Regional Science Research Articles

Beyond Parametric Bounds: Exploring Regional Unemployment Patterns Using Semiparametric Spatial Autoregression

Abstract Background It is a well-known phenomenon that nonlinearities that are inherent in the relationship among economic variables negatively affect the commonly used estimators in the econometric models. The nonlinearities cause an instability of the estimated parameters that, in particular, are unable to capture a local relationship between the response and the covariate. Objectives The main aim of the paper is the simultaneous consideration of spatial effects as well as nonlinearities through an advanced semiparametric spatial autoregressive econometric model. The paper seeks to contribute to empirical studies of regional science focused on the application of semiparametric spatial autoregressive econometric models. Methods/Approach We outline an approach that can be used to correct nonlinearities by incorporating a semiparametric idea within the framework of econometric models. We use an expansion by penalised basis splines that are highly flexible and are able to capture local nonlinearities between variables. Results In the empirical study, we fit different econometric models that attempt to explain the dynamics of the European Union's regional unemployment. Conclusions The results show that regional unemployment exhibits significant spatial dependence, indicating interconnectedness among neighbouring regions and suggesting the adoption of a semiparametric spatial autoregressive model for improved modelling flexibility, surpassing traditional parametric approaches.

ҚАЗАҚСТАН РЕСПУБЛИКАСЫНЫҢ УРБАНИЗАЦИЯ ПРОЦЕСІНІҢ ЖӘНЕ УРБАНИЗАЦИЯЛАНҒАН АУМАҚТАРДЫҢ ИННОВАЦИЯЛЫҚ ДАМУЫНЫҢ ӨЗАРА ТӘУЕЛДІЛІГІН ТАЛДАУ

The article examines the relevance of the management of innovative development of cities and urban agglomerations, as evidenced by the widespread adoption in this area of both international strategic documents and at the national level. To achieve the goal of the strategy "Kazakhstan-2050" to enter the country into the top 30 economically most developed countries of the world by 2050, it is necessary to diversify the country's economy, one of the factors of which is the spatial development of the country, where urbanized territories play a key role. The issues of sustainable urban development and achieving a high level of urbanization are included in the strategic policy documents and plans of the Government of the country. Thus, these priorities are reflected in the Strategic Development Plan of Kazakhstan until 2025, where the main focus of the reform "Strong Regions and Urbanization" is aimed at the development of medium and small cities, the implementation of Smart City projects, the digitalization of urban infrastructure and an increase in the proportion of urban residents to 60% by 2025. This article examines the fundamental works of world regional science, classical and neoclassical urban concepts. During the dissertation work, monographs, scientific papers, and research by domestic and foreign scientists on the specifics of urbanization processes, the impact of urbanization on the socio-economic development of the country, urbanization policy, and improving the management processes of innovative development of cities and urban agglomerations were studied. The achievement of this goal has determined the need to systematize theoretical approaches to determining the essential characteristics of the urbanization process, to reveal the content of the concept of "urbanized territories"; to explore theoretical concepts of patterns and principles of the formation of cities and the urban environment; The practical significance of the study is to develop practical recommendations for the management of innovative development of urbanized territories in Kazakhstan. The results of the study will analyze the problems of the urbanization process in Kazakhstan, identify and analyze the situation concerning the ratio of urbanization and innovative development, develop a mechanism for managing the innovative development of urbanized territories, focused on using the innovative potential of cities and urban agglomerations in areas that provide the greatest return;

Effects of Game-Based Learning on Improving Grammar Skills of Grade 9 Students

As the educational system transcends to 21st-century learning, various methods in the teaching-learning process are used to motivate students, one of which is game-based learning. This study explores the effects of game-based learning in improving the grammar skills of grade 9 students at Regional Science High School-III, Philippines. The results from the 1st quarter item analysis elicited the least learned competency, which allowed researchers to examine and determine the effects of game-based learning in improving the English grammar proficiency of the 143 grade 9 students, particularly in the use of modals. The study used a quasi-experimental research design, where the researchers adopted an assessment tool to determine the students’ English grammar proficiency level. The teachers assigned the experimental group with 8 game-based lessons and the control group who experienced the traditional lessons. The researchers used a paired sample t-test using the Jamovi software. The study found that there is a highly significant difference between the pre-test and post-test scores of the respondents before and after the integration of game-based learning lessons, resulting in the rejection of the null hypothesis. Furthermore, for English teachers, the intervention is perceived as beneficial in improving the English grammar skills of the learners. The study presented the description of various game-based lessons and determined the respondents’ proficiency levels. It was found that students progressed from being developing proficient to proficient when game-based lessons were applied. Thus, game-based learning is effective as it also makes the learning environment fun, conducive, exciting, and learner-centered.

Sustainable and inclusive development in left-behind places

AbstractScholarly work in economic geography and regional science has recently seen a renewed interest in spatial inequalities, driven significantly by the debate on left-behind places and the resulting geographies of discontent. The plight of left-behind places calls for new place-based policy responses that address the specific challenges of these regions but that at the same time address grand societal challenges such as climate change, biodiversity loss, or pollution with synthetic chemicals. Despite growing attention among economic geographers and regional scientists to either green or inclusive regional development approaches, how to reconcile environmental sustainability and social inclusiveness in highly challenged left-behind places remains poorly understood. This editorial reflects on and critically discusses the literature on left-behind places and distils unifying conceptual characteristics of left-behindness. We argue that left-behindness is a temporal, relational, multidimensional, discursive, but not deterministic concept. The non-determinism of left-behindness opens up different choices for actors to shape regional futures. Imagining and negotiating these futures involves dealing with difficult potential trade-offs between environmental sustainability and social inclusiveness, some of which are explored by the articles in this special issue.

Old wisdom and the New Economic Geography: Managing uncertainty in 21st century regional and urban development

The New Economic Geography (NEG) has over the past decades become a leading paradigm in regional science and geography. This paper seeks to provide a retrospective and prospective look into its achievements and current challenges. Clearly, regions are not oases of tranquility. Uncertainty and shocks in regional and urban development are omnipresent and call for adaptive and resilient strategies on spatial dynamics. The spatial arena is governed by many factors; this is mapped out in the present paper by means of a ‘Pentagon’ model of critical territorial capital inputs which form interdependent anchor points for policy and action based on the principle of confluence. The space-economy is multi-faceted and three prominent challenges in particular, are highlighted in this study: (i) the influence of digital technology on the standard NEG framework; (ii) the livability and proximity conditions in urban agglomerations, critically assessed through the lenses of the currently popular 15-minute city framework; (iii) the implications of social wellbeing and happiness motives for regional and urban planning in an NEG context. The conclusion of the study is that the NEG legacy and principles continue to be prominent signposts for regional and urban analysis and policy, conditional upon a flexible adaptivity of this legacy to new framework conditions in the ever-changing space-economy.

Comparative analysis of machine learning techniques for accurate prediction of unfrozen water content in frozen soils

Unfrozen water content (UWC) plays a critical role in determining the thermal, hydraulic, and mechanical properties of frozen soils. Existing empirical, semi-empirical, and theoretical models for UWC estimation have limitations in terms of accuracy as well as generalizability. To address these challenges, the present study explored the application of six machine learning techniques to predict UWC in frozen soils: Random Forest (RF), eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), K-Nearest Neighbors (KNN), Support Vector Regression (SVR), and Backpropagation Neural Network (BPNN). Considering the UWC hysteresis phenomenon between the freezing and thawing processes, experimental UWC data collected from the literature were separated into two sub-datasets: freezing branch dataset (FBD) and thawing branch dataset (TBD). Based on that, a comprehensive framework integrating Bayesian optimization and 10-fold cross-validation was established to optimize the six models' hyperparameters and to evaluate their performance. The results highlighted significant variations in the predictive capability among the six machine learning models, with ensemble methods (i.e., RF, XGBoost, LightGBM) generally demonstrating superior accuracy. Feature importance analysis, robustness checks, and uncertainty quantification further elucidated the strengths and limitations of each model. The present study provides profound insights into the selection and application of machine learning models for accurately modeling the properties of frozen soils for cold regions science and engineering.

Characteristics and influencing factors of the industry-university-research collaborative innovation network in China's new energy vehicle industry

Industry-university-research collaboration is the primary channel of industrial innovation, and China is a common context for research on innovation in the new energy vehicle industry. This study analyzes the industry-university-research collaborative innovation network in China's new energy vehicle industry using various software programs, including Gephi and ArcGIS, based on collaborative invention patent data related to the new energy vehicle industry provided by the global patent database incoPat. According to the findings of this study, the highest number of patents obtained through industry-university-research collaboration was observed in new energy vehicle device and accessory manufacturing, whereas the number of new entrants was significantly higher than the number of incumbents albeit in a downward trend, suggesting that the creation of new collaborative relationships among new entrants has always been the main phenomenon in the process of building an industry-university-research innovation system in the new energy vehicle industry. As private firms have long been playing an integral role in industry-university-research collaboration in the new energy vehicle industry, the number of private firms in the network exhibited an upward trend annually, while the dual heterogeneous connection mode was the primary connection mode in industry-university-research collaboration. There were some differences between the spatial characteristics of intraprovincial and interprovincial collaboration in the industry-university-research collaborative network in China's new energy vehicle industry. The analysis results obtained using GeoDetector revealed that the influence of economic base, level of openness to the outside world, government dominance, market dominance, regional science and technology finance, and entrepreneurial spirit varied from one stage to another.

A bibliometric portrait of a regional science scholar: in memory of professor Börje Johansson

A bibliometric portrait of a regional science scholar: in memory of professor Börje Johansson

Improving the Regional Science and Technology Innovation Ability under the Background of Data Element Marketization: Insights from the Yunnan Province

Under the background of the marketization of data elements, enhancing regional scientific and technological innovation capabilities has become the main driving force for urban sustainable development. It contributes to the sustainable development of the region. Based on the data of the Yunnan statistical yearbook, we built a regional science and technology innovation index system from three dimensions of science and technology innovation input, output, and benefit. Firstly, the entropy method is used to obtain the weight of each index. Secondly, TOPSIS is used to evaluate the 36 index data of each prefecture. Finally, the scores and rankings of the scientific and technological innovation ability of each prefecture are obtained. The research can effectively find the advantages and disadvantages of scientific and technological innovation in the Yunnan Province, provide data support and decision support for regional economic development, and play an important role in promoting the level of technological innovation in modern industries. At the same time, research projects can help various regions allocate various technological innovation resources reasonably, enhance their original innovation capabilities, lead the development of strategic emerging industries and future industries, and accelerate the formation of new quality productivity.

Can science and technology resources co-evolve with high-tech industries? Empirical evidence from China

Based on the theories of synergetic and evolutionary economics, we build a theoretical model of the co-evolutionary mechanisms of the composite systems of science and technology resources and high-tech industries in China. According to the established index system of the composite systems, we calculated the steady-state solution of the co-evolve and drew the potential function curve of science and technology resources and high-tech industries in China during 2010–2022 using the Haken model. Our empirical results show that high-tech industries are the order parameter of co-evolve. During the sample period, there is a synergistic growth effect of two-way promotion between science and technology resources and high-tech industries in China. However, within the system, the positive feedback mechanism of science and technology resources to high-tech industries in China is not perfect, and the allocation of science and technology resources needs to be further optimized, with a low degree of system order and large room for improvement. In addition, the endowment of science and technology resources and the development degree of high-tech industries in China are different in the eight comprehensive economic zones, and their co-evolvement is different. Therefore, by combining the advantages and allocating the elements of regional science and technology resources, we can better leverage the comparative advantages of high-tech industries in China and improve the degree of co-evolve in the system.

The Relative Probability of Facebook Friendship in the United States

We mapped Facebook’s Social Connectedness Index (SCI) between adjacent counties in the Contiguous 48 U.S. States. The index is calculated as the number of Facebook friends between counties, divided by the product of active Facebook users in the two counties. The results follow regional science principles that tell us that fewer flows may occur across political (administrative) borders such as state boundaries, and between economic zones, including transition zones between metropolitan areas and hinterland boundaries. We also found low connectivity between adjacent counties that are divided by interstate highways and low connectivity within densely populated areas. High connectivity is found in rural areas, and areas of cultural significance, such as highly African American regions in the U.S. South and isolated regions in Appalachia.

Regional Science and Environmental Economics: An Open Access Journal for the Field of Regional and Environmental Economics

Regional Science and Environmental Economics: An Open Access Journal for the Field of Regional and Environmental Economics

How Does Regional Science Address Environmental Issues? A Bibliometric Analysis of Two Decades of Publications

Using bibliometric methods, this paper is aimed at providing an overview of Regional Science publications that address environmental issues. The analysis covers a corpus of 1145 articles that refer to the environment in their title, abstract or keywords and published in 18 journals between 1999 and 2020. Although these publications account for only 6 percent of the articles published in these journals over that period, their number gradually increased. To gain a clearer picture of the environmental issues addressed, we characterise them according to whether an integrative or topical approach is adopted and by their spatial dimensions. This analytical framework is first applied by searching for specific terms in their title, keywords and abstract. The results show that both approaches are equally effective; further, these articles address intraregional or interregional environmental issues more than global environmental issues. Second, we conduct a keyword co-occurrence analysis revealing four coherent thematic article groups treating environmental issues from the perspectives of amenities and migration, governance and policy, innovation and clusters, and land use and urban sprawl. More detailed analyses of each group allowed us to refine our understanding of how environmental issues were addressed. Finally, a cross-cutting view of the four thematic groups suggests that Regional Science approaches environmental issues through spatial disparities and inequalities, spatial interactions and interdependencies, and the spatial dimension of public action. The research perspectives in each of these areas are highlighted.

The anglicization of science in China

Abstract The preeminence of English as the lingua franca in global science has led to English-dominant publication practices, even in non-English-speaking countries. We examine the complex dynamics of language use in scientific publications in China, a major contributor to global scientific output, and the tensions between English and the native language. By analyzing 2,209,987 multilingual publications from 183,457 projects funded by the National Natural Science Foundation of China, we reveal a strong preference for English as the publication language in China, with 66.2% of publications in English versus 33.8% in Chinese. Key projects and natural sciences and engineering projects favor English more; regional projects and social sciences projects use Chinese more. However, English has a growing prevalence over the years across all research fields, project types, and publication venues. There is a negative correlation between the shares of English usage in journals and conference proceedings. We find only a minor overlap between English and Chinese-language publications, indicating unique contributions rather than repetitive content. However, Chinese-language publications are more likely to be similar to English-language publications. For highly similar cross-language publication pairs, the Chinese version tends to be published earlier. The findings underscore the risk of underestimating China’s scientific output by only counting English-language publications. We highlight the importance of creating a comprehensive multilingual database and the significant role of non-English-language research in global scientific discourse. Keywords: multilingual publishing; scientific communication; language policy; academic multilingualism; bibliometrics; quantitative analysis.

A location analytics perspective of regional science at a crossroad

Location analytics have been a mainstay in regional science since its inception. Why? Perhaps the biggest reason is the ability to tease out important spatial heterogeneity nuances, but also to communicate geographically oriented analysis, planning, management and policy issues in rigorous ways, often as mathematical models, that can be subjected to further scrutiny and evaluation. Further, addressing broad challenges facing emergency response, food production, risk mitigation, transportation, public health, crime, housing and other issues through such approaches has proven an immense benefit to society. This paper focuses on the evolving subfield within regional science of location analysis and modeling, highlighting contributions to date but also detailing exciting areas of advancement involving spatial optimization and geographic information science. The paper includes a reflection on regional science journal publication trends, but also broader patterns of location analytics activity. It is hoped that this review will lead to a reassessment of regional science priorities, and consideration of the role that our specialty areas have in maintaining core strengths as well as potential for growing the discipline in the coming years.

Using a spatial autoregressive model with spatial autoregressive disturbances to investigate origin-destination trip flows.

Spatial interaction models with spatial origin-destination (OD) filters are powerful tools to characterize trip flows in space, which is a classic and important problem in regional science. To the authors' knowledge, existing studies adopting OD filters mostly specify the spatial dependence as an autoregressive process, which may not be the full picture of spatial effects. To examine the problem, this paper proposes the hypotheses that 1) spatial OD dependences can take place in both the spatial autoregressive term and the spatial error term in a spatial interaction model. 2) Estimating a spatial autoregressive model with spatial autoregressive disturbances (SARAR) model with OD filters would disentangle where the spatial dependence exists and by how much. 3) The marginal effects obtained from SARAR models would be preferred to analysts when SARAR models outperform spatial autoregressive (SAR) models and spatial error models (SEM) from the statistical point of view. To assess these hypotheses, this paper specifies, estimates, and applies SARAR models with OD filters to investigate trip distributions. By comparing against alternative models, this paper investigates the estimation results in SAR, SEM and SARAR models using an empirical data collected from Hangzhou, China. The contribution of this paper is to be the first in developing an SARAR model with OD filters for trip distribution analyses and examining its performance.

Exploring economic activity from outer space: A Python notebook for processing and analyzing satellite nighttime lights

Nighttime lights (NTL) data are widely recognized as a useful proxy for monitoring national, subnational, and supranational economic activity. These data offer advantages over traditional economic indicators such as GDP, including greater spatial granularity, timeliness, lower cost, and comparability between regions regardless of statistical capacity or political interference. However, despite these benefits, the use of NTL data in regional science has been limited. This is in part due to the lack of accessible methods for processing and analyzing satellite images. To address this issue, this paper presents a user-friendly geocomputational notebook that illustrates how to process and analyze satellite NTL images. First, the notebook introduces a cloud-based Python environment for visualizing, analyzing, and transforming raster satellite images into tabular data. Next, it presents interactive tools to explore the space-time patterns of the tabulated data. Finally, it describes methods for evaluating the usefulness of NTL data in terms of their cross-sectional predictions, time-series predictions, and regional inequality dynamics.

Geographies and determinants of rent burden: A regional economic analysis of the U.S. metropolitan landscape

Rental housing affordability, a growing topic in interdisciplinary scholarship, remains relatively peripheral to geography and regional science. This article focuses on geographies of rent burden and factors affecting it at the metropolitan level in the conterminous U.S. By conducting cartographic and regression analyses, we examine relationships between rent burden and numerous related aspects derived from scholarly work. Besides offering a new measurement of rent burden, we put a special emphasis on regional economic specializations as potential predictors of rent burden’s intensity. The relationship between these two have not been studied in existing scholarship. Our results indicate that the most consistent determinants of more intense rent burden in numerous models include higher housing values and poverty rates, substantial shares of racial/ethnic minorities, and family structure represented by lower percent married. Regarding economic specializations, we find that manufacturing is a strong predictor of lower rent burden in most models, with its effect demonstrating an opposite direction—higher rent burden occurs in metropolises not specializing in manufacturing. Simultaneously, metropolises with substantial concentrations of employment in (i) education and medicine and (ii) arts, entertainment, and recreation exhibit higher rent burden and most of these metropolises are mid- and small-sized.

Benefits and Risks Associated With Statin Therapy for Primary Prevention in Old and Very Old Adults : Real-World Evidence From a Target Trial Emulation Study.

There is little consensus on using statins for primary prevention of cardiovascular diseases (CVDs) and all-cause mortality in adults aged 75 years or older due to the underrepresentation of this population in randomized controlled trials. To investigate the benefits and risks of using statins for primary prevention in old (aged 75 to 84 years) and very old (aged ≥85 years) adults. Sequential target trial emulation comparing matched cohorts initiating versus not initiating statin therapy. Territory-wide public electronic medical records in Hong Kong. Persons aged 75 years or older who met indications for statin initiation from January 2008 to December 2015 were included. Participants with preexisting diagnosed CVDs at baseline, such as coronary heart disease (CHD), were excluded from the analysis. Among 69 981 eligible persons aged 75 to 84 years and 14 555 persons aged 85 years or older, 41 884 and 9457 had history of CHD equivalents (for example, diabetes) in the respective age groups. Initiation of statin therapy. Incidence of major CVDs (stroke, myocardial infarction, or heart failure), all-cause mortality, and major adverse events (myopathies and liver dysfunction). Of 42 680 matched person-trials aged 75 to 84 years and 5390 matched person-trials aged 85 years or older (average follow-up, 5.3 years), 9676 and 1600 of them developed CVDs in each age group, respectively. Risk reduction for overall CVD incidence was found for initiating statin therapy in adults aged 75 to 84 years (5-year standardized risk reduction, 1.20% [95% CI, 0.57% to 1.82%] in the intention-to-treat [ITT] analysis; 5.00% [CI, 1.11% to 8.89%] in the per protocol [PP] analysis) and in those aged 85 years or older (ITT: 4.44% [CI, 1.40% to 7.48%]; PP: 12.50% [CI, 4.33% to 20.66%]). No significantly increased risks for myopathies and liver dysfunction were found in both age groups. Unmeasured confounders, such as lifestyle factors of diet and physical activity, may exist. Reduction for CVDs after statin therapy were seen in patients aged 75 years or older without increasing risks for severe adverse effects. Of note, the benefits and safety of statin therapy were consistently found in adults aged 85 years or older. Health Bureau, the Government of Hong Kong Special Administrative Region, China, and National Natural Science Foundation of China.

Project HOFOMI (Home for the Minds for the Grade 10 Learners of the Regional Science High School for Region I

This research paper investigates the effectiveness of a targeted reading intervention program, referred to as Project HOFOMI, on improving the reading comprehension levels of Grade 10 learners. The study employed pretest and post test assessments based on the Reading GATES survey to evaluate changes in students' comprehension abilities before and after the intervention. The results demonstrate a significant enhancement in reading comprehension skills among Grade 10 learners following the implementation of Project HOFOMI. Specifically, a notable shift was observed from Grade 9 to Grade 10 reading levels, indicating the program's success in elevating learners' proficiency. Statistical analysis confirms the substantial impact of Project HOFOMI, with post test scores showing a significant increase compared to pretest scores. Moreover, qualitative feedback from participants highlights high levels of satisfaction and perceived effectiveness of the intervention in fostering comprehensive learning and personal growth. The findings underscore the importance of evidence-based educational interventions in addressing specific learning needs and promoting skill development among students. Recommendations include further investigation into improving outcomes for higher-grade levels and the continuous monitoring and adaptation of intervention strategies to ensure sustained progress in reading comprehension skills.