Modelling long-run energy consumption under model uncertainty

The causality between energy consumption and real income in developed countries has been a very vital research topic in recent years. Raising concerns about climate change and global warming increase the pressure on policy makers to take action against energy depletion. Unfortunately these efforts c...

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Main Authors: Stefan Humer, Csereklyei, Z.
Format: Report
Language:unknown
Subjects:
Online Access:http://ecomod.net/system/files/CsereklyeiHumer_ModellingPrimaryEnergy_underUncertainty_0.pdf
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spelling ftrepec:oai:RePEc:ekd:002672:4374 2024-04-14T08:13:50+00:00 Modelling long-run energy consumption under model uncertainty Stefan Humer Csereklyei, Z. http://ecomod.net/system/files/CsereklyeiHumer_ModellingPrimaryEnergy_underUncertainty_0.pdf unknown http://ecomod.net/system/files/CsereklyeiHumer_ModellingPrimaryEnergy_underUncertainty_0.pdf preprint ftrepec 2024-03-19T10:27:27Z The causality between energy consumption and real income in developed countries has been a very vital research topic in recent years. Raising concerns about climate change and global warming increase the pressure on policy makers to take action against energy depletion. Unfortunately these efforts coincide with one of the largest global economic recessions in the past century. Establishing the link between energy consumption and other key macroeconomic variables like real GDP, labour force, capital stock and technology thus currently appears as a particularly relevant research effort.In this area of the literature, uncertainty about the choice of a statistical model is rarely considered. Whenever one model is opted over reasonable alternative models to represent knowledge about a specific process, model uncertainty occurs. We argue that inference on the basis of a single model without taking model uncertainty into account can lead to strongly biased conclusions. Consequently we tackle this problem by applying simple model-averaging techniques to commonly used panel cointegration models.We expect to find that taking into account the uncertainty associated with selecting a single model with model-averaging techniques leads to a more accurate representation of the link between energy consumption and other macroeconomic variables and a significantly increased out-of-sample forecast performance. Algeria, Argentina, Australia, Austria, Bangladesh, Belgium, Brazil, Canada, Chile, China, Colombia, Denmark, Ecuador, Egypt, Finland, France, Germany, Greece, Hong Kong, Iceland, India, Indonesia, Iran, Ireland, Italy, Japan, Korea, Malaysia, Mexico, Netherlands, New Zealand, Norway, Pakistan, Peru, Philippines, Portugal, Singapore, South Africa, Spain, Sweden, Switzerland, Thailand, United Kingdom, United States & Venezuela (45 countries), Energy and environmental policy, Modeling: new developments Report Iceland RePEc (Research Papers in Economics) Canada Norway New Zealand Argentina
institution Open Polar
collection RePEc (Research Papers in Economics)
op_collection_id ftrepec
language unknown
description The causality between energy consumption and real income in developed countries has been a very vital research topic in recent years. Raising concerns about climate change and global warming increase the pressure on policy makers to take action against energy depletion. Unfortunately these efforts coincide with one of the largest global economic recessions in the past century. Establishing the link between energy consumption and other key macroeconomic variables like real GDP, labour force, capital stock and technology thus currently appears as a particularly relevant research effort.In this area of the literature, uncertainty about the choice of a statistical model is rarely considered. Whenever one model is opted over reasonable alternative models to represent knowledge about a specific process, model uncertainty occurs. We argue that inference on the basis of a single model without taking model uncertainty into account can lead to strongly biased conclusions. Consequently we tackle this problem by applying simple model-averaging techniques to commonly used panel cointegration models.We expect to find that taking into account the uncertainty associated with selecting a single model with model-averaging techniques leads to a more accurate representation of the link between energy consumption and other macroeconomic variables and a significantly increased out-of-sample forecast performance. Algeria, Argentina, Australia, Austria, Bangladesh, Belgium, Brazil, Canada, Chile, China, Colombia, Denmark, Ecuador, Egypt, Finland, France, Germany, Greece, Hong Kong, Iceland, India, Indonesia, Iran, Ireland, Italy, Japan, Korea, Malaysia, Mexico, Netherlands, New Zealand, Norway, Pakistan, Peru, Philippines, Portugal, Singapore, South Africa, Spain, Sweden, Switzerland, Thailand, United Kingdom, United States & Venezuela (45 countries), Energy and environmental policy, Modeling: new developments
format Report
author Stefan Humer
Csereklyei, Z.
spellingShingle Stefan Humer
Csereklyei, Z.
Modelling long-run energy consumption under model uncertainty
author_facet Stefan Humer
Csereklyei, Z.
author_sort Stefan Humer
title Modelling long-run energy consumption under model uncertainty
title_short Modelling long-run energy consumption under model uncertainty
title_full Modelling long-run energy consumption under model uncertainty
title_fullStr Modelling long-run energy consumption under model uncertainty
title_full_unstemmed Modelling long-run energy consumption under model uncertainty
title_sort modelling long-run energy consumption under model uncertainty
url http://ecomod.net/system/files/CsereklyeiHumer_ModellingPrimaryEnergy_underUncertainty_0.pdf
geographic Canada
Norway
New Zealand
Argentina
geographic_facet Canada
Norway
New Zealand
Argentina
genre Iceland
genre_facet Iceland
op_relation http://ecomod.net/system/files/CsereklyeiHumer_ModellingPrimaryEnergy_underUncertainty_0.pdf
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