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

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 ligh...

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Main Authors: Yongguang Zhu, Deyi Xu, Saleem H. Ali, Ruiyang Ma, Jinhua Cheng
Format: Article
Language:English
Published: MDPI AG 2019-08-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/12/16/3154
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spelling doaj-733db7610aa24e6ba71ac6068bf13a4e2020-11-24T21:34:18ZengMDPI AGEnergies1996-10732019-08-011216315410.3390/en12163154en12163154Can Nighttime Light Data Be Used to Estimate Electric Power Consumption? New Evidence from Causal-Effect InferenceYongguang Zhu0Deyi Xu1Saleem H. Ali2Ruiyang Ma3Jinhua Cheng4School of Economics and Management, China University of Geosciences, Wuhan 430074, ChinaSchool of Economics and Management, China University of Geosciences, Wuhan 430074, ChinaCenter for Energy and Environmental Policy, University of Delaware, Newark, DE 19716, USASchool of Economics and Management, China University of Geosciences, Wuhan 430074, ChinaSchool of Economics and Management, China University of Geosciences, Wuhan 430074, ChinaNighttime 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.https://www.mdpi.com/1996-1073/12/16/3154electric power consumptionnighttime light datapanel econometricspanel Granger causality
collection DOAJ
language English
format Article
sources DOAJ
author Yongguang Zhu
Deyi Xu
Saleem H. Ali
Ruiyang Ma
Jinhua Cheng
spellingShingle Yongguang Zhu
Deyi Xu
Saleem H. Ali
Ruiyang Ma
Jinhua Cheng
Can Nighttime Light Data Be Used to Estimate Electric Power Consumption? New Evidence from Causal-Effect Inference
Energies
electric power consumption
nighttime light data
panel econometrics
panel Granger causality
author_facet Yongguang Zhu
Deyi Xu
Saleem H. Ali
Ruiyang Ma
Jinhua Cheng
author_sort Yongguang Zhu
title Can Nighttime Light Data Be Used to Estimate Electric Power Consumption? New Evidence from Causal-Effect Inference
title_short Can Nighttime Light Data Be Used to Estimate Electric Power Consumption? New Evidence from Causal-Effect Inference
title_full Can Nighttime Light Data Be Used to Estimate Electric Power Consumption? New Evidence from Causal-Effect Inference
title_fullStr Can Nighttime Light Data Be Used to Estimate Electric Power Consumption? New Evidence from Causal-Effect Inference
title_full_unstemmed Can Nighttime Light Data Be Used to Estimate Electric Power Consumption? New Evidence from Causal-Effect Inference
title_sort can nighttime light data be used to estimate electric power consumption? new evidence from causal-effect inference
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2019-08-01
description 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.
topic electric power consumption
nighttime light data
panel econometrics
panel Granger causality
url https://www.mdpi.com/1996-1073/12/16/3154
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