Growth and Change最新文献

Existing research on the impact of labor mobility on the welfare of urban native labor has inconsistent findings due to differences in the objective measures of welfare and the relatively homogeneous scale of migration within the samples. We focus on subjective well-being (SWB) as a comprehensive measure of welfare and select China, characterized by significant disparities in labor mobility across cities, as the sample for a study grounded in externality theory. Empirical results derived from microdata of the 2016 China Labor—force Dynamics Survey and corresponding annual city data show that: (1) The relationship between labor force inflow and the SWB of urban native labor in the host city is significantly a U-shaped curve. When the inflow of labor reaches 0.44 times the size of the urban native labor, the SWB of the latter will reach its lowest point. (2) The labor force outflow has no significant effect on the SWB of urban native labor who stayed behind in the origin city. (3) Costs of living, employment opportunities, and working hours play a mediating role in the relationship between labor inflow and the SWB of urban native labor in the host city.

Migrant workers have historically followed a short-term migration pattern similar to that of migratory birds, which hinders their full integration into urban life, both behaviorally and emotionally. Strengthening migrant workers' settlement intentions through social networks is considered the most optimal solution to addressing the social issues arising from large-scale urban-rural circulation. Contrasting with research that evaluates internal migration issues from a macroeconomic policy perspective, this paper examines the role of individual migrant workers' social networks in shaping their settlement intentions within the framework of informal institutions. Utilizing a large dataset from the China Migrants Dynamic Survey (CMDS), we find that migrant workers with extensive social networks are more likely to settle permanently in cities compared to those with fewer social networks. Importantly, we identify social inclusion and participation in public affairs as key mechanisms through which social networks influence migrant workers' settlement intentions. The heterogeneity analysis reveals that social networks play a particularly significant role in increasing the settlement intentions of first-generation migrants, well-educated migrants, married migrants, and family-based migrants. We subject these results to a series of endogeneity tests and robustness checks, and find that our main conclusion remains consistent and reliable.

This study employs geospatial analysis and social network analysis to reveal the geographical and relational dimensions of complementary technological cooperation among Chinese cities. Furthermore, using a panel negative binomial regression model, we examine the impact of complementary technological cooperation on urban innovation capacity, and compare it with the effects of non-complementary cooperation. Our findings reveal that: (1) The geographical structure of the complementary technological cooperation network has evolved from a “triangular” configuration—centered on Beijing, Shanghai, and Shenzhen—toward a “rhombus-shaped” structure incorporating Chengdu, with a further tendency toward a “hexagonal” spatial pattern. (2) The social structure of the complementary technological cooperation network exhibits a classic “core–periphery” pattern, with the network's core gradually shifting from a dual-core configuration dominated by Beijing and Shanghai to a single-core, multi-centered structure centered on Beijing. (3) Complementary technological collaboration significantly enhances urban innovation capacity and proves more effective than non-complementary cooperation. This advantage stems from the fact that complementary cooperation not only directly improves innovation output capability but also strengthens the technological relatedness density within cities that non-complementary linkages cannot match.

This study examines how institutional innovation programs foster the transition of small businesses in Sub-Saharan Africa from survival to scalable entrepreneurial ventures. Using a mixed-methods framework and 720 region-years of data (2010–2024), we evaluate both direct program impacts and broader ecosystem spillovers through difference-in-differences models, spatial lag analysis, and instrumental variable techniques. Robustness was assessed with placebo tests, entropy balancing, and threshold analysis. The results show that the Boost Africa initiative increased crowdfunding activity by 42.8%, with 36% of the effects spilling over into neighboring regions. Impacts peaked in the third year and were significantly enhanced by mobile money penetration. Sectoral analysis indicates that fintech interventions delivered the highest returns, while equity investments consistently outperformed grants. Methodologically, the study integrates formal (crowdfunding) and informal (mobile money) sector metrics, applies historical missionary settlements as instruments, and quantifies spatial spillovers—offering a novel framework for assessing ecosystem-wide effects. The findings highlight how blended finance, when paired with digital inclusion, can catalyze systemic entrepreneurial growth, providing actionable guidance for optimizing intervention design and timing in emerging economies.

With the swift pace of urbanization and industrialization, air pollution has emerged as a critical issue, severely impacting public health and impeding the progress toward sustainable development. This study delves into the nexus between Financial Inclusion (FI) and Air Pollution Reduction (APR), employing a balanced panel dataset that encompasses 255 Chinese prefecture-level cities from 2011 to 2022. Through the application of econometric models and a series of robustness tests, we uncover an inverse U-shaped dynamic between the advancement of FI and APR. Our findings indicate that during the nascent stages of FI, there is a positive impact on APR. However, this beneficial effect plateaus and potentially reverses when FI progresses beyond an optimal threshold. Further analysis elucidates three primary economic channels through which FI may influence APR: alleviation of energy poverty, stimulation of innovation, and household consumption. Notably, these mechanisms exhibit distinct patterns of influence across cities with varying levels of economic development and geographical locations. The findings hold significant implications for policy-making, suggesting that the Chinese government must balance the acceleration of FI with a keen awareness of its regional impacts. Tailored environmental policies and innovative financial instruments can foster green growth and sustainable development.

The impact of local and global networks on innovation has been extensively studied. However, existing literature has not explored whether these effects result from territories gradually improving their networks, or competing with each other through their networks. This paper aims to address this gap by examining innovation networks in Latin American cities. Using patent data from the USPTO, we construct local networks connecting actors within cities and a global network linking different cities in different countries. We estimate the effects of networks on innovation using panel data regressions. To discern whether these effects result from cities' improvements or competition, the models follow the within-between approach. Our findings indicate that cities benefit from improvements in their local network, regardless of whether this network is worse or better than that of other territories. This is not the case in the global network, where cities compete with each other by gaining better access to resources flowing through the network. These findings hold important research and policy implications, especially for developing countries where relative backwardness, weak local networks, and limited participation in global networks may hinder territories' ability to compete with more developed counterparts.

As suburbanization accelerates globally, large-scale developments—such as new towns and redevelopment zones—are increasingly used by policymakers to alleviate urban congestion and promote spatially balanced growth. While theoretically offering superior infrastructure and living environments, such projects are complex, capital-intensive, and exposed to political and market uncertainties that can lead to misalignment between planning goals and outcomes. This study offers the first empirical analysis of population migration dynamics within the context of a large-scale new town development project. Focusing on Taiwan's National Taipei University Special District (NTPUSD), this study examines inter-district migration patterns using administrative data, with particular attention to the role of housing prices, commute times, and infrastructure access. The findings show that lower housing prices—especially when combined with shorter commutes—are significant drivers of migration. High-income households are more sensitive to price differences, while middle-income households move from moderately priced areas to upgrade housing. The price effect is minimal in low-income districts. Migration patterns also evolved over time: early migrants were predominantly young households seeking affordability, whereas later waves were influenced more by improved amenities and transport. These results offer important insights for urban planners and policymakers managing suburban growth and integration.

The high-speed railway (HSR) in China has brought tremendous economic development for cities across the country. Utilizing a dataset of over 3.9 million authorized innovated patents from 324 cities between 2000 and 2022, this study investigates the impacts of HSR on technological diversity and complexity. Employing a staggered difference-in-difference (DID), Propensity Score Matching (PSM) model and instrumental variable (IV) model, the analysis reveals that the introduction of HSR enables cities to diversify into new, less related, and more complex technological domains, thereby enhancing both the complexity and diversity of a city's knowledge base. However, our heterogeneity analysis suggests that HSR fosters breakthrough advancements and the adoption of more complex technologies in developed cities, but it mainly facilitates access to more related but less complex technologies in underdeveloped cities. This study underscores HSR as a crucial strategic tool for promoting technology diversification and knowledge complexity, while also highlighting the potential of HSR for exacerbating knowledge inequality among cities. The findings deepen our understanding of how regional inequality might be shaped as by technological evolution and transportation development.