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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| Format: | Article |
| Language: | English |
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MDPI AG
2019-08-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/12/16/3154 |
| _version_ | 1798040671467077632 |
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| author | Yongguang Zhu Deyi Xu Saleem H. Ali Ruiyang Ma Jinhua Cheng |
| author_facet | Yongguang Zhu Deyi Xu Saleem H. Ali Ruiyang Ma Jinhua Cheng |
| author_sort | Yongguang Zhu |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-11T22:10:48Z |
| format | Article |
| id | doaj.art-733db7610aa24e6ba71ac6068bf13a4e |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-11T22:10:48Z |
| publishDate | 2019-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-733db7610aa24e6ba71ac6068bf13a4e2022-12-22T04:00:33ZengMDPI 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 |
| 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 |
| title | 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_short | 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 |
| 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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