Using the panel data of Chinese-listed manufacturing firms from 2008 to 2019, in this paper we apply the patent data and econometric models to identify digital technology innovation and to explore the mechanism for the digital technology innovation on industrial upgrading of the manufacturing firms. We also use the total factor productivity of firms to measure industrial upgrading of manufacturing firms. Our empirical results show that digital technology innovation is conducive to industrial upgrading of manufacturing firms. We find that the total factor productivity of firms with digital technology patents is significantly higher than that of firms without digital technology patents, and more importantly, the total factor productivity increases on higher scales of digital technology patents at an increasing rate. In addition, owning digital technology patents generates boosts to the total factor productivity of manufacturing firms through reducing the operating costs, improving the efficiency of resource allocation and enhancing the innovation capability.

With the development of the economy, collaborative R&D has become an important tool for Chinese companies to improve their performance. This paper explores the relationship between inter-firm collaborative R&D and firm performance in terms of both financial performance and technological innovation performance. Using panel data of more than 1,300 Chinese listed companies from 2007 to 2016 and using multiple regression analysis, we find that inter-firm collaborative R&D has a positive impact on technological innovation performance and potential market competitiveness, but a negative impact on profitability indicators. In addition, we further divided the companies into technology “leaders” and “followers,” and the results showed that the benefits of collaborative R&D are greater for the followers.

As a modern means of transportation, the automobile plays an important role in people’s travel. However, the environmental and energy problems brought by the automobile industry cannot be ignored. Based on unique Chinese urban and new car registration data, this paper empirically analyzes the emission reduction effect of car purchase tax incentives, its spatial heterogeneity, and impact on car consumption structure using difference-in-difference model, regression discontinuity design model, and other methods. We find that the tax incentives can effectively suppress the emission of urban pollutants. The quantile regression shows that the emission reduction effect of the tax incentives shows a dynamic change characteristic of weakening as the pollution level in cities increases. In addition, tax incentives for the purchase of low-energy consumption vehicles increase the market share of small-emission vehicles and change the consumption structure.

We investigate the impacts of the public attention towards the COVID-19 on the situation of the epidemic worldwide and on public mobility with Google trends. We use the number of searches for two keywords ‘corona virus’ and ‘mask’ on the Google search index to show people’s public attention towards the epidemic. The findings show that confirmed cases and death rates are significantly positively (negatively) associated with the public attention paid to epidemic in the early (later) stage of the epidemic. The reason may be that in the early stage of the epidemic, public attention increased outpatient rates and therefore confirmed cases significantly, while in the later stage, public attention accordingly increased cure rates significantly. The epidemic significantly eases for people’s mobility trends when refraining from going outdoors. Such impacts are more profound for low-income countries.