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The vector information of mountainous roads is great significance, including regional economics, emergency response, disaster management, among others. Nevertheless, there are irregular deformations in existing vector data, coupled with incomplete extraction results for mountainous roadways. These issues pose challenges in establishing a matching model between road extraction results and existing vector data, significantly reducing the efficiency of automated updates for the current vector data. Targeting roads as a distinct artificial feature and leveraging their topological connectivity, we propose a vector data updating method based on matching point pair grouping. Firstly, we employ the SDUNet model to extract mountainous road and utilize the Superglue model to match road binary images with vector binary images, resulting in sets of initial matching point pairs. Subsequently, we propose a road line extraction model that groups matching point pairs, eliminates misaligned pairs based on road topological connectivity, and establishes a mapping relationship between road lines and vector lines. Ultimately, through road line optimization and vector line optimization methods, we accomplish the automatic updating of vector data for mountainous roadways. Through a comprehensive analysis of over 2600 vector data, our method demonstrates substantial advantages in terms of both F1 and IoU compared to alternative methods. [ABSTRACT FROM AUTHOR]

This study aims to determine the occurrence of convergence in inclusive economic growth at both the national and regional levels, as well as the factors that drive the increase in inclusive economic growth to reduce regional disparities. The analysis used is sigma convergence, absolute beta convergence, and conditional beta convergence. The data used is a panel consisting of 21 provinces in the Western Region of Indonesia (KBI), including Sumatra, Java and Kalimantan, 13 provinces in the Eastern Region of Indonesia (KTI), namely Sulawesi, Nusa Tenggara and Bali, Maluku and Papua, as well as national level consisting of 34 provinces in Indonesia from 2017 to 2021. This study shows that at the national level, KBI and KTI, there has been both sigma convergence and absolute beta convergence. Conditional beta convergence only occurs at the national level and KBI. Meanwhile, in KTI, there is no process of conditional beta convergence or what can be called divergence occurring. Variables that significantly affect the convergence process at the national level include government expenditure in the economic, health, and social protection sectors, domestic investment, and the open unemployment rate. At the KBI, significant factors include government expenditure in social protection sectors domestic investment and the unemployment rate. At the KTI, significant factors include government expenditures on the economic, health, and social protection sectors, foreign investment, and the unemployment rate. [ABSTRACT FROM AUTHOR]

We examine the effect of a place-based policy in China, the Northeastern Revitalization Program. In 2003 the State Council of the People's Republic of China initiated the program in northeastern China by removing an agricultural tax, enhancing the urban social security system, facilitating foreign investment, and restructuring state-owned enterprises in the region. Using the synthetic control method, we find that the program had no significant effect on GDP per capita in all three regions. Liaoning had slightly worse GDP per capita post-treatment, as did Heilongjiang (albeit to a lesser extent). While the multiple synthetic control analysis shows that economic outcomes were worse post-treatment, the impact of this program was heterogeneous across the three regions. We argue the lackluster performance likely comes from the continuing dominance of inefficient state-owned enterprises in the provinces. [ABSTRACT FROM AUTHOR]

In the past two decades, Turkey has experienced a noteworthy increase in the establishment of universities and enrollment of students across various degree programs. However, this surge in higher education has been accompanied by a growing number of unemployed higher education graduates. To address this phenomenon, this research conducts a comprehensive analysis of the relationship between different levels of tertiary education, undergraduate, master's, and Ph.D. (Doctorate) and unemployment. The study utilizes TurkStat's regional database, covering data from 26 provinces in Turkey spanning the years 2008 to 2021. Prior to delving into coefficient analysis, the Dumitrescu and Hurlin (2012) panel causality test was applied to identify the direction of potential causality and to establish an accurate model. The findings suggest a potential causal relationship running from being a higher education graduate, at all levels (bachelor's, master's, and PhD ), to unemployment rate. Subsequently, to further scrutinize this relationship in light of causality findings, the Panel Augmented Mean Group estimator (AMG) was employed. The results indicate that a 1% increase in the total number of Bachelor's degree graduates is associated with a 1.16% increase in unemployment rate. Based on these findings, it can be argued that, instead of further investing in higher education, a policy approach targeting middle-skilled jobs through advanced investment in vocational high schools may be more cost-effective. [ABSTRACT FROM AUTHOR]

With the development of the economy, many regions have experienced a slowdown in economic growth. In order to promote the development of the electric vehicle (EV) industry, the country has also begun to introduce various policies to encourage the development of the EV industry. In this context, many local governments have begun to introduce policies and measures related to the development of the EV industry, such as increasing land use for the development of the EV industry and increasing support for the new energy automobile industry. These policy measures have played a positive role in promoting the development of the EV industry, but there are also some problems. For example, when many local governments introduce policies to support the development of the new energy automobile industry, their support for the EV industry is not significant. This article studied the collaborative optimization of the EV industry chain in response to issues such as insufficient technical strength, imbalanced supply-demand relationship, and insufficient downstream service chain capabilities in the EV industry chain. This article analyzed the composition of the EV industry chain and established an EV industry chain model to address these issues. This article used collaborative optimization algorithms to analyze the production volume of EVs in the EV industry chain, as well as the comprehensive efficiency, pure technical efficiency, and scale efficiency values of upstream, midstream, and downstream. Through experimental analysis, it was found that the comprehensive efficiency value of the upstream of the EV industry chain after using the collaborative optimization algorithm was 0.0792 higher than before. The research results of this article have provided reference significance for the analysis of collaborative optimization algorithms in other fields. [ABSTRACT FROM AUTHOR]

A metropolitan area comprises a collection of cities and counties bound by strong socioeconomic ties. Despite the pivotal role that metropolitan areas play in regional economics, their delineation remains a challenging task for researchers and urban planners. Current threshold-based delineation methods select counties based on their connection strength with prespecified core counties. Such an approach often neglects potential interactions among outlying counties and fails to identify polycentric urban structures. The delineation of a metropolitan area is fundamentally a spatial optimization problem, whose objective is to identify a set of counties with high interconnectivity while also meeting specific constraints, such as area, contiguity, and shape. In this study, we present a novel spatial optimization model designed for metropolitan area delineation. This model aims to maximize intercounty connection strength in terms of both industry and daily life. This approach ensures a more accurate representation of the multicore structure that is commonly seen in developed metropolitan areas. Additionally, our model avoids the possibility of holes in metropolitan area delineation, leading to more coherent and logical metropolitan boundaries. We provide a mixed-integer programming formulation for the proposed model. Its efficacy is demonstrated by delineating the boundaries of the Nanjing and Lhasa metropolitan areas. This study also delves into discussions and policy implications pertinent to both of these metropolitan areas. [ABSTRACT FROM AUTHOR]

Though most studies find that sports stadiums are not strong drivers of economic activity in metropolitan areas, localized development effects may be sufficient to justify public subsidies for a host municipality if circumstances are favorable. This analysis examines the economic ramifications of an intra-metropolitan area relocation of Atlanta's professional baseball team from a traditional standalone downtown stadium to a new stadium-anchored mixed-use development in suburban Cobb County. Using the synthetic control method, the study employs metro-Atlanta counties to construct a counterfactual outcome for estimating changes in sales tax revenue after the ballpark opened. The findings indicate a net increase in taxable sales in the county; however, the magnitude of the effect is small and not statistically significant. Though net new spending is evident, approximately one-third of the project's sales appear to derive from crowding out other local economic activity. In total, added tax collections fall well short of covering the public subsidies provided by Cobb. The stadium's limited economic impact, despite its favorable location and ancillary mixed-use development, further supports past findings that sports venues are poor investments as economic development projects. [ABSTRACT FROM AUTHOR]

"Empirical Regional Economics: Economic Base Theory, Models and Applications" is an accessible textbook by Richard Conway that provides an introduction to regional economics for undergraduate and graduate students. The textbook is divided into three parts: theory, application of models, and case studies. It focuses on the Puget Sound region of Washington State, but the lessons learned can be applied to other regions. The book offers a comprehensive overview of regional economic growth, models, and case studies, although it lacks engagement with contemporary issues such as climate change. Overall, it is a valuable resource for educators and researchers in the field of regional science. [Extracted from the article]

Assessing the urban rooftop photovoltaic (PV) economics is important for scaling up rooftop PVs for rapid decarbonization. In this study, socioeconomic, technological, and policy factors were integrated into a rooftop PV economic assessment. This comprehensive method was applied to 21 cities in the Guangdong province of China, in combination with local real parameters. The results show that, with higher urbanization levels, electricity tariffs, and PV self-consumption rates, cities in the Pearl River Delta area generally had better economic performance in terms of both economic scale and profitability. They accounted for 75% of the total rooftop PV potential in Guangdong Province and had an internal rate of return (IRR) as high as 14.6–19.2% for Commercial and Industrial buildings (C&I), and 9.9–15.9% for residential buildings (R). Socioeconomic, technological, and policy factors jointly affect the economic performance and create a promising future for Guangdong rooftop PVs. It is projected that the IRR of current worst performing cities will grow by 4.9–5.8, and 4.4–5.9 percentage points, and the payback period will be shortened by 5.8–6.7 and 3.4–4.1 years by 2030 for R and C&I buildings, respectively. Among the three factors, technological advancement had the most significant long-term effect, followed by socioeconomic development. Policy factors play an important role in alleviating short-term cash flow pressure. Integrating the three factors in the assessment provides us with a more comprehensive picture of how urban rooftop PV economics will evolve and a better idea of how to prioritize rooftop PV development. Suggestions for prioritizing the deployment of rooftop PV systems in Guangdong by 2030 were provided. • Socioeconomic, technological, and policy factors were integrated into the urban rooftop PV economics assessment. • An orderly deployment plan for urban rooftop PVs in the Guangdong province of China is proposed. • The technology factor had the most significant effect on rooftop PV economic trends through capital cost reduction. • Socio-economic development contributes to higher electricity demand and revenue. • Policy factors play an important role in the short term in alleviating the cash flow pressure through preferential loan rate. [ABSTRACT FROM AUTHOR]