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Firm-Level Estimates of Fuel Substitution: An Application to Carbon Pricing

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  • Hyland, Marie
  • Haller, Stefanie

Abstract

We estimate partial and total own and cross price elasticities between electricity, gas and oil, using firm-level data. We find that, based on the partial elasticity measure, electricity is the least-responsive fuel to changes in its own price and in the price of other fuels. The total elasticity measure, which adjusts the partial elasticity for changes in aggregate energy demand induced by individual fuel price changes, reveals that the demand for electricity is much more price responsive than the partial elasticity suggests. Our results illustrate the importance of accounting for the feedback effect between interfactor and interfuel elasticities when considering the effectiveness of environmental taxation. We use the estimated elasticities to simulate the impact of a €15/tCO2 carbon tax on average energy-related CO2 emissions. The carbon tax results in a small reduction in CO2 emissions from oil and gas use, but this reduction is partially offset by an increase in emissions due to increased electricity consumption by some firms.
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  • Hyland, Marie & Haller, Stefanie, 2015. "Firm-Level Estimates of Fuel Substitution: An Application to Carbon Pricing," Papers WP513, Economic and Social Research Institute (ESRI).
    • Handle: RePEc:esr:wpaper:wp513
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    1. T.D. Stanley & Hristos Doucouliagos, 2010. "Picture This: A Simple Graph That Reveals Much Ado About Research," Journal of Economic Surveys, Wiley Blackwell, vol. 24(1), pages 170-191, February.
    2. World Bank & Ecofys & Vivid Economics & Thomas Michael Kerr, "undated". "State and Trends of Carbon Pricing 2016," World Bank Publications - Reports 25160, The World Bank Group.
    3. Alan D. Woodland, 1993. "A Micro-Econometric Analysis of the Industrial Demand for Energy in NSW," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 57-90.
    4. Fuss, Melvyn A., 1977. "The demand for energy in Canadian manufacturing : An example of the estimation of production structures with many inputs," Journal of Econometrics, Elsevier, vol. 5(1), pages 89-116, January.
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    Cited by:

    1. Fetzer, Thiemo & Palmou, Christina & Schneebacher, Jakob, 2024. "How do firms cope with economic shocks in real time?," CAGE Online Working Paper Series 722, Competitive Advantage in the Global Economy (CAGE).
    2. Zachlod-Jelec, Magdalena & Boratynski, Jakub, 2016. "How large and uncertain are costs of 2030 GHG emissions reduction target for the European countries? Sensitivity analysis in a global CGE model," MF Working Papers 26, Ministry of Finance in Poland.
    3. Benoît Chèze, Julien Chevallier, Nicolas Berghmans, and Emilie Alberola, 2020. "On the CO2 Emissions Determinants During the EU ETS Phases I and II: A Plant-level Analysis Merging the EUTL and Platts Power Data," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 153-184.
    4. Thiemo Fetzer & Christina Palmou & Jakob Schneebacher, 2024. "How Do Firms Cope with Economic Shocks in Real Time?," ECONtribute Discussion Papers Series 337, University of Bonn and University of Cologne, Germany.
    5. Thiemo Fetzer & Christina Palmou & Jakob Schneebacher, 2024. "How Do Firms Cope with Economic Shocks in Real Time?," CESifo Working Paper Series 11367, CESifo.
    6. Magdalena Zachlod-Jelec & Jakub Boratyński, 2016. "How large and uncertain are costs of 2030 emission reduction target for the European countries? Sensitivity analysis in a global CGE model," EcoMod2016 9449, EcoMod.
    7. Cao, Jing & Ho, Mun S. & Ma, Rong, 2020. "Analyzing carbon pricing policies using a general equilibrium model with production parameters estimated using firm data," Energy Economics, Elsevier, vol. 92(C).
    8. Fetzer, Thiemo & Palmou, Christina & Schneebacher, Jakob, 2024. "How do firms cope with economic shocks in real time?," The Warwick Economics Research Paper Series (TWERPS) 1517, University of Warwick, Department of Economics.

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