| Literature DB >> 35155343 |
Aidi Xu1,2, Fangbin Qian1,2, Chih-Hung Pai1, Na Yu1, Pan Zhou3.
Abstract
This study investigates the impact of coronavirus disease 2019 (COVID-19) on economic development of China by measuring the HP financial index as an alternative variable of the digital economy. This study shows that economy of China developed further with the dissemination of COVID-19. Furthermore, the digital economy increased the level of economic development more prominently at the onset of COVID-19 pandemic. Moreover, an analysis of regional heterogeneity reveals that the eastern region maintained economic stability through its digital economy during COVID-19, while the central region improved its digital economy during COVID-19 pandemic. Although the economically underdeveloped western region has not suffered too seriously from COVID-19 pandemic, considering the sustained impact of disease and the uncertainty of its transmission speed, the region should vigorously develop its digital economy to manage public risk.Entities:
Keywords: COVID-19; China economy; digital pneumonia; sustainability; uncertain public risks
Mesh:
Year: 2022 PMID: 35155343 PMCID: PMC8828997 DOI: 10.3389/fpubh.2021.778671
Source DB: PubMed Journal: Front Public Health ISSN: 2296-2565
Digital economy index system.
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|---|---|---|
| Number of Alipay accounts per 10,000 people | ||
| Coverage | Account coverage | Percentage of Alipay users according to their cards |
| Average number of bank cards bound to each Alipay account | ||
| Per capita payment | ||
| Payment business | Amount paid per capita | |
| High frequency (50 times or more per year) active users accounted for one time or more uses per year | ||
| Per capita purchases of Yu'e Bao | ||
| Money fund business | Per capita purchase amount of Yu'e Bao | |
| Number of people who purchased Yu'e Bao, per 10,000 Alipay users | ||
| The number of users with internet consumer loans per million Alipay adult users | ||
| Personal consumption loans | Per capita loans | |
| Per capita loan amount | ||
| The number of small and micro internet business loan users per million Alipay adult users | ||
| Investment business | Small and micro business operators | Average number of loans per household for small and micro-operators |
| Average loan amount of small and micro-operators | ||
| Number of insured users per million Alipay users | ||
| Insurance business | Insurance per capita | |
| Insurance amount per capita | ||
| Number of people participating in internet investment and wealth management per 10,000 Alipay users | ||
| Investment business | Investment per capita | |
| Investment amount per capita | ||
| Per capita credit calls for natural persons | ||
| Credit business | Number of users using credit-based services per Alipay user (including financial, accommodation, travel, and social) | |
| Mobility | Proportion of mobile payments | |
| Proportion of mobile payment amounts | ||
| Affordability | Average loan interest rate for small and micro-operators | |
| Average personal loan interest rate | ||
| Credit | ||
| Proportion of Huabei's payment amount | ||
| Degree of digitization | Creditization | Proportion of the number of Credit Sesame free deposits (compared to all cases where a deposit is required) |
| Percentage of Credit Sesame free deposits (compared to all cases where deposits are required) | ||
| Percentage of user QR code payment | ||
| Facilitation | The proportion of the amount paid by the user's QR code |
QR, quick response.
Results of the entropy method.
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|---|---|---|---|
| Beijing | 399.00 | 417.88 | 4.73 |
| Tianjin City | 344.11 | 361.46 | 5.04 |
| Hebei province | 305.06 | 322.70 | 5.78 |
| Shanxi province | 308.73 | 325.73 | 5.51 |
| Inner Mongolia autonomous region | 293.89 | 309.39 | 5.27 |
| Liaoning province | 311.01 | 326.29 | 4.91 |
| Jilin province | 292.77 | 308.26 | 5.29 |
| Heilongjiang province | 292.87 | 306.08 | 4.51 |
| Shanghai | 410.28 | 431.93 | 5.28 |
| Jiangsu province | 361.93 | 381.61 | 5.44 |
| Zhejiang province | 387.49 | 406.88 | 5.00 |
| Anhui province | 330.29 | 350.16 | 6.02 |
| Fujian province | 360.51 | 380.13 | 5.44 |
| Jiangxi province | 319.13 | 340.61 | 6.73 |
| Shandong province | 327.36 | 347.81 | 6.25 |
| Henan province | 322.12 | 340.81 | 5.80 |
| Hubei province | 344.40 | 358.64 | 4.13 |
| Hunan province | 310.85 | 332.03 | 6.81 |
| Guangdong province | 360.61 | 379.53 | 5.25 |
| Guangxi Zhuang autonomous region | 309.91 | 325.17 | 4.92 |
| Hainan | 328.75 | 344.05 | 4.65 |
| Chongqing | 325.47 | 344.76 | 5.93 |
| Sichuan province | 317.11 | 334.82 | 5.58 |
| Guizhou province | 293.51 | 307.94 | 4.92 |
| Yunnan province | 303.46 | 318.48 | 4.95 |
| Tibet | 293.79 | 310.53 | 5.70 |
| Shaanxi province | 322.89 | 342.04 | 5.93 |
| Gansu province | 289.14 | 305.50 | 5.66 |
| Qinghai province | 282.65 | 298.23 | 5.51 |
| Ningxia Hui autonomous region | 292.31 | 310.02 | 6.06 |
| Xinjiang Uygur autonomous region | 294.34 | 308.35 | 4.76 |
Descriptive statistics of variables.
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|---|---|---|---|---|
| Gross domestic product (GDP) | 11.08 | 0.39 | 10.40 | 12.01 |
| Digital economy (DE) | 5.80 | 0.10 | 5.64 | 6.07 |
| COVID-19 outbreak (COV) | 4.26 | 3.34 | 0 | 11.13 |
| Industrialization level (SIZE) | 1.834 | 1.197 | −1.064 | 4.182 |
| Urbanization level (CITY) | 7.664 | 0.645 | 5.225 | 8.749 |
| Foreign direct investment (FDI) | 3.258 | 0.847 | 1.450 | 6.194 |
| Advanced industrial structure (ADV) | 4.624 | 0.580 | 3.230 | 6.193 |
The direct impact of coronavirus disease 2019 (COVID-19) pandemic and the digital economy on the level of economic development of China.
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|---|---|---|
| Digital economy (DE) | 0.2156*** | 0.6757*** |
| COVID-19 outbreak (COV) | −0.0124*** | −0.1749*** |
| Industrialization level (SIZE) | 1.4152*** | 1.5124*** |
| Urbanization level (CITY) | 0.2524*** | 0.1641*** |
| Foreign direct investment (FDI) | −0.153* | −0.2231* |
| Advanced industrial structure (ADV) | 1.5124* | 2.2241* |
| Constant | −3.5355*** | −4.5524*** |
*** and * represent significant level at 1%, 5% and 10% respectively.
Indirect impact of COVID-19 pandemic and the digital economy on level of economic development of China.
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|---|---|---|
| Digital economy (DE) | 0.1864*** | 0.4987*** |
| COVID-19 outbreak (COV) | −0.0116*** | −0.1975*** |
| The intersection of the digital economy and | 0.3646*** | 1.5393*** |
| the COVID-19 pandemic (DE*COV) | ||
| Industrialization level (SIZE) | 1.4241*** | 1.5244*** |
| Urbanization level (CITY) | 0.2212*** | 0.1241*** |
| Foreign direct investment (FDI) | −0.1241* | −0.2241* |
| Advanced industrial structure (ADV) | 1.5553* | 2.2767* |
| Constant | −3.5685*** | −4.5457*** |
*** and * represent significant level at 1%, 5% and 10% respectively.
Regional heterogeneity of the impact of COVID-19 and the digital economy on level of economic development of China.
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|---|---|---|---|
| Digital economy (DE) | 0.7612*** | 0.5212*** | 0.2153*** |
| COVID-19 outbreak (COV) | −0.165*** | −0.345*** | −0.021*** |
| The intersection of digital economy and | 0.7831** | 0.7952*** | 0.2415* |
| COVID-19 pandemic (DE*COV) | |||
| Industrialization level (SIZE) | 1.5055*** | 1.4718*** | 1.2405*** |
| Urbanization level (CITY) | 0.3058*** | 0.3019*** | 0.3176*** |
| Foreign direct investment (FDI) | −0.3591*** | −0.4061*** | −0.2860*** |
| Advanced industrial structure (ADV) | 2.341*** | 2.4129*** | 1.7010*** |
| Constant | −3.5685*** | −4.5457*** | −2.4214*** |
***, **, and * represent significant level at 1%, 5% and 10% respectively.