This study investigates the dynamics of poverty persistence in the Sulawesi Corridor, Indonesia—encompassing the provinces of South Sulawesi, West Sulawesi, and Central Sulawesi—by analyzing socio-economic determinants and spatial interactions at the regency/city level. While poverty research in Sulawesi is extensive, most previous studies have relied on static panel data models, which fail to capture the inherently dynamic nature of poverty behavior. This study addresses these gaps by analyzing 43 regencies and cities over the 2017–2024 period using a Spatial Autoregressive Dynamic Panel Model. This framework simultaneously accounts for poverty inertia, contemporaneous spatial interactions, and spatio-temporal dependencies. The empirical results suggest a high degree of poverty persistence, indicating significant path-dependency. The estimation also reveals substantial spatial spillover effects, confirming that poverty does not occur in isolation. A key finding indicates that the Gini Ratio is the most consistently significant determinant, suggesting that poverty in this corridor is primarily driven by income inequality rather than a lack of aggregate output. Furthermore, the results points toward the presence of ‘Backwash Effects’, where economic growth and human capital accumulation in growth centers appear to absorb resources from neighboring areas, exacerbating poverty polarization. These findings underscore the necessity of shifting policy interventions from growth-centric models toward an inclusive cross-regional distributive framework to break the cycle of spatial poverty traps.
Regional differences in R D composition are often interpreted as signs of different institutional or structural profiles. Yet these differences may also be related to the overall size of regional R D activity. This paper examines that relationship across Türkiye’s NUTS-2 regions. Regional R D composition is measured by the log ratio of business to higher-education R D expenditure, using Eurostat data for 2021–2024. The baseline analysis covers 19 regions with available sectoral R D data and relates composition to the absolute size of regional R D expenditure. The results show a strong positive association between R D scale and BERD/HERD composition. This relationship is also visible in each individual year and remains stable across alternative specifications, influence checks and selected control variables. Additional sensitivity analyses that incorporate the seven regions with suppressed sectoral data also preserve the positive direction of the relationship under a wide range of assumptions. Because total GERD includes the R D components used to construct the BERD/HERD ratio, the results are interpreted as descriptive rather than causal. The findings suggest that regional R D composition should be read alongside the scale of regional R D activity before stronger conclusions are drawn about differences in regional research structures.
Expanding renewable energy in developing countries is essential for achieving global sustainable development and fighting climate change. However, many developing economies face financial constraints that limit their capacity to invest in renewable energy technologies despite increasing international climate commitments. This study examines the role of international public financial support in promoting renewable energy use across thirty-six developing countries from 2000 to 2020. It employs panel cointegration techniques and the pooled mean-group autoregressive distributed lag model to explore long-term relationships among renewable energy consumption, international public financial flows, income levels, per capita carbon emissions, and government effectiveness. Additionally, it uses quantile regression and panel causality analyses to ensure robustness. The quantile findings indicate that public investment flows have a positive and significant effect on renewable consumption at low-to-moderate quantiles, but become insignificant at higher quantiles, likely because external public finance is more effective in supporting countries at earlier stages of renewable energy adoption than those with more mature renewable energy systems. Income levels also positively influence renewable energy adoption, while government effectiveness shows no significant impact. The causality analysis indicates a bidirectional relationship between international financial support and renewable energy use, with income exerting a unidirectional influence on renewable energy consumption. The findings highlight the importance of strengthening international cooperation, improving the allocation of climate finance, and supporting strategic investments in sustainable energy infrastructure to achieve SDGs 7 and 13 in developing nations.
Global warming and the increased frequency of high-temperature episodes have not only heightened interest in understanding average temperatures but also reinforced interest in how temperature distributions are changing. This study examines the evolution of global temperature distributions by country from 1960 to 2021, using reference years for each two decades to make various comparisons. A key focus is the adherence to Zipf’s law in the upper portion of the distribution: Zipf’s law holds true when, upon ordering countries from most to least extreme temperatures, the drop between ranges follows a very regular pattern. The aim is to determine in which ranges Zipf’s law appears and how the exponent changes as the sample size increases. Finally, the study tests Eeckhout’s hypothesis, which posits a reduction in the coefficient when the sample size is increased under specific conditions. The results are conclusive: the more extreme the weather, the higher productivity, electricity consumption, health, and tourism activity the country will benefit.
We identify empirically the determinants of per-capita CO _2 emissions growth in 227 European NUTS-2 regions for the period 1995–2022. In order to account for geographical spillovers of unknown form, we employ Bayesian averaging of spatial autoregressive models, addressing uncertainty on the specification of spatial links across regions. Our results indicate that the initial level of emissions, the regional economic structure, population growth, the number of days requiring indoor cooling, as well as the number of cars per-capita, are robust determinants of per-capita emissions growth.
