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Sectoral Electricity Demand and Direct Rebound Effects in New Zealand

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  • Rabindra Nepal, Muhammad Indra al Irsyad, and Tooraj Jamasb

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 effects 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 sectors respectively while we find no rebound effect at the aggregate level. The rebound effect is insignificant in the residential sector. These findings lead to policy recommendations for sector specific energy conservation measures and policies.

Suggested Citation

  • Rabindra Nepal, Muhammad Indra al Irsyad, and Tooraj Jamasb, 2021. "Sectoral Electricity Demand and Direct Rebound Effects in New Zealand," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    • Handle: RePEc:aen:journl:ej42-4-nepal
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    Cited by:

    1. Uddin, Gazi Salah & Hasan, Md. Bokhtiar & Phoumin, Han & Taghizadeh-Hesary, Farhad & Ahmed, Ali & Troster, Victor, 2023. "Exploring the critical demand drivers of electricity consumption in Thailand," Energy Economics, Elsevier, vol. 125(C).
    2. Pan, Yinghao & Zhang, Chao-Chao & Lee, Chien-Chiang & Lv, Suxiang, 2024. "Environmental performance evaluation of electric enterprises during a power crisis: Evidence from DEA methods and AI prediction algorithms," Energy Economics, Elsevier, vol. 130(C).

    More about this item

    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
    • 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
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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