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Can Nighttime Light Data Be Used to Estimate Electric Power Consumption? New Evidence from Causal-Effect Inference

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  • Yongguang Zhu

    (School of Economics and Management, China University of Geosciences, Wuhan 430074, China
    Research Center of Resource and Environmental Economics, China University of Geosciences, Wuhan 430074, China
    Center for Energy and Environmental Policy, University of Delaware, Newark, DE 19716, USA)

  • Deyi Xu

    (School of Economics and Management, China University of Geosciences, Wuhan 430074, China
    Research Center of Resource and Environmental Economics, China University of Geosciences, Wuhan 430074, China)

  • Saleem H. Ali

    (Center for Energy and Environmental Policy, University of Delaware, Newark, DE 19716, USA
    Sustainable Minerals Institute, University of Queensland, Brisbane, St. Lucia 4072, Australia)

  • Ruiyang Ma

    (School of Economics and Management, China University of Geosciences, Wuhan 430074, China)

  • Jinhua Cheng

    (School of Economics and Management, China University of Geosciences, Wuhan 430074, China
    Research Center of Resource and Environmental Economics, China University of Geosciences, Wuhan 430074, China)

Abstract

Nighttime light data are often used to estimate some socioeconomic indicators, such as energy consumption, GDP, population, etc. However, whether there is a causal relationship between them needs further study. In this paper, we propose a causal-effect inference method to test whether nighttime light data are suitable for estimating socioeconomic indicators. Data on electric power consumption and nighttime light intensity in 77 countries were used for the empirical research. The main conclusions are as follows: First, nighttime light data are more appropriate for estimating electric power consumption in developing countries, such as China, India, and others. Second, more latent factors need to be added into the model when estimating the power consumption of developed countries using nighttime light data. Third, the light spillover effect is relatively strong, which is not suitable for estimating socioeconomic indicators in the contiguous regions between developed countries and developing countries, such as Spain, Turkey, and others. Finally, we suggest that more attention should be paid in the future to the intrinsic logical relationship between nighttime light data and socioeconomic indicators.

Suggested Citation

  • Yongguang Zhu & Deyi Xu & Saleem H. Ali & Ruiyang Ma & Jinhua Cheng, 2019. "Can Nighttime Light Data Be Used to Estimate Electric Power Consumption? New Evidence from Causal-Effect Inference," Energies, MDPI, vol. 12(16), pages 1-14, August.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:16:p:3154-:d:258208
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    2. Naeher,Dominik & Narayanan,Raghavan & Ziulu,Virginia, 2021. "Impacts of Energy Efficiency Projects in Developing Countries : Evidence from a SpatialDifference-in-Differences Analysis in Malawi," Policy Research Working Paper Series 9842, The World Bank.
    3. Pengpeng Chang & Xueru Pang & Xiong He & Yiting Zhu & Chunshan Zhou, 2022. "Exploring the Spatial Relationship between Nighttime Light and Tourism Economy: Evidence from 31 Provinces in China," Sustainability, MDPI, vol. 14(12), pages 1-22, June.

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