Search Results (530)

The COVID-19 pandemic triggered unprecedented economic disruptions, raising critical questions about the resilience and adaptability of macroeconomic productivity across countries. This study examines the impact of COVID-19 on macroeconomic efficiency and productivity dynamics in 37 OECD countries using quarterly data from 2018Q1 to 2024Q4. By employing a Slack-Based Measure Data Envelopment Analysis (SBM-DEA) and the Malmquist Productivity Index (MPI), we decompose total factor productivity (TFP) into efficiency change (EC) and technological change (TC) across three periods: pre-pandemic, during-pandemic, and post-pandemic. Our framework incorporates both desirable (GDP) and undesirable outputs (inflation, unemployment, housing price inflation, and interest rate distortions), offering a multidimensional view of macroeconomic efficiency. Results show broad but uneven productivity gains, with technological progress proving more resilient than efficiency during the pandemic. Post-COVID recovery trajectories diverged, reflecting differences in structural adaptability and innovation capacity. Regression analysis reveals that stringent lockdowns in 2020 were associated with lower productivity in 2023–2024, while more adaptive policies in 2021 supported long-term technological gains. These findings highlight the importance of aligning crisis response with forward-looking economic strategies and demonstrate the value of DEA-based methods for evaluating macroeconomic performance beyond GDP. Full article

This study evaluates the risk-adjusted performance of Hospitality REITs using multi-factor asset pricing models and downside risk measures with the aim of assessing their diversification potential and crisis sensitivity. Unlike prior studies that examine REITs in aggregate, this study isolates Hospitality REITs to explore their unique cyclical and macroeconomic sensitivities. This study looks at the risk-adjusted performance of Hospitality Real Estate Investment Trusts (REITs) in relation to more general REIT indexes and the S&P 500 Index. The study reveals that monthly returns of Hospitality REITs increasingly move in tandem with the stock markets during financial crises, which reduces their historical function as portfolio diversifiers. Investing in Hospitality REITs exposes one to the hospitality sector; however, these investments carry notable risks and provide little protection, particularly during economic upheavals. Furthermore, the study reveals that Hospitality REITs underperform on a risk-adjusted basis relative to benchmark indexes. The monthly returns of REITs show significant volatility during the post-COVID-19 era, which causes return-to-risk ratios to be below those of benchmark indexes. Estimates from multi-factor models indicate negative alpha values across conditional models, indicating that macroeconomic variables cause unremunerated risks. This industry shows great sensitivity to market beta and size and value determinants. Hospitality REITs’ susceptibility comes from their showing the most possibility for exceptional losses across asset classes under Value at Risk (VaR) and Conditional Value at Risk (CvaR) downside risk assessments. The findings have implications for investors and portfolio managers, suggesting that Hospitality REITs may not offer consistent diversification benefits during downturns but can serve a tactical role in procyclical investment strategies. Full article

Historical buildings are exposed to an increased risk of fire. The direct influence comes from the buildings’ structural design and the fire protection level. The fundamental principle for reducing the loss of heritage value in historical buildings due to fire is fire protection, as part of crisis management. This article focuses on selected castle buildings from Slovakia. Three castle buildings were selected based on their location in the country. All of them are currently used for museum purposes. Using an analytical form, we assessed fire hazards and fire safety measures in two parts, calculated the fire risk index, and proposed solutions. Qualitative research, which is more suitable for the issue at hand, was used to evaluate the selected objects. The main methods used in the research focused on visual assessment of the current condition of the objects and analysis of fire documentation and its comparison with currently valid legal regulations. Based on the results, we can conclude that Kežmarok Castle (part of the historical city center) has a small fire risk (fire risk index = 13 points). Trenčín Castle (situated on a rock above the city) and Stará Ľubovňa Castle (situated on a limestone hill outside the city, surrounded by forest) have an increased risk of fire (fire risk index = 50–63). Significant risk sources identified included surrounding forest areas, technical failures related to outdated electrical installations, open flames during cultural events, the concentration of highly flammable materials, and complex evacuation routes for both people and museum collections. Full article

Background: The global impact of the COVID-19 pandemic has significantly influenced elderly functionality, particularly in terms of balance, gait, and independence in daily activities. This study sought to evaluate how these aspects have changed over the course of the health crisis. Methods: We employed the Tinetti scale for assessing balance and gait, and the Barthel Index for measuring functional independence, conducting a comparative analysis of scores before and after the onset of the pandemic in a sample of elderly individuals. Results: Our findings indicated an increase in Tinetti scores, suggesting some improvement in balance and mobility, albeit with marked variability across participants. On the other hand, Barthel scores showed a significant decline, pointing to a reduction in functional independence. Conclusions: These results suggest that the impact of COVID-19 on elderly functionality is not uniform, highlighting the need for personalized rehabilitation strategies. Such strategies should not only focus on physical recovery but also consider the psychological and social repercussions of the pandemic to fully address the diverse needs of this vulnerable population. Full article

Urban mobility resilience plays a central role in sustainable urban planning discussions, especially considering the challenges of extreme events, climate change, and the increasing scarcity of fossil fuels. This study evaluates urban mobility resilience in Petrópolis (RJ), incorporating socio-spatial heterogeneity and energy vulnerability. This research fills methodological gaps in the literature by proposing a composite resilience index that integrates technical, socioeconomic, and fossil fuel dependency variables within a robust multicriteria framework. We selected eleven variables relevant to urban mobility and organized them into inference blocks. We normalized the variables using Gaussian functions, respecting their maximization or minimization characteristics. We applied the Analytic Hierarchy Process (AHP) to assign weights to the criteria and then aggregated and ranked the results using multicriteria analysis. The final index represents the adaptive capacity of urban territories facing the energy crisis, and we applied it spatially to the neighborhoods of Petrópolis. The analysis identified a significant concentration of neighborhoods with low resilience, particularly in quadrants, combining deficiencies in public transportation, high dependence on fossil fuels, and socioeconomic constraints. Factors such as limited pedestrian access, insufficient motorized public transport coverage, and a high proportion of elderly residents emerged as significant constraints on urban resilience. Intervention strategies that promote active mobility, improve accessibility, and diversify transportation modes proved essential for strengthening local resilience. The results emphasize the urgent need for public policies to reduce energy vulnerability, foster active mobility, and promote equity in access to transportation infrastructure. Full article

In recent years, heavy metal pollution in farmland soil has become a crisis due to human activities or natural impacts, with particular emphasis on cases from China, where this issue is prominent, greatly affecting crop production and food safety. In the context of a low heavy metal (HM) content in farmland soil, which is difficult to monitor in real time, effective and rapid monitoring of soil plays a decisive role in subsequent targeted protection measures. To this end, this paper provides a narrative review of the application of spectral sensing technology on the basis of the quantitative inversion of heavy metal content in farmland soil using different platforms (ground, airborne, and spaceborne). The sensing process evaluates the mechanism by which soil produces different weak spectral features from the perspective of the heterogeneity of farmland soil. Different methods used for the quantitative inversion of heavy metals (by studying the correlation between soil heavy metals and organic matter, clay minerals, metal oxides, crop vegetation index, etc.) and their feasibility were clarified. At the same time, relevant research on key technologies used in various processes—such as follow-up pretreatment, spectral feature extraction, and the establishment of inversion models for spectral data of different farmland soil types—was summarized, with a primary focus on cases in China. Finally, the challenges, applications, and research directions related to heavy metal spectral inversion in farmland soil were discussed. Full article

The implications of digital finance for financial stability has come under serious scrutiny since the aftermath of the 2008 global financial crisis (GFC). Empirical evidence on this nexus are somewhat inconsistent and ambiguous. This study therefore attributes this puzzle to multiple structural breaks (MSBs) which were long neglected by previous studies. Consequently, this study aims to identify possible MSBs in the digital finance–stability nexus and examine if its impact is consistent/weakened in the presence of MSBs in a sample of 41 developing African economies for the 2004–2023 periods. Results from the PCA index generation report that instability is more susceptible to bank crisis/Z-score. Again, the panel extension of BP98 MSBs detection identified three breaks with their confidence intervals overlapping the periods of the 2006–2011 GFC/subprime mortgage crises, the 2012–2016 Br-exit referendum and the 2017–2021 COVID 19 pandemic/Ukraine war. The quantile regression methodology also shows that these breaks weaken the impact of digital finance (i.e., mobile banking and internet banking) on financial stability, particularly for economies at lower quantiles of financial stability but with marginal effects for economies at higher quantiles. The study concludes that digital finance can stabilize the financial system of developing economies when shocks from structural breaks are controlled. Therefore, the study contributes to knowledge by developing a new econometric model for BP98 panel extension of MSBs detection, calibrating an index for financial stability and detecting valid break dates for three major breaks. Structural and financial development through policy coordination to forestall the effects of structural breaks were recommended. Full article

This study investigates the cross-country spillover effects of investor sentiment, specifically Fear and Greed, between the United States and South Africa, within the broader context of increasing global financial integration and behavioral finance. Using monthly data from June 2007 to June 2024, this research constructs and tests the validity of a South African Fear and Greed Index, adapted from CNN’s U.S.-centric index, to better capture the unique dynamics and contribute to an alternate sentiment index for an emerging market. Employing the Diebold and Yilmaz (DY) connectedness framework, this study quantifies both static and dynamic spillover effects via a vector autoregression-based variance decomposition model. The results reveal significant bidirectional sentiment transmission, with the U.S. acting as a dominant net transmitter and South Africa as a net receiver, along with notable cross-country effects closely linked to the global economic trend. Spillover intensity escalates during periods of global economic stress, such as the 2008 financial crisis and the COVID-19 pandemic. The findings highlight that the USA significantly influences South Africa and that the adapted SA Fear and Greed Index better accounts for South African market conditions. Full article

This paper investigates the spillover effects and transmission networks of systemic risk within China’s national economic sectors under extreme conditions from both time and frequency domain perspectives, building upon the spillover index methodology and calculating the ∆CoVaR index for Chinese industries. The findings indicate the following: (1) Extreme-risk spillovers synchronize across industries but exhibit pronounced time-varying peaks during the 2008 Global Financial Crisis, the 2015 crash, and the COVID-19 pandemic. (2) Long-term spillovers dominate overall connectedness, highlighting the lasting impact of fundamentals and structural linkages. (3) In terms of risk volatility, Energy, Materials, Consumer Discretionary, and Financials are most sensitive to systemic market shocks. (4) On the risk spillover effect, Consumer Discretionary, Industrials, Healthcare, and Information Technology consistently act as net transmitters of extreme risk, while Energy, Materials, Consumer Staples, Financials, Telecom Services, Utilities, and Real Estate primarily serve as net receivers. Based on these findings, the paper suggests deepening the regulatory mechanisms for systemic risk, strengthening the synergistic effect of systemic risk measurement and early warning indicators, and coordinating risk monitoring, early warning, and risk prevention and mitigation. It further emphasizes the importance of avoiding fragmented regulation by establishing a joint risk prevention mechanism across sectors and departments, strengthening the supervision of inter-industry capital flows. Finally, it highlights the need to closely monitor the formation mechanisms and transmission paths of new financial risks under the influence of the pandemic to prevent the accumulation and eruption of risks in the post-pandemic era. Authorities must conduct annual “Industry Transmission Reviews” to map emerging risk nodes and supply-chain vulnerabilities, refine policy tools, and stabilize market expectations so as to forestall the build-up and sudden release of new systemic shocks. Full article

The current study examines the application of advanced machine learning (ML) techniques for forecasting credit risk in Islamic (participation) and traditional banks in the United Kingdom in 2010–2023. Leveraging an equally weighted panel dataset and guided by robust empirical literature, we integrate structural econometric modeling—i.e., the stochastic frontier approach (SFA) to measuring the Lerner index of market power—with current best-practice tree-based ML algorithms (CatBoost, XGBoost, LightGBM, and Random Forest) to predict non-performing loans (NPLs). The results show that bank-level financial performance measures, particularly loan ratio, profitability, and market power, outperform macroeconomic factors in forecasting credit risk. Among the models tested, CatBoost was more accurate and explainable, as confirmed by SHAP-based explainability analysis. The implications of the research have practical applications for risk managers, regulators, and policymakers in terms of valuing the explanatory power of explainable AI tools to enhance financial oversight and decision-making in post-crisis UK banking. Full article

Drought, a natural phenomenon intricately intertwined with the broader canvas of climate change, exacts a heavy toll by ushering in acute terrestrial water scarcity. Its ramifications reverberate most acutely within the agricultural heartlands, particularly those nestled in arid regions. To address this pressing issue, this study harnesses the temperature vegetation dryness index (TVDI) as a robust drought indicator, enabling a granular estimation of land water content trends. This endeavor unfolds through the sophisticated integration of geographic information systems (GISs) and remote sensing technologies (RSTs). The methodology bedrock lies in the judicious utilization of 72 high-resolution satellite images captured by the Landsat 7 and 8 platforms. These images serve as the foundational building blocks for computing TVDI values, a key metric that encapsulates the dynamic interplay between the normalized difference vegetation index (NDVI) and the land surface temperature (LST). The findings resonate with significance, unveiling a conspicuous and statistically significant uptick in the TVDI time series. This shift, observed at a confidence level of 0.05 (Z_S = 1.648), raises a crucial alarm. Remarkably, this notable surge in the TVDI exists in tandem with relatively insignificant upticks in short-term precipitation rates and LST, at statistically comparable significance levels. The implications are both pivotal and starkly clear: this profound upswing in the TVDI within agricultural domains harbors tangible environmental threats, particularly to groundwater resources, which form the lifeblood of these regions. The call to action resounds strongly, imploring judicious water management practices and a conscientious reduction in water withdrawal from reservoirs. These measures, embraced in unison, represent the imperative steps needed to defuse the looming crisis. Full article

The “Grain for Green” policy has led to a reduction in cultivated land area in the Loess Plateau, intensifying the conflict between ecological conservation and food security. As a key strategy to mitigate this tension, irrigated farmland has undergone significant changes in both its spatial extent and water consumption, which may further exacerbate the water crisis. Hence, the spatio-temporal dynamics and driving forces behind these changes require greater attention and have not yet been comprehensively explored. This study integrates multi-source datasets and employs piecewise linear regression and the Logarithmic Mean Divisia Index (LMDI) model to analyze the spatio-temporal evolution of cultivated land and irrigation water use. Furthermore, it quantifies the contributions of key factors such as cultivated land area, irrigation intensity, and crop planting structure to irrigation water dynamics. The results show that (1) The total cultivated land area in the Loess Plateau decreased by 12.4% from 1985 to 2020, with increases primarily concentrated along the Yellow River between Hekou and Longmen, while decreases were predominantly observed around major cities such as Xi’an, Taiyuan, and Yuncheng. Conversely, the irrigated area exhibited an overall upward trend, with minor declines occurring between 1977 and 1985. (2) While the total irrigation water use increased overall, piecewise linear regression analysis identified four distinct phases, with the first three phases showing growth, followed by a decline after 2001. (3) The expansion of agricultural irrigation areas emerged as the primary driver of increased irrigation water use, whereas advancements in irrigation efficiency effectively reduced water consumption. This study provides novel insights into the spatio-temporal dynamics of irrigation water use in the Loess Plateau and offers valuable guidance for optimizing water resource management and advancing sustainable development in the region. Full article

This study examines the impact of economic policy uncertainty (EPU) on agricultural land conversion. Using a newspaper-based index of EPU and a comprehensive panel dataset covering 270 prefecture-level cities in China, we estimate a city fixed effects model to explore this relationship. Our results indicate that a one-standard-deviation increase in EPU leads to a 22.2% increase in the conversion of agricultural land to urban residential, commercial, and industrial uses. This finding suggests that the surge in EPU triggered by the global financial crisis accounts for approximately 45% of the increase in agricultural land conversion. The adverse effect on agricultural land preservation mainly stems from intensified fiscal pressures and heightened demands on local governments to meet economic growth targets. To address potential endogeneity concerns, we employ the one-period lagged U.S. EPU index and its temporal variations as an instrument for China’s EPU, leveraging cross-country spillover effects. Our instrumental variable estimates confirm the validity of the land conversion effect and its underlying mechanisms. Furthermore, we find that the effects of EPU are particularly pronounced in cities located in non-eastern China and those that depend heavily on fixed asset investment for local economic development. Finally, our analysis of potential policy interventions to mitigate EPU-induced agricultural land loss suggests that strengthening market-oriented reforms and reducing province-level quotas on agricultural land conversion can effectively offset the impact of rising EPU. Full article

Geographic Information Systems and the use of thematic maps have become well-established tools in archaeology. However, not all the sectors of archaeology still take advantage of these technologies. One such sector is numismatics, where there are still relatively few works on the implementation of coin spatial databases and the related maps. This can be verified both in academic journals indexed in major scientific databases (such as Scopus, ScienceDirect, and Web of Science) and in broader platforms like Google Scholar. In this paper, in an attempt to begin filling the gap, the methodology and results of the creation of the GIS and the Atlas of Antoniniani in Sicily are presented. The second half of the third century ASD is an interesting period because of the socioeconomic crisis that characterized it. The Atlas serves as a useful tool for providing a fresh new insight into the economy and coin circulation during this time. Full article

Sustainable agricultural development in China in the face of growing environmental concerns relies critically on how well regulatory policies strengthen agricultural resilience. This study aims to systematically investigate the impact of air pollution on agricultural economic resilience and its mechanisms of action and to explicitly assess the moderating role of environmental regulation. This study develops a thorough index system that evaluates agricultural economic resilience in three areas: risk resistance and recovery, adaptive adjustment capacity, and restructuring innovation. Panel data from 30 Chinese provinces from 2000 to 2023 is used to achieve this. The implications of air pollution and its diverse consequences on agricultural economic resilience are systematically assessed using a two-way fixed-effects and moderating-effects model. The following are the primary conclusions: First, air pollution has a significant negative impact on the economic resilience of agriculture. This conclusion holds after considering the endogeneity problem and a series of robustness tests, such as the exclusion of samples, random sampling, and quantile regression. Second, different dimensions of agricultural economic resilience, intensity levels, and economic growth phases influence how much air pollution reduces agricultural economic resilience. Notably, at various stages of economic growth, air pollution steadily weakens the economic resilience of agriculture. In particular, the impact is more pronounced in the post-financial-crisis phase of domestic demand expansion and the phase of financial clearing and high-quality development. According to a dimensional perspective, air pollution significantly reduces the farm sector’s capacity to endure and recover from dangers while also making adaptive modifications easier, and the impact on transformational innovation is not significant. In terms of intensity, in contrast to places with higher resilience, those with lower resilience are disproportionately more adversely affected by air pollution. Third, environmental control mitigates some of the detrimental effects of air pollution on agricultural economic resilience. Based on these results, this study calls for stricter air pollution control measures, strengthens environmental regulatory support for agricultural resilience, and demonstrates region-specific governance solutions to guarantee the stability and sustainability of the agricultural economic framework. Full article