Search results

This paper aims to draw on a number of indicators of innovation to evaluate and compare two central regions – Hubei and Hunan – with three leading regions of China – Beijing, Shanghai and Guangdong.

The paper focuses on absorptive capacity at the level of domestic regions of China, using data on R&D expenditures, human resources in higher education and in high-tech industries. The paper uses social network analysis to investigate innovation networks based on patents from the SIPO and USPTO.

Results indicate that, in Hubei and Hunan, R&D expenditures do not translate into as many innovative outputs as in the coastal and Southern regions. Moreover, high-tech industries contribute towards a relatively low proportion of the regional outputs of Hubei and Hunan, where especially the electronics industry is very poorly represented. Findings also suggest that Hubei and Hunan have a relatively limited access to foreign technologies embedded in ties with international partners. By contrast, the more advanced three regions tend to develop collaborative activities across national boundaries to a higher extent than across regional boundaries.

The analysis of China's regional innovation system has implications for research on national innovation systems. Policy-makers can benefit from the comparative analysis of regions.

The study is primarily exploratory, and the findings contribute to the literature and ongoing discussion on data sources and methods for the analysis of regional innovation.

This paper investigates the impact of investor attention on the COVID-19 concept stocks in China's stock market from the perspectives of the macroeconomy, the stock market and the COVID-19 pandemic.

On the basis of controlling the time effects and individual fixed effects, this paper studies the impact of investor attention on the COVID-19 concept stocks in China's stock market through a set of fixed effect panel data models. Among them, investor attention focuses on macroeconomy, stock market and the COVID-19 pandemic, respectively, while stock indicators cover return, volatility and turnover. In addition, this paper also examines the heterogeneity influence of investor attention on the COVID-19 concept stocks from the perspective of time and stock classification.

Findings indicate that the attention to macroeconomy does not have a statistically significant effect on the return, unlike the attention to stock market and COVID-19 incident. Three types of investor attention have significant positive effects on the volatility and turnover rate. During the outbreak of the domestic epidemic, the impact of investor attention was significantly higher than that during the outbreak of the epidemic overseas. A finer-grained analysis shows that the attention to stock market has significantly increased the return of preventive type and treatment type stocks, while diagnostic-related stocks have been most affected by the attention to COVID-19 incident.

The major limitation of this work is the construction of investor attention. Although Baidu index is widely used, investor attention can be assessed more accurately based on more unstructured data. In addition, the effect of the COVID-19 can also be investigated in a longer time domain. Further research can be combined with the dynamics of the COVID-19 pandemic to more comprehensively evaluate its impact on the stock market.

The research proves that investor attention plays an important role in stock pricing and provides empirical evidence on the behavioral foundations of the conceptual sector of the stock market under uncertainty. It also has practical implications for regulators and investors interested in conducting accurate asset allocation and risk assessment.