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The influence of electricity prices on saving electricity in production: Automated multivariate time-series analyses for 99 Danish trades and industries

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  • Bjerregaard, Casper
  • Møller, Niels Framroze

Abstract

We examine whether industries save electricity per unit of output when electricity prices rise. This is of interest for policy makers considering changing tariffs on industrial electricity consumption. Previous studies use national or sector-level data offering limited information about how individual industries are affected, which is needed for better targeting policies. Using Danish time-series data (1966–2015), we therefore analyze industries at a detailed level. In particular, for each of 99 industries, we use Autometrics to find a well-specified partial VAR model for the intensities of electricity and other energy (an aggregate of oil, coal, gas, district heating and biomass). The model allows for cointegration and is conditional on energy prices and heating degree days. We find that, 15 industries (26% of total industrial electricity use in 2015), save electricity (per unit of output) when this becomes more expensive. For another 18 industries (10%), both electricity and other energy are saved when electricity prices increase. Finally, there are only 4 industries (3%), for which the savings on electricity are compensated by an increase in other energy.

Suggested Citation

  • Bjerregaard, Casper & Møller, Niels Framroze, 2022. "The influence of electricity prices on saving electricity in production: Automated multivariate time-series analyses for 99 Danish trades and industries," Energy Economics, Elsevier, vol. 107(C).
    • Handle: RePEc:eee:eneeco:v:107:y:2022:i:c:s0140988321003327
    DOI: 10.1016/j.eneco.2021.105444
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    1. Suganthi, L. & Samuel, Anand A., 2012. "Energy models for demand forecasting—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1223-1240.
    2. Bernstein, Ronald & Madlener, Reinhard, 2015. "Short- and long-run electricity demand elasticities at the subsectoral level: A cointegration analysis for German manufacturing industries," Energy Economics, Elsevier, vol. 48(C), pages 178-187.
    3. Zachariadis, Theodoros & Pashourtidou, Nicoletta, 2007. "An empirical analysis of electricity consumption in Cyprus," Energy Economics, Elsevier, vol. 29(2), pages 183-198, March.
    4. Carlos Santos & David Hendry & Soren Johansen, 2008. "Automatic selection of indicators in a fully saturated regression," Computational Statistics, Springer, vol. 23(2), pages 317-335, April.
    5. Nasr, G. E. & Badr, E. A. & Dibeh, G., 2000. "Econometric modeling of electricity consumption in post-war Lebanon," Energy Economics, Elsevier, vol. 22(6), pages 627-640, December.
    6. Thomas Bue Bjorner & Henrik Holm Jensen, 2002. "Interfuel Substitution within Industrial Companies: An Analysis Based on Panel Data at Company Level," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 27-50.
    7. Erdogdu, Erkan, 2007. "Electricity demand analysis using cointegration and ARIMA modelling: A case study of Turkey," Energy Policy, Elsevier, vol. 35(2), pages 1129-1146, February.
    8. Juselius, Katarina, 2006. "The Cointegrated VAR Model: Methodology and Applications," OUP Catalogue, Oxford University Press, number 9780199285679, Decembrie.
    9. Yuan, Jia-Hai & Kang, Jian-Gang & Zhao, Chang-Hong & Hu, Zhao-Guang, 2008. "Energy consumption and economic growth: Evidence from China at both aggregated and disaggregated levels," Energy Economics, Elsevier, vol. 30(6), pages 3077-3094, November.
    10. Lee, Chien-Chiang & Chang, Chun-Ping, 2005. "Structural breaks, energy consumption, and economic growth revisited: Evidence from Taiwan," Energy Economics, Elsevier, vol. 27(6), pages 857-872, November.
    11. Galindo, Luis Miguel, 2005. "Short- and long-run demand for energy in Mexico: a cointegration approach," Energy Policy, Elsevier, vol. 33(9), pages 1179-1185, June.
    12. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry & Felix Pretis, 2015. "Detecting Location Shifts during Model Selection by Step-Indicator Saturation," Econometrics, MDPI, vol. 3(2), pages 1-25, April.
    13. Johansen, Soren, 1992. "Cointegration in partial systems and the efficiency of single-equation analysis," Journal of Econometrics, Elsevier, vol. 52(3), pages 389-402, June.
    14. Polemis, Michael. L., 2007. "Modeling industrial energy demand in Greece using cointegration techniques," Energy Policy, Elsevier, vol. 35(8), pages 4039-4050, August.
    15. Bentzen, Jan & Engsted, Tom, 1993. "Short- and long-run elasticities in energy demand : A cointegration approach," Energy Economics, Elsevier, vol. 15(1), pages 9-16, January.
    16. Sinton, Jonathan E. & Levine, Mark D., 1994. "Changing energy intensity in Chinese industry : The relatively importance of structural shift and intensity change," Energy Policy, Elsevier, vol. 22(3), pages 239-255, March.
    17. Fouquet, Roger & Pearson, Peter & Hawdon, David & Robinson, Colin & Stevens, Paul, 1997. "The future of UK final user energy demand," Energy Policy, Elsevier, vol. 25(2), pages 231-240, February.
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    1. Satish Suresh Tanavade & Ganesh Nagraj Patil & C. V. Sudhir & A. M. Saravanan, 2023. "Strategic Energy Management and Carbon Footprint Reduction in University Campuses: A Comprehensive Review," International Journal of Energy Economics and Policy, Econjournals, vol. 13(6), pages 15-27, November.

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    More about this item

    Keywords

    Energy savings; Industrial energy consumption; Cointegrated VAR; Autometrics; Automatic modeling;
    All these keywords.

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • D2 - Microeconomics - - Production and Organizations
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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