Growth and Change最新文献

China exhibits notable regional disparities, with inland cities generally trailing behind their coastal counterparts—a gap strongly linked to their distance to core ports. Drawing on data from 284 prefecture-level and higher cities, this study provides evidence that the digital economy significantly alleviates the geographical disadvantage faced by inland cities remote from core ports. Inland cities boasting a robust digital economy have narrowed the per capita GDP gap with coastal cities. Mechanistically, the digital economy weakens the correlation between trade costs and geographical distance, expands the import-export volumes of inland cities, attracts more foreign direct investment, and enables them to reap the benefits of agglomeration effects. This research provides a novel perspective for coordinating regional development in the digital era.

This article analyses regional economic resilience from different perspectives and examines its relationship with regional dynamics and disparities. The labor markets of the regions of Brazil, Chile and Colombia were analyzed in the context of one of the most significant global recessionary shocks for South America, the Asian crisis. The study uses cycle dating methodology and a dynamic algorithm for the endogenous identification of structural breaks. The least resilient regions, according to different approaches, were concentrated in Chile and Colombia. These regions experienced prolonged recovery phases, which in some cases led to structural breaks and amplified regional disparities.

This study analyzes two decades of land use changes in Cache County, Utah, focusing on the shift from agricultural land to urban areas using publicly available National Land Cover database, demographic and parcel datasets. Through GIS-based change detection, raster image analysis and integration of population and employment statistics, we reveal varying urbanization insights across selected municipalities. We introduced a development index, combining land transition, population growth and employment prospects, to assess the desirability of cities. Results highlight that housing demand from population increase does not hold a direct linear relationship to farmland conversion and supports urban densification. Smithfield was identified as the regional development hotspot in Cache County. The study highlights the need for proactive land use planning to balance growth with farmland preservation and demonstrates a replicable GIS-based approach for monitoring urbanization. Our findings offer valuable insights for regional urban planners and policymakers aiming for sustainable growth and informed land use decisions.

The study aims to forecast future urban growth and comprehend potential risks, with a particular focus on the dynamic nature of urban growth in medium-sized cities. By identifying factors affecting growth in urban areas, the SLEUTH model was utilized to analyze patterns of urban growth and associated changes in land use. Four scenarios were developed to anticipate urban development in Osmaniye, a medium-sized Turkish city, using the SLEUTH model for the year 2039. Scenarios S.1 and S.4 focus on the impacts of public investment on urban growth, while S.2 and S.3 examine the effects of urbanization on rural areas. Scenario S.3 also explores diverting urban development from high-risk seismic zones. S.1 poses the highest risk to agriculture (51% urbanization), while S.3 is the least threatening (37%). For forests, S.2 presents the highest risk (31%), but S.3 is the safest (25%). Overall, Scenario 3 provides the most effective approach for urbanization strategy, particularly for rural areas, protecting them from urbanization pressures and preserving geologically hazardous locations in Osmaniye. The study highlights how the SLEUTH model demonstrates the interaction between urban growth and spatial limitations, emphasizing the importance of understanding the consequences of urban growth for implementing effective zoning regulations.

As artificial intelligence (AI) becomes increasingly integrated into economic and societal domains, it emerges as a pivotal force driving the shift toward low-carbon energy systems. This study examines how AI impacts the transformation of urban energy systems by utilizing a panel dataset comprising 278 Chinese spanning the years 2010–2019. The findings confirm that AI significantly enhances energy transition performance in urban settings. By precisely optimizing the integration and consumption of renewable energy, driving the energy efficiency revolution, and breaking the dependence on high-carbon energy development models, as well as enhancing grid resilience and ensuring energy supply security to overcome the vulnerabilities of the energy transition, AI also strengthens the innovation capacity of energy transition through accelerating technological breakthroughs and incubating new business models. Heterogeneity analysis reveals that AI better facilitates energy transition in those cities that are small and medium in size, cities with a solid industrial base, cities with a high level of economic clustering, and cities located in central and eastern China. Mechanism tests show that during AI-enabled transition processes, green technology innovation, human–machine compatibility, and energy efficiency play significant roles. Further analysis using a threshold model reveals that as electronic commerce, human capital, and business growth increase, AI's marginal effects on energy transition exhibit an incremental trend. This implies that improving digital infrastructure, raising human capital levels, and boosting economic growth are pathways to realizing the transformative effects of AI. This study assesses AI technology's effectiveness in promoting energy sustainability and high-quality development goals.

Despite the integration of China’s manufacturing industry with Information and Communication Technology (ICT) continuing to deepen, total factor productivity (TFP) of the manufacturing industry has not increased significantly as expected. Based on panel data from 28 manufacturing sub-sectors from 2002 to 2020, this study investigates whether the Solow productivity paradox exists. Considering that both the decline of factor expansion constraints and the rise of TFP can promote output growth, this study further discusses the role of factor expansion constraints in shaping the relationship between ICT and TFP. Empirical results indicate that the Solow paradox persists in manufacturing, particularly in sub-sectors heavily dependent on factor inputs. Moreover, the threshold model reveals that only when factor expansion constraints exceed the threshold, the promotion effect of ICT on TFP appears. Further research indicates that ICT can alleviate factor expansion constraints, but this effect has a crowding out effect on its role in improving TFP. This study emphasizes that the impact of ICT on TFP depends not only on external conditions, but also on the application direction of ICT, which provides theoretical support for formulating industrial policies that leverage ICT to enhance TFP.

To examine whether economic resources in neighboring municipalities affect policy innovation adoption, this study investigated work resumption and production policies implemented by 290 Chinese municipalities. Word Mover's Distance was employed to measure policy innovation adoption, and spatial econometric models were used to analyze spatial spillover effects. The results reveal distinct spillover effects across different regional contexts. Specifically, we found negative spillovers from policy innovation adoption in eastern regions but positive spillovers in non-eastern region. Additionally, in eastern areas there are spatial negative spillovers from foreign direct investment (FDI) on policy innovations and positive spillovers from economic development. Furthermore, in non-eastern regions, fiscal decentralization has spatially positive spillovers on policy innovation, but FDI and economic development have negative spillovers. These findings suggest that regionally tailored strategies are essential to address asymmetric spillover effects and promote more balanced and effective policy innovation across different development contexts.

Finance is a critical factor in all stages of the food enterprise, from production to distribution, procurement, and consumption. Yet, in many developing countries, weak financial sector development and the prevalence of unregulated self-employed economic activities pose a significant challenge to food security. This study examines the extent to which the financial sector development and informality influence food security in Sub-Saharan Africa (SSA). We develop a conceptual framework linking financial sector development to food production and test it empirically, controlling for the role of informality. The findings show that the effect of financial development on food production in SSA is inconclusive and sensitive to the measures employed. In terms of informality, total, female, and male self-employment are generally found to hinder food security, although the magnitude and direction of these effects differ across income and regional groupings. Importantly, the interaction between financial sector indicators and informality measures suggests that access to finance enhances the potential of the informal sector to contribute positively to food production. These findings suggest that developing countries should prioritize both the regulation of the informal sector and the strengthening of financial sector institutions to expand access to finance. Their combined effects hold the potential to improve food production and, ultimately, food security in SSA.