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

Yongguang Zhu, Deyi Xu, Saleem H. Ali, Ruiyang Ma and Jinhua Cheng
Additional contact information
Yongguang Zhu: School of Economics and Management, China University of Geosciences, Wuhan 430074, China
Deyi Xu: School of Economics and Management, China University of Geosciences, Wuhan 430074, China
Saleem H. Ali: Center for Energy and Environmental Policy, University of Delaware, Newark, DE 19716, USA
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

Energies, 2019, vol. 12, issue 16, 1-14

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.

Keywords: electric power consumption; nighttime light data; panel econometrics; panel Granger causality (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/1996-1073/12/16/3154/pdf (application/pdf)
https://www.mdpi.com/1996-1073/12/16/3154/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:12:y:2019:i:16:p:3154-:d:258208

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().