Green economic efficiency and its influencing factors in China from 2008 to 2017: Based on the super-SBM model with undesirable outputs and spatial Dubin model

China's transportation sector carbon dioxide emissions efficiency and its influencing factors based on the EBM DEA model with undesirable outputs and spatial Durbin model

The impacts of environmental pollution and brain drain on income inequality

Background Severe air pollution in China threatens human health, and its negative impact decreases the urban settlement intentions of migrants in destination cities. We establish a comprehensive framework based on the push-pull migration model to investigate this phenomenon. Methods We employ a logistic model to analyze air pollution's impact on the settlement intentions of the floating population based on the CMDS 2017 in China, combining the city-level socioeconomic variables with the individual-level variables. Results Our results show that the annual average concentration of PM2.5 increases by 1 unit and that the probability of migrants' settlement intentions will decrease by 8.7%. Using a heterogeneity analysis, we find that the following migrant groups are more sensitive to air pollution: males, people over 30 years old, less educated people, and migrants with nonagricultural hukou. With every 1 unit increase in PM2.5, each group's settlement intentions decrease by 13.2, 16.7, 16.9, and 12.6%, respectively. Conclusions Our results are consistent with existing studies. This study discovers that both external environment and internal factors influence migrants' settlement intentions. Specifically, the differences in population sizes, economic development levels, public services, infrastructure conditions, and environmental regulations between cities play a significant role in migration decisions. We also confirm heterogeneous sensitivities to air pollution of different migrant subgroups in terms of individual characteristics, family factors, migration features, social and economic attributes.

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How does air pollution affect urban settlement of the floating population in China? New evidence from a push-pull migration analysis.

Russia has experienced population decline in years and the economic development in Russia is largely restricted by labor shortage, particularly for the Far North and East region. In order to explore the migration mechanisms, six socioeconomic factors were selected to explore the influences on the net migration. Data from the 82 regions covering four time periods (2000, 2005, 2010 and 2015) was processed use spatial panel econometric analysis and the time-period fixed effects Spatial Durbin Model (SDM) was selected as the best fit model after tests. The results indicates that, unemployment and infant death rate are significantly negatively associated with net migration, while urbanization rate, urban scale and life expectancy are significantly positively associated with net migration; every 100 USD increase in per capita GRP (Gross Regional Product) is positively related with averagely 5.4 net migrates in the region; every 1 year increase in life expectancy would increase 1052 net migrates; every 1sqm increase in urban scale would increase the net migrates by 11.75 and every 1% increase in unemployment would lead to a decrease of 0.54 net migrates. Spillover effect was also found for per capita GRP and life expectancy, indicating that the increase of per capita GRP and life expectancy in neighboring regions can also increase the attractiveness in one region. It can be concluded that better job market, better economic status and health related wellbeing are all attracting factors for migrates and these factors can even make the neighborhood region more attractive for immigrates. Considering the ambitious development plan for the Russia Far North and East regions, related suggestions on attracting migrates are provided.

Jixia Huang

Papers

A Study of the Socioeconomic Factors Influencing Migration in Russia