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Sectoral Electricity Demand and Direct Rebound Effect in New Zealand

Author

Listed:
  • Nepal, Rabindra

    (Faculty of Business, School of Accounting, Economics and Finance, Centre for Contemporary Australasian Business and Economics Studies (CCABES), University of Wollongong, Australia)

  • al Irsyad, Muhammad Indra

    (R&D Centre of Electricity, Renewables, and Energy Conservation Technology, Ministry of Energy and Mineral Resources, Indonesia)

  • Jamasb, Tooraj

    (Department of Economics, Copenhagen Business School)

Abstract
This paper is one of the limited studies to investigate rebound effects in sectoral electricity consumption and the specific case of New Zealand. New Zealand, like other OECD economies, has aimed for energy efficiency improvements and reduced electricity consumption from 9.2 MWh per capita in 2010 to 8.6 MWh per capita in 2015. However, following a significant decline since 2010, electricity consumption in the main New Zealand sectors is increasing. Energy conservation could play an important role in meeting the growing demand for electricity but rebound effect can affect the effectiveness of conservation policies. We decompose the sectoral electricity prices to capture the asymmetric demand response to electricity price changes and estimate electricity demand elasticity during 1980 and 2015 to estimate the sectoral rebound effects. We find partial rebound effects of 54% and 23% in the industrial and commercial sector respectively while we find no partial rebound effect at aggregate sectoral level. The rebound effect is insignificant in the residential sector. These findings lead to policy recommendations for more sector specific energy conservation measures and policies.

Suggested Citation

  • Nepal, Rabindra & al Irsyad, Muhammad Indra & Jamasb, Tooraj, 2020. "Sectoral Electricity Demand and Direct Rebound Effect in New Zealand," Working Papers 9-2020, Copenhagen Business School, Department of Economics.
    • Handle: RePEc:hhs:cbsnow:2020_009
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    as
    1. Wang, Zhaohua & Lu, Milin & Wang, Jian-Cai, 2014. "Direct rebound effect on urban residential electricity use: An empirical study in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 124-132.
    2. Font Vivanco, David & Kemp, René & van der Voet, Ester, 2016. "How to deal with the rebound effect? A policy-oriented approach," Energy Policy, Elsevier, vol. 94(C), pages 114-125.
    3. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    4. O'Sullivan, Kimberley C. & Stanley, James & Fougere, Geoffrey & Howden-Chapman, Philippa, 2016. "Heating practices and self-disconnection among electricity prepayment meter consumers in New Zealand: A follow-up survey," Utilities Policy, Elsevier, vol. 41(C), pages 139-147.
    5. Karen Turner, 2013. ""Rebound" Effects from Increased Energy Efficiency: A Time to Pause and Reflect," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    6. Sorrell, Steve & Dimitropoulos, John, 2008. "The rebound effect: Microeconomic definitions, limitations and extensions," Ecological Economics, Elsevier, vol. 65(3), pages 636-649, April.
    7. Bentzen, Jan, 2004. "Estimating the rebound effect in US manufacturing energy consumption," Energy Economics, Elsevier, vol. 26(1), pages 123-134, January.
    8. Lim, Kyoung-Min & Lim, Seul-Ye & Yoo, Seung-Hoon, 2014. "Short- and long-run elasticities of electricity demand in the Korean service sector," Energy Policy, Elsevier, vol. 67(C), pages 517-521.
    9. Hendrik Schmitz and Reinhard Madlener, 2020. "Direct and Indirect Energy Rebound Effects in German Households: A Linearized Almost Ideal Demand System Approach," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5), pages 89-118.
    10. Kenneth Gillingham & David Rapson & Gernot Wagner, 2016. "The Rebound Effect and Energy Efficiency Policy," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 10(1), pages 68-88.
    11. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    12. Dermot Gately & Hiliard G. Huntington, 2002. "The Asymmetric Effects of Changes in Price and Income on Energy and Oil Demand," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 19-55.
    13. Massimo, Filippini, 2011. "Short- and long-run time-of-use price elasticities in Swiss residential electricity demand," Energy Policy, Elsevier, vol. 39(10), pages 5811-5817, October.
    14. Hunt, Lester C. & Ryan, David L., 2015. "Economic modelling of energy services: Rectifying misspecified energy demand functions," Energy Economics, Elsevier, vol. 50(C), pages 273-285.
    15. A. Greening, Lorna & Greene, David L. & Difiglio, Carmen, 2000. "Energy efficiency and consumption -- the rebound effect -- a survey," Energy Policy, Elsevier, vol. 28(6-7), pages 389-401, June.
    16. Narayan, Paresh Kumar & Prasad, Arti, 2008. "Electricity consumption-real GDP causality nexus: Evidence from a bootstrapped causality test for 30 OECD countries," Energy Policy, Elsevier, vol. 36(2), pages 910-918, February.
    17. Narayan, Paresh Kumar & Smyth, Russell, 2005. "The residential demand for electricity in Australia: an application of the bounds testing approach to cointegration," Energy Policy, Elsevier, vol. 33(4), pages 467-474, March.
    18. Zhang, Yue-Jun & Peng, Hua-Rong, 2017. "Exploring the direct rebound effect of residential electricity consumption: An empirical study in China," Applied Energy, Elsevier, vol. 196(C), pages 132-141.
    19. Saunoris, James W. & Sheridan, Brandon J., 2013. "The dynamics of sectoral electricity demand for a panel of US states: New evidence on the consumption–growth nexus," Energy Policy, Elsevier, vol. 61(C), pages 327-336.
    20. Dergiades, Theologos & Tsoulfidis, Lefteris, 2008. "Estimating residential demand for electricity in the United States, 1965-2006," Energy Economics, Elsevier, vol. 30(5), pages 2722-2730, September.
    21. Saunders Harry D, 2005. "A Calculator for Energy Consumption Changes Arising from New Technologies," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 5(1), pages 1-35, September.
    22. Okajima, Shigeharu & Okajima, Hiroko, 2013. "Estimation of Japanese price elasticities of residential electricity demand, 1990–2007," Energy Economics, Elsevier, vol. 40(C), pages 433-440.
    23. Halicioglu, Ferda, 2007. "Residential electricity demand dynamics in Turkey," Energy Economics, Elsevier, vol. 29(2), pages 199-210, March.
    24. J. Daniel Khazzoom, 1980. "Economic Implications of Mandated Efficiency in Standards for Household Appliances," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 21-40.
    25. Orea, Luis & Llorca, Manuel & Filippini, Massimo, 2015. "A new approach to measuring the rebound effect associated to energy efficiency improvements: An application to the US residential energy demand," Energy Economics, Elsevier, vol. 49(C), pages 599-609.
    26. Saunders, Harry D., 2008. "Fuel conserving (and using) production functions," Energy Economics, Elsevier, vol. 30(5), pages 2184-2235, September.
    27. Dermot Gately, 1993. "The Imperfect Price-Reversibility of World Oil Demand," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 163-182.
    28. Koli Fatai & Les Oxley & Frank G. Scrimgeour, 2003. "Modeling and Forecasting the Demand for Electricity in New Zealand: A Comparison of Alternative Approaches," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 75-102.
    29. Sorrell, Steve & Dimitropoulos, John & Sommerville, Matt, 2009. "Empirical estimates of the direct rebound effect: A review," Energy Policy, Elsevier, vol. 37(4), pages 1356-1371, April.
    30. Steinbuks,Jevgenijs, 2017. "Assessing the accuracy of electricity demand forecasts in developing countries," Policy Research Working Paper Series 7974, The World Bank.
    31. Harty D. Saunders, 1992. "The Khazzoom-Brookes Postulate and Neoclassical Growth," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 131-148.
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    More about this item

    Keywords

    Electricity; Demand; Rebound; Heating; Time series analysis;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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