Covid-19's Impact on China's Economy Based on Data of Spring Festival Travel Rush

Reduced mobility and less anthropogenic activity under special case circumstances over various parts of the world have pronounced effects on air quality. The objective of this study is to investigate the impact of reduced anthropogenic activity on air quality in the mega city of Shanghai, China. Observations from the highly sophisticated multi-axis differential optical absorption spectroscope (MAX-DOAS) instrument were used for nitrogen dioxide (NO2) and formaldehyde (HCHO) column densities. In situ measurements for NO2, ozone (O3), particulate matter (PM2.5) and the air quality index (AQI) were also used. The concentration of trace gases in the atmosphere reduces significantly during annual Spring Festival holidays, whereby mobility is reduced and anthropogenic activities come to a halt. The COVID-19 lockdown during 2020 resulted in a considerable drop in vertical column densities (VCDs) of HCHO and NO2 during lockdown Level-1, which refers to strict lockdown, i.e., strict measures taken to reduce mobility (43% for NO2; 24% for HCHO), and lockdown Level-2, which refers to relaxed lockdown, i.e., when the mobility restrictions were relaxed somehow (20% for NO2; 22% for HCHO), compared with pre-lockdown days, as measured by the MAX-DOAS instrument. However, for 2019, a reduction in VCDs was found only during Level-1 (24% for NO2; 6.62% for HCHO), when the Spring Festival happened. The weekly cycle for NO2 and HCHO depicts no significant effect of weekends on the lockdown. After the start of the Spring Festival, the VCDs of NO2 and HCHO showed a decline for 2019 as well as 2020. Backward trajectories calculated using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model indicated more air masses coming from the sea after the Spring Festival for 2019 and 2020, implying that a low pollutant load was carried by them. No impact of anthropogenic activity was found on O3 concentration. The results indicate that the ratio of HCHO to NO2 (RFN) fell in the volatile organic compound (VOC)-limited regime.

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The hit of the novel coronavirus outbreak to China's economy

China Economic Review ◽

10.1016/j.chieco.2021.101606 ◽

2021 ◽

Vol 67 ◽

pp. 101606

Author(s):

Hongbo Duan ◽

Qin Bao ◽

Kailan Tian ◽

Shouyang Wang ◽

Cuihong Yang ◽

...

Keyword(s):

The Novel ◽

Novel Coronavirus ◽

China’S Economy

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The Impact of Participation in PPP Projects on Total Factor Productivity of Listed Companies in China

Sustainability ◽

10.3390/su13147603 ◽

2021 ◽

Vol 13 (14) ◽

pp. 7603

Author(s):

Xiangdong Liu ◽

Guangxi Cao

Keyword(s):

Total Factor Productivity ◽

High Speed ◽

Operation Mode ◽

Listed Companies ◽

Financing Constraints ◽

Eastern Region ◽

Time Varying ◽

Factor Productivity ◽

The Impact ◽

China’S Economy

The key to transforming China’s economy from high-speed growth to high-quality development is to improve total factor productivity (TFP). Based on the panel data of China’s listed companies participating in PPP (Public–Private Partnerships) projects from 2010 to 2019, this paper constructs the time-varying DID method to test the impact of participation in PPP projects on the company’s TFP empirically, explore the mechanism of the effect of participation in PPP projects on the company’s TFP, and then conduct heterogeneous analysis from four perspectives: region, industry, ownership form, and operation mode. The empirical results show that participation in PPP projects can significantly promote the growth of the company’s TFP, which mainly comes from the promotion of the innovation level of listed companies and the alleviation of financing constraints by participating in PPP projects. In addition, participation in PPP projects has a significant impact on TFP of listed companies in the eastern region, listed companies in the secondary and tertiary industries, state-owned listed companies, and listed companies participating in PPP projects under the BOT mode.

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Social Sensing of the Imbalance of Urban and Regional Development in China Through the Population Migration Network around Spring Festival

Sustainability ◽

10.3390/su12083457 ◽

2020 ◽

Vol 12 (8) ◽

pp. 3457 ◽

Cited By ~ 1

Author(s):

Ruoxin Zhu ◽

Diao Lin ◽

Yujing Wang ◽

Michael Jendryke ◽

Rui Xin ◽

...

Keyword(s):

Urban Development ◽

Regional Development ◽

Analytical Framework ◽

Pagerank Algorithm ◽

Rich Club ◽

Importance Index ◽

Spring Festival ◽

Spatiotemporal Behavior ◽

Urban And Regional Development ◽

Reform And Opening Up

Regional development differences are a universal problem in the economic development process of countries around the world. In recent decades, China has experienced rapid urban development since the implementation of the reform and opening-up policy. However, development differs across regions, triggering the migration of laborers from underdeveloped areas to developed areas. The interaction between regional development differences and Spring Festival has formed the world’s largest cyclical migration phenomenon, Spring Festival travel. Studying the migration pattern from public spatiotemporal behavior can contribute to understanding the differences in regional development. This paper proposes a geospatial network analytical framework to quantitatively characterize the imbalance of urban/regional development based on Spring Festival travel from the perspectives of complex network science and geospatial science. Firstly, the urban development difference is explored based on the intercity population flow difference ratio, PageRank algorithm, and attractiveness index. Secondly, the community detection method and rich-club coefficient are applied to further observe the spatial interactions between cities. Finally, the regional importance index and attractiveness index are used to reveal the regional development imbalance. The methods and findings can be used for urban planning, poverty alleviation, and population studies.

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Does energy-price regulation benefit China's economy and environment? Evidence from energy-price distortions

Energy Policy ◽

10.1016/j.enpol.2017.02.031 ◽

2017 ◽

Vol 105 ◽

pp. 108-119 ◽

Cited By ~ 34

Author(s):

Keyi Ju ◽

Bin Su ◽

Dequn Zhou ◽

Junmin Wu

Keyword(s):

Price Regulation ◽

Energy Price ◽

Price Distortions ◽

China’S Economy

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Trends of Private Consumption in the Restructuring of China’s Economy

East Asian Policy ◽

10.1142/s1793930515000392 ◽

2015 ◽

Vol 07 (04) ◽

pp. 52-64

Author(s):

Chien-Hsun CHEN

Keyword(s):

Economic Growth ◽

Gross Domestic Product ◽

Private Consumption ◽

Decisive Role ◽

Domestic Product ◽

Domestic Consumption ◽

Labour Income ◽

Rapid Economic Growth ◽

Labour Share ◽

China’S Economy

The benefits deriving from rapid economic growth have chiefly accrued to capital returns. Consequently, the decline in the share of Chinese gross domestic product (GDP) accounted for by labour income has been most pronounced. To sustain growth, China will have to ensure robust consumption. Increasing the labour share in GDP and hence promoting domestic consumption will play a decisive role in rebalancing China’s economy.

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Trend analysis and forecast of daily reported incidence of hand, foot and mouth disease in Hubei, China by Prophet model

Scientific Reports ◽

10.1038/s41598-021-81100-2 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Cong Xie ◽

Haoyu Wen ◽

Wenwen Yang ◽

Jing Cai ◽

Peng Zhang ◽

...

Keyword(s):

Moving Average ◽

Arima Model ◽

Foot And Mouth Disease ◽

Mouth Disease ◽

Spring Festival ◽

High Incidence ◽

Foot And Mouth ◽

Accurate Forecast ◽

Changing Patterns ◽

Two Peaks

AbstractHand, foot, and mouth disease (HFMD) is common among children below 5 years. HFMD has a high incidence in Hubei Province, China. In this study, the Prophet model was used to forecast the incidence of HFMD in comparison with the autoregressive-integrated moving average (ARIMA) model, and HFMD incidence was decomposed into trends, yearly, weekly seasonality and holiday effect. The Prophet model fitted better than the ARIMA model in daily reported incidence of HFMD. The HFMD incidence forecast by the Prophet model showed that two peaks occurred in 2019, with the higher peak in May and the lower peak in December. Periodically changing patterns of HFMD incidence were observed after decomposing the time-series into its major components. In specific, multi-year variability of HFMD incidence was found, and the slow-down increasing point of HFMD incidence was identified. Relatively high HFMD incidences appeared in May and on Mondays. The effect of Spring Festival on HFMD incidence was much stronger than that of other holidays. This study showed the potential of the Prophet model to detect seasonality in HFMD incidence. Our next goal is to incorporate climate variables into the Prophet model to produce an accurate forecast of HFMD incidence.

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