Disaggregating electricity generation technologies in CGE models: A revised technology bundle approach with an application to the U.S. Clean Power Plan

Cai, Yiyong; Arora, Vipin

doi:10.1016/j.apenergy.2015.05.041

“…As seen in the figure, imposing a carbon price will result in a shift toward higher share costs of labor and capital, and less oil, coal and gas, mimicking the transition toward cleaner technologies. The CTEM model 6 (Cai and Arora, 2015; is otherwise identical to CTAP but uses an electricity technology bundle ( Figure 7). The CTEM model features disaggregated modeling of the electricity sector into a bundle of 13 generation technologies (Coal, Oil, Gas, Nuclear, Hydro, Wind, Solar, Biomass, Waste, Geothermal, Coal plus CCS, Oil plus CCS, Gas plus CCS).…”

Section: Disaggregating Electricity Technologies: From Ctap-1 To Ctem-1mentioning

confidence: 99%

Sensitivity of modeling results to technological and regional details: The case of Italy's carbon mitigation policy

Standardi

¹

,

Cai

²

,

Yeh

³

2017

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Model differences in technological and geographical scales are common, but their contributions to uncertainties have not been systematically quantified in the climate policy literature. This paper carries out a systematic assessment on the sensitivity of Computable General Equilibrium models to technological and geographical scales in evaluating the economic impacts of carbon mitigation policies. Taking Italy as an example, we find that the estimation for carbon price and the economic cost of a de-carbonization pathway by means of a model with technological and regional details can be lower than a model without such details by up to 40%. Additionally, the effect of representing regional details appears to be far more important than the effect of representing the details of electricity technology in both the estimated carbon prices and the estimated economic impacts. Our results for Italy highlight the importance of modeling uncertainties of these two key assumptions, which should be appropriately acknowledged when applying CGE models for policy impact assessment. Our conclusions can be generalized to different countries and policy scenarios not in terms of absolute numbers but in terms of economic explanations. In particular, intra-national trade and the sub-national sectoral/technological specialization are important variables for understanding the economic dynamics behind these outcomes.

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“…The CRESH function is a more general form of the CES function, allowing for different degrees of price elasticities among the fuel types (Cai and Arora, 2015). For this modeling exercise, the price elasticities of substitution for energy demand in GTEM-C are calibrated to reflect the empirical findings of Urga and Walters (2003), RAND (2005) and Stern (2012), as well as the EIA's National Energy Modeling System (NEMS) modeling assumptions (U.S. EIA, 2013) as shown in Table 2.…”

Section: The General Equilibrium Model Gtem-cmentioning

confidence: 99%

North American natural gas and energy markets in transition: insights from global models

Yeh

¹

,

Cai

²

,

Huppman

³

et al. 2016

Energy Economics

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“…Our starting point is the CTAP model developed by Cai and Arora (2015), which is a variant of the neo-classical CGE model Global Trade Analysis Project (GTAP) (Hertel, 1997). GTAP is calibrated to the GTAP 8 database (Narayanan et al, 2012) (Miller and Blair, 2009).…”

Section: General Characteristics Of Cge Modelsmentioning

confidence: 99%

“…Competing electricity technologies are combined through the CRESH (Constant Ratios of Elasticities of Substitution, Homothetic) function (see Hanoch, 1971;Pant, 2007;Cai and Arora, 2015), which allows for differing levels of substitution between any two technologies.…”

Section: Disaggregating Electricity Technologies: From Ctap-1 To Ctem-1mentioning

confidence: 99%

Sensitivity of Modeling Results to Technological and Regional Details: The Case of Italy's Carbon Mitigation Policy

Standardi

¹

,

Cai

²

,

Yeh

³

2017

SSRN Journal

Self Cite

0

View full text Add to dashboard Cite

Model differences in technological and geographical scales are common, but their contributions to uncertainties have not been systematically quantified in the climate policy literature. This paper carries out a systematic assessment on the sensitivity of Computable General Equilibrium models to technological and geographical scales in evaluating the economic impacts of carbon mitigation policies. Taking Italy as an example, we find that the estimation for carbon price and the economic cost of a de-carbonization pathway by means of a model with technological and regional details can be lower than a model without such details by up to 40%. Additionally, the effect of representing regional details appears to be far more important than the effect of representing the details of electricity technology in both the estimated carbon prices and the estimated economic impacts. Our results for Italy highlight the importance of modeling uncertainties of these two key assumptions, which should be appropriately acknowledged when applying CGE models for policy impact assessment. Our conclusions can be generalized to different countries and policy scenarios not in terms of absolute numbers but in terms of economic explanations. In particular, intra-national trade and the sub-national sectoral/technological specialization are important variables for understanding the economic dynamics behind these outcomes.

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Disaggregating electricity generation technologies in CGE models: A revised technology bundle approach with an application to the U.S. Clean Power Plan

Cited by 51 publications

References 22 publications

Sensitivity of modeling results to technological and regional details: The case of Italy's carbon mitigation policy

Sensitivity of modeling results to technological and regional details: The case of Italy's carbon mitigation policy

North American natural gas and energy markets in transition: insights from global models

Sensitivity of Modeling Results to Technological and Regional Details: The Case of Italy's Carbon Mitigation Policy

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