Growth and Change最新文献

This paper investigates how the expansion of higher education influences regional patterns of regional specialization. Exploiting a natural experiment arising from the large-scale college expansion in China, we apply a triple-difference (DDD) approach to identify the causal impact. Our findings reveal that industries with greater demands for human capital tend to account for a larger output share in cities that experienced more significant college expansion. This effect is primarily driven by the growth of existing firms, rather than the entry or exit of firms. Sub-group analyses further indicate that firms with educated and skilled workforces, and those investing in staff training and R&D, were more affected. Strong evidence highlights labor productivity improvements and R&D-driven TFP gains as key mechanisms, with no support for the technology adoption channel.

This study investigates whether the inflow of highly educated migrants increases the wages of highly educated locals, a question that has been a subject of controversy in the migration literature. Focusing on South Korea, which has undergone one of the world's most rapid increases in its highly educated workforce, the findings reveal that regional economic diversity plays a positive moderating role in the relationship between the inflow of highly educated migrants and the wages of highly educated locals. Furthermore, by employing conditional process analysis and structural equation modeling (SEM), this study demonstrates that this moderation occurs as regional economic diversity enhances the indirect market-side impact of highly educated in-migrants on the wages of highly educated locals through an increase in their employment.

Urban–rural wage disparities are a pervasive phenomenon observed across various countries and regions. This paper examines the impact of takeaway delivery on wage levels, with a particular focus on laborers from distinct urban and rural backgrounds. By integrating data from the Chinese Household Income Project (CHIP) and takeaway delivery agencies, this study conducts sub-sample regression analyses to explore wage differences attributable to residential location and household registration status. The findings reveal that among the four groups categorized by urban–rural status, only individuals with rural household registration but residing in urban areas experience a statistically significant and positive wage impact. This result remains robust across multiple robustness checks. The urban–rural wage sorting effects are analyzed from two perspectives: First, as a physically demanding form of employment, the development of takeaway delivery contributes to wage increments for rural-registered laborers. Second, the disparity in access to takeaway delivery related resource between urban and rural areas allows urban residents to benefit more significantly from wage increases. This paper underscores the critical role of government policies in leveraging the development of takeaway delivery to explore rural advantages and address the persistent issue of unbalanced urban–rural development.

The global COVID-19 pandemic dramatically altered virtually all aspects of social and political life. In particular, stay-at-home orders and social distancing mandates reduced the desirability of densely populated urban centers and sparked urban out-migration. Migration responses to such exogenous shocks, however, vary across socioeconomically differentiated communities and are shaped by established migration channels. This paper builds a case study of out-migration from New York City drawing on home locations recorded for individual mobile devices to examine two research questions. (1) How do out-migration patterns from New York City during the COVID-19 pandemic vary between class-differentiated neighborhoods? (2) To what extent do previously established migration routes shape migration patterns during the pandemic? The results demonstrate that those leaving affluent neighborhoods moved further distances and were more likely to be directed toward high amenity recreation destinations. In addition, the analysis reveals that past migration behavior greatly increases the likelihood of outmigration during the pandemic, and those leaving affluent origins followed previously established outmigration pathways. In contrast, those leaving low-income neighborhoods are more likely to return to origins with established histories of sending migrants to New York City. Combined, these results demonstrate the ways class context shaped migration responses to the COVID-19 pandemic and how past migration behavior at both individual and aggregate scales influences both the likelihood of moving and choice of destination.

Against the backdrop of global climate change and industrial restructuring, the ice-snow economy, as a dual-driven industry characterized by “resource-consumption,” is emerging as a crucial engine for regional development in China. Based on panel data from 15 national-level urban agglomerations in China between 2012 and 2021, this study employs a three-dimensional analytical framework encompassing the dimensions of resources, consumption, and policy to empirically examine the impact mechanisms of the ice-snow economy on urban network evolution, the moderating role of policy coordination, and the contribution of network structure to regional economic growth. The findings reveal that the ice-snow economy facilitates the formation of both localized and globalized networks through dual mechanisms of “resource-dependent agglomeration” and “consumption-driven diffusion,” with the magnitude of these effects differing across different types of urban agglomerations. Policy coordination significantly enhances the network externalities of the ice-snow economy, promoting localized networks in cold-region urban agglomerations and globalized networks in non-cold-region urban agglomerations. While localized networks contribute more to current regional economic growth, globalized networks exhibit increasing growth potential as infrastructure improves and policy coordination deepens. This study provides theoretical foundations and practical insights for understanding urban network evolution and regional policy design in resource-based characteristic industries in China.

Urban growth is a dynamic phenomenon influenced and shaped by a multitude of diverse, interconnected factors. Although identifying the most significant driving factors is a prerequisite for forecasting future urban growth, the selection of factors in numerous current studies is subjective. This study conducted a systematic review of the existing literature within the field, utilizing a qualitative content analysis to identify the factors influencing urban growth along with their pertinent indicators. Then, the potential connections among the factors derived from the articles were analyzed using CytoScape. Ultimately, the 51 identified factors were categorized into nine categories, including: accessibility, demographic, economic, environmental, institutional and planning, physical, proximity, social, and topographic factors. This study's primary contribution is a comprehensive, evidence-based typology of urban growth drivers, which can serve as an authoritative reference for researchers and planners.

Optimizing resources allocation at both time and space dimensions, green growth driven by industrial relocation can effectively prevent pollution leakage. Based on a rich Chinese province-industrial panel data during 2008–2022, this article employs a spatial Durbin model to capture the non-linear effects of industrial relocation on environmental pollution and green growth. After a set of robustness tests, results confirm significant spatial spillover effects, the environmental effect of industrial relocation shows a significant U-shaped curve, but the economic effect is an inverted U-shaped curve. Industrial relocation regions indeed achieve de-pollution and move toward high-end production, and the overall pollution leakage is attributed to the relocation of resource-intensive industries. The spatial boundary tests show that pollution leakage can spread over a geographical distance of 1250 km, while the green growth has only radiated to regions with similar economic strength. Besides, investment structure, technological improvement and employment creation are significant transmission pathways, and green growth is main induced by employment creation effect. This article provides important policy implications for orderly industrial relocation and green development.

Migrant entrepreneurship is a vital engine of urban innovation and economic growth, yet its potential is often constrained by institutional barriers. This study investigates the foundational role of inclusive urban public services—closely linked to migrants' rights to survival and development—in supporting migrant entrepreneurial activity. Drawing on recent reforms in China aimed at equalizing urban public services, we find that greater inclusivity in urban public service provision significantly promotes migrant entrepreneurship. Mechanism analyses identify three pathways: inclusive urban public services (i) generate psychological incentives that strengthen migrants' sense of belonging in cities, (ii) encourage migrant households to allocate labor and financial resources to urban areas, and (iii) expand migrants' access to bilateral social networks rich in market opportunities, all of which foster entrepreneurial action. Heterogeneity analyses further show that improvements in urban public service inclusivity not only raise the quality of migrant entrepreneurship but also exert stronger effects in central regions, where fiscal capacity and economic development are more balanced than in eastern or western regions. These findings underscore the substantial economic returns of integrating migrants into formal governance systems and provide broader insights into unlocking migrant entrepreneurial potential in developing countries.

The Low-Carbon City Pilot Policy (LCCPP) represents a key institutional initiative in China to reduce carbon emissions and promote green development, serving as a foundation for achieving green technological innovation (GTI). Existing studies have primarily focused on the low-carbon performance and mechanisms of pilot cities themselves, while overlooking the spillover effects of the policy on in neighboring cities. This study employs a difference-in-differences method to examine the green spillover effects of the LCCPP, focusing on neighboring non-pilot cities of pilot areas. The study finds that the LCCPP significantly improves GTI in neighboring non-pilot cities, primarily through competitive pressure, imitation learning, and financial transmission effects. Heterogeneity analysis reveals that the green spillover effects of the LCCPP are more pronounced when neighboring cities are located in the eastern and central regions, have well-developed infrastructure, and exhibit strong green governance capacity. Further analysis shows that the spillover effects of the LCCPP are closely linked to the strength of economic ties between cities. Moreover, the spillover effects exhibit a significant distance decay pattern, with the effective spillover range limited to within 200 km. Our findings offer valuable insights for promoting GTI and accelerating the construction of low-carbon cities.