Asia-Pacific Journal of Regional Science最新文献

This study examined the effects of regional proliferation resulting from Indonesia’s decentralization policies, with a focus on the formation of new districts and cities. The analysis used longitudinal data and applied a difference-in-differences (DiD) model and event study approach to evaluate the impacts of these policies on firm performance and growth. The findings showed that regional proliferation initially attracts industries to newly created areas, but firm performance may decline in the long term. Productivity and output showed improvements in the early years following proliferation, particularly during periods such as local elections. The ability of new regions to utilize their autonomy effectively varied, with some regions developing quickly while others faced challenges. Overall, this research provides causal evidence that decentralization can stimulate business productivity and industrial growth, although long-term support and strategic policy implementation remain crucial for the success of newly formed regions.

The growing environmental challenges faced by Egypt highlight a need to examine how key macroeconomic factors influence environmental sustainability. In response, this research analyzes the short-run and long-run effects of economic growth, financial development, and energy consumption on environmental degradation in Egypt. Using annual time-series data from 1960 to 2022, we employ the Autoregressive Distributed Lag (ARDL) methodology and Error Correction Model (ECM) to assess the short-run and long-run effects of these macroeconomic factors on environmental degradation. Additionally, Granger causality tests are applied to explore causal linkages among the variables, while the Cholesky variance decomposition method estimates the proportionate impact of shocks on CO₂ emissions. The results revealed that, in the short-run, energy consumption, financial development, urbanization, and economic growth negatively impacted environmental quality, whereas trade openness and the squared term of economic growth improved it. In the long-run, however, all variables—except for the squared term of economic growth—contributed to increased CO₂ emissions. Furthermore, the study identified significant bidirectional causality between economic growth and energy consumption. Variance decomposition estimates indicate that economic growth and trade openness are primary drivers of CO₂ emissions in Egypt, accounting for 28.45% and 20.11% of the observed variation, respectively. These findings suggest that Egypt’s economic growth and international trade are pollution-intensive, highlighting the need for targeted policy interventions. We recommend the promotion of a clean energy transition through environmental awareness campaigns, investments in renewable energy technologies, financial sector reforms, and the development of sustainable urban infrastructure to support low-carbon economic growth and enhance environmental sustainability.

Two primary objectives of sustainable development goals are poverty reduction and environmental quality. Recent findings, however, point to a potential conflict between pursuing these two objectives. This study aimed to investigate the existence of a dilemma between rural poverty and environmental quality in Indonesia. Unlike previous studies, we focused on rural poverty and environmental quality index to examine the poverty-environmental degradation nexus. We also attempted to reveal the socio-economic dynamics that affect rural poverty and environmental quality. We used the data from 33 provinces of Indonesia between 2015 and 2022 and employed the system-generalized method of moments (SysGMM) approach. The results showed that rural poverty and environmental quality support trade-off relationships that improve environmental quality and increase rural poverty. Population density and income inequality hindered the improvement of environmental quality. Meanwhile, human development, rural labor wages, and information communication and technology (ICT) supported the improvement of environmental quality. Economic growth, electricity access, and ICT supported the alleviation of the rural poor. Therefore, the central and regional governments should make efforts to reduce income inequality and increase ICT access to simultaneously improve the quality of the environment and reduce rural poverty.

The seven sister states of northeast India are renowned for their diverse landscapes and vibrant cultural heritage. From the Himalayas in the north to the plateau plains in the south, the region offers lush rainforests and rich biodiversity, making it ideal for ecotourism. This study aimed to map and analyze the ecotourism potential across Northeast India's seven sister states through state-wise geospatial analysis. Geographic information system (GIS) and the full consistency method (FUCOM) multi-criteria decision analysis model were used for this purpose. While many multi-criteria decision making (MCDA) models have been used to identify ecotourism potential, FUCOM-based geospatial analysis is new to this area and ecotourism potential identification. Utilizing the receiver operating characteristic (ROC) curve, the study assessed the effectiveness of each state and region in identifying suitable tourism zones. It highlighted the rich natural resources and cultural diversity of the seven sister states, which offer an ideal environment for ecotourism development. Through comparative analyses, we identified areas with the highest ecotourism potential and emphasized the importance of sustainable tourism initiatives to benefit both the environment and local communities. The potential zones in the Northeast States were categorized into five groups: Very High (23.34%), High (25.76%), Moderate (20.15%), Low (22.39%) and Least Potential (8.36%). The results suggest that improving infrastructure, engaging communities, enhancing marketing, advancing research, and fostering strong collaboration are significant ways to unlock its ecotourism potential.

Economic corridors are long-term projects that must address challenges beyond physical infrastructure to become fully operational. Most of these challenges, including institutional coordination, logistical integration, and creating favorable conditions for trade and investment, require complex networks of interaction among the corridor agents. This study analyzed the actor network within the Bioceanic Road Corridor (BRC) "Mato Grosso do Sul—Ports of northern Chile" to assess how their roles and interactions influence the development of the project. Based on 240 surveys and the application of social network analysis (SNA), we mapped key relationships within the BRC. Our contributions extend the analysis of economic corridors from a relational space perspective, highlighting the influence of key actors in shaping the development of these projects. Our findings reveal poor coordination between the private sector and subnational public agencies, threatening the corridor’s success. Limited private sector involvement restricts opportunities for regional economic growth, investment, job creation, and trade. Additionally, weak coordination among subnational actors worsens institutional fragmentation, hindering the implementation of policies aligned with local needs. To avoid BRC becoming a "white elephant," institutional coordination must improve and incentives for private sector participation—such as public–private partnerships, tax incentives, and investment programs—are essential to unlock its potential for regional development.

Indonesia is recognized as one of the countries with abundant natural resources, especially in the mining sector. However, revenue from these natural resources have not significantly improved the population’s well-being or reduced poverty rate. Notably, some regions with high natural resource revenue still experience high poverty level. Therefore, this study delved into the intricate relationships between natural resource abundance and poverty dynamics in Indonesia. Utilizing panel data spanning from 2015 to 2022 across 444 regencies/cities, we employed advanced econometric techniques, Method of Moment Quantile Regression (MMQR), to unravel the nuanced effects of natural resource revenue on poverty rates. Moreover, our study challenged conventional linear analyses of the natural resource curse hypothesis, emphasizing the need for non-linear modeling approaches to capture the intricate dynamics at play. Our findings reveal a non-linear relationship between natural resource revenue and poverty, characterized by an inverted-N-shape, with significant impacts observed in lower and medium quantile groups. Surprisingly, the linkage between natural resource revenue–poverty does not appear in the high quantile group, suggesting that natural resource revenue is insufficient to benefit the region with severe/extreme poverty rate. Our research underscores the importance of considering cross-sectional dependence and employing robust estimation methods like MMQR to address complex interactions within panel datasets. These findings contribute to the ongoing discourse on natural resource management and poverty alleviation strategies, providing valuable insights for policymakers and researchers alike.

With deepening cooperation between China and ASEAN countries, the driving force of Chinese enterprises’ location choice for direct investment in ASEAN should not only consider their own competitive advantages but also consider environmental and resource factors such as geography, economy and culture of the host country. Therefore, this paper first expounds on the location choice of Chinese enterprises’ investment in ASEAN and then presents research hypotheses based on the enterprises’ own experiences and the three proximities of geography, economy and social culture. A Probit regression analysis model is adopted to analyze the evolutionary driving force of Chinese enterprises’ investment locations in ASEAN. The study reveals the following findings: First, Chinese enterprises’ investments in ASEAN countries exhibit a “clustering-dispersal” pattern in industries such as energy, transportation and real estate forming industrial clusters of various ASEAN cities. Second, the attributes of multinational corporations, including corporate characteristics, geographical factors, economic factors, and cultural factors, significantly influence the expansion of the ASEAN investment network, and heterogeneous investment preferences exist across different regions.

This paper measures the Financial Stability Sentiments Index (FSSI) for the economy of Pakistan, an interesting country case due to its resilient banking sector. We used a Natural Language Processing technique to quantify these sentiments from annual financial stability review reports published by the State Bank of Pakistan, central bank of Pakistan. The index captured events of high and low financial stress in Pakistan, such as the Global Financial Crisis and recent tightening by the Federal Reserve. Regarding the information content of our index, it serves as a leading indicator for selected indicators of financial soundness in Pakistan. Further, asymmetric analysis of the impact of financial stability sentiments on financial stability showed that improvements in the FSSI lead to a higher distance-to-default for two sets of diverse banking institutions in Pakistan, indicating improved financial stability as bank assets far outweigh their obligations. Finally, the index shows an intuitive and significant impact on selected financial soundness indicators as well as the real macroeconomic variables in Pakistan.

Climate change threatens the environmental and socio-economic sustainability of people living in the ecologically fragile hills of Northeast India. To respond effectively to these challenges, there is a need for an integrated vulnerability assessment to guide the formulation of adaptation strategies. Climate vulnerability refers to an area's susceptibility or inability to cope with the adverse impacts of climate change, including variability and extremes, highlighting the need to assess both environmental and socioeconomic factors. This study conducted a district-level assessment of climate vulnerability in Manipur using a Composite Vulnerability Index (CVI) that combined environmental (8 indicators) and socioeconomic (6 indicators) factors with an unequal weighting scheme. GIS techniques were employed to map the CVI, Environmental Vulnerability Index (EVI), and Socioeconomic Vulnerability Index (SVI), revealing spatial variations in climate vulnerability and its driving factors. The results of the CVI indicated that Imphal West District(CVI = 0.234) was the least climate-vulnerable, due to its low social vulnerability (SVI = 0.196) and intermediate EVI score (0.323). On the other hand, Thoubal emerged as the most climate-vulnerable district in the state because of its high social vulnerability. Districts such as Churachandpur (EVI = 0.742) exhibited high environmental vulnerability, whereas the Senapati District (0.227) experienced minimum vulnerability according to the EVI. Grouping of districts into low, medium and high climate vulnerability categories was validated using hierarchical cluster analysis. This underscored the significance of targeted interventions for districts experiencing different levels of climate vulnerability. The findings of this study may be relevant for similar contexts within the Indian Himalayan states, especially in tropical and subtropical regions where urgent climate adaptation measures are essential. Moreover, the methods show significant flexibility, enabling comparisons of vulnerability across districts of the region and elsewhere. Importantly, it can adjust indicators to anticipate future changes in socioeconomic conditions.