Energy consumption, survey data and the prediction of industrial production in Italy: a comparison and combination of different models
We investigate the prediction of italian industrial production and first specify a model based on electricity consumption showing that the cubic trend in such a model mostly captures the evolution over time of the electricity coefficient, which can be well approximated by a smooth transition model,...
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Veröffentlicht in: | Journal of forecasting 2000-09, Vol.19 (5), p.419-440 |
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description | We investigate the prediction of italian industrial production and first specify a model based on electricity consumption showing that the cubic trend in such a model mostly captures the evolution over time of the electricity coefficient, which can be well approximated by a smooth transition model, with no gains in predictive power. We also analyse the performance of models based on data of two different business surveys. According to the standard statistics of forecasting accuracy, the linear energy‐based model is not outperformed by any other model, nor by a combination of forecasts. However, a more comprehensive set of evaluation criteria sheds light on the relative merit of each individual model. A modelling strategy which makes full use of all information available is proposed. Copyright © 2000 John Wiley & Sons, Ltd. |
doi_str_mv | 10.1002/1099-131X(200009)19:5<419::AID-FOR749>3.0.CO;2-J |
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Forecast</addtitle><description>We investigate the prediction of italian industrial production and first specify a model based on electricity consumption showing that the cubic trend in such a model mostly captures the evolution over time of the electricity coefficient, which can be well approximated by a smooth transition model, with no gains in predictive power. We also analyse the performance of models based on data of two different business surveys. According to the standard statistics of forecasting accuracy, the linear energy‐based model is not outperformed by any other model, nor by a combination of forecasts. However, a more comprehensive set of evaluation criteria sheds light on the relative merit of each individual model. A modelling strategy which makes full use of all information available is proposed. 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A modelling strategy which makes full use of all information available is proposed. Copyright © 2000 John Wiley & Sons, Ltd.</abstract><cop>Chichester, UK</cop><pub>John Wiley & Sons, Ltd</pub><doi>10.1002/1099-131X(200009)19:5<419::AID-FOR749>3.0.CO;2-J</doi><tpages>22</tpages></addata></record> |
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subjects | Business cycles combination of forecasts Comparative analysis Economic models Electric power Electricity Electricity distribution Energy consumption Forecasting Forecasts Households Industrial production Information sources Italy Regression analysis smooth transition regression Studies Survey data Variables |
title | Energy consumption, survey data and the prediction of industrial production in Italy: a comparison and combination of different models |
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