China has experienced sustained economic growth alongside major changes in agricultural institutions, food circulation, and market openness. Whether economic growth improves residents' dietary nutrition under these changing conditions remains unclear. We use annual data for China from 1961 to 2018 to examine the long-run relationship between gross domestic product growth and residents' dietary nutrition. We employ autoregressive distributed lag models to identify the long-run relationship in the full sample, and then conduct segmented regressions based on major historical phases of China's economic development. In the full sample, economic growth is positively associated with both nutritional quantity and nutritional quality in the long run, but this relationship is not stable over time. Before 1978, the relationship between economic growth and nutritional quantity in China is not significant, whereas after 1978 it becomes significantly positive. The relationship between economic growth and nutritional quality is significantly negative before 1978 and turns significantly positive thereafter. The relationship between economic growth and nutritional outcomes is clearly phase-specific, and its patterns differ between nutritional quantity and nutritional quality. Economic growth does not translate into nutritional improvement in a uniform way. In China, the relationship between economic growth and nutritional outcomes depends on the historical phase and differs between nutritional quantity and nutritional quality. Understanding the nutritional consequences of economic growth requires placing them in the broader context of institutional transformation and the evolution of the food system.
Real-world choices often require balancing short- and long-term goals. We reasoned that seemingly suboptimal single-trial decisions may reflect strategic planning over longer timescales. We demonstrate that male macaques freely navigating in virtual reality strategically aborted offers, forgoing immediate rewards to maximize session-long returns. This behavior was highly individual-specific, suggesting that macaques account for their own long-run performance. Reinforcement-learning models suggest that this strategy is supported by modular actor-critic networks in which a policy module optimizes long-term value while also incorporating state-action values for rapid policy adjustment. These models predict that policy changes for matched offers should emerge at offer presentation, even when aborts occur much later. Consistent with this prediction, units and population dynamics in dorsolateral prefrontal cortex (dlPFC), but not parietal area 7a or dorsomedial superior temporal area (MSTd), encoded upcoming reward-optimizing aborts at offer onset. These findings cast dlPFC as a specialized policy module within closed-loop behaviors.
Climate change and environmental degradation pose significant challenges to agrarian economies, yet the relationship between aggregate environmental performance and staple crop production remains insufficiently quantified. This study investigates the association between environmental performance, measured by the Environmental Performance Index (EPI), and cereal production in Ethiopia over the period 2010-2023 (non-interpolated data) and 2002-2023 (with interpolation for robustness) using an Autoregressive Distributed Lag (ARDL) bounds testing approach. Arable land, fertilizer consumption per hectare, agricultural labor, and annual precipitation are included as control variables. The long-run results indicate that arable land has a positive and statistically significant association with cereal production, while fertilizer consumption exhibits a negative and significant long-run association, consistent with soil degradation dynamics. In the short run, fertilizer use positively associates with production, whereas environmental performance has a negative and significant association, suggesting short-run adjustment costs. The long-run EPI coefficient is statistically insignificant, indicating that no systematic long-run trade-off is detectable in the data. The error correction term (-0.51) implies that 51% of disequilibrium is corrected annually. Diagnostic and stability tests confirm model adequacy for the full sample, while robustness checks using a restricted non-interpolated sample, a non-agricultural EPI sub-index, and inclusion of precipitation support the main findings. The results suggest that environmental policies may impose short-run production costs but do not persistently hinder long-run agricultural performance. Policies should link fertilizer subsidies to lime application on acidic soils and provide temporary compensation for farmers affected by land set-asides.
Malaria remains endemic in northern Ghana, with seasonal outbreaks placing significant strain on health facilities in the Tamale Metropolitan Area. Although climatic variability is known to influence malaria transmission, the specific short- and long-run relationships between temperature, rainfall, relative humidity, and malaria outcomes in this setting remain poorly understood. This study models the impact of climate variability on population-adjusted malaria morbidity in the Tamale Metropolitan Area using a time series approach. Monthly time series data on laboratory-confirmed malaria morbidity (converted to rates per 1,000 population), as well as temperature, rainfall, and relative humidity, were obtained from the District Health Information Management System and the Ghana Meteorological Agency for the period January 2014 to December 2020 (84 observations). The Autoregressive Distributed Lag (ARDL) bounds testing approach was selected for its ability to handle variables with mixed orders of integration (I(0) and I(1)) and to simultaneously estimate short- and long-run dynamics. No logarithmic transformation was applied, preserving direct interpretation of coefficients as changes in malaria rates per 1,000 population. The ARDL cointegration test confirmed a long-run equilibrium relationship between each climatic variable and malaria morbidity. In the short run, increases in relative humidity, temperature, and rainfall were significantly associated with higher malaria morbidity (p < 0.05 to p < 0.001). In the long run, however, temperature showed a significant inverse relationship: a one-unit (1 °C) increase in temperature was associated with a 0.37 case per 1,000 population decrease in malaria morbidity (p = 0.038). Model diagnostic tests (Ljung-Box and ARCH-LM) indicated that residuals were white noise, supporting model validity. Climatic variables, particularly temperature, play a significant but complex role in malaria transmission in the Tamale Metropolitan Area, with opposing short- and long-run effects. These findings support the development of climate-informed early warning systems tailored to northern Ghana. To strengthen local malaria control and climate adaptation strategies, future efforts should integrate intervention coverage and health system data, improve surveillance, and apply advanced time-series methods to better capture non-linear and delayed climate effects. Not applicable.
This study examines whether family governance moderates the productivity returns to structured management practices. Using combined data from the UK Management and Expectations Survey (MES) and the Annual Respondents Database X (ARDx) and applying a reformulated Mundlak model, we show that structured management practices are positively associated with labour productivity, but that family ownership significantly weakens their long-run productivity returns. This negative moderating effect is stronger for incentives-related and target-setting practices and is more pronounced among small and medium-sized enterprises and service-sector firms. Overall, our findings highlight execution credibility as a central mechanism linking firm governance structures to the economic returns of formal management systems. Formal management practices such as targets, key performance indicators (KPIs), and incentive schemes are widely promoted as tools to boost productivity, yet our study shows that they do not deliver the same long-run benefits across firms. Using UK firm-level data, we find that while structured management practices are generally associated with higher productivity, their long-run benefits are significantly weaker in family-owned firms, because informal family governance can undermine consistent and credible execution over time. This effect is especially pronounced for practices that rely on impartial performance evaluation and rule-based enforcement, as well as among SMEs and service-sector firms. The main implication of this study is that improving productivity requires not only the adoption of better management practices but also strengthening governance structures that support their effective execution, particularly in family firms.
This study investigates the relationship between life expectancy among older adults and key fiscal variables such as state development expenditure, central development expenditure, and pension expenditure, using an auto-regressive distributed lag model. The analysis explores both short- and long-run dynamics over an extended period. Results show that state and central development expenditures have a significant positive impact on the life expectancy of men aged 60 and above. However, lagged central development expenditure exerts a negative and statistically significant effect on the life expectancy of older adult women, suggesting potential gender disparities in the benefits of public spending. Bounds testing confirms a stable long-run association between the fiscal variables and life expectancy among older adults. The findings underscore the importance of inclusive and gender-sensitive development policies to enhance the quality of life for older adults in India, offering valuable insights for fiscal planning.
Stunting remains a major development challenge in many countries, including Ecuador. In this paper, I examine whether agrarian reform policies implemented during the 1960s and 1970s help explain long-run patterns of child stunting. The Ecuadorian reform relied on two distinct land allocation strategies: Public land transfers (PLT), designed to promote frontier settlement, and expropriation, aimed at redistributing land from large estates. Combining household survey data with historical maps and administrative records, I estimate the long-run relationship between these policies and child stunting by exploiting historical variation in land allocation across parishes. I find that areas exposed to PLT exhibit significantly lower rates of child stunting, while expropriation shows no robust association. Across specifications, PLT exposure is associated with stunting rates that are 3-17 percent lower relative to the mean. Cohort evidence further indicates that the relationship is stronger for mothers plausibly exposed to PLT during early childhood. Consistent with this pattern, mothers from more exposed PLT cohorts attained higher levels of education, suggesting that maternal human capital may be one channel linking frontier settlement policies to lower child stunting.
What is already known about the topic? Physician density is influenced by demographic and macroeconomic factors. However, most existing studies analyze these determinants in isolation or focus on short-term correlations, providing limited insight on their dynamic interaction over time. What does this study add to the literature? This study provides the first long-run analysis of physician density in Italy across distinct institutional regimes: the pre-National Health Service (NHS) period (1953-1978), the centralized NHS era (1979-2001) and the decentralized regional phase (2002-2020). Using Local Projections, we show that structural drivers have regime-dependent effects. Importantly, after 2001, demographic aging emerged as a key driver, but its impact has been offset by constraints from rising public debt. What are the policy implications? Rising demand for healthcare services, driven by population aging, is placing increasing pressure on the Italian healthcare system. In a publicly financed Beveridge-type system, addressing these pressures requires adequate fiscal capacity. Yet, in the European context, the scope for expanding public spending is constrained by fiscal rules. This creates a structural tension between growing healthcare needs and the resources available to address them. For this reason, physician workforce planning should be shielded from short-term budget pressures through a targeted fiscal mechanism - plausibly framed, within the broader EU fiscal framework, as a "health investment golden rule" - aimed at preserving long-horizon health-system capacity. This should not be interpreted as a general exemption for healthcare spending, but as a safeguard for expenditure related to workforce planning, training capacity, hiring continuity, and measures to reduce territorial imbalances. Italy has experienced profound demographic, technological and macroeconomic change since 1953, with effects on physician density shaped by changing institutional regimes. This study identifies the long-term determinants of physician density in Italy and assesses how their influence varies across three regimes: the pre-National Health Service (NHS) period (1953-1978), the centralized NHS era (1979-2001), and the mature decentralized regional phase (2002-2020). We use annual data (1953-2020) on physicians per 1000 inhabitants (a proxy for healthcare system capacity), age composition, a composite innovation index combining medical patents and total factor productivity (TFP), real GDP per capita, and public debt. Impulse responses are estimated using Local Projections, separately by institutional regime. Before 1978, physician density shows no significant response to aging, GDP or debt shocks. During 1979-2001, a one-standard-deviation (s.d.) shock to GDP growth is associated with a 0.8% increase in physician density over five years. After 2001, a one-s.d. shock to the aging index is associated with a 6% increase in physician density, while a debt shock offsets half of this effect. In the same period, technological innovation is associated with higher physician density. Institutional design affects the elasticity of physician density. Economic expansion supported physician growth under the centralized NHS, whereas in the decentralized regional phase demographic responsiveness is constrained by fiscal pressures. This points to the need for fiscal arrangements that protect long-run healthcare workforce planning, especially in European Beveridge-type publicly financed systems, where service capacity depends on both public budgeting and institutional coordination.
Statistical inference is based on the laws of probability. However, frequentists and Bayesians interpret probability differently. Frequentists interpret probability as a long-run frequency over repeated sampling. Consequently, frequentist probability statements are sampling probabilities from a sampling distribution. A sampling distribution is the hypothetical long-run distribution of a statistic we would expect to observe, assuming the population value is fixed. The frequentist interpretation is confusing and leads to the widespread misinterpretation of P-values and confidence intervals. Bayesians interpret probability as a strength of belief. Consequently, Bayesian probability statements are inferential probabilities. An inferential probability is a direct statement about the quantity of interest, that is, the truth of the hypothesis and the size of the treatment effect, given the data observed. As clinicians and researchers, we seek inferential probabilities ('What is the probability the treatment works given the study data?') not sampling probabilities ('If the treatment does not work, how surprising are the study data?'). I explore the frequentist and Bayesian perspectives on probability, address the barriers to adopting Bayesian methods, and make the case for Bayesian inference in anaesthesia research.
This paper analyzes the long-run associations between environmental, financial, macroeconomic, and healthcare factors on life expectancy in E7 countries over the period 1990-2023. Special emphasis is placed on PM2.5 air pollution exposure, which has become one of the key environmental factors influencing population health and longevity. The analysis examines the effects of domestic credit to the private sector (DCPS), foreign direct investment (FDI), inflation (INF), exposure to PM2.5 air pollution (PM2.5), immunization coverage (IMM), and hospital beds per 1,000 people (HBEDS) using life expectancy (LE) as the dependent variable. Second-generation panel unit root and cointegration tests are used in the empirical framework. FMOLS and DOLS estimators are then used. The CCEMG estimator and FE-DKSE are used to evaluate robustness. The findings show a stable long-run connection between the variables. Financial development and FDI are positively associated with LE, but inflation and PM2.5 exposure are negatively associated with LE. Immunization coverage is generally positively associated with life expectancy, while hospital beds are negatively associated with LE. The robustness estimations generally support the baseline findings. This study adds to existing research by examining how finances, economy, environment, and health care impact LE in the E7 countries. It takes into account the connections and differences between these nations. The findings highlight that financial growth, economic stability, clean environments, and preventive healthcare play crucial roles in long-term health outcomes for large emerging economies.
Bidis are the most commonly used smoked tobacco product in India. Despite their significant health burden, bidi taxation remains low and there are tax exemptions for small producers. We used a multistate life table model to project the 50-year impact of bidi tax reform under two scenarios: 10% and 30% tax-induced price increases combined with removal of small-producer exemptions. Outcomes included years of life gained (YLG), changes in direct health expenditures, indirect morbidity costs, economic output from averted premature mortality, consumer spending and tax revenues. Total economic effects were defined as reductions in direct health expenditures and indirect morbidity costs plus gains in economic output. Long-run monetary outcomes were discounted at 3%. A 10% price increase yields 21.78 million YLG (95% uncertainty interval (UI) 13.25 to 32.42 million) and Indian rupees (INR) 560.1 billion (0.25% of total health expenditure (THE)) in discounted health savings over 50 years; a 30% increase yields 47.95 million YLG (95% UI 29.17 to 71.37 million) and INR 1232.3 billion (0.54% of THE). Total economic effects reach INR 2530.8 billion (1.12% of THE) and INR 5557.7 billion (2.45% of THE) under the 10% and 30% scenarios, respectively. Discounted tax revenues increase by INR 519.9 billion and INR 1390.0 billion. Absolute gains are largest in Uttar Pradesh and West Bengal, while Uttarakhand, Haryana and Tripura show the highest per capita and proportional benefits. Strengthening bidi taxation and removing exemptions would substantially reduce smoking, improve health and generate significant long-term economic and fiscal gains.
This study examines the relationship between multidimensional economic insecurity, structural socioeconomic change, and female suicide vulnerability in China. The analysis employs a qualitative secondary-data approach using annual national time-series data for China covering 2000-2024, sourced from the World Health Organization Mortality Database, World Bank World Development Indicators, and International Labour Organization labour statistics. Descriptive trend and comparative analyses supported by graphical visualisation techniques were used to examine patterns and associations among the variables. The findings reveal a substantial long-run decline in the female suicide rate from 15.18 per 100,000 women in 2000 to 8.69 in 2024, although a mild increase was observed after 2020. Labour market indicators evolved unevenly: vulnerable employment declined markedly, wage employment increased, labour force participation fell gradually, and unemployment fluctuated within a narrow range. Among the indicators examined, vulnerable employment showed the strongest alignment with female suicide vulnerability, whereas unemployment displayed a weaker relationship. This study advances a gender-sensitive and multidimensional framework linking suicide vulnerability to labour market insecurity, employment structure, inequality, and demographic transformation, with implications for public health and labour policy. Cette étude examine la relation entre l'insécurité économique multidimensionnelle, les mutations socio-économiques structurelles et la vulnérabilité au suicide chez les femmes en Chine. L'analyse repose sur une approche qualitative exploitant des données secondaires — des séries chronologiques nationales annuelles pour la Chine couvrant la période 2000-2024, issues de la base de données sur la mortalité de l'Organisation mondiale de la Santé, des indicateurs du développement dans le monde de la Banque mondiale et des statistiques du travail de l'Organisation internationale du Travail. Des analyses descriptives des tendances et des comparaisons, appuyées par des techniques de visualisation graphique, ont permis d'étudier les schémas et les associations entre les variables. Les résultats révèlent une baisse substantielle à long terme du taux de suicide féminin, passant de 15,18 pour 100 000 femmes en 2000 à 8,69 en 2024, bien qu'une légère hausse ait été observée après 2020. Les indicateurs du marché du travail ont évolué de manière contrastée : l'emploi vulnérable a nettement reculé, l'emploi salarié a progressé, le taux d'activité a diminué graduellement et le chômage a fluctué dans une fourchette restreinte. Parmi les indicateurs examinés, l'emploi vulnérable présentait la corrélation la plus marquée avec la vulnérabilité au suicide féminin, tandis que le chômage affichait un lien plus faible. Cette étude propose un cadre d'analyse multidimensionnel et sensible à la dimension de genre, reliant la vulnérabilité au suicide à l'insécurité sur le marché du travail, à la structure de l'emploi, aux inégalités et aux mutations démographiques, avec des implications pour les politiques de santé publique et de l'emploi.
Artificial intelligence (AI) is reshaping national economies, yet country-level AI-macro relationships remain poorly understood. Using annual data for the United States and China, 1980-2020, we develop a four-layer triangulation framework-Pattern Causality, Granger causality, VECM-based cointegration, and lead-lag correlation-to map directional associations between AI activity indicators and macro aggregates through weighted networks and heatmaps. Three patterns recur. First, nonlinear AI-macro dependence is moderate and mostly positive, making AI indicators useful monitoring signals rather than stand-alone decision triggers. Second, publications and patents carry short-run predictive content in Granger tests, making them candidate early-warning indicators for macro surveillance. Third, cointegration places AI indicators mainly on the adjustment margin: Macro fundamentals condition long-run AI-macro co-movement more than AI indicators lead it. The international layer adds an important qualification. United States-China collaboration variables raise AI node centrality, especially for China, but a mechanical-expansion null benchmark shows that most of this increase is expected from enlarging the network; beyond-mechanical collaboration evidence concentrates in the cointegration layer. Overall, the US pathway is patent-oriented and selective, whereas China's is denser and more collaboration-intensive. The framework supports AI-macro risk monitoring and hypothesis generation, not structurally identified causal claims.
Reducing carbon emissions remains a major challenge for Lithuania under the European Green Deal, particularly due to the dominance of energy-related emissions and evolving economic dynamics. This study investigates the key drivers of CO₂ emissions, focusing on energy intensity, research and development (R&D), waste management, international legal compliance, economic growth, and trade openness over the period 1996Q1-2024Q4. To capture nonlinear, time-varying, and frequency-dependent relationships, the study employs advanced wavelet-based techniques, including Wavelet Power Spectrum, Wavelet Coherence, and Partial Wavelet Coherence. The findings reveal that energy intensity is the most dominant and persistent driver of emissions, exhibiting strong long-run effects, while economic growth also contributes positively, confirming the presence of scale effects. In contrast, R&D and institutional quality show conditional and time-dependent emission-reducing impacts, whereas waste management plays a relatively weak and indirect role. Based on these results, the study recommends prioritizing energy efficiency improvements, strengthening green innovation policies, enhancing institutional effectiveness, and accelerating the transition toward renewable energy systems to achieve sustainable emission reductions.
Aviation safety events, including incidents, accidents, and fatal crashes, often trigger surges of public attention that can reshape risk perceptions and erode trust in air travel. Understanding how public attention develops and evolves in response to such events is critical for informing crisis communication and public relations in the aviation industry. Using Google Trends Search Index (GTI) data for "Boeing" and "Airbus" as proxies for public attention and Aviation Herald safety event counts as indicators of safety performance, we examine the temporal dynamics between aviation safety events and collective attention during 2008 - 2025. Given the mixed integration orders across the time series, we employ the Autoregressive Distributed Lag (ARDL) bounds-testing framework and cross-validate the results using the Toda-Yamamoto causality approach. The ARDL results reveal a long-run equilibrium between public attention and safety performance for both manufacturers. The reparametrized Error Correction Model (ECM) reveals the short-lived nature of public attention, highlighting the importance of issuing timely, fact-based updates early in the news cycle to curb misinformation. This bursty pattern is further supported by the Toda-Yamamoto causality tests and visually demonstrated through the orthogonalized impulse-response functions (OIRFs). Finally, the asymmetric finding that only Boeing-related crashes exhibit a significant contemporaneous association with public attention may reflect heightened reputational salience surrounding the iconic manufacturer during the study period.
Waste biomass can deliver climate mitigation through two fundamentally different routes: durable carbon removal via biochar and fossil-jet displacement via sustainable aviation fuel (SAF). We harmonize published techno-economic assessments to a common 2024 delivered-to-market basis and compare both pathways as climate-service abatement cost (USD tCO 2 - 1 removed or avoided). For biochar, we combine an empirical cost-capacity relationship with audited net-removal factors. For SAF, we distinguish the commercially dominant waste-lipid route from the waste- and residue-derived pathways needed for larger long-run scale. Commercial biochar systems currently deliver a median abatement cost of about 177 USD tCO 2 - 1 (5th-95th percentile: 111-497 USD tCO 2 - 1 ), while waste-derived SAF centers near 448 USD tCO 2 - 1 . Current SAF supply is still overwhelmingly lipid-based, whereas the lignocellulosic and municipal-solid-waste routes needed for larger long-term aviation abatement remain earlier in commercialization. These differences suggest complementary timelines: biochar is a near-term removal option, while SAF remains a longer-term aviation decarbonization pathway.
Much debate has centered on the relative effects of economic and cultural factors on support for far-right parties. Recent work, however, has proposed a synthesis focused on the role of social status, a concept capturing a combination of economic position and social esteem. While previous studies have adduced suggestive evidence that status loss shapes far-right support, this paper presents the broadest empirical assessment of the proposition to date. Focusing on long-term status change, operationalized as intergenerational occupational mobility, we find a strong relationship between mobility and support for the far right across 11 European countries. Moreover, adopting a modeling approach that addresses confounding between status levels and status change, we demonstrate an asymmetry: while downward mobility predicts increased far-right voting, upward mobility has little effect. The findings suggest that long-run economic forces that have depressed the occupational prospects of native-born workers contribute to the far right's rise.
The transition to clean energy in the United States remains insufficient despite rising environmental concerns and increasing renewable energy adoption. This study investigates whether better institutional quality can effectively drive cleaner energy outcomes by examining the impact of governance alongside key macroeconomic factors. Using quarterly data from 1990 to 2024, the study employs a wavelet quantile regression approach to capture nonlinear and time-varying dynamics across short-, medium-, and long-run horizons. The findings reveal that economic growth, foreign direct investment, and trade openness positively influence renewable energy consumption, particularly over longer time horizons. In contrast, carbon emissions exhibit a negative relationship with renewable energy adoption. Surprisingly, institutional quality shows a predominantly negative effect, suggesting that stronger institutions may reinforce existing fossil fuel-based energy structures rather than accelerate transition. These results highlight the complexity of institutional roles in energy transformation and emphasize the need for targeted regulatory reforms to support renewable energy expansion in the United States.
We revisit the energy-growth-environment nexus in Saudi Arabia (1970-2023) and ask, for the first time in a single-country time-series setting, whether urbanisation and human capital moderate the energy-CO₂ elasticity. Within an augmented STIRPAT framework, we test moderation using orthogonalised interaction terms that remove mechanical multicollinearity, and we estimate the relationship with ARDL bounds testing, NARDL decomposition, Toda-Yamamoto causality, and FMOLS/DOLS/CCR. A stable long-run relationship is confirmed (F = 6.89; ECT = - 0.67). Energy consumption is the dominant driver of emissions (elasticity ≈ 0.94), while urbanisation and trade openness act as direct mitigating determinants. Crucially, the orthogonalised energy-urbanisation and energy-human-capital interactions are not statistically significant: once structural breaks and core covariates are included, urbanisation and human capital operate through direct channels rather than by bending the energy-emissions elasticity - a substantive null that contrasts with cross-country studies and constrains policy modelling. Causality is bidirectional between emissions and growth, and trade openness causes both emissions and energy use; the NARDL provides insufficient evidence to detect asymmetry, so the parsimonious linear specification is preferred for inference. For Saudi Arabia's net-zero-2060 target, these results imply that decarbonising the energy mix is indispensable, while Vision 2030's urban and human-capital investments yield direct emissions benefits.
Focusing on the nexus between digital governance and energy inequality, this paper examines whether government transparency reforms induced by public data openness improve governance efficiency while simultaneously exacerbating household energy inequality. We ask whether efficiency gains within China's governance system may come at the cost of increasing the vulnerability of households with weaker adaptive capacity, and whether the long-run environmental and governance benefits are sufficient to justify these short-run distributional costs. Drawing on micro-level data from the China Health and Retirement Longitudinal Study (CHARLS) spanning 2011-2020 and city-level data on the phased rollout of public data platforms, we employ a multi-period difference-in-differences framework to evaluate the impact of public data openness on household energy poverty. We construct a Multidimensional Energy Poverty Index (MEPI) to capture household-level deprivation in energy affordability, energy accessibility, and living environment conditions. The baseline results show that public data openness significantly increases household energy poverty, indicating an adverse impact on energy-related welfare. Heterogeneity analyses show that the adverse effects are concentrated among retired households and residents in cities with stringent environmental mandates, limited resource endowments, or net population outflows, where limited fiscal buffers make it difficult to cushion the regressive shocks associated with digital and green transitions. Mechanism analyses indicate that this effect operates mainly through two channels: enhanced environmental information transparency strengthens informal environmental regulation, while the diversion of governmental attention toward digital governance weakens energy subsidies and infrastructure investment, thereby intensifying the energy burden on vulnerable groups. Additional analyses reveal the dual nature of public data openness: it promotes green transition and governance efficiency while simultaneously reshaping the distribution of social resources. To address these challenges, we propose policy recommendations in three directions: a public data-driven cost-sharing mechanism, an offline proxy network, and a cadre evaluation system prioritizing energy equality.