It is of great theoretical and practical significance to investigate the influence of intelligent city construction on urban innovation. Based on the data of 238 cities in China from 2006 to 2019, this paper utilizes the staggered difference-in-differences (staggered DID) model and the mediating effect model to examine the impact and mechanisms of smart city construction on urban innovation. We find that China’s smart city pilot policies significantly promote urban innovation. Mechanism analysis shows that this innovation promotion effect acts through improving urban informatization, government financial expenditure on science and technology, and the upgrading of the city’s industrial structure. Further analysis shows that smart city construction has a stronger promoting effect on innovation in cities of a larger scale, that located in the eastern region, and have a lower level of science and education. Overall, our findings provide new insights into urban innovation and objectively assess the impact of smart city construction in China.

With the development of China’s economy and the deepening of urbanization, the number of migrants whose parents have migrant work experience continues to rise. However, what is the long-term impact of parental migrant work experience on migrant children? Existing literature has not yet adequately answered. Based on the data from the China Migrants Dynamic Survey in 2016–2017, this article uses a multiple linear regression model to examine the impact of parental migrant work experience on the income of rural-urban migrants and its impact mechanism and heterogeneity empirically. We find that parental migrant work experience has a positive impact on the monthly income of second-generation rural-urban migrants. Specifically, compared with those whose parents had no such experience, the average monthly income of those whose parents had such experience increased significantly by 3.08% (approximately 124 yuan), and this effect was more apparent when fathers had migrant work experience. The main influencing channel comes from the significant increase in the probability of rural-urban migrants choosing self-employment. The results of the heterogeneity analysis showed that this effect was more significant in the sample of males and those with high school education and below. After a series of robustness tests, these conclusions remain valid. This work enriches the corresponding research literature and provides empirical evidence for studying the long-term effects of parents’ early experiences on their children.

This study leverages panel data from the China Family Panel Studies (CFPS) to uncover a robust relationship between housing wealth and mental health among children aged 10–15. Using instrumental variable approach, we find that a 1% increase in housing wealth causes a 7.1% improvement in children’s mental health status across various dimensions like anxiety and self-esteem. Heterogeneity analysis shows that the positive impact of housing wealth on children’s mental health is more pronounced in households owning larger and higher-value homes. We identify financial stress relief, reduced housing crowding, better parental mental health, and enhanced social skills as key mechanisms driving the housing wealth-child mental health link. Our study provides novel empirical evidence that housing markets shape children’s non-cognitive development beyond just consumption. These results highlight that stable housing conditions and home values can reduce inequalities by cultivating socio-emotional skills vital for child well-being.

This study leverages longitudinal data from the China Family Panel Studies (CFPS, 2012–2020) to examine the association between teacher support and cognitive ability among children aged 10–16 living in economically disadvantaged rural areas of China. Employing a difference-in-differences (DID) framework, we found that exposure to the Rural Teacher Support Program (RTSP) is associated with an improvement of about 0.19 standard deviations in students’ cognitive abilities after accounting for individual-, family-, and county-level characteristics. Two key mechanisms appear to underlie this association, reflected in increased teacher quantity and enhanced student satisfaction with teachers. Heterogeneity analyses further show that these benefits are more pronounced among female students and those from low-income households, suggesting that teacher-centered institutional improvements may help mitigate developmental disparities. Overall, the longitudinal results indicate that better teacher-related environments are likely to support children’s cognitive development, which in turn may help reduce educational inequality in under-resourced areas.