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A Note On Forecasting With Econometric Models

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  • Allen, P. Geoffrey

Abstract

Forecasts made by econometricians are typically conditioned on actual values of explanatory variables, even when at the time of the forecast, such variables might not be available. As a first step, one might test the adequacy of econometric specification by comparing conditional post sample forecasts with those of a univariate ARIMA model. Second, when explanatory variables must themselves be forecast, those for which this can be done only badly, should be omitted from the final model. A better forecast will result. An example of screening out badly forecasted explanatory variables is presented.

Suggested Citation

  • Allen, P. Geoffrey, 1984. "A Note On Forecasting With Econometric Models," Northeastern Journal of Agricultural and Resource Economics, Northeastern Agricultural and Resource Economics Association, vol. 13(2), pages 1-4, October.
  • Handle: RePEc:ags:nejare:28916
    DOI: 10.22004/ag.econ.28916
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    References listed on IDEAS

    as
    1. Grayham E. Mizon & David F. Hendry, 1980. "An Empirical Application and Monte Carlo Analysis of Tests of Dynamic Specification," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 21-45.
    2. Hudson, Michael A. & Capps, Oral, Jr., 1984. "Forecasting Ex-Vessel Prices for Hard Blue Crabs in the Chesapeake Bay Region: Individual and Composite Methods," Northeastern Journal of Agricultural and Resource Economics, Northeastern Agricultural and Resource Economics Association, vol. 0(Number 1), pages 1-7, April.
    3. J. D. Sargan, 1980. "The Consumer Price Equation in the Post War British Economy: An Exercise in Equation Specification Testing," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 113-135.
    4. Hudson, Michael A. & Capps, Oral, Jr., 1984. "Forecasting Ex-Vessel Prices for Hard Blue Crabs in the Chesapeake Bay Region: Individual and Composite Methods," Journal of the Northeastern Agricultural Economics Council, Northeastern Agricultural and Resource Economics Association, vol. 13(1), pages 1-7, April.
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