CnOpenData中国城市层面电力短缺指数

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。

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数据应用指南

Visual representation of the word frequencies of power shortage keywords

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时间区间

2001-2017

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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

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样本数据

province_code	province_name	year	China's provincial EPU index
11	北京	2017	68.1627655
12	天津	2017	139.3325806
13	河北	2017	79.15668488
14	山西	2017	189.1946869
15	内蒙古	2017	76.54681396
21	辽宁	2017	91.38005066
22	吉林	2017	89.98912048
23	黑龙江	2017	7.519604683
31	上海	2017	80.68917847
32	江苏	2017	47.75826263
33	浙江	2017	97.14289093
34	安徽	2017	111.6440353
35	福建	2017	160.7241058
36	江西	2017	102.082283
37	山东	2017	78.49134827
41	河南	2017	96.05151367
42	湖北	2017	99.25975037
43	湖南	2017	54.22574615
44	广东	2017	56.38425064
45	广西	2017	118.8451614
46	海南	2017	57.19842529
50	重庆	2017	107.0997543
51	四川	2017	118.5892792
52	贵州	2017	90.86172485
53	云南	2017	38.87081146
54	西藏	2017	163.8305817
61	陕西	2017	99.39268494
62	甘肃	2017	137.8933868
63	青海	2017	79.26584625
64	宁夏	2017	102.7975769
65	新疆	2017	46.38435364
11	北京	2016	47.85101318
12	天津	2016	143.1006927
13	河北	2016	115.6779938
14	山西	2016	98.37980652
15	内蒙古	2016	108.1842651
21	辽宁	2016	80.5438385
22	吉林	2016	104.2610016
23	黑龙江	2016	81.40262604
31	上海	2016	128.4771423
32	江苏	2016	43.71399307
33	浙江	2016	90.4801178
34	安徽	2016	125.6614151
35	福建	2016	94.90132904
36	江西	2016	113.8047638
37	山东	2016	55.01879883
41	河南	2016	86.23591614
42	湖北	2016	139.5249634
43	湖南	2016	58.70393753
44	广东	2016	57.20541382

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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.

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数据更新频率

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