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Composite Forecasting: An Integrated Approach and Optimality Reconsidered
Robert F. Phillips
Journal of Business & Economic Statistics
Vol. 5, No. 3 (Jul., 1987), pp. 389-395
Stable URL: http://www.jstor.org/stable/1391614
Page Count: 7
You can always find the topics here!Topics: Analytical forecasting, Lagrange multipliers, Linear regression, Gross national product, Economic statistics, Statistical forecasts, Forecasting techniques, Economic forecasting, Matrices, Statistical estimation
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This article shows when the theoretical Lagrange multiplier solution for combining forecasts has a regression representation. This solution is not optimal in general because it imposes a restriction on an otherwise more general linear form. The optimal linear predictor based on N forecasts is presented. This predictor is or is not a regression function depending on whether the latter function is linear. I also show that the Lagrange multiplier solution may often be nearly optimal. Hence, when estimating a composite forecast, the restriction imposed by this solution may prove useful. This observation is supported in an empirical example.
Journal of Business & Economic Statistics © 1987 American Statistical Association