The environmental effect of technical change:A spatial model with city-level data in China

This paper studies the environmental effects of technical change using a spatial model with panel data from 284 prefecture-cities over 2004-2015 in China.We find that the effects of technical change vary across different dimensions of technical change and different pollution indicators.Furthermore,we also provide robust evidence for the existence of the spatial effects of technical change on environmental pollution across cities.First,indigenous technical change displays three patterns of effects on the four pollutants:a positive effect on wastewater,a negative effect on PM_(2.5)concentrations,and an inverted U-shaped relationship with SO_(2)and soot emissions.The spatial effect of indigenous technical change promotes cleaner industrial productions(fewer emissions of SO_(2),soot and wastewater)but higher PM_(2.5)concentrations.Second,technology transfers from foreign direct investment are associated with less pollution except for wastewater,and their spatial effects are unanimously negative on all pollutants.Finally,absorptive capacity can also promote cleaner industrial production,but its spatial effects can do otherwise.Accordingly,the government should take the spatial spillover effects of technical change into account when implementing specific policies,pin down specific pollutants to make full use of the pollution-reducing effects of technical change,and improve the absorptive capacity of domestic firms.

Evaluation of regional water resources carrying capacity based on binary index method and reduction index method

Based on the regional water resources carrying capacity(WRCC)evaluation principles and evaluation index system in the National Technical Outline of Water Resources Carrying Capacity Monitoring and Early Warning(hereafter referred to as the Technical Outline),this paper elaborates on the collection and sorting of the basic data of water resources conditions,water resources development and utilization status,social and economic development in basins,analysis and examination of integrity,consistency,normativeness,and rationality of the basic data,and the necessity of WRCC evaluation.This paper also describes the technique of evaluating the WRCC in prefecture-level cities and city-level administrative divisions in the District of the Taihu Lake Basin,which is composed of the Taihu Lake Basin and the Southeastern River Basin.The evaluation process combines the binary index evaluation method and reduction index evaluation method.The former,recommended by the Technical Outline,uses the total water use and the amount of exploited groundwater as evaluation indices,showing stronger operability,while the latter is developed by simplifying and optimizing the comprehensive index system with greater systematicness and completeness.The mutual validation and adjustment of the results of the above-mentioned two evaluation methods indicate that the WRCC of the District of the Taihu Lake Basin is overloaded in general because some prefecture-level cities and city-level administrative divisions in the Taihu Lake Basin and the Southeastern River Basin are in a severely overloaded state.In order to explain this conclusion,this paper analyzes the causes of WRCC overloading from the aspects of basin water environment,water resources development and utilization,water resources regulation and control ability,water resources utilization efficiency,and water resources management.

基于手机APP使用记录的中国城市经济发展度量研究

With the rise of smart phones,mobile applications have been widely used in daily life.However,the relationship between individuals’mobile application usage and cities’economic development has yet to be investigated.To study this question,this work utilizes a dataset containing users’history of mobile application usage records(MAURs)and investigates how MAURs are related to Chinese cities’economic development.Our analysis shows the cities’GDP and number of MAURs are highly correlated,and at the individual level,people in wealthier cities(higher GDP per capita)tend to have more active mobile application usage(MAURs per capita).The results also demonstrate the relevance between cities’GDP and MAURs varies significantly among different demographic groups,with male users’relevance consistently higher than female users’and working-age people’s relevance higher than other age groups.A boosted tree regression model is then applied to predict cities’GDP with MAURs and proves to achieve high goodness-of-fit(over 0.8 R-square)and good prediction accuracy,especially for the economically developed and populous regions in China.To the best of our knowledge,this is the first time that the relationship between MAURs and cities’economic development is revealed,which contributes to novel knowledge discovery for regionalization and urban development.