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Research on the economic development pattern of Chinese counties based on electricity consumption

Abstract With the implementation of the Policy of “Targeted Poverty Alleviation” in 2013, China has been in the critical stage to fight against poverty and the county economy has entered into a new stage of development which presents new evolutionary characteristics. However, traditional poverty county assessments are mostly based on the economic census, which not only costs a lot of manpower and material resources, but also shows the feature of hysteresis and scarcity. In this paper, county-level electricity consumption data is adopted to explore the characteristics of China's county-level economy development based on BIRCH clustering since electricity consumption data can be more sensitive and objective in reflecting regional economic development and residents' income level. The results show that four kinds of county-level economic development patterns can be categorized in China with different industrial structures. Then the potential problems with different development patterns are explored and suitable policy suggestions for each pattern is proposed separately. It can be found that electricity consumption should be a useful auxiliary tool for economic development assessment and monitoring for China and other similar developing countries.
- State Grid Corporation of China (China) China (People's Republic of)
- Chinese Academy of Sciences China (People's Republic of)
- China University of Political Science and Law China (People's Republic of)
- China University of Political Science and Law China (People's Republic of)
- University of Nebraska at Omaha United States
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).17 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
