Quotation Csereklyei, Zsuzsanna, Humer, Stefan. Forthcoming. Projecting Long-Term Primary Energy Consumption with Error Correction Models. WU Working Papers in Economics.


RIS


BibTeX

Abstract

In this paper we use the long-term empirical relationship among primary energy consumption, real income, physical capital, population and technology, obtained by averaged panel error correction models, to project the worldwide long-term primary energy consumption up to 2100. In forecasting long-term primary energy consumption, we work with four different Shared Socioeconomic Pathway Scenarios (SSPs) developed for the Intergovernmental Panel on Climate Change (IPCC) framework, assuming different challenges to adaptation and mitigation. We find that in all scenarios, China, the United States and India will be the largest energy consumers, while highly growing countries will also significantly contribute to energy use. We observe for most scenarios a sharp increase in global energy consumption, followed by a levelling-out and a decrease towards the second half of the century. The reasons behind this pattern are not only slower population growth, but also infrastructure saturation and increased total factor productivity. This means, as countries move towards more knowledge based societies, and higher energy efficiency, their primary energy usage is likely to decrease as a result. Global primary energy consumption is expected however to increase significantly in the coming decades, thus increasing the pressure on policy makers to cope with the questions of energy security and greenhouse gas mitigation at the same time.

Tags

Press 'enter' for creating the tag

Publication's profile

Affiliation WU
Type of publication Working/discussion paper, preprint
Language English
Title Projecting Long-Term Primary Energy Consumption with Error Correction Models
Title of whole publication WU Working Papers in Economics
Year 2013

Associations

People
Humer, Stefan (Details)
External
Csereklyei, Zsuzsanna
Organization
Institute for Macroeconomics IN (Details)
Research areas (Ă–STAT Classification 'Statistik Austria')
5323 Econometrics (Details)
Google Scholar: Search