中国城市层面电力短缺指数简介

Power shortage index for 218 Chinese cities

  • Contributors: Dongmei Guo, Qin Li, Peng Liu, Xunpeng Shi, Jian Yu
  • Abstract: This paper uses the text analysis method to construct a city-level power shortage index. We selected daily newspapers from 218 prefecture-level city as the data source and used a combination of selected high-frequency words with expert investigation to screen out basic terms related to power shortage. The following 20 keywords were identified: peak scheduling management, power generation, waste heat power generation, off-peak, grid disconnection, power rationing, switching off, orderly power consumption, tripping, peak avoidance, disconnection, plant power consumption, staggered peak avoidance, pull road, accident electricity, overload, transferring power supply, security of electricity, power rationing, and load transfer.

Mr. Jian Yu and his collaborators present a power shortage index to characterize the city-level power outages for 218 Chinese cities from 2001 to 2017. Please cite the following papers when using this data:

  • Guo, D., Li, Q., Liu, P., Shi, X., Yu, J., 2023. Power shortage and firm performance: Evidence from a Chinese city power shortage index, Energy Economics, Vol.119, No.106593.

经中央财经大学俞剑老师授权,CnOpenData建立了该数据的展示区及数据索引,便于学者浏览。

数据下载请点击Power shortage index for 218 Chinese cities


数据应用指南

Visual representation of the word frequencies of power shortage keywords

Visual representation of the word frequencies of power shortage keywords


时间区间

2001-2017


字段展示

Economic policy uncertainty (EPU) index
city
year
power shortage index with 5 keywords
power shortage index with 20 keywords
planned power shortage index
unplanned power shortage index

样本数据

province_codeprovince_nameyearChina's provincial EPU index
11北京201768.1627655
12天津2017139.3325806
13河北201779.15668488
14山西2017189.1946869
15内蒙古201776.54681396
21辽宁201791.38005066
22吉林201789.98912048
23黑龙江20177.519604683
31上海201780.68917847
32江苏201747.75826263
33浙江201797.14289093
34安徽2017111.6440353
35福建2017160.7241058
36江西2017102.082283
37山东201778.49134827
41河南201796.05151367
42湖北201799.25975037
43湖南201754.22574615
44广东201756.38425064
45广西2017118.8451614
46海南201757.19842529
50重庆2017107.0997543
51四川2017118.5892792
52贵州201790.86172485
53云南201738.87081146
54西藏2017163.8305817
61陕西201799.39268494
62甘肃2017137.8933868
63青海201779.26584625
64宁夏2017102.7975769
65新疆201746.38435364
11北京201647.85101318
12天津2016143.1006927
13河北2016115.6779938
14山西201698.37980652
15内蒙古2016108.1842651
21辽宁201680.5438385
22吉林2016104.2610016
23黑龙江201681.40262604
31上海2016128.4771423
32江苏201643.71399307
33浙江201690.4801178
34安徽2016125.6614151
35福建201694.90132904
36江西2016113.8047638
37山东201655.01879883
41河南201686.23591614
42湖北2016139.5249634
43湖南201658.70393753
44广东201657.20541382

参考文献

  • Guo, D., Li, Q., Liu, P., Shi, X., Yu, J., 2023. Power shortage and firm performance: Evidence from a Chinese city power shortage index, Energy Economics, Vol.119, No.106593.

数据更新频率

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