The Uncertainty of USA GDP Forecasts Determined by the Variables Aggregation

Mihaela Bratu ()
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Mihaela Bratu: Academy of Economic Studies, Faculty of Cybernetics, Statistics and Economic Informatics, Bucharest
Authors registered in the RePEc Author Service: Mihaela Simionescu

EuroEconomica, 2011, issue 30, 109-122

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 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 onestep-ahead forecasts resulted from 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.

Keywords: source of uncertainty; forecasts; accuracy; disaggregation over variables; strategy of prediction; DM test (search for similar items in EconPapers)
Date: 2011
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Journal Article: Uncertainty of USA GDP Forecasts Determined by The Variables Aggregation (2011)
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