Growth and Change最新文献

The manufacturing industry (MI) in China has long been constrained by low-end lock-in. Digital infrastructure, as a solid foundation of the digital economy, has played an increasingly crucial role in economic growth as the digital transformation of global society accelerates. This raises an important question: Can the rapid development of digital infrastructure promote the upgrading of manufacturing enterprises (UME)? To investigate this, we selected manufacturing enterprises listed on the Shanghai and Shenzhen stock exchanges from 2004 to 2020 to empirically analyze the impact and mechanisms of digital infrastructure on UME. We find that digital infrastructure indeed significantly promotes enterprise upgrading. A heterogeneity analysis further reveals that this influence is more pronounced fro small-scale and low-tech manufacturing enterprises relative to large-scale or high-tech enterprises, and that it digital infrastructure contributes more to UME in underdeveloped rather than developed regions. Our mechanism analysis indicates that digital infrastructure supports UME by enhancing resource allocation efficiency and fostering technological innovation. These findings may have significant implications for developing countries, pointing toward a necessity for strengthening digital infrastructure and deepening its integration with the manufacturing sector. In particular, underdeveloped regions and small-scale, low-tech manufacturing enterprises should prioritize using digital infrastructure to advance the modernization of traditional manufacturing operations.

Africa's sustainable development is challenged by rapid urbanization and persistent food insecurity. It is critically important to understand how digital innovation can be used to shape the relationship between urbanization and food security. This study investigates the asymmetric impact of urbanization on food security in Africa, emphasizing the moderating role of Information and Communication Technology (ICT). Using a panel quantile Autoregressive Distributed Lag with a Pooled Mean Group (PQARDL-PMG) approach on data from 41 African countries (1990–2023), we examine how urbanization and ICT jointly influence the four dimensions of food security across varying contexts. Results reveal that increases in urbanization positively affect food availability and accessibility, while declines in urbanization significantly weaken utilization and stability. ICT improves food security outcomes, but its interaction with urbanization reveals asymmetric effects. Rising urbanization combined with ICT shows negative effects on food availability at higher quantiles, while ICT mitigates the adverse impacts of urban decline by improving availability, accessibility, and stability. Policy implications call for reorienting urban strategies to prioritize food systems, including protecting peri-urban farmland and strengthening rural-urban linkages through digitally enabled infrastructure.

This paper analyzes the long-term rise of labor market detachment within the United States. We construct a measure of the detachment rate that identifies prime-age men and women who have been out of the labor force for more than a year. Detachment has risen for men in most local labor markets since 1980, and for women since around 2000, with more than a third of the prime-age population detached in some parts of the country. We show there has been a widening in the spatial distribution of detachment and a corresponding increase in its geographic concentration. Empirical results indicate that detachment rose more in places with weak local economies, particularly those that experienced a loss of routine production and administrative support jobs due to globalization and technological change, and that frictions in local labor market adjustment contributed to its uneven rise. Moreover, the rise in detachment has been concentrated among older prime-age individuals and those without a college degree, and, consistent with regional reinvention, occurred less in places with high human capital. These findings point to an important role for place-based economic development policy in distressed regions with persistently high detachment.

This study examines the impact of Saudi Vision 2030 on urban mobility changes in Riyadh, focusing on how the national policies have spurred sustainable transportation reforms in a city traditionally reliant on cars. As the capital and economic center of Saudi Arabia, Riyadh has experienced rapid population growth and urban sprawl, resulting in severe traffic congestion, high energy consumption, and limited mobility options. Launched in 2016, Vision 2030 is a national development plan that emphasizes sustainable urban transportation as essential for achieving environmental, economic, and social goals. Using a qualitative approach, the research combines analysis of policy documents with secondary data on infrastructure and performance. It evaluates the progress and initial results of key projects such as the Riyadh Metro, Riyadh Bus Network, and related smart mobility initiatives. The findings demonstrate that these infrastructure efforts have significantly increased public transportation capacity and coverage. Early indications suggest a slight shift away from private cars, with expected reductions in fuel consumption and CO₂ emissions. The study also highlights ongoing challenges such as behavioral resistance, lack of sufficient active transportation infrastructure, spatial inequalities in transit access, and gaps in institutional coordination. Ridesharing services and smart mobility platforms are emerging as helpful additions, but require better integration into the formal transportation network. Overall, the research finds that while Vision 2030 has built a strong foundation for a sustainable mobility shift, long-term success will rely on multimodal integration, inclusive planning, and increased public participation. Riyadh's experience offers valuable lessons for other cities in the Global South working toward government-led sustainable urban transformation.

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.