As one of the most vulnerable sectors exposed to the COVID-19 pandemic, transport sectors have been severely affected. However, the shocks and impact mechanisms of infectious diseases on transport sectors are not fully understood. This paper employs a multi-sectoral computable general equilibrium model of China, CHINAGEM, with highly disaggregated transport sectors to examine the impacts of the COVID-19 pandemic on China’s transport sectors and reveal the impact mechanisms of the pandemic shocks with the decomposition analysis approach. This study suggests that, first, multiple shocks of the COVID-19 pandemic to transport sectors are specified, including the supply-side shocks that raised the protective cost and reduced the production efficiency of transport sectors, and the demand-side shocks that reduced the demand of households and production sectors for transportation. Second, the outputs of all transport sectors in China have been severely affected by the COVID-19 pandemic, and passenger transport sectors have larger output decreases than freight transport sectors. While the outputs of freight transport sectors are expected to decline by 1.03–2.85%, the outputs of passenger transport sectors would decline by 3.08–11.44%. Third, with the decomposition analysis, the impacts of various exogenous shocks are quite different, while the changes in the output of different transport sectors are dominated by different exogenous shocks. Lastly, while the supply-side shocks of the pandemic would drive output decline in railway, waterway, and aviation transport sectors, the demand-side shocks would drive so in the road, pipeline, and other transport sectors. Moreover, the COVID-19 pandemic has negative impacts on the output of most non-transport sectors and the macro-economy in China. Three policy implications are recommended to mitigate the damages caused by the COVID-19 pandemic to the transport sectors.

ObjectiveLiving arrangements are important to the elderly. However, it is common for elderly parents in urban China to not have a living situation that they consider ideal. An understanding of their preferences assists us in responding to the needs of the elderly as well as in anticipating future long-term care demands. The aim of this study is to provide a clear understanding of preferences for future living arrangements and their associated factors among middle-aged and older people in urban China.MethodsData were extracted from the CHARLS 2011–2012 national baseline survey of middle-aged and elderly people. In the 2011 wave of the CHARLS, a total of 17,708 individual participants (10,069 main respondents and 7,638 spouses) were interviewed; 2509 of the main respondents lived in urban areas. In this group, 41 people who were younger than 45 years old and 162 who had missing data in the variable “living arrangement preference” were excluded. Additionally, 42 people were excluded because they chose “other” for the variable “living arrangement preference” (which was a choice with no specific answer). Finally, a total of 2264 participants were included in our study.ResultsThe most popular preference for future living arrangements was living close to their children in the same community/neighborhoods, followed by living with adult children. The degree of community handicapped access, number of surviving children, age, marital status, access to community-based elderly care centers and number of years lived in the same community were significantly associated with the preferences for future living arrangements among the respondents.ConclusionThere is a trend towards preference for living near adult children in urban China. Additionally, age has a positive effect on preference for living close to their children. Considerations should be made in housing design and urban community development plans to fulfill older adults’ expectations. In addition, increasing the accessibility of public facilities in the residential area was important to the elderly, especially for those who preferred living in proximity to their children rather than co-residing with their children. We found that more surviving children were associated with a lower likelihood of choosing “institutionalization”, and it positively contributed to preference for intergenerational living arrangements in our study. As expected, compared with their married counterparts, people who were separated/divorced/widowed preferred living with adult children rather than living independently. A relatively shorter length of residence in the same community was an important indicator of preference for independent living; this finding might require further research.

China has initiated various dedicated policies on clean energy substitution for polluting fossil-fuels since the early 2010s to alleviate severe carbon emissions and environmental pollution and accelerate clean energy transformation. Using the autoregressive integrated moving average (ARIMA) regression, we project the potentials of substituting coal and oil with clean energy for different production sectors in China toward the year 2030. Based on the projections, a dynamic multi-sectoral computable general equilibrium model, CHINAGEM, is employed to examine: the impacts of future clean energy substitution on China’s energy production, outputs of non-energy sectors, macro-economy, and CO2 emissions. First, we found that most production sectors are projected to replace polluting fossil-fuels with clean energy in their terminal energy consumption in 2017–2030. Second, clean energy substitution enables producing green co-benefits that would enable improvements in energy production structure, reductions in national CO2 emissions, and better real GDP and employment. Third, technological progress in non-fossil-fuel electricity could further benefit China’s clean and low-carbon energy transformation, accelerating the reduction in CO2 emissions and clean energy substitution. Furthermore, the most beneficiary are energy-intensive and high carbon-emission sectors owing to the drop in coal and oil prices, while the most negatively affected are the downstream sectors of electricity. Through research, various tentative improvement policies are recommended, including financial support, renewable electricity development, clean energy utilization technology, and clean coal technologies.

No abstract

No abstract