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Predictive Consequences of Using Conditioning or Causal Variables

Author

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  • Granger, C.W.J.
  • Thomson, P. J.

Abstract

Forecasts based on two information sets, one of which includes the other plus additional causal variables are considered. Given a general cost function of forecast errors, it is shown that the expected cost is smaller for the information set that includes the causal variables.

Suggested Citation

  • Granger, C.W.J. & Thomson, P. J., 1987. "Predictive Consequences of Using Conditioning or Causal Variables," Econometric Theory, Cambridge University Press, vol. 3(1), pages 150-152, February.
    • Handle: RePEc:cup:etheor:v:3:y:1987:i:01:p:150-152_00
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    Cited by:

    1. Oliver Linton & Pedro Gozalo, 1996. "Conditional Independence Restrictions: Testing and Estimation," Cowles Foundation Discussion Papers 1140, Cowles Foundation for Research in Economics, Yale University.
    2. Fatih Ozatay, 1993. "Forecasting Contemporaneously Aggregated Variables Using Granger-Causal Variables," Discussion Papers 9302, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    3. McCrorie, J. Roderick & Chambers, Marcus J., 2006. "Granger causality and the sampling of economic processes," Journal of Econometrics, Elsevier, vol. 132(2), pages 311-336, June.
    4. Han Lin Shang & Kaiying Ji & Ufuk Beyaztas, 2021. "Granger causality of bivariate stationary curve time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 626-635, July.
    5. Fatith Ozatay, 2002. "Effects of contemporaneous aggregation on the predictive power of information variables," Applied Economics Letters, Taylor & Francis Journals, vol. 9(5), pages 339-342.

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