Asia-Pacific Journal of Regional Science最新文献

Education plays a vital role in the development of any country or region, making it imperative to address obstacles that hinder educational quality such as school bullying. This is an under-researched topic in the social sciences. Bullying is a form of social mistreatment that may have detrimental effects, because students who experience frequent bullying tend to perform poorer compared to their peers who do not report such incidents. Given this evidence, it is crucial to assess the educational performance of countries by considering the overall well-being, including mental well-being, of students. In this context, data envelopment analysis (DEA) is a valuable method for evaluating the performance of decision-making units in education. In our paper, we discuss various approaches to apply DEA when dealing with "undesirable" outputs like bullying. Common techniques involve transforming undesirable outputs using reciprocal transformations and employing a "bad-output" model. However, these methods have several drawbacks, such as altering the nature of the selected output items, loss of linearity, reduced robustness of the efficiency frontier, and limited versatility. To address these concerns, our paper proposes and tests a value inversion–DEA model that can consistently transform "undesirable" data into a reverse measurement scale, while preserving linearity. We demonstrate the high versatility of this model across different types of DEA models with undesirable outputs. Furthermore, we apply this proposed method to assess the educational efficiency of OECD countries, focusing on bullying as an undesirable output. Our findings show that significant improvements in performance are possible in many countries by addressing school bullying.

With the advancement of technology and advent of a networked society, economic agents within a region benefit from local interactions within the region as well as the external economies. However, strengthening extra-regional ties may have negative consequences for regions near the center if all their economic resources are absorbed by the core. It is unclear, for regional economic agents, whether the negative network externalities dominate the positive ones. This has not been fully elucidated in the previous studies. To contribute to a breakthrough for this research topic, this study identified the impacts of network externalities on improvements in productivity and productive efficiency using stochastic frontier analysis. The analysis revealed that the borrowed size effect of agglomeration in the manufacturing industry significantly raises total factor productivity through shifts in the production frontier. It also revealed that the shadow effect of agglomeration does not adversely affect the productive efficiency of industry in either the manufacturing or non-manufacturing sector. These results imply that enhancing quality transportation infrastructure and improving inter-regional transportation networks can enhance the production performance of regional industries.

Poverty is a major socio-economic problem facing most developing countries. In Egypt, approximately 30% of citizens live below the poverty level, which is more evident at the regional level. Reducing poverty can be achieved through better allocation of government spending, because it is essential for promoting economic growth, improving income distribution and reducing poverty. Understanding the relationships between government spending and regional poverty reduction can enhance the ability of policymakers to design programs that effectively reduce regional poverty and lessen income inequality. This study aimed to analyze the impact of government spending in alleviating regional poverty in Egypt. A panel data set for 27 Egyptian governorates from 2010 to 2018 was employed. The two-way fixed effect regression model was used to apply the differences between regions over time. The results showed that only social government spending significantly affects poverty reduction at the national level. Health, education and social government spending showed significant negative impacts on poverty at the region level, especially in Upper Egypt and Cairo.

This paper aims to assess the impacts of climatic shifts caused by climate change on tourism destinations and provide a strategic roadmap to manage tourism development and investments in Turkiye. To assess the climate change impacts on the tourism sector, we focus on spatial variations in climate change, model the changing suitability of climatic conditions on tourism activities in different regions of Turkiye and estimate future climate conditions by considering climate scenarios. The “Tourism Climate Index” (TCI) is adopted to compare the suitability of the climate for tourism activities during the base years (1963–2017) and the projected years (2040–2069). In applying current and estimated climatic data, the case study destinations are assembled into three groups based on magnitude and direction of change, namely, alarming, moderate, and advantageous destinations. To provide a strategic roadmap, a matrix is developed regarding the number of international tourists, the number of accommodation facilities, tourism type and TCI results. As a result, nine zones are defined to represent the risks and potentials of the destinations, their priority levels in future tourism development are determined, and recommendations for each zone are formulated. İstanbul and Antalya excel with their high demand, advanced infrastructure and potential for an extended tourism season, while Nevşehir, Ankara, and Konya stand out as alternative destinations. On the other hand, İzmir and Muğla stand out with their high risk and high demand. The significance of this study lies in adaptions of climatic shifts to a tourism development roadmap. The results are critical for formulation of strategic tourism development plans from the local to the national levels for sustaining viability of the tourism market.

This study examined the volatility connectedness between rice price and selected fertilizer commodity products among global rice-producing countries that are mainly in the Asian and Pacific regions. For this purpose, natural gas, selected fertilizers, rice monthly price data, and commodity volatilities were estimated by exponential weighted moving average (EWMA). Furthermore, the connectedness of the volatilities were demonstrated by applying the TVP-VAR-based Diebold–Yilmaz approach. First, we constructed eight separate networks for each country and then determined the total connectedness index (TCI), net pairwise directional connectedness (NPDC), and pairwise connectedness index (PCI). The average TCI for all countries varied between 40 and 55%. The dynamic TCIs showed that the impact of food price volatility from 2007 to 2008 persisted until 2009. Connectedness across all networks was seen to decline after 2010, dropping to 40% or lower. Upon analyzing bilateral interconnectivity through the lens of the PCI values, a robust connectedness between triple superphosphate fertilizer price volatility and Bangladesh, Brazil, China, and Pakistan was evident. The interconnectedness of urea fertilizer and natural gas volatility with rice price volatility, along with the substitution relationships between other fertilizers, offers valuable information for investors to construct portfolios.

Previous theoretical studies on economic development and demographics have discussed the impacts of childcare policies but have not specifically addressed the relationships between population concentration in urban areas and fertility rates. While many studies focus on population size and density in regions and countries to understand regional economies, few studies explore the effects of childcare policies on demographics. Therefore, we investigated the effects of regional childcare policies on population migration and regional and total fertility rates. Our study presents a two-region overlapping generations model with the following findings: (1) increasing the tax rate to enhance urban childcare facilities leads to a short-term increase in the urban population proportion and restructures the economy to support urban area population concentration. (2) With a constant tax rate, the dispersion economy declines in total fertility as it develops, while the agglomeration economy sees an increase in total fertility during development. This model can clearly highlight the effects of policies aimed at addressing the shortage of childcare facilities in urban areas.

Debates on the advantages of regional industrial specialization versus diversification are a central focus in economic theory. Concepts of related and unrelated variety offer a potentially insightful framework to explore this complex issue. This study examined the effects of related and unrelated variety on employment and labor productivity growth for 81 provinces in Turkey using the proximity approach to measure relatedness. We found that only the related variety contributes to regional economic growth in Turkey. When regional disparities between the western and eastern provinces are accounted for, the related variety positively affects employment growth in the western provinces. On the other hand, labor productivity and related variety relationships appear to be valid only for the relatively less developed eastern provinces. These findings have significant implications for economic policies, particularly for nations such as Turkey where regional economic disparities are a major concern. This study underscores the need for a deeper understanding of the intricate dynamics of regional industrial mixes and the roles they play in regional economic growth.

Philosophies of contentment, peace and happiness underpin Indian culture. However, the low ranking of India in the World Happiness Report is a matter of concern. The objective of the study was to explore the determinants of subjective wellbeing (SWB) in India. We used data from 5 waves of world value surveys consisting of 11 Indian states in the post liberalized era (1990–2014). The dependent variables were happiness and life satisfaction. In addition, several socio-economic variables were also adopted to assess their impacts on SWB. The estimated results from the heteroscedastic ordered probit model showed that there is a significant impact of demographic and socio-economic variables on the happiness and life satisfaction of Indians. Factors such as high-income levels, financial satisfaction, freedom of choice and life control showed a positive impact on both happiness and life satisfaction of individuals. Moreover, belief in religion, family, friends, trust of most people and a meaningful life were also positively associated with happiness of Indians. Furthermore, male, elderly and unhealthy people were more unhappy and dissatisfied with their life. This study contributes to the literature by identifying several determinants of SWB for Indians after the country’s integration of the international market. The government needs to collect happiness related data during the census so that the country can implement happiness enhancing policies.

Previous studies on the happiness levels of people in developing countries showed that urban areas had better healthcare conditions and residents were happier, whereas rural areas were more vulnerable and residents were less happy. Numerous studies have shown that residents of rural areas in developed countries are happier. However, a few studies have comprehensively examined the happiness of residents in rural areas of developing countries. Contrary to the aforementioned statement, people in rural areas may be happier, but this remains to be explored. During the COVID-19 pandemic, people worldwide showed clinically significant levels of depression, anxiety, and mental distress (Santomauro in Lancet 398(10312):1700–1712, 10.1016/S0140-6736(21)02143-72021, 2021). Upon lifting lockdown measures and recovering economic activity, primarily due to mass vaccination programs, knowledge about happiness regarding the recovery processes of this mental distress was not enough. Furthermore, a few studies evaluated the mental health and happiness of residents in the rural areas of developing countries during the pandemic. Based on this background, this study analyzed the reality of urban and rural happiness during the pandemic in Bali, a developing country, and aimed to show that rural residents were happier. Higher levels of happiness among rural residents observed in the first survey was confirmed using a second survey. Both chronological surveys were conducted in the same region using the same questionnaire halfway through the COVID-19 pandemic until the near-endemic period. This survey was conducted from June to July 2022. The responses of 280 people from the same districts as the first survey were quantitatively compared. Based on these data, we performed a simple analysis, comparison of means, factor analysis, multiple regression analysis, canonical correlation analysis, and covariance structure analysis. The survey results showed that rural areas did not outperform urban areas in terms of happiness itself. Additionally, happiness levels were mostly unchanged in both areas compared to the previous survey. Residents in rural areas showed decreased medical concerns, better income recovery, and limited patience compared to the earlier results. Alternatively, residents in urban areas showed increased anxiety about medical care, decreased income, and higher levels of loneliness and depression. In other words, the recovery of income and reduced concern about medical care in rural areas were in contrast to the low level of happiness. These results also point to lower levels of happiness among residents in urban areas. Therefore, the happiness recovery level following the pandemic appears better in rural areas and slower in urban areas. That is, the hypothesis was proven correct. Interestingly, the results of this study differ from those of previous studies, which report higher happiness levels among urban residents in developing countries and lower hap