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Exploring the use of dynamic linear panel data models for evaluating energy/economy/environment models — an application for the transportation sector

Authors: Robert C. Pietzcker; Page Kyle; Andreas Schäfer; Andreas Schäfer;

Exploring the use of dynamic linear panel data models for evaluating energy/economy/environment models — an application for the transportation sector

Abstract

This paper uses the RoSE transportation sector scenarios of the GCAM and REMIND energy-economy-models for the U.S. region to derive and compare these models’ intrinsic elasticities with those resulting from historical trends, estimates from the literature, and across each other. To estimate the model-intrinsic elasticities, we explore the use of dynamic linear panel data models. On the basis of 26 scenarios (panels) between 2010 and 2050, our analysis suggests that nearly all model-intrinsic elasticities with respect to final energy use are roughly comparable to each other, to those observed historically, and to those from other studies. The key difference is these models’ comparatively low intrinsic income elasticity of final energy use. This and other minor differences are interpreted through key assumptions underlying both energy-economy-models.

Countries
Germany, United Kingdom
Keywords

Atmospheric Science, Global and Planetary Change, Unit Root, 330, 550, Final Energy, Panel Data Model, Price Elasticity, Income Elasticity

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    12
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Top 10%
Top 10%
Average