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High-quality innovation is an inevitable requirement for high-quality economic development, and an accurate grasp of the regional distribution characteristics of the level of highquality innovation development (HQID) can better understand and simulate high-quality innovation. This paper constructs a dataset of high-value inventions based on the Chinese patent database using textual analysis methods and the criteria for High-Quality Inventions proposed by the State Intellectual Property Office, and explores inter-provincial variability and convergence by using the Theil index, α convergence, and β convergence. This paper finds that High-Quality Inventions are significantly and positively correlated with various indicators measuring the quality and value of patents. In general, the overall level of HQID is on an upward trend with clear differences among provinces, which shows a regional unbalanced but overall rapid development. From the regional differences of HQID, the regional differences of HQID have been narrowed, mainly within the region. In terms of the convergence of HQID, α convergence, absolute β convergence, conditional β convergence, and club convergence exist nationally and within each region, which indicates that the gap between the national and regional levels of HQID has been narrowing over time. HQID has a positive promotion effect on the relationship between HQID and economic growth, economic growth rate, and total factor productivity. High-quality innovation can improve the quality of input factors, cultivate new dynamic energy for economic development, and then promote high-quality economic development. In the context of the shift of IP work from pursuing quantity to improving quality, the scientific understanding of high-quality innovation, the development status, and the differences of regional innovation high-quality development is of great significance for improving innovation quality and efficiency, and effectively supporting high-quality economic development. [ABSTRACT FROM AUTHOR]

Based on the database of green patents of China's A-share listed enterprises from 2001 to 2018, this paper identifies the impact of the province-managing-county (PMC) fiscal reform on the green innovation performance of enterprises by using staggered DID method. The results show that the PMC fiscal reform significantly promotes enterprises' green innovation performance, and this impact is not only reflected in the quantity of green patents but also in the quality. The mechanism test finds that the policy effect of PMC fiscal reform comes from the attraction of environmental investment and optimization of human capital structure. The PMC fiscal reform expands the financial autonomy of county governments, facilitating the compensation and allocation mechanism. Moreover, the paper incorporates the county-power-expansion (CPE) reform into the robustness test to exclude the interference of other policies in the same period. [ABSTRACT FROM AUTHOR]

Due to the particularity of biomedical industry, it has become necessary for biomedical enterprises to seek innovative research and development (R&D) cooperation to maintain advanced technologies and products in multiple fields. Under such circumstance, the biomedical industry has gradually formed a certain cluster to promote the development of the industry. So far, the biomedical industry cluster has formed in China, mainly within the Yangtze River Delta, Pearl River Delta, and Beijing-Tianjin-Hebei three urban agglomerations. Within the industrial clusters, the frequency of innovation cooperation among enterprises, universities, research institutions, and other relevant organizations in the biomedical area is high, and the capacity for innovation cooperation is strong as well. This paper used the representative cross-section data of cooperative patents from the medical science and technology patent database of China National Knowledge Infrastructure (CNKI), researching the R&D cooperation within the three major urban agglomerations in China from 2008 to 2016 (Yangtze River Delta Urban Agglomeration, Pearl River Delta Urban Agglomeration, Beijing-Tianjin-Hebei Urban Agglomeration) on total 36 cities' spatial pattern characteristics of biomedical cooperation and the influencing factors. The spatial interaction model was used to study the spatial, economic, political, and R&D influencing factors of cross-city cooperation. The degree of aggregation showed that cross-city R&D cooperation mainly occurred in well-developed and central cities of urban agglomerations. Econometric results revealed that spatial, economic, political, and R&D bias factors did have a significant impact on the frequency of biomedical R&D cooperation across cities. [ABSTRACT FROM AUTHOR]

Trade and the environment are two grave concerns of sustainable development in the new development pattern of the Chinese economy. Reducing corporate pollution intensity (CPI) is an essential means of securing economic sustainability, energy conservation, and emissions reduction, and participating in global value chains (GVCs) is a key driver of CPI reduction. Based on the elucidation of the mechanism by which GVC position affects CPI through technological innovation, this paper used the matching data of the enterprise pollution discharge database, the customs import and export database, the enterprise patent database, and the industrial enterprise database from 2000 to 2014 to empirically test the impact of GVC position on CPI. Furthermore, the robustness of the core conclusions was further verified by using the data of listed companies and manufacturing sub-sectors from 2010 to 2019. The main conclusions were as follows: ① GVC position generally showed a positive environmental effect. GVC position could reduce the pollution emissions per unit of output value of enterprises. This core conclusion still held after robustness tests such as replacement of measurement indicators, replacement of sample data, and endogenous discussions. ② The results of the analysis of the mechanism of action showed that GVC position would reduce CPI through the output effect and technological innovation effect. ③ The results of the heterogeneity analysis showed that, under different corporate ownership types, technical levels, and regional characteristics, GVC position had a more obvious impact on improving the environmental effects of foreign-funded enterprises, high-tech enterprises, and enterprises in China’ s eastern region. ④ The research perspective of the article shifted from the micro-enterprise level to the meso-level industry level. The results of the dynamic decomposition of pollutant emission intensity at the industry level showed that the contribution of the resource reallocation effect to the reduction of industry pollution emission intensity was 55.39%, and it was an important channel for GVC position to pollution intensity. To this end, the study puts forward relevant policy suggestions from the aspects of implementing a more active opening strategy, enhancing the technological innovation capabilities of enterprises, and encouraging the coordinated development of multi-type enterprises and regional coordinated development, providing theoretical support and empirical evidence for promoting high-quality economic development in China. [ABSTRACT FROM AUTHOR]

This paper is to test the relationship between temperature change and industrial green innovation by combing data of China's average temperature change in cities with green patent database of listed companies.First, the results find that rising annual average temperature can inhibit green innovation. For every 1 °C increases in summer, green innovation reduces by 3.2%, and for every 1 °C increases in winter, green innovation increases by 1.9%. Second, rising summer temperature inhibits green innovation by crowding out research and development (R&D) funds and draining labor. While, rising temperature increases green innovation by increasing environmental responsibility and green venture capital. Third, differences in green R&D difficulty, process and objectives were also compared, temperature change has a stronger inhibition on green process innovation than green product innovation. And rising temperature inhibits green exploratory innovation and promotes green developmental innovation. Fourth, rising temperature increases green innovation in polluting firms as temperature is higher than 21 °C. And it inhibits green innovation in clean firms as temperature is higher than 27 °C. This paper can provide policy implications on climate regulation and promoting green innovation. [Display omitted] • For 1 °C increases in summer, industrial green innovation reduce by 2.1%. • Influence paths include cost inhibition effect and responsibility forcing effect. • Temperature increases green simple innovation and weaken green complex innovation. • Suitable temperature for green innovation is 18°C–27 °C. • Classify green innovation from the difficulty, process and purpose of R&D. [ABSTRACT FROM AUTHOR]