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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. 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.
    2. Oliver Linton & Pedro Gozalo, 1996. "Conditional Independence Restrictions: Testing and Estimation," Cowles Foundation Discussion Papers 1140, Cowles Foundation for Research in Economics, Yale University.
    3. 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.
    4. 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.
    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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