Based on the data of 281 cities from 2005 to 2016, we constructed difference-in-difference (DID) models to study the impact of national innovative-city-pilot policy on urban innovation from the three dimensions of dynamic effect, heterogeneity, and influence path. The research found that: (1) The innovative-city-pilot policy has significantly improved the level of urban innovation. This conclusion is still valid after a series of robustness tests. (2) The policy does not have a lag effect, but it has a certain dynamic and continuous effect. (3) This policy is more conducive to innovation in provincial capitals or sub-provincial cities, and has little effect on innovation in other cities; there is no significant difference in the policy effects on eastern, mid-western cities, but the average policy effect in eastern cities is slightly higher than in the mid-western cities. (4) The impact mechanism test shows that the pilot policy affects urban innovation through government fiscal expenditures, the degree of urban industrial agglomeration, and the level of human capital.

This study employs high-dimensional factors model to depict the development of monetary policy uncertainty (MPU) in China over the past decades and develops a logical analytical framework to analyze the effect of MPU on the dynamic adjustment of a firm’s capital structure through bank risk-taking channels. We investigate how MPU affects dynamic adjustment of a firm’s capital structure using a panel data set of China public manufacturers between 2007 and 2018 and find that the higher the MPU, the more detrimental it is to the dynamic adjustment of firm’s capital structure. Further, bank risk-taking plays the role of a financial stabilizer. In addition to the willingness to take risks in on-balance sheet operations and the scale of loans, the risk-taking of our banks may also be reflected in the adjustment of the off-balance-sheet shadow banking scale. This study also finds that in terms of on-balance sheet business, heighten MPU decreases the scale of bank credit and tightens loan approval criteria, in terms of off-balance sheet business, heighten MPU decreases the scale of shadow banking, thereby leading to a lower dynamic adjustment of firm’s capital structure. JEL classification C13, C36, E50, G21

China’s university science and technology parks (USTPs) were established with the aim of closely combining the scientific and educational intellectual resources of universities with the advantageous innovation resources of the market to form a fusion of industry and education. This paper uses the establishment of national university science and technology parks (NUSTPs) as a “quasi-natural experiment.” We used the panel data of 293 cities from 1999 to 2017 as a sample to analyze the impact of NUSTP establishment on urban innovation, using the difference-in-difference method. The research found the following: (1) The establishment of NUSTPs significantly improves the level of urban innovation, and the conclusion is still valid after a series of robustness tests. The urban innovation effect of the establishment of NUSTPs is dynamic, non-lagging, and continuous. (2) The innovation effect differs significantly, depending on the city region, the city scale, and the university level. Specifically, the innovation effect of the establishment of NUSTPs is significant for cities in middle and western cities, large-scale cities, and cities with double first-class and local universities setting up USTPs, while the effect is not significant for cities in eastern cities, small- and medium-scale cities, and non-double first-class and ministry-affiliated institutions. (3) The impact mechanism test shows that NUSTPs contribute to urban innovation by increasing the city’s human capital, enhancing the degree of industrial agglomeration, and creating an innovation space effect.

As an important policy tool for urban economic development, transportation infrastructure development can influence the environmental loads and economic performances of cities. Naturally, the following questions arise. In China, has the transportation infrastructure development improved the urban green development efficiency (UGDE)? Is the effect heterogeneous across cities? In this study, we constructed a theoretical model that included the residential utility and transportation infrastructure to analyze the influence path of the transportation infrastructure on the UGDE. Based on the panel data of China’s 268 prefecture-level cities covering the period 2011–2017, we adopted the all-factor nonradial directional distance function (TNDDF) method to measure the UGDE, and we then applied the panel data to investigate the impact of the transportation infrastructure on the UGDE. Overall, the increase in the traffic infrastructure remarkably enhanced the UGDE. Furthermore, the impact was heterogeneous across cities. The larger the city, the more obvious the promotion effect of the transportation infrastructure on the UGDE. The research conclusion of the study reminds us that we should make efforts on the supply side when building cities, placing transportation infrastructure construction on the same level as ecological environmental protection to achieve high-quality urban development.

As we enter the digital era, the digital economy provides an opportunity for China’s manufacturing industry to achieve ‘smart manufacturing’ and provides important support for China to move from a ‘big manufacturing country’ to a ‘strong manufacturing country’. This paper constructs an indicator system for the level of digital economy development in Chinese cities by determining the connotation of China’s digital economy based on the characteristics of its digital economy development. Based on the application of entropy value method to measure the level of digital economy development of cities, we empirically investigate the impact of the level of digital economy development of cities on the innovation efficiency of manufacturing industry using mixed panel data of listed Chinese A-share manufacturing companies and cities from 2011 to 2019. The empirical study finds that the level of urban digital economy development is conducive to improving the overall innovation efficiency, innovation quality efficiency and innovation quantity efficiency of enterprises, and overall, the digital economy has a significant contribution to the innovation efficiency of manufacturing industry. There is regional, firm size and industry heterogeneity in the impact of urban digital economy development level on manufacturing innovation efficiency, and this heterogeneity is further manifested in the types of manufacturing innovation efficiency. For example, the urban digital economy enhances the innovation efficiency of small-scale firms mainly through the quantity of innovation rather than the quality of innovation.