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The Assessement Of Uncertainty In Predictions Determined By The Variables Aggregation

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  • Mihaela Bratu

Abstract

The aggregation of the variables that compose an indicator, as GDP, which should be forecasted, is not mentioned explicitly in literature as a source of forecasts uncertainty. In this article we demonstrate that variables aggregation is an important source of uncertainty in forecasting and we evaluate the accuracy of predictions for a variable obtained by aggregation using two different strategies. Actually, the accuracy is an important dimension of uncertainty. In this study based on data on U.S. GDP and its components in 1995-2010, we found that GDP one- step-ahead forecasts made by aggregating the components with variable weights, modeled using ARMA procedure, have a higher accuracy than those with constant weights or the direct forecasts. Excepting the GDP forecasts obtained directly from the model, the one-step-ahead forecasts resulted form the GDP components' forecasts aggregation are better than those made on an horizon of 3 years . The evaluation of this source of uncertainty should be considered for macroeconomic aggregates in order to choose the most accurate forecast.

Suggested Citation

  • Mihaela Bratu, 2011. "The Assessement Of Uncertainty In Predictions Determined By The Variables Aggregation," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 2(13), pages 1-31.
    • Handle: RePEc:alu:journl:v:2:y:2011:i:13:p:31
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    References listed on IDEAS

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    More about this item

    Keywords

    source of uncertainty; forecasts; accuracy; disaggregation over variables; strategy of prediction; DM test;
    All these keywords.

    JEL classification:

    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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