Encouraging the resumption of economic activity after COVID-19: Evidence from a large scale-field experiment in China.

As the COVID-19 pandemic comes to an end, governments find themselves facing a new challenge: motivating citizens to resume economic activity. What is an effective way to do so? We investigate this question using a field experiment in the city of Zhengzhou, China, immediately following the end of the city's COVID-19 lockdown. We assessed the effect of a descriptive norms intervention providing information about the proportion of participants' neighbors who have resumed economic activity. We find that informing individuals about their neighbors' plans to visit restaurants increases the fraction of participants visiting restaurants by 12 percentage points (37%), among those participants who underestimated the proportion of neighbors who resumed economic activity. Those who overestimated did not respond by reducing restaurant attendance (the intervention yielded no "boomerang" effect); thus, our descriptive norms intervention yielded a net positive effect. We explore the moderating role of risk preferences and the effect of the intervention on subjects' perceived risk of going to restaurants, as well as the contrast with an intervention for parks, which were already perceived as safe. All of these analyses suggest our intervention worked by reducing the perceived risk of going to restaurants.

Special economic zone and infant mortality: Evidence from China.

By exploiting the development of special economic zones (SEZs) in China as a quasi-natural experiment, this paper evaluates how such zones affect infant mortality. Difference-in-differences analysis reveals that SEZs significantly decrease the local infant mortality rate, and the impact is larger for male infants and infants with less-educated mothers. Further studies show that the SEZs, which acts as an economic growth shock, improve infant survival by increasing the local income. Furthermore, there is no supportive evidence that the SEZs significantly alter either women's fertility-associated behaviors or environmental pollution. These results highlight the previously ignored human capital-related consequences of place-based policies in China.

Clean air as an experience good in urban China.

The surprise economic shutdown due to COVID-19 caused a sharp improvement in urban air quality in many previously heavily polluted Chinese cities. If clean air is a valued experience good, then this short-term reduction in pollution in spring 2020 could have persistent medium-term effects on reducing urban pollution levels as cities adopt new "blue sky" regulations to maintain recent pollution progress. We document that China's cross-city Environmental Kuznets Curve shifts as a function of a city's demand for clean air. We rank 144 cities in China based on their population's baseline sensitivity to air pollution and with respect to their recent air pollution gains due to the COVID shutdown. The largest experience good effect should take place for cities featuring a high pollution sensitive population and where air quality has sharply improved during the pandemic. The residents of these cities have increased their online discussions focused on environmental protection, and local officials are incorporating "green" industrial subsidies into post-COVID stimulus policies.

Household income inequality aggravates high-temperature exposure inequality in urban China.

The exposure to extremely high temperatures varies across population groups. Those with better adaptation strategies (such as air conditioning) suffer less. This paper combines China's daily mean temperature data with comprehensive national survey data at the household level and estimates the relationship between high-temperature exposure and adaptation behavior of urban dwellers. We find that the usage of air conditioning and electric fans by urban households in China increases with their summer high-temperature exposures. The rise in the number of days with extreme heat (mean temperature exceeding 80 °F) induces the purchase and use of air conditioning. High-temperature adaptability varied across households-the rich are more likely to increase air conditioning usage to cope with the high-temperature discomfort; while the poor are less likely to afford such a market product for adaptation, they suffer more from high-temperature exposure. Such a variation in the affordability and usage of market products to adapt to climate risks will exacerbate the climate-induced inequality.

How does air pollution affect household consumption? Evidence from China.

Increasing air pollution not only affects the population's health but also changes its consumption structures and patterns. Using China Family Panel Studies, this study investigates the relationship between air pollution and household consumption. The findings reveal that household consumption is considerably affected by air pollution: One standard deviation rise of PM2.5 concentration will decrease the household consumption by 8.7%. Moreover, this effect is irreversible in the short term. What is more, air pollution has significantly changed consumption structure and patterns. Heterogeneous analysis indicates that the influence of air pollution on consumption generates the so-called Matthew Effect, wherein medium and low-income and rural households are exposed to a greater negative effect. Mechanism tests indicate that air pollution may reduce household consumption through three channels: increase negative emotions, decrease outdoor activities, and depress future expectations. The conclusions drawn in this paper enrich our understanding of the economic impact caused by air pollution and bring important significance to the government in promoting the coordination and sustainable development of the environment and economy.

Improving health and reducing health inequality: An innovation of digitalization?

RATIONALE: The association between digitalization and individual health has attracted increasing attention from both scholars and policymakers. Existing research, however, has not agreed on whether digitization can improve health or reduce health inequality. OBJECTIVE: The purpose of this study is to clarify whether and how the development of digitalization may be related to health and health disparities. METHODS: We rely on China Family Panel Studies (CFPS) surveys from 2012 to 2018 to obtain a sample of 82,471 observations to explore the impact of digitalization on self-rated health and health inequality and its transmission mechanisms. The hypotheses are tested by Ordinary Least Squares Modeling. RESULTS: As expected, digitalization is significantly and positively correlated with self-rated health. Furthermore, the development of digitalization has led to a notable decrease in health inequality. The influencing mechanisms of digitalization include income, healthcare consumption and health behaviors. Both dimensions of digitalization-internet development and digital finance-generate significant effects and the effects of internet development are greater. CONCLUSIONS: This study is the first to systematically investigate the impact of digitalization development on health and health inequality. Our findings provide evidence for the health promotion theory by clarifying the benefits of digitalization in improving residents' health and reducing health inequality. Therefore, utilizing the tools of digitalization efficiently could be a focus of policymakers aiming to accomplish the SDGs' health targets.