Search Results (214)

This study explores the drivers of income inequality using crude oil prices, consumer prices, economic development, trade openness, unemployment, and human capital as predictors. Despite a lot of research conducted on income inequality, there have been very few studies capable of simultaneously analysing the influence of energy prices, macroeconomic conditions, trade openness, conditions in the labour market, and human capital, as well as accounting for the dynamic persistence and potential endogeneity of inequality across countries. To fill this research gap, based on a panel of 230 observations, analyses are run using pooled ordinary least squares, as well as fixed and random effects derived from model-selection tests that favour the random effects specification. An analysis using a dynamic panel data model was also carried out in this study. The empirical results show that crude oil prices, trade openness, and unemployment are all positively correlated with income inequality and that GDP per capita and human capital have a significant deterrent effect on the expansion of income inequality. With the random effects model, a US$1 increase in crude oil prices increases the Gini index by 0.0186 points; meanwhile, one-percentage-point increases in trade openness and unemployment contribute to increases in inequality of 0.0142 points and 0.722 points, respectively. On the other hand, a US$1000 increase in GDP per capita lowers the Gini index by about 0.0699 points, and an improvement of 0.1 point in human capital decreases inequality by approximately 1.497 points. Controlling for country-specific effects does little to show an association with consumer prices. The model accounts for 43.11 per cent of the variation in income inequality. The findings show that inclusive growth strategies, investment in human capital and labour-market policies are evidently pivotal to addressing inequality fostered by economic transformation and energy-price volatility. Full article

Background/Objectives: We aimed to evaluate the temporal associations and heterogeneous patterns between the Beijing Diagnosis-Related Group (DRG) 2.0 payment reform and hospitalization costs and resource utilization among patients receiving major colorectal cancer (CRC) surgery and to explore hospital adaptive cost adjustment behaviors under bundled payment constraints. Methods: Utilizing inpatient data of 1232 colorectal cancer surgical patients from a Beijing hospital spanning January 2021 to October 2024, we adopted segmented regression interrupted time-series analysis (ITSA), with April 2022 defined as the policy intervention point. The analysis used total hospitalization expenses, itemized costs, cost composition proportions, and length of stay (LOS) as outcome indicators, conducted heterogeneity analysis, and applied seasonal autoregressive integrated moving average (SARIMA) counterfactual forecasting as a supplementary sensitivity check. All medical expenditures were inflation-adjusted based on Beijing’s medical consumer price index (CPI), with 2024 as the base year. Results: After DRG implementation, total hospitalization costs showed an immediate decrease of 13,111.73 CNY and a sustained monthly downward trend of 1312.60 CNY. Medical consumable fees were the main component associated with total-cost reduction, and their proportion declined immediately by 4.1 percentage points. LOS showed no abrupt immediate decline but shortened by 0.22 days per month over the post-reform period. Heterogeneous association patterns were observed across selected clinical and treatment subgroups. SARIMA counterfactual forecasting provided supplementary, directional sensitivity evidence for the primary outcomes and was interpreted cautiously for volatile sub-item expenditures. Conclusions: DRG 2.0 reform was associated with lower hospitalization costs and improved bed-turnover efficiency among CRC surgical patients, mainly through reductions in consumable expenditures. Full article

The study uses a case study (Parliament House, Ghana) to identify a sustainable energy pathway for public institutions in emerging economies, from technical and economic viewpoints, towards the net-zero agenda. Technically, the study uses GIS (Google Earth Pro, v7.3.7) mapping and Python (Jupyter notebook from Anaconda, v4.20) simulation to assess rooftop/carport solar PV–grid integration and explore green hydrogen and ammonia productions. It combines a GIS rooftop solar resources assessment with a forward/backward sweep hosting-capacity analysis and a cascaded economic comparison of grid, hydrogen (H₂), and ammonia (NH₃) to inform decisions about RE investment scenarios in Ghana. The economic assessment uses net present value (NPV), internal rate of return (IRR), profitability index (PI), discounted payback period (DPP), and levelized cost of energy (LCOE, LCOH, and LCOA). A 6.3 MW (10,569 MWh) solar electricity system is proposed to meet the 2.56 MW (7554 MWh) demand with 3014 MWh excess. Hydrogen and ammonia production stood at 60.3 tons and 343,579 kg from excess electricity, respectively. The facility’s CO₂ contribution in 25 years period with the grid supply is 160,539 tons, while with PV deployment, it can save 211,611 tons. A total of GHS 58,558,962 (GHS 36,306,556 for local demand and GHS 22,252,405 for grid sales), GHS 12,328,785, and GHS 43,805,636 are required to set up the solar PV, hydrogen, and ammonia plants, respectively. Results from 100% local consumption and grid sales scenarios indicate an NPV of GHS 106.91, an IRR of 75%, a payback period of 3 years, a profitability index of 3.1, and an LCOE of GHS 0.68. An NPV of GHS 84.57 million, IRR of 56%, PI of 3.8, DPP of 4 years, and LCOE of GHS 1.06/kWh were recorded for the grid sales. Hydrogen sales had a negative NPV of GHS 16.78 million, a PI of 0.7, and an LCOH of GHS 87.2 per kg. Similarly, a negative NPV of GHS 70.72 million, a PI of 0.27, and an LCOA of GHS 29,419.55 per ton were recorded for the ammonia sales. The Parliament House can save 106.91 million GHS over 25 years if it chooses to go solar after meeting its local requirements. Results from the Python simulation show a 5.6% reduction in bus voltage for the system without PV, while the configuration with PV injections saw a voltage increase of up to 11.4%. The system loss increased 113.3 kW in case 1 to 1659.2 kW in case 2. Solar-to-grid is the recommended pathway, while H2/NH3 are not competitive under present costs. The sensitivity analysis shows that changes in key input variables (CAPEX, electricity input cost, and selling price) affect the prospective H₂/NH₃ sales under current market conditions in Ghana. Therefore, policymakers should make conscious efforts to lower these parameters (CAPEX and electricity input cost) to boost green hydrogen and ammonia penetration in the transition agenda. A new law is required to encourage consumers to sell to the grid rather than rely on the current net metering scheme, which limits prosumers’ generation to 500 kW and forbids grid sales. Full article

Food price inflation provides an important economic context for consumer behaviour related to food; however, its impact on sustainable and responsible food consumption remains understudied. This cross-sectional study analyzed self-reported changes in food-related behaviour among Polish consumers during a period of strong upward pressure on food prices and identified demographic and socioeconomic factors associated with the intensity of these changes. In June 2023, a CAWI survey was conducted among a quota sample of 1000 adults in Poland, representative in terms of age and gender. To assess changes in the analyzed areas of food-related behaviours (food procurement, shopping planning, meal preparation, use of food service establishments, consumption of selected food products, and food waste), the Friedman test and the Wilcoxon test with Holm correction were used. To examine the relationship between the reported changes and the demographic and socioeconomic characteristics of the respondents, a synthetic change-intensity index was constructed based on 52 items covering the six behavioural domains. The significance of the relationship was tested using Pearson’s chi-square test and ordinal logistic regression. Respondents reported changes in all areas analyzed. A decline in the consumption of selected food groups was observed, including fresh fruits and vegetables and fish, with the largest decline in consumption noted for alcoholic beverages. The extent of these changes varied significantly according to characteristics such as age, place of residence, employment status, source of income, and income level. The results indicate that high food price pressures were accompanied by multidimensional changes in consumer food-related behaviours, including more frugal management of food resources and reduced consumption of certain food products. These results underscore the importance of maintaining economic access to nutritionally dense foods, particularly among economically vulnerable households. Full article

Industrial consumers increasingly operate photovoltaic (PV) generation and battery energy storage systems (BESS) against volatile day-ahead electricity prices. This paper presents a simulation environment for a community of three heterogeneous industrial prosumers, anchored in twelve months of day-ahead prices from the Bulgarian Independent Energy Exchange (IBEX), commercial hardware envelopes, and the terms of a market offtake contract that indexes remuneration to the day-ahead price, passes negative prices through to the producer, and mandates curtailment in strongly negative periods. A mixed-integer linear programming (MILP) dispatch model with binary charge/discharge modes and endogenous PV curtailment is solved daily in independent and coordinated regimes, under cost-only and capacity-aware objectives, for Sofia and Stara Zagora. On an energy-only basis, before capacity charges, storage turns the community from a net payer (39.1 kEUR/yr grid-only; 13.1 kEUR/yr with PV) into a net earner (8.64 kEUR/yr independent; 10.12 kEUR/yr coordinated), and the battery retrofit more than doubles the merchant plant’s net revenue. Cost-optimal dispatch synchronizes charging and raises the coincident grid peak to 241 kW; a capacity-aware objective cuts it to 133–140 kW (−42–45%) for under 0.9 kEUR/yr foregone income; under the two tested capacity-charge conventions, only the capacity-aware schedule remains net-positive after the modeled charge. The coordination gain grows with the import price adder and remains positive across 15–45 EUR/MWh. Full article

This study investigates the empirical links between climatic/socio-economic factors and Consumer Price Food Indices (CPFIs) across 47 advanced and emerging economies from 2001 to 2022. Utilizing a balanced panel dataset compiled from the World Bank’s World Development Indicators, FAO databases, and UNDP Human Development Reports, the analysis applies fixed-effects and random-effects panel data models to evaluate the drivers of food price dynamics. The empirical results reveal that socio-economic variables, specifically the Human Development Index (HDI), food price inflation, and agricultural productivity, are consistently associated with food indices, underscoring the critical role of structural development and nominal inflationary pressures. Climatic factors, particularly temperature anomalies, also exert a significant impact: a one-degree Celsius increase in temperature anomalies is associated with a 0.82-unit rise in the food price index level, whereas expansions in forest area and agricultural land are linked to price reductions. These findings indicate that food price dynamics are shaped by the intricate interplay of climate variability and socio-economic conditions. Consequently, policy recommendations emphasize targeted investments in socio-economic development, climate adaptation measures (including support for climate-resilient agriculture), and sustainable land management (forest conservation and optimized land use) to enhance food system resilience and support long-term food security. Full article

The Baltic states disconnected from the Soviet-era BRELL ring and synchronized with the Continental European grid in February 2025, completing a decade of new electricity and gas interconnections in the Poland–Lithuania–Latvia–Estonia corridor. This study examines how energy security evolved across the four markets as those interconnections were added, drawing on ENTSO-E cross-border flow data, Eurostat energy balances and ENTSOG gas transmission statistics for 2018–2025, and builds a composite Baltic Regional Electricity Security Index (BRESI) from three dimensions of electricity security: supply diversification, interconnection utilization and import dependency, with price convergence analyzed separately. The gains were uneven. Lithuania still imported 47% of the electricity it consumed in 2024, whereas Poland covered almost all of its own demand. Synchronization first sent prices sharply higher, with Lithuanian peaks of EUR 325/MWh against a January average of EUR 88/MWh, before the market settled. Across the corridor, electricity links ran at about 60 to 70 percent of capacity and gas links at 35 to 50; security improved where flows and market coupling were in place, while idle capacity added little. The index rose for all four countries between 2019 and 2024; the improvement holds under every aggregation and weighting variant tested, and monthly price spreads averaged EUR 19/MWh between Poland and Lithuania against under EUR 5/MWh inside the Baltic market, a pattern that persisted after synchronization. On this basis the study argues for more storage, earlier delivery of the Harmony Link, and shared balancing to cope with variable renewable output. Full article

Background: Human papillomavirus (HPV)-attributable cancers remain largely preventable but continue to generate increasing treatment costs where vaccination and screening coverage are limited. We estimated direct inpatient pharmaceutical reimbursement attributable to HPV-related cancers in Bulgaria and examined the drivers of expenditure growth. Methods: National Health Insurance Fund reimbursement data (2021–2025) were analysed for antineoplastic medicines used to treat eight HPV-associated cancer sites. Site-specific population-attributable fractions (PAFs) were applied to estimate HPV-attributable expenditure. Uncertainty in PAFs was quantified using 10,000 Monte Carlo simulations and discrete attribution scenarios. Expenditure growth was decomposed into price, volume, and net product-entry/exit effects using Fisher indices. Expenditure was additionally expressed in constant 2021 euros using the Harmonised Index of Consumer Prices. Results: Estimated HPV-attributable inpatient pharmaceutical reimbursement totalled EUR 54.2 million (probabilistic median; 95% uncertainty interval: EUR 53.3–55.0 million). Cervical cancer accounted for 81.8% of the total. Results varied by less than ±6% across attribution scenarios and remained EUR 44.6 million when head-and-neck cancers were excluded. Annual expenditure increased from EUR 3.67 million in 2021 to EUR 19.89 million in 2025, representing a 5.4-fold nominal and 4.2-fold inflation-adjusted increase. Growth was concentrated in cervical cancer and was driven primarily by the introduction of new therapies rather than higher prices or greater use of existing medicines. Net product entry explained 88.8% of total log growth, while reimbursement prices for continuing products declined by approximately 31%. Pembrolizumab, first reimbursed for cervical cancer in 2023, accounted for EUR 16.03 million of cervical cancer expenditure in 2025. Conclusions: These ecological estimates indicate a rapid increase in HPV-attributable inpatient pharmaceutical reimbursement in Bulgaria, largely driven by cervical cancer and the introduction of immunotherapy. The findings have implications for budget forecasting, procurement planning, and economic evaluation of HPV prevention strategies. Full article

In South Korea, apartments dominate the residential housing market, accounting for 67.5% of total housing transactions in the fourth quarter of 2018. With this figure continuing to rise, apartments are the most significant asset for many families. Consequently, precise and timely valuations are crucial for stakeholders, including homeowners, buyers, and mortgage lenders. Traditionally, these stakeholders have relied on the qualitative judgments of certified real estate agents. Because of market opacity and low liquidity, agents often use a comparative approach, referencing the most recent transaction prices of nearby comparable apartments. However, this method is subjective, potentially biased, time-consuming, and costly. Our study seeks to offer a more objective and quantitative method for determining fair apartment prices in Korea, helping market participants make informed decisions. The prediction target is the monthly representative price of an apartment complex (the within-complex average of transaction prices), from which a complex-level price index is subsequently constructed; we distinguish this target from individual transaction prices throughout. By employing clustering methods to identify similar apartments and imputation techniques for missing values, our model demonstrates promising results, with a mean absolute percentage error as low as 5.38% in the worst-case (consecutive-mask) setting and 4.76% in the typical (random-mask) setting. Because the training (2006–2015) and test (2016–2022) periods are temporally disjoint, these figures reflect out-of-sample performance rather than in-sample fit. We further validate the resulting series against external references: it attains a 5.03% MAPE against actual transactions nationwide—outperforming the appraiser-based Kookmin Bank index (7.29%)—and, once aggregated, closely tracks the official KREB transaction-based index while becoming available earlier; complex-level Granger tests confirm that our series temporally leads the appraiser-based series about 1.5 times as often as the reverse. We also outline the missing-data assumptions under which the approach is valid. Full article

Many investors have relied on Bitcoin as a hedge against inflation. However, differences in inflation measurement and monetary policies across countries make it difficult to determine whether Bitcoin effectively serves as an inflation hedge. This study examined Bitcoin’s effectiveness as an inflation hedge in the United States and India using monthly data on Bitcoin returns and Consumer Price Index (CPI) changes from January 2015 to December 2024 (N = 118, after first-differencing and lag alignment). The study employed Ordinary Least Squares (OLS) models, bivariate Vector Autoregression (VAR) Granger causality tests, Bai–Perron Structural Break Analysis, Impulse Response Functions (IRFs), and Quantile Regression analyses. The findings revealed no significant relationship between CPI and Bitcoin returns in either the United States or India, providing no empirical support for the Fisher Hypothesis. However, Granger causality results showed that lagged Bitcoin returns significantly predicted future U.S. CPI values, while no such relationship was observed for India. The predictive power of the model for the U.S. was lost after October 2022 due to the crypto winter phenomenon. This indicates that Bitcoin is not used as a hedge against inflation but is rather considered a financially driven information asset, which is subject to market influences. Full article

Rural electrification in Sub-Saharan Africa faces a trilemma: cutting carbon emissions, making it economically viable, and achieving fair access to energy for all. This paper develops a multi-objective framework that optimises carbon revenue, net present value (NPV), total energy supply, cooking fuel (firewood and LPG), health costs, and benefit to society. The model uses continuous decision variables: daily energy allocation among four sources (solar, generator, firewood, LPG) to three population groups (men, women, children). The case study is a rural community of 7000 people in Nigeria (Tier 1 energy consumers). Six policy scenarios are considered: baseline, high carbon price, low carbon price, microfinance, government subsidy and community cooperative. This study compared algorithms and identified a hybrid Non-dominated Sorting Genetic Algorithm and Particle Swarm Optimisation II as the most suitable algorithm for solving the formulated optimisation problem. It was found that NPV and unit cost of energy would increase to $175,500 and 26.4 ¢/kWh, respectively, by increasing the price of carbon from $8/ton to $12/ton. Firewood generates health savings and carbon revenue in the range of $4100–$12,270/year. Prices below $8/ton do not induce optimal reconfigurations in the system. The best energy supply (2825 kWh/day) and the lowest unsatisfied demand occur in the government subsidy scenario with the greatest disparity index, displaying an equity-efficiency trade-off. The framework shows that sustainable access to energy can be unlocked using strategic integration of carbon finance, valuation of health benefits and equity constraints. Full article

This paper proposes a mathematical model of price change perception in economic environments. The model introduces the Kullback–Leibler (KL) divergence between the expected price and the observed price as an index of attentional salience and integrates Takemura’s (1998, 2021) Mental Ruler Theory with the attention framework based on KL information proposed by Itti and Baldi (2009). We refer to this model as the SKL (Sum of the Kullback–Leibler Divergence) model, which explains the psychological mechanism underlying price judgment processes. Within this framework, the evaluation function for price change judgments is formulated as the integral of attentional salience, where attention is represented by the KL divergence associated with price changes. The proposed model is evaluated using 18 years of quarterly data (2008–2026) from the Bank of Japan’s Opinion Survey on General Public’s Views and Behavior, together with corresponding Consumer Price Index (CPI) data. Its explanatory power is assessed by comparison with conventional linear models, traditional psychophysical function models, and models based solely on KL information. The results indicate that the proposed model provides relatively superior explanatory performance, particularly in capturing periods of substantial changes in perceived inflation. Full article

This study introduces a comprehensive framework for understanding sustainable online shopping preferences, validated using survey data collected in Serbia and Slovenia in 2025 (n = 572), thereby enhancing its generalizability. The primary aim of this research is to examine the extent to which specific environmental, social, and economic indicators influence decision-making processes for online purchasing and delivery. A detailed quantitative analysis was conducted using a structured questionnaire that included a wide range of variables related to online shopping behaviors and delivery preferences. The findings indicate that preferences for sustainability are inherently complex and multifaceted, shaped by critical factors such as environmental concerns, social responsibility, trust, skepticism towards sustainability claims, willingness to pay (WTP), and price sensitivity. Demographic variables, particularly gender and age, show consistent links to preferences for environmental considerations and corporate social responsibility (CSR), while income impacts trust-related behaviors and WTP. Furthermore, the analysis distinguishes between two distinct decision-making approaches: a value-driven sustainability cluster represented by EcoIndex, SocialIndex, and WTPIndex, and a cost-minimization strategy focused on price sensitivity (PriceIndex), with trust acting as a related yet separate factor (CredibilityIndex). Overall, this study emphasizes that a range of interconnected dimensions significantly shape sustainable online shopping preferences. The study was conducted in two developing European countries. Additionally, the findings highlight the need to address universal market barriers, such as price sensitivity, information asymmetry, and consumer skepticism. In a business context, they underscore the importance of adopting advanced analytical methods to enhance decision-making and optimize sustainable business strategies. Full article

Against the backdrop of intensifying global climate change, climate policy uncertainty (CPU) and investor sentiment have become critical factors influencing the stability of financial markets. In this study, a quantitative index of investor sentiment is constructed using stock trading volume, turnover rate, price-to-earnings ratio, circulating market value, and the consumer confidence index. The QVAR-DY model is employed to analyze the risk contagion mechanisms among CPU, investor sentiment, and China’s financial sub-markets across different quantiles. Furthermore, five machine learning models—LSTM, BiLSTM, CNN, XGBoost, and LightGBM—are used to forecast risk spillover indices, and their performance is compared with three benchmark models (ARIMA, Persistence, and HistMean) to systematically evaluate the advantages of machine learning models in capturing tail risk spillover effects. The findings reveal significant cross-market risk contagion in financial markets, characterized by asymmetry. The level of risk spillover under extreme conditions is substantially higher than under normal conditions, indicating high sensitivity to extreme events and major policies. CPU exhibits the most pronounced spillover effect on the money market, while investor sentiment has the greatest impact on the stock market. The stock, real estate, and commodity markets act simultaneously as sources of risk and receivers of shocks. In terms of forecasting performance, LightGBM performs best under normal conditions, whereas LSTM achieves the highest prediction accuracy under extreme conditions. Full article

Oral health problems among older adults represent a growing public health concern due to increasing life expectancy and treatment needs. This study aimed to assess dental treatment needs and cost burden within the context of oral health policies. This retrospective study included anonymized data from 250 patients aged ≥65 years (F/M: 121/129; 65–89 years). Sociodemographic characteristics, treatment needs, and costs were obtained from the Hospital Information Management System (HIMS). Costs were adjusted to 2025 Turkish lira values using the Consumer Price Index and converted to international dollars using purchasing power parity (PPP). Patients were classified by total treatment costs using K-means cluster analysis. Periodontal (61.2%), restorative (36.0%), and endodontic (41.2%) treatment needs, which are largely preventable through oral hygiene practices, were more frequent among patients with a lower mean age, whereas tooth loss and prosthodontic treatment needs (89.6%) increased with mean age. Cluster analysis identified two groups: a low-cost group (67.6%) and a high-cost group (32.4%). The high-cost group had a lower mean age (68.84 ± 4.27 years) compared to the low-cost group (70.73 ± 5.18 years), indicating that relatively younger patients needed more complex and costly treatments. Out-of-pocket payments were notable for prosthodontic and surgical treatments, although Social Security Institution (SSI) payments constituted most of the costs. Preventive and early dental care strategies are essential to reduce treatment complexity and cost burden among older adults within the framework of oral health policy. Full article