McNees, Stephen K, 1986. "Forecasting Accuracy of Alternative Techniques: A Comparison of U.S. Macroeconomic Forecasts: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 1-23, January.
    13. Paul A. Anderson, 1979. "Help for the regional economic forecaster: vector autoregression," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 3(Sum).
    14. Thomas J. Sargent, 1979. "Estimating vector autoregressions using methods not based on explicit economic theories," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 3(Sum).
    15. Litterman, Robert, 1986. "Forecasting with Bayesian vector autoregressions -- Five years of experience : Robert B. Litterman, Journal of Business and Economic Statistics 4 (1986) 25-38," International Journal of Forecasting, Elsevier, vol. 2(4), pages 497-498.
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    Cited by:

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    2. Sarantis, Nicholas & Swales, Caspar, 1999. "Modelling and forecasting regional service employment in Great Britain1," Economic Modelling, Elsevier, vol. 16(3), pages 429-453, August.

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