Economic policy uncertainty (EPU) index for China’s 31 provinces
- Contributors:Jian Yu, Xunpeng Shi, Dongmei Guo, Longjian Yang
- Abstract: Following the methodology of Baker et al. (2016), we constructed a set of EPU indexes at the provincial level in China. First, we selected the daily newspapers of 31 provinces in China as the source for news media reports . Second, we made the following provisions on the definition of the EPU index obtained through keyword searches: if there was at least one economic policy keyword and at least one keyword expressing uncertainty, the news article was considered a target article. Third, we calculated the annual total number of target articles for each of the 31 provinces, and divided it by the total number of target articles in the newspapers that contained the keyword “economy” in that year, to obtain the article proportion of the EPU in the 31 provinces . Fourth, we standardized the proportion of EPU articles in the 31 provinces by using the standard deviation of each province to obtain the EPU index for the 31 provinces.
Mr. Jian Yu and his collaborators present a provincial EPU index to characterize the province-level EPU for China’s 31 provinces from 2000 to 2017. Please cite the following papers when using this data:
- Yu, J., Shi, X., Guo, D., Yang, L., 2021. Economic policy uncertainty (EPU) and firm carbon emissions: Evidence using a China provincial EPU index, Energy Economics, Vol. 94 , No.105071.
With the authorization of Professor Yu Jian from the Central University of Finance and Economics, CnOpenData established a display area and data index for this data to facilitate scholars’ browsing.
For data download, please click Economic policy uncertainty (EPU) index for China's 31 provinces.
Data Application Guide
Comparison of keywords criteria between Baker’s China EPU and China’s provincial EPU
| Keywords criteria | Baker’s China EPU | China’s provincial EPU |
|---|---|---|
| Economic | economy, economic | Economy |
| Policy | policy, spending, budget, politics, interest rate, reform, government, Beijing, authorities, tax, regulation, regulatory, Central Bank, People’s Bank of China, PBOC, deficit, WTO | (Promote, stimulate, expand) consumption, adjust interest rates/interest rate adjustments, (expand, reduce) investment, (increase, reduce) tax/tax reduction/tax policy/fiscal and tax reform, fiscal expenditure/fiscal system/fiscal stimulus, Currency/monetary policy, export expansion, value-added tax/consumption tax/corporate income tax/personal income tax/property tax/tariff, transfer payments, local debt, pensions, policy pilots, strengthening supervision |
| Uncertainty | uncertain, uncertainty | Uncertain, forecast, expected, pilot, trial, demonstration, maybe, possible, to be, expected |
| Country | China, Chinese | China, our country, domestic |
Time interval
2000-2017
Field display
| Economic policy uncertainty (EPU) index |
|---|
| province_code |
| province_name |
| year |
| China's provincial EPU index |
Sample data
| province_code | province_name | year | China's provincial EPU index |
|---|---|---|---|
| 11 | Beijing | 2017 | 68.1627655 |
| 12 | Tianjin | 2017 | 139.3325806 |
| 13 | Hebei | 2017 | 79.15668488 |
| 14 | Shanxi | 2017 | 189.1946869 |
| 15 | Inner Mongolia | 2017 | 76.54681396 |
| 21 | Liaoning | 2017 | 91.38005066 |
| 22 | Jilin | 2017 | 89.98912048 |
| 23 | Heilongjiang | 2017 | 7.519604683 |
| 31 | Shanghai | 2017 | 80.68917847 |
| 32 | Jiangsu | 2017 | 47.75826263 |
| 33 | Zhejiang | 2017 | 97.14289093 |
| 34 | Anhui | 2017 | 111.6440353 |
| 35 | Fujian | 2017 | 160.7241058 |
| 36 | Jiangxi | 2017 | 102.082283 |
| 37 | Shandong | 2017 | 78.49134827 |
| 41 | Henan | 2017 | 96.05151367 |
| 42 | Hubei | 2017 | 99.25975037 |
| 43 | Hunan | 2017 | 54.22574615 |
| 44 | Guangdong | 2017 | 56.38425064 |
| 45 | Guangxi | 2017 | 118.8451614 |
| 46 | Hainan | 2017 | 57.19842529 |
| 50 | Chongqing | 2017 | 107.0997543 |
| 51 | Sichuan | 2017 | 118.5892792 |
| 52 | Guizhou | 2017 | 90.86172485 |
| 53 | Yunnan | 2017 | 38.87081146 |
| 54 | Tibet | 2017 | 163.8305817 |
| 61 | Shaanxi | 2017 | 99.39268494 |
| 62 | Gansu | 2017 | 137.8933868 |
| 63 | Qinghai | 2017 | 79.26584625 |
| 64 | Ningxia | 2017 | 102.7975769 |
| 65 | Xinjiang | 2017 | 46.38435364 |
| 11 | Beijing | 2016 | 47.85101318 |
| 12 | Tianjin | 2016 | 143.1006927 |
| 13 | Hebei | 2016 | 115.6779938 |
| 14 | Shanxi | 2016 | 98.37980652 |
| 15 | Inner Mongolia | 2016 | 108.1842651 |
| 21 | Liaoning | 2016 | 80.5438385 |
| 22 | Jilin | 2016 | 104.2610016 |
| 23 | Heilongjiang | 2016 | 81.40262604 |
| 31 | Shanghai | 2016 | 128.4771423 |
| 32 | Jiangsu | 2016 | 43.71399307 |
| 33 | Zhejiang | 2016 | 90.4801178 |
| 34 | Anhui | 2016 | 125.6614151 |
| 35 | Fujian | 2016 | 94.90132904 |
| 36 | Jiangxi | 2016 | 113.8047638 |
| 37 | Shandong | 2016 | 55.01879883 |
| 41 | Henan | 2016 | 86.23591614 |
| 42 | Hubei | 2016 | 139.5249634 |
| 43 | Hunan | 2016 | 58.70393753 |
| 44 | Guangdong | 2016 | 57.20541382 |
References
- Yu, J., Shi, X., Guo, D., Yang, L., 2021. Economic policy uncertainty (EPU) and firm carbon emissions: Evidence using a China provincial EPU index, Energy Economics, Vol. 94 , No.105071.
Data update frequency
Updated from time to time