{"title":"Borrowed size and agglomeration shadows in Japan: a spatial econometric analysis of regional productivity","authors":"Akihiro Otsuka","doi":"10.1007/s41685-025-00398-2","DOIUrl":"10.1007/s41685-025-00398-2","url":null,"abstract":"<div><p>This study examined the influence of spatial interdependencies on regional total factor productivity in Japan by focusing on the contrasting effects of borrowed size and agglomeration shadows. Using panel data from 47 Japanese prefectures between 2000 and 2018, we compared the manufacturing and non-manufacturing sectors by estimating the Spatial Durbin Model and the Spatial Durbin–SARAR Model. These models enable a detailed decomposition of productivity effects into direct (within region) and indirect (spillover) components across space. The results indicated that industrial agglomeration and transport capital positively influence local productivity in both sectors. However, negative spillovers, interpreted as agglomeration shadow effects, were also observed, where the concentration in neighboring regions suppressed local performance. Human capital exerted a consistently positive impact on manufacturing, with evidence of interregional spillover effects. These findings highlight the sector-specific spatial dynamics and indicate the need for differentiating regional policy responses. For the manufacturing sector, promoting networked industrial clustering and labor mobility can enhance productivity but must be balanced against the risks of overconcentration. In the non-manufacturing sector, decentralized service economies and spatially equitable infrastructure investments are critical for reducing competitive displacement from urban cores. By clarifying the conditions under which borrowed size and agglomeration shadow effects prevail, this study contributes to spatial productivity theory and offers actionable insights for designing regionally differentiated development strategies.</p></div>","PeriodicalId":36164,"journal":{"name":"Asia-Pacific Journal of Regional Science","volume":"9 4","pages":"1115 - 1144"},"PeriodicalIF":1.7,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s41685-025-00398-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145600991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Mediating effect of potential benefits on awareness, environment sustainability and revisit intentions in ecotourism sites: a case study of Himachal Pradesh, India","authors":"Shweta Rana, Deeksha Rana, Seema Choudhary","doi":"10.1007/s41685-025-00396-4","DOIUrl":"10.1007/s41685-025-00396-4","url":null,"abstract":"<div><p>Ecotourism enables travellers to explore and learn about nature. This study investigated the relationships between awareness, environment sustainability, hindrances in ecotourism development, and potential benefits and intentions to revisit among tourists of Himachal Pradesh. The study area comprised four districts of Himachal Pradesh, namely Lahaul-Spiti, Kinnaur, Kullu and Solan Districts. Structural Equation modelling was employed to assess the influence of awareness, environmental sustainability and hindrances in ecotourism development on revisit intentions, mediated by potential benefits. PLS-Predict was employed to examine the predictive effectiveness of the model. Primary data was acquired from 261 tourists using a purposive sampling method. Partial Least Squares-Structural Equation Modelling (PLS-SEM) was used for hypothesis testing. The structural model demonstrated that both “awareness” and “environmental sustainability\" positively affects “revisit intentions” through the mediating influence of “potential benefits”. Although the ecotourism policies of Himachal Pradesh focus on institutional framework and community development, adherence should be given to make tourists cognisant about the environment and surroundings of the state. It is important that the educational aspects of ecotourism should be incorporated so that environmental sustainability can be maintained in the long run.</p></div>","PeriodicalId":36164,"journal":{"name":"Asia-Pacific Journal of Regional Science","volume":"9 4","pages":"997 - 1023"},"PeriodicalIF":1.7,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145600995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Does fiscal decentralization increase urban temperature? The case of Indonesian metropolitans","authors":"Adiwan F. Aritenang","doi":"10.1007/s41685-025-00395-5","DOIUrl":"10.1007/s41685-025-00395-5","url":null,"abstract":"<div><p>In Indonesia, the advent of decentralization marked a profound politico-economic transformation from a centralized authoritarian government in 1999. After more than two decades, Indonesian urban studies have overlooked the relationships between regional economic growth and environmental consequences, especially in the context of fiscal decentralization. We hypothesized that variations in fiscal decentralization and capital expenditure lead to higher land surface temperature at the local level, highlighting the need for tailored urban environmental policies. Using six metropolitans on Java Island—Jakarta, Bandung, Cirebon, Jogjakarta, Semarang, and Surabaya—this study examined the effects of two components of fiscal decentralization, intergovernmental transfer funds and capital expenditure, on the urban environment between 2014 and 2022. The environmental quality was approximated by Land Surface Temperature (LST) obtained from the Google Earth Engine (GEE) platform. Structural breaks analysis and panel fixed-effect regression were also performed. Evidence of structural breaks due to the pandemic and mixed effects of intergovernmental transfer and capital expenditure on urban temperature were revealed. These findings contribute to the literature by providing empirical evidence on the role of fiscal decentralization and urbanization on variations in urban temperature.</p></div>","PeriodicalId":36164,"journal":{"name":"Asia-Pacific Journal of Regional Science","volume":"9 4","pages":"955 - 973"},"PeriodicalIF":1.7,"publicationDate":"2025-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145600988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Carbon emissions embodied in exports from regional comprehensive economic partnership member countries: perspectives on internal and external dynamics","authors":"Hong Chen, Abdul Rais Abdul Latiff, Soo Y. Chua","doi":"10.1007/s41685-025-00391-9","DOIUrl":"10.1007/s41685-025-00391-9","url":null,"abstract":"<div><p>Trade dynamics within Regional Comprehensive Economic Partnership (RCEP) regions shift from globalization to regionalization, thus a comprehensive understanding of the emission dynamics associated with internal versus external exports is critical. This study employed structural decomposition analysis to examine the drivers of emissions embodied in exports (EEE) originating from within and destined for beyond RCEP from 2010 to 2019. Results showed that internal EEE growth was primarily driven by demand effects, while external EEE declines were mainly due to reductions in carbon intensity. Technology spillovers through external trade reduced emissions in middle- and high-income countries, whereas internal trade increased emissions in low-income countries due to pollution haven effects. Intra-RCEP trade also enhanced production efficiency when compared to external or purely domestic trade. External demand was predominantly characterized by household consumption, while internal demand driven by investment and government spending. These findings underscore the need for policies that promote the diffusion of clean technologies, regional integration and greener investment, as well as the implementation of stricter emission controls in low-income regions to effectively mitigate emissions amid evolving trade patterns within the RCEP framework.</p></div>","PeriodicalId":36164,"journal":{"name":"Asia-Pacific Journal of Regional Science","volume":"9 4","pages":"931 - 953"},"PeriodicalIF":1.7,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145600994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
David Gómez-Ríos, Sebastián Gómez-Ríos, Juan Felipe Castellanos-Martínez
{"title":"Carbon emissions and economic growth decoupling in the city of medellín and its metropolitan area: a longitudinal sectoral analysis (2000–2023)","authors":"David Gómez-Ríos, Sebastián Gómez-Ríos, Juan Felipe Castellanos-Martínez","doi":"10.1007/s41685-025-00392-8","DOIUrl":"10.1007/s41685-025-00392-8","url":null,"abstract":"<div><p>As one of the most polluted cities in Latin America, Medellín faces recurrent air quality crises, driven by transportation emissions and topographical constraints that exacerbate pollution retention. At the same time, the city is recognized as a hub for urban innovation, implementing policies aimed at sustainable mobility and green infrastructure. Therefore, we examined the decoupling relationships between economic growth and carbon emissions in Medellín’s metropolitan area, Colombia’s second-largest urban center, from 2000 to 2023. Using the Logarithmic Mean Divisia Index (LMDI) and the Tapio decoupling elasticity model, this study integrated updated datasets, including Copernicus Atmosphere Monitoring Service (CAMS) emission inventories and local air quality monitoring data. Results indicated a predominance of weak decoupling with GDP growth at an annual rate of 5.66% while emissions increased marginally at 0.25%. Sectoral analysis revealed that the tertiary sector, responsible for 72% of GDP and 59% of emissions, exhibited alternating periods of weak (15) and strong decoupling (6), driven by efficiency improvements and structural changes. In contrast, the secondary sector consistently reduced contributions to production and carbon emissions after 2008 configuring 7 instances of strong decoupling in the last years. Population growth was identified as a major inhibitor of decoupling, contributing to rising emissions in the transportation sector, which remains as the primary source of urban emissions. Energy and carbon intensity reductions contributed positively to decoupling, particularly in commercial and service-based activities. These findings highlight the need for deeper targeted policy interventions and sector-specific strategies to accelerate regional decoupling and support sustainable urban development.</p></div>","PeriodicalId":36164,"journal":{"name":"Asia-Pacific Journal of Regional Science","volume":"9 4","pages":"905 - 930"},"PeriodicalIF":1.7,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s41685-025-00392-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145600989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Heterogeneous effects of climate and socioeconomic factors on wheat and maize production in Madhya Pradesh, India: evidence from Just and Pope production function","authors":"Aaqif Rashid Lone, Biswajit Patra","doi":"10.1007/s41685-025-00394-6","DOIUrl":"10.1007/s41685-025-00394-6","url":null,"abstract":"<div><p>Changes in the effects of climate on agricultural yield are becoming common in the literature. The present study investigated how both climatic and socioeconomic variables affect means and variations in crop yield. We examined factors that affect the yields of two major crops, wheat and maize, cultivated in different seasons in Madhya Pradesh, India. For empirical analysis, we employed the Just and Pope production function, covering the period from 1999 to 2017 based on the latest district-level available data of Madhya Pradesh. An increase in rainfall enhanced the mean yield of both crops in Central India, showing the yield of these crops is highly dependent on rainfall. Average temperature and number of extreme cold days adversely affected the wheat yield in the region. Furthermore, an increase in fertilizer consumption raised mean crop yield, but it was not uniform, because this leads to an increase in variation of crop yields. The findings also confirmed the presence of an inverted ‘U’-shaped relationship between the mean maize yield and rainfall. However, there was a ‘U’ shaped relationship between mean wheat yield and temperature. Surprisingly, irrigation showed a differential impact on mean yield in different seasons. Normally, irrigation is a risk reducing input and diminishes variance in yields. These results provide policy insights to state and local governments for adaptation measures against climate change to protect the mean yield and control variations in yield of these major crops in the central part of India.</p></div>","PeriodicalId":36164,"journal":{"name":"Asia-Pacific Journal of Regional Science","volume":"9 3","pages":"807 - 830"},"PeriodicalIF":1.7,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145005514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Influence of information and communication technology, human development, military expenditures, and renewable energy on environmental quality in the Middle East and North Africa Region","authors":"Wadad Saad, Farah Boussi","doi":"10.1007/s41685-025-00390-w","DOIUrl":"10.1007/s41685-025-00390-w","url":null,"abstract":"<div><p>In the context of rising climate pressures, the Middle East and North Africa (MENA) Region is confronted with the challenge of reconciling its high economic growth with environmental sustainability. Despite sustained global efforts toward achieving Sustainable Development Goal 13 (climate action), most countries in the region are still hampered by resource dependency, a lack of effective policy implementation, and ongoing ecological pressures. This paper looks at how information and communication technology (ICT), human development (HD), military expenditures (ME), and renewable energy (REC) affect the environmental quality (ENQ) based on three indicators, i.e., carbon dioxide emissions (CO<sub>2</sub>e), ecological footprint (EFP) and greenhouse gas emissions (GHGe) in ten MENA countries between 2001 and 2022 within the Environmental Kuznets Curve (EKC) framework. Employing the Pooled Mean Group (PMG) estimation model, the results show that although ME and NREC worsen the environment by increasing CO<sub>2</sub>e, HD, ICT and REC improve ENQ by reducing CO<sub>2</sub>e in the long run. However, HD, ICT, REC, NREC and FDI worsen the environment by increasing EFP, while ICT improves the environment by mitigation. Meanwhile, HD, ME and REC decrease GHGe, while ICT and NREC increase them. Furthermore, all three models support the EKC hypothesis in the MENA Region. Based on the overall findings, MENA nations must establish a conducive policy framework by adopting green growth strategies, promoting clean energy, leveraging ICT for sustainability, integrating eco-friendly practices into military operations, and allocating defense budgets to environmental initiatives, all of which are crucial for advancing climate action in the region.</p></div>","PeriodicalId":36164,"journal":{"name":"Asia-Pacific Journal of Regional Science","volume":"9 3","pages":"773 - 805"},"PeriodicalIF":1.7,"publicationDate":"2025-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145005512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Socioeconomic determinants of coffee intake: a multi-regional analysis","authors":"Md. Mominul Islam, Sabrina Islam","doi":"10.1007/s41685-025-00393-7","DOIUrl":"10.1007/s41685-025-00393-7","url":null,"abstract":"<div><p>Coffee is one of the most widely consumed beverages globally, with its consumption influenced by socio-economic factors, such as income levels, pricing, and regional preferences. This study examined the relationships between income and coffee consumption across different regions to analyze whether coffee behaves as a normal good. Using an unbalanced panel dataset from 53 countries, we incorporated key economic variables including Gross Domestic Product (GDP) per capita, coffee and tea consumption, and the prices of ground coffee and tea. A fixed-effects regression model was employed to assess the impact of income variations on coffee intake. The findings revealed significant regional disparities. For the European and African & Middle Eastern Regions, income showed a positive effect on coffee consumption when grouped with all variables. For the Asia–Pacific (APAC) and American regions, income within the regression showed no statistical significance whatsoever. Therefore, income appears, for half the regions, to be significant in determining coffee consumption, i.e., the more money one has, the more coffee they are able to consume, which reiterates that coffee is a normal good. These results contribute to the existing literature by providing a comparative regional analysis of income-driven coffee consumption. The findings also have practical implications for coffee producers, policymakers, and businesses seeking to understand market demands. Understanding regional coffee trends can support demand forecasting and pricing strategies. However, future studies should also examine consumer behavior and marketing dynamics. </p></div>","PeriodicalId":36164,"journal":{"name":"Asia-Pacific Journal of Regional Science","volume":"9 3","pages":"869 - 902"},"PeriodicalIF":1.7,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145005506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Urban air quality modeling and health impact analysis using geospatial methods and machine learning algorithms","authors":"Chetan Rathod, Aneesh Mathew, Abhilash T. Nair","doi":"10.1007/s41685-025-00387-5","DOIUrl":"10.1007/s41685-025-00387-5","url":null,"abstract":"<div><p>This study utilized geospatial techniques and machine learning (ML) algorithms, viz. Random Forest and XGBoost, for predicting the air quality and the AirQ+ model for assessing health risks in urban environments. We analyzed the annual variations in sulfur dioxide (SO<sub>2</sub>) and nitrogen dioxide (NO<sub>2</sub>) levels of five Indian metropolitan cities from 2019 to 2022. Preliminary analysis indicated the highest levels of NO<sub>2</sub> and SO<sub>2</sub> in Delhi and Kolkata as compared to other metropolises. Kolkata had an 11% increase in SO<sub>2</sub> concentrations in 2022 compared to 2019, while Delhi had a 20% increase in NO<sub>2</sub> concentrations in 2022 compared to 2019. The air pollutant levels predicted by ML algorithms were analyzed in the AirQ+ model for health risks. The health impact assessment conducted using the AirQ+ model revealed concerning trends. In 2023, particulate matter (PM<sub>2.5</sub>) was attributed to 20.26% of respiratory disease cases per 100,000 population in Delhi, followed by NO<sub>2</sub>, accounting for 11.01%. In Kolkata, SO<sub>2</sub> was responsible for 3.21% of respiratory disease cases. By implementing this approach, policymakers can estimate the air pollution levels and potential respiratory disease health risks. This knowledge can help them formulate targeted interventions, such as implementing pollution control measures, managing health risks, and issuing health advisories, to protect public health and improve air quality in cities.</p></div>","PeriodicalId":36164,"journal":{"name":"Asia-Pacific Journal of Regional Science","volume":"9 3","pages":"693 - 731"},"PeriodicalIF":1.7,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145005510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}