Investing in human capital can assist in achieving technological innovations, while the spatial spillover effects of human capital on urban innovation in urban agglomeration are largely ignored. Using the panel data of 108 cities in China’s Yangtze River Economic Belt (YREB) during 2011–2020, this paper explores the interactions between human capital and urban innovation with a two-way fixed effects Spatial Durbin Model framework, which incorporates the interpretation of spatial spillover effects. The results show that urban innovation in the YREB has spatial heterogeneity in the structure, which is reflected in its diffusion from the downstream cities on the eastern coast to the upstream cities in the western region. Then, the low-level human capital inhibits the development of local innovation, while intermediate and high-level human capital improves local innovation. Furthermore, the spatial spillover effect shows an opposite trend. The impact of human capital on urban innovation is not significant in the downstream cities, such as Shanghai and Nanjing. Finally, three policy directions are proposed to optimize the human capital structure of the YREB, which are, strengthening investment in human capital and technological innovation, enhancing the talent spillover effect, and improving basic education.
Properly addressing external shocks in urban agglomeration is critical to sustaining the complex regional system. The COVID-19 pandemic has been widely acknowledged as an unintended external shock, but the temporal and spatial transmission patterns are largely ignored. This study analyzed the temporal and spatial transmission patterns of COVID-19 at the macro, meso, and micro levels, and proposes a conceptual model for regional comprehensive risk calculation, taking the Beijing-Tianjin-Hebei (BTH) area as the focus region. Our results showed that 1) at the temporal scale, the epidemic in the BTH area experienced stages of rapid increase, gradual decrease, and stabilization, and the first wave of the epidemic was under control from 23 February 2020; 2) at the spatial scale, confirmed cases were largely distributed at the terminal of the migration network, with closely interconnected cities in the BTH area, including Beijing, Tianjin, Tangshan, and Langfang, holding the highest comprehensive epidemic risk, thus requiring special attention for epidemic prevention and control. Finally, a “two-wheels” conceptual framework was built to discuss implications for future policies for addressing external shocks. Our proposed framework consists of an isolation wheel, which involves information sharing from the holistic perspective, and a circulation wheel, which emphasizes stakeholder involvement from the individual perspective. The findings of this study provide a knowledge basis for epidemic prevention and control as well as useful implications for addressing external shocks in the future.
Based on the data obtained on carbon emissions in Guangdong Province, China, from 1997 to 2019, this study focused on the relationship between energy consumption and population development in Guangdong Province. This study quantitatively analyzed the impact of different population structures and technological progress on carbon emissions in Guangdong Province by establishing an extended model of Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT). The results showed that the population size factor was not as good as the population structure factor for carbon emissions. In addition, different demographic factors affected carbon emissions differently with both positive and negative effects. Finally, relevant policy suggestions were proposed from the perspectives of encouraging the childbearing of appropriate-age residents, optimizing the population structure, reducing the separation of people and households, guiding residents to return to the traditional family model, guiding residents to live a low-carbon life, optimizing industrial institutions, and adjusting the energy consumption structure.
Abstract. On the basis of analyzing the pros and cons of different urbanization level measurement methods, this paper puts forward urbanization level measurement method based on entity space and then uses entity space data to describe the urbanization rate of various districts and counties of JingJinJi Region in 2005 and 2009. According to the analysis of time and space differences on such basis, JingJinJi may be divided from high to low order according to the urbanization rate of the entity space: central urban area, urban development area and suburb, which respectively bear different functions. According to the comparison of entity space urbanization rate and population urbanization rate in the aspects of sequence, primacy ratio, zipf index, etc., we find the non-intensive land use status quo of urban development area of JingJinJi and the feature that the distribution of entity space urbanization scale is much uniform than distribution of population urbanization scale. Accordingly, the paper puts forward the following suggestions : (1) The space construction should depend upon function division; (2) The urban development area should pay attention to the construction of the supporting facilities and meanwhile enhance land use rate; (3) The urban construction should be enhanced in small and middle regions and counties surrounding Beijing and Tianjin.
The total factor productivity of grain (TFPG) is critically important to secure food production, while its spatiotemporal heterogeneity in the urbanized area is largely ignored. Selecting 41 cities in the Yangtze River Delta, this study uses the data envelopment analysis (DEA) Malmquist index method to measure the TFPG in each city from 2012 to 2020 based on panel data, and explores the driving factors of the spatiotemporal evolution of the TFPG with the geographically and temporally weighted regression model. The results indicate the following: (1) Both the TFPG and technological progress varies in the same direction, indicating that technological progress dominates the TFPG in the studied region. The changes in technical efficiency, pure technical efficiency, and scale efficiency are relatively stable. (2) The spatial distribution of the TFPG shows a decentralized trend, with a pattern of high in the north and east areas and low in the south and west areas. (3) The driving factors, such as the development level of the grain economy, the amount of fertilizer used per unit area, and gross domestic product (GDP) per capita, have a restraining effect on the improvement of the TFPG, in which the amount of fertilizer used per unit area is the critical factor. (4) The scale of per capita labor operation, the proportion of the grain-growing population, and output of grain per hectare exert a promoting effect on the TFPG, in which both the proportion of the grain-growing population and output of grain per hectare are the critical factors. Finally, improving the efficiency of fertilizer use, expanding the production scale of the grain planting industry, and increasing the output of grain per hectare are proposed to improve the TFGP in the Yangtze River Delta.
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