Econometric modeling of CO2 emissions abatement: Comparing alternative approaches
- 1. GOVCOPP and DEGEIT, University of Aveiro, Campus Universitário de Santiago, Aveiro, 3810-193 (Portugal)
Description
As investments and policies that promote renewable energy (RE) projects in electricity systems are most often grounded on the goal of reducing emissions of greenhouse gases, and actual investment and policy decisions are shaped by the estimates of the accrued emissions savings, it is crucial that these estimates are as accurate as possible. In this paper we compare different econometric models that estimate the amount of carbon abated due to RE in terms of their results and their inherent methodological benefits and drawbacks. Specifically, we use the British, French and Spanish grids as case studies for the application of a selection of econometric models and compare the resulting CO2 abatement estimates. We find that, across the three markets, estimates can vary substantially across the different models – this can lead to an over or underestimation of the emissions abated by RE. Overall, our results highlight the need for choosing econometric specifications that lead to results that are congruent with the operational framework of the examined power systems.
Additional details
Identifiers
- DOI
- 10.1016/j.rser.2019.02.001;
- PII
- S1364032119300851;
Publishing Information
- Journal Title
- Renewable and Sustainable Energy Reviews
- Journal Volume
- 105
- Journal Page Range
- p. 310-322
- ISSN
- 1364-0321
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 55020379
- Subject category
- S29: ENERGY PLANNING, POLICY AND ECONOMY;
- Descriptors DEI
- CARBON DIOXIDE; COMPUTERIZED SIMULATION; ECONOMETRICS; ELECTRICITY; EMISSION; POWER SYSTEMS; RENEWABLE ENERGY SOURCES; SPECIFICATIONS
- Descriptors DEC
- CARBON COMPOUNDS; CARBON OXIDES; CHALCOGENIDES; ECONOMICS; ENERGY SOURCES; ENERGY SYSTEMS; OXIDES; OXYGEN COMPOUNDS; SIMULATION
Optional Information
- Copyright
- Copyright (c) 2019 Elsevier Ltd. All rights reserved.