Exploring long-term residence among the urban floating population is crucial to understanding urban growth in China,particularly since the 2008 financial crisis.By using China Migrants Dynamic Survey data for 2012–20...Exploring long-term residence among the urban floating population is crucial to understanding urban growth in China,particularly since the 2008 financial crisis.By using China Migrants Dynamic Survey data for 2012–2014,China Labor-force Dynamics Survey data for 2014–2016,and macroscale urban matched data,we analyzed the spatial pattern of long-term residential behavior in China’s urban floating population in 2012–2016 and developed an urban spatial utility equilibrium model containing‘macro’urban factors and‘micro’individual and household factors to explain the pattern.The results first revealed that long-term residence is defined as≥6 yr for the urban floating population in China.Second,members of this population are more likely to be long-term residents of the megacities in the three urban agglomerations in eastern China as well as of small and medium-sized cities in western and northeastern China,whereas short-term residence is more likely in cities in central China and near the three urban agglomerations.Third,urban population density and housing prices,both have a significant U-shaped effect,are main factors affecting the spatial pattern of long-term residence.展开更多
With growing regional economic integration,transportation systems have become critical to regional development and economic vitality but vulnerable to disasters.However,the regional economic ripple effect of a disaste...With growing regional economic integration,transportation systems have become critical to regional development and economic vitality but vulnerable to disasters.However,the regional economic ripple effect of a disaster is difficult to quantify accurately,especially considering the cumulated influence of traffic disruptions.This study explored integrating transportation system analysis with economic modeling to capture the regional economic ripple effect.A state-of-the-art spatial computable general equilibrium model is leveraged to simulate the operation of the economic system,and the marginal rate of transport cost is introduced to reflect traffic network damage post-disaster.The model is applied to the 50-year return period flood in2020 in Hubei Province,China.The results show the following.First,when traffic disruption costs are considered,the total output loss of non-affected areas is 1.81 times than before,and non-negligible losses reach relatively remote zones of the country,such as the Northwest Comprehensive Economic Zone(36%of total ripple effects).Second,traffic disruptions have a significant hindering effect on regional trade activities,especially in the regional intermediate input—about three times more than before.The industries most sensitive to traffic disruptions were transportation,storage,and postal service(5 times),and processing and assembly manufacturing(4.4 times).Third,the longer the distance,the stronger traffic disruptions'impact on interregional intermediate inputs.Thus,increasing investment in transportation infrastructure significantly contributes to mitigating disaster ripple effects and accelerating the process of industrial recovery in affected areas.展开更多
The work presented in this paper relates to the prediction of trade distribution ofinter-regions while the transportation costs, commodity supply and demand functions for multiplecommodities are given. Under the condi...The work presented in this paper relates to the prediction of trade distribution ofinter-regions while the transportation costs, commodity supply and demand functions for multiplecommodities are given. Under the condition of the local transportation competition and congestion,a mathematical programming model in an integral form is developed to predict the inter-region nows,supply prices and demand prices by each commodity class. It is proved that the proposed mathematicalprogramming model is equivalent to the spatial price equilibrium problem. An algorithm is proposedto solve this problem. In this article, a numerical example is given to illustrate the application of theproposed model and algorithm.展开更多
基金Under the auspices of National Natural Science Foundation of China(No.42001132)MOE(Ministry of Education in China)Project of Humanities and Social Sciences(No.20YJC790009)Natural Science Basic Research Program of Shannxi,China(No.2020JQ-838)。
文摘Exploring long-term residence among the urban floating population is crucial to understanding urban growth in China,particularly since the 2008 financial crisis.By using China Migrants Dynamic Survey data for 2012–2014,China Labor-force Dynamics Survey data for 2014–2016,and macroscale urban matched data,we analyzed the spatial pattern of long-term residential behavior in China’s urban floating population in 2012–2016 and developed an urban spatial utility equilibrium model containing‘macro’urban factors and‘micro’individual and household factors to explain the pattern.The results first revealed that long-term residence is defined as≥6 yr for the urban floating population in China.Second,members of this population are more likely to be long-term residents of the megacities in the three urban agglomerations in eastern China as well as of small and medium-sized cities in western and northeastern China,whereas short-term residence is more likely in cities in central China and near the three urban agglomerations.Third,urban population density and housing prices,both have a significant U-shaped effect,are main factors affecting the spatial pattern of long-term residence.
基金supported by the National Natural Science Foundation of China(Grant Nos.42177448 and 41907393)。
文摘With growing regional economic integration,transportation systems have become critical to regional development and economic vitality but vulnerable to disasters.However,the regional economic ripple effect of a disaster is difficult to quantify accurately,especially considering the cumulated influence of traffic disruptions.This study explored integrating transportation system analysis with economic modeling to capture the regional economic ripple effect.A state-of-the-art spatial computable general equilibrium model is leveraged to simulate the operation of the economic system,and the marginal rate of transport cost is introduced to reflect traffic network damage post-disaster.The model is applied to the 50-year return period flood in2020 in Hubei Province,China.The results show the following.First,when traffic disruption costs are considered,the total output loss of non-affected areas is 1.81 times than before,and non-negligible losses reach relatively remote zones of the country,such as the Northwest Comprehensive Economic Zone(36%of total ripple effects).Second,traffic disruptions have a significant hindering effect on regional trade activities,especially in the regional intermediate input—about three times more than before.The industries most sensitive to traffic disruptions were transportation,storage,and postal service(5 times),and processing and assembly manufacturing(4.4 times).Third,the longer the distance,the stronger traffic disruptions'impact on interregional intermediate inputs.Thus,increasing investment in transportation infrastructure significantly contributes to mitigating disaster ripple effects and accelerating the process of industrial recovery in affected areas.
文摘The work presented in this paper relates to the prediction of trade distribution ofinter-regions while the transportation costs, commodity supply and demand functions for multiplecommodities are given. Under the condition of the local transportation competition and congestion,a mathematical programming model in an integral form is developed to predict the inter-region nows,supply prices and demand prices by each commodity class. It is proved that the proposed mathematicalprogramming model is equivalent to the spatial price equilibrium problem. An algorithm is proposedto solve this problem. In this article, a numerical example is given to illustrate the application of theproposed model and algorithm.
