Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/235125 
Year of Publication: 
2021
Series/Report no.: 
Working Paper Series No. 13
Publisher: 
Bocconi University, Centre for Research on Geography, Resources, Environment, Energy and Networks (GREEN), Milan
Abstract: 
Projections of energy intensity are important for the assessment of future energy demand, future emission pathways, and the costs of climate policies. We estimate and simulate energy intensity based on a conditional convergence approach, and show how based on the results the long-run minimum of energy intensity attainable can be estimated. We consider education, urbanization, and institutional factors and ftnd them to positively impact energy intensity improvements. We link the estimated econometric models to an iterative projection model, resulting in a ftnite long-term lower limit of energy intensity of GDP to be around 0:35MJ/$ at the global level in most SSPs. Yet, by 2100, we estimated that energy intensity below one is hard to achieve based on historical patterns. By 2100, the projected energy intensities are in the range of 1MJ/$ at the global level. These results show that scenarios such as the ones used in the SR15 can be rationalized based on empirically founded projections, and that in particular the very low energy demand scenarios can be considered feasible on empirical grounds. The speed at which such ow values are achievable is however the big question and achieving them will require substantially going beyond historical technical change patterns.
Subjects: 
Energy Intensity
Energy Demand
Convergence
JEL: 
O44
P18
Q47
C23
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.