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How sensitive to time period sampling is the asymmetric price response specification in energy demand modelling?

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  • Adofo, Yaw Osei
  • Evans, Joanne
  • Hunt, Lester Charles

Abstract

The purpose of this paper is to investigate the criticism that energy demand estimates based on a specific price decomposition are sensitive to the chosen time period used for the estimation. To analyse this in a systematic way, different time series sample periods are constructed from annual data for 17 OECD countries covering the overall period 1960 to 2008. The specific price decomposition under consideration, often used to estimate asymmetric price response models of energy demand, separates the impact of prices above the previous maximum, of a price recovery below the previous maximum and of a price cut. Therefore, the analysis does not just involve using different time periods; instead, for each time period investigated, a new dataset is constructed and for each dataset, the price variable is decomposed in this way. An energy demand relationship allowing for asymmetric price responses is therefore estimated for each different sample period and the results suggest that recalculation of the decomposed price variables for each different period does affect the stability of the estimated energy demand responses. In contrast, a similarly estimated energy demand relationship with symmetric price responses for each different sample period is found to have less instability.

Suggested Citation

  • Adofo, Yaw Osei & Evans, Joanne & Hunt, Lester Charles, 2013. "How sensitive to time period sampling is the asymmetric price response specification in energy demand modelling?," Energy Economics, Elsevier, vol. 40(C), pages 90-109.
  • Handle: RePEc:eee:eneeco:v:40:y:2013:i:c:p:90-109
    DOI: 10.1016/j.eneco.2013.05.015
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    References listed on IDEAS

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    Cited by:

    1. Adeyemi, Olutomi I. & Hunt, Lester C., 2014. "Accounting for asymmetric price responses and underlying energy demand trends in OECD industrial energy demand," Energy Economics, Elsevier, vol. 45(C), pages 435-444.
    2. Lin, Boqiang & Li, Jianglong, 2014. "The rebound effect for heavy industry: Empirical evidence from China," Energy Policy, Elsevier, vol. 74(C), pages 589-599.
    3. 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.
    4. Yang, Lisha & Li, Jianglong, 2017. "Rebound effect in China: Evidence from the power generation sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 53-62.
    5. Salisu, Afees A. & Ayinde, Taofeek O., 2016. "Modeling energy demand: Some emerging issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1470-1480.
    6. repec:eee:eneeco:v:69:y:2018:i:c:p:379-394 is not listed on IDEAS

    More about this item

    Keywords

    Energy demand modelling; Asymmetric price responses; Stability of estimates;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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