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Can pecuniary and environmental incentives via SMS messaging make households adjust their electricity demand to a fluctuating production?

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  • Møller, Niels Framroze
  • Andersen, Laura Mørch
  • Hansen, Lars Gårn
  • Jensen, Carsten Lynge

Abstract

The increasing deployment of renewables introduces substantial variability into the production of electricity, requiring demand to be more movable across time. We analyze data from a large Danish field experiment (2015–2016) to investigate whether households can be prompted, via SMS messages, to move electricity consumption, and if so, whether these are motivated by pecuniary or environmental motives. The analysis has two steps: As a novel approach, we first use automatic model selection, which allows a different time-series regression for each of the 1488 households studied. From this, we obtain a cross-section of estimated SMS effects, which we then regress on the motive type. Since households can opt out there is a risk of self-selection. We therefore control for the size, income and average consumption of the household, and the age, educational- and labor market status of the SMS recipient. The results suggest that SMS messages can to some extent motivate households to move consumption. Although a stronger financial motive seems more effective, mixing financial and environmental motives seems the most effective. Finally, women and elderly people are more inclined to move consumption.

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  • Møller, Niels Framroze & Andersen, Laura Mørch & Hansen, Lars Gårn & Jensen, Carsten Lynge, 2019. "Can pecuniary and environmental incentives via SMS messaging make households adjust their electricity demand to a fluctuating production?," Energy Economics, Elsevier, vol. 80(C), pages 1050-1058.
  • Handle: RePEc:eee:eneeco:v:80:y:2019:i:c:p:1050-1058
    DOI: 10.1016/j.eneco.2019.01.023
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    More about this item

    Keywords

    Household-level electricity demand; General-to-Specific automatic model selection; SMS messaging; Field experimental data;
    All these keywords.

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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