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Data Details

Dataset of International Fossil Energy and Renewable Energy Trade Dependence Network (2011-2020)


JIANG Xinjie1HE Ze2CHONG Zhaohui*1
1 School of Business，Shantou University，Shantou 515063，China2 Energy Research Institute，Chinese Academy of Macroeconomics Research，Beijing 100038，China

DOI:10.3974/geodb.2023.05.03.V1

Published:May 2023

Visitors：3583       Data Files Downloaded：59      
Data Downloaded：7.49 MB      Citations：

Key Words：

International energy trade,trade dependence,network matrix

Abstract：

The Dataset of International Fossil Energy and Renewable Energy Trade Dependence Network (2011-2020) was developed based on the statistical data of bilateral fossil energy and renewable energy trade between countries and regions in the world published by the United Nations Trade Database. The value of trade dependence between bilateral trading countries was calculated using proportion of imports and exports in bilateral trade and Herfindahl Hissman Index (HHI). The dataset includes the following data of international fossil energy and renewable energy from 2011 to 2020: (1) description of export volume; (2) adjacency matrix; (3) assortativity; (4) mean value of trade dependence. The dataset is archived in. xlsx format, and consists of 2 files with data size of 159 KB (compressed into 129 KB). The analysis paper based on the dataset was published in Geographical Research, Vol. 41, No. 12, 2022.

Foundation Item：

National Social Science Fund of China (19ZDA055); Guangdong Province of China (2020GXJK213); Ministry of Education of China (20YJC790189); China's Central Scientific Institutions (S2207-2); National Natural Science Foundation of China (42201196)

Data Citation：

JIANG Xinjie, HE Ze, CHONG Zhaohui*. Dataset of International Fossil Energy and Renewable Energy Trade Dependence Network (2011-2020)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2023. https://doi.org/10.3974/geodb.2023.05.03.V1.

References：

[1] He, Z., Yang, Y., Liu, Y., et.al. Characteristics of evolution of global energy trading network and relationships between major countries [J]. Progress in Geography, 2019, 38(10): 1621-1632.
     [2] Liu, L. Q., Chen, Z. H. Power advantage, trade dependence, and their similarities with a country’s foreign policy: Evidence from world input-output table [J]. Forum of World Economics & Politics, 2019, (4): 66-88.
     [3] Liu, L. Q., Yan, X. F., Yang, L. S., et.al. Research on the evolution and endogenous mechanism of international trade dependence network [J]. China Industrial Economics, 2021(2): 98-116. DOI: 10.19581/j.cnki.ciejournal.2021.02.015.
     [4] Chong, Z. H., Jiang, X. J., He Z. Research on the network dependence characteristics and substitution in international trade: Fossil energy and renewable energy [J]. Geographical Research, 2022, 41(12): 3214-3228. DOI: 10.11821/dlyj020220398.
     [5] Yang, Y. Energy globalization of China: Interaction logic and spatial transition [J]. Acta Geographica Sinica, 2022, 77(02): 295-314. DOI: 10.11821/dlxb202202003.
     [6] Fu, X., Yang, Y., Dong, W., et al. Spatial structure, inequality and trading community of renewable energy networks: A comparative study of solar and hydro energy product trades [J]. Energy Policy, 2017, 106: 22-31. DOI: 10.1016/j.enpol.2017.03.038.
     [7] Yuan, Y. L., Yan, J., Zhang, P. P., et al. Assortativity measures for weighted and directed networks [J]. Journal of Complex Networks, 2021, 9(2): 1-18. DOI: 10.1093/comnet/cnab017.
     [8] Zhang, H. W., Wang, Y., Yang, C., et al. The impact of country risk on energy trade patterns based on complex network and panel regression analyses [J]. Energy, 2021, 222: 119979. DOI: 10.1016/j.energy.2021.119979.
     [9] Zhou, B., Lu, X., Holme, P. Universal evolution patterns of degree assortativity in social networks [J]. Social Networks, 2020, 63: 47-55. DOI: 10.1016/j.socnet.2020.04.004.
     

Data Product:

ID Data Name Data Size Operation
1 DependenceNetwork_F&R_2011-2020.rar 129.94KB
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