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• W1599624104 abstract "Forecast combination methodologies exploit complementary relations between different types of econometric models and often deliver more accurate forecasts than the individual models on which they are based. This paper examines forecasts of seasonally unadjusted monthly industrial production data for 17 countries and the Euro Area, comparing individual model forecasts and forecast combination methods in order to examine whether the latter are able to take advantage of the properties of different seasonal specifications. In addition to linear models (with deterministic seasonality and with nonstationary stochastic seasonality), more complex models that capture nonlinearity or seasonally varying coefficients (periodic models) are also examined. Although parsimonous periodic models perform well for some countries, forecast combinations provide the best overall performance at short horizons, implying that utilizing the characteristics captured by different models can contribute to improved forecast accuracy." @default.
• W1599624104 created "2016-06-24" @default.
• W1599624104 creator A5028286627 @default.
• W1599624104 date "2008-01-01" @default.
• W1599624104 modified "2023-09-27" @default.
• W1599624104 title "COMPARING SEASONAL FORECASTS OF INDUSTRIAL PRODUCTION" @default.
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