Faktoru modeļu agregēta un dezagregēta pieeja IKP prognožu precizitātes mērīšanā
Measuring GDP forecasting accuracy using factor models: aggregated vs. disaggregated approach
MPRA Paper from University Library of Munich, Germany
The purpose of this paper is to conduct whether the disaggregated data of GDP gives us any additional information in the sense of forecasting accuracy. To test latter hypothesis author employs Stock-Watson factor model. GDP is disaggregated both on expenditure basis and on output basis. Thus both approaches should widen overlook to comparison’s capability. In order to measure forecasting accuracy root mean squared error measure was employed. Author concludes that disaggregated approach outperforms aggregated data but at very little extent. In addition, factor model showed better results in the sense of forecasting accuracy and outperformed univariate models on average by 20-30%.
Keywords: Factor model; out-of-sample forecasting; disaggregated approach; real-time database. (search for similar items in EconPapers)
JEL-codes: C22 C32 C53 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:30386
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