Understanding the determinants of electricity consumption is essential for designing effective economic and energy policies in advanced economies. This study examines the macroeconomic, institutional, and environmental factors influencing electricity consumption in 19 Euro Area countries during 2006–2024. Using a balanced panel dataset and a fixed-effects regression model, the analysis examines the associations between electricity consumption and GDP per capita, manufacturing value added, regulatory quality, electricity prices, renewable energy share, and heating degree days. The results indicate that GDP per capita, manufacturing value added, and regulatory quality are positively associated with electricity consumption, suggesting that higher levels of economic development, industrial activity, and institutional quality are associated with higher electricity demand. In contrast, electricity prices and renewable energy are negatively associated with electricity consumption, highlighting the importance of market incentives and structural changes related to the energy transition. Heating degree days exhibited the strongest estimated association with electricity consumption, highlighting the importance of climatic conditions across the Euro Area. The study contributes to the energy economics literature by providing an integrated assessment of economic, institutional, and environmental drivers of electricity consumption within a highly integrated economic region. The findings offer relevant implications for policymakers seeking to balance economic growth, energy transition objectives, and long-term electricity demand management.
The European Union has mandated digital reporting of cross-border VAT transactions from 2030, yet quasi-experimental evidence on the official compliance gap remains limited and does not cover the full range of national transaction-reporting architectures. This paper estimates their effect on that gap in 24 member states over 2000 to 2023, coding twelve mandates from the underlying legal instruments and applying the Callaway and Sant’Anna framework with never-treated comparisons. The baseline staggered estimate indicates a 4.23 percentage point reduction (95% CI [−6.45, −1.83]), remaining between 3.73 and 5.43 points across nineteen specifications including an imputation estimator and a neighbour-excluding comparison, and 2.76 under the most conservative identification check. Point estimates more than triple over five years. Pre-adoption coefficients are individually indistinguishable from zero though jointly significant, and formal sensitivity analysis shows the adoption-year and average post-adoption effects withstand modest though not large parallel-trend violations. The results do not show continuous reporting outperforms periodic reporting, and exploratory analysis detects no capacity moderation. What orders the cohort estimates is the completeness of the obligation, since the three mandates reaching one side of the transaction or part of the taxpayer population produce the three weakest effects. Findings support the fiscal premise of the VAT in the Digital Age reform and counsel patient evaluation of the rollout.
This study examines the effects of population, unemployment rate, construction costs, income per capita, and interest rates on housing prices using annual data from 1990 to 2024. Adopting time series econometric analyses, including stationarity, the ARDL model, VAR, Granger causality and dynamic estimation of VDC and IRF. The results confirm a long-run equilibrium relationship between housing prices and the selected macroeconomic variables. Income per capita and construction costs positively influence housing prices, whereas interest rates have a significant negative effect. In the short run, only income per capita is significant. The findings provide important policy insights for improving housing affordability through sustainable income growth, prudent monetary policy, and efficient housing development. Future studies should incorporate regional and institutional factors to better explain housing price dynamics.
The rapid digitalisation of retail banking has been promoted as a driver of efficiency and innovation. However, when digital strategies prioritise cost reduction over accessibility, they can generate financial exclusion among older adults. This paper examines how citizen mobilisation can place age-related financial exclusion onto corporate and regulatory agendas, using the Spanish petition “Soy mayor, pero no idiota” as a single case study. Launched in December 2021 by a 78-year-old retired physician, the petition gathered nearly 650,000 signatures and denounced exclusion caused by branch closures and forced digital migration. Drawing on agenda-building theory and Miguel Reale’s three-dimensional theory of law, the analysis traces how a private grievance became a public and institutional problem. Within weeks, Spanish banking associations introduced inclusive measures. Shortly afterwards, Law 4/2022 was approved. While the legislative process had already begun months earlier, the petition coincided with—and may have contributed to—specific banking- and age-related provisions. The findings show that digital banking strategies can heighten age-related vulnerability when they ignore digital literacy and accessibility gaps. Situating the case within the financial-inclusion literature (including the FATF 2025 guidance), the study also highlights unintended consequences of digitalisation such as over-indebtedness, scams and privacy risks. Citizen mobilisation, framed around dignity, prompted industry self-regulation and reinforced legislative attention to inclusion.
Understanding the relationship between economic growth, energy use, and environmental degradation remains a key challenge for resource-dependent economies undergoing energy transition. This study re-examines the effects of economic growth, energy consumption, renewable energy, and capital formation on CO2 emissions in Kazakhstan using annual data for 1992–2024. To account for structural changes and ensure robust inference, the analysis employs the Bai–Perron structural break test, the Autoregressive Distributed Lag (ARDL) approach, and alternative cointegration estimators including Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegrating Regression (CCR). The results reveal a stable long-run relationship among the variables. Economic growth and energy consumption significantly increase CO2 emissions, indicating the persistence of a carbon-intensive growth pattern in Kazakhstan. The effect of renewable energy is not robust across estimation techniques and does not provide consistent evidence of an emissions-reducing impact. Capital formation also shows limited explanatory power for long-run environmental outcomes. Overall, the findings suggest that Kazakhstan has not yet achieved a decoupling between economic growth and environmental degradation. The study contributes to the literature by jointly incorporating structural breaks, multiple cointegration estimators, and an extended sample period within a country-specific framework. The results imply that expanding renewable energy capacity alone may be insufficient to improve environmental quality, highlighting the need for broader structural transformation and low-carbon development strategies.
The existing empirical literature on Morocco has examined FDI and economic growth, taxation and growth, and taxation and FDI separately. This study addresses this gap by investigating taxation’s moderating role in the FDI–growth nexus using Moroccan data from 1990 to 2024 and an Autoregressive Distributed Lag (ARDL) bounds-testing approach. The findings show that FDI is positively associated with long-run GDP growth, real GDP, and GDP per capita, whereas the aggregate fiscal burden and its interaction with FDI are negatively associated with these outcomes. Nevertheless, the marginal association of FDI remains positive across Morocco’s observed tax range, although it declines by 4.11%, 31.08%, and 13.47%, respectively. These findings show that the realised fiscal burden conditions the FDI–growth relationship.
This article examines how dollarization reinforces the vulnerability of strategic sectors that are highly dependent on imports, using the Lebanese pharmaceutical sector as a case study. To this end, it employs a recursive dynamic computable general equilibrium model calibrated on a 2019 social accounting matrix to assess the effects of exchange rate shocks, constraints on access to foreign currency, and the weakening of healthcare financing mechanisms. The results show that these effects are transmitted mainly through three channels: the pass-through of import prices, the contraction of imports resulting from foreign currency scarcity, and the loss of household purchasing power resulting from the increase in out-of-pocket healthcare expenditures. The simulations reveal an increase in pharmaceutical prices, a decline in imports, a contraction in effective demand, and a deterioration of sectoral equilibria. These effects become particularly pronounced when price shocks and foreign currency constraints occur simultaneously. The results also highlight the central role of institutional healthcare financing mechanisms in amplifying or mitigating the effects of the crisis. The article therefore contributes to the literature on dollarized economies by proposing a conceptualization of sectoral vulnerability under dollarization, applicable to essential sectors exposed to supply disruptions.
This study examines whether exports from Israel to MENA countries influence Israel’s military expenditure indirectly through Israel’s economic growth during the period 1995–2023. The analysis is conducted for three samples: the aggregate MENA region, MENA countries with diplomatic relations with Israel, and MENA countries without diplomatic relations with Israel. Using Ordinary Least Squares (OLS) estimation and Wald tests, the results indicate that growth in Israel’s exports to the aggregate and diplomatic MENA samples contributes positively to Israel’s economic growth, which in turn significantly increases military expenditure. The indirect effect of exports on military expenditure through economic growth is found to be positive and statistically significant in these two samples. By contrast, no significant direct or indirect effects are observed for trade with non-diplomatic MENA countries. Overall, the findings suggest that trade can influence military expenditure indirectly through economic growth, particularly where stronger diplomatic and economic ties exist.
In South Africa, the culture and creative industry still faces structural constraints and rapid technological change. While digital infrastructure has opened new paths for creative production, distribution, and commercialisation, the extent to which digital connectivity and innovation translate into tangible, measurable performance in the creative economy remains a question. In this paper, the study investigates the short- and long-run relationships among technological innovation, telecommunications infrastructure, digital services intensity, and the performance of South Africa’s creative economy over the period 1999–2023 using an Autoregressive Distributed Lag (ARDL) model. The study uses patent applications as an indicator of formal innovation, as well as of fixed telecommunications infrastructure, digital services exports, and overall economic activity. The negative and marginally significant long-run association of digital services exports is also observed, while overall GDP is insignificant. The error-correction mechanism is negative and statistically significant, although its small magnitude suggests a slow recovery toward the long-run equilibrium. The study’s results show that the development of the creative economy is not only about increasing overall digital connectivity but also about innovation capacity and technological infrastructure within the creative innovation ecosystem. The study further observes that technological access alone is insufficient to achieve sector-level benefits and that it must be accompanied by stronger innovation support, commercialisation capabilities, and institutional support for creative companies. From a policy perspective, the findings call for greater attention to intellectual property development, innovation capabilities, digital production capacity, and infrastructure to help creative companies translate their technology into business. The study provides time-series evidence on the link between technological innovation, digital infrastructure, and creative economy performance in an African emerging-market context, and it offers policy-relevant insights for developing innovation-led creative sector development in South Africa amid uneven digital and economic development.
This study investigates the role of institutional policy support in enhancing climate adaptation strategies and maize productivity among smallholder farming households in Southwest Nigeria, a region critical for maize production yet vulnerable to climate variability. Employing a household-level data approach, data were collected from maize-based households across six states using questionnaires and interviews, supplemented by secondary climate and policy records. We employed a multivariate probit (MVP) regression with instrumental variable correction, addressing endogeneity in institutional support variables. Bayesian linear regression modeled maize yield as a function of institutional support, incorporating weakly informative priors and Markov Chain Monte Carlo (MCMC) sampling for posterior estimation. The Bayesian approach provides full posterior distributions and credible intervals, facilitates probabilistic interpretation of policy effects, improves estimation stability in the presence of multicollinearity, and enables rigorous sensitivity. Model robustness was evaluated via Bayesian fit metrics and sensitivity analysis with bootstrap resampling across prior types. Multivariate probit regression identifies institutional support, credit, irrigation, market access, and road infrastructure as key drivers of adaptation strategy adoption, modulated by socioeconomic (gender, experience) and farm-specific factors (farm size). Bayesian linear regression confirms significant yield impacts from institutional variables. Subgroup analysis indicates greater benefits for large farms over small farms, with gender-neutral impacts. While institutional support significantly boosts adaptation and productivity, gaps in irrigation access, climate information, and smallholder targeting limit equitable outcomes. The findings advocate for enhanced infrastructure, financial incentives, and tailored policies to strengthen climate resilience and food security, aligning with Nigeria’s climate goals and the Sustainable Development Goals.
This study examines regional correlates of real agricultural output in Kazakhstan using a harmonized panel of 14 agricultural regional units observed from 2016 to 2025. To distinguish production-volume changes from nominal price movements, the main dependent variable is a chain-linked measure of real agricultural output constructed from official regional physical volume indices. The analysis considers agricultural employment, sown area, cattle stock, contemporaneous and lagged agricultural investment, non-agricultural gross regional product, and sectoral concentration measured by the Herfindahl–Hirschman Index. The empirical strategy combines parsimonious two-way fixed-effects models, wild cluster bootstrap inference, correlated random-effects diagnostics, region-specific linear trends, and sensitivity analyses excluding administratively reorganized regional units. Sown area shows the most consistent positive association with real agricultural output in the baseline fixed-effects specifications. However, the coefficient becomes statistically insignificant after region-specific trends are introduced. Agricultural employment, cattle stock, aggregate investment, non-agricultural GRP, prior agricultural specialization, and sectoral concentration do not show robust associations across the revised specifications. Models using annual real-output growth as an alternative dependent variable also produce no robust relationships. The findings indicate that aggregate production inputs alone do not fully explain regional agricultural performance in Kazakhstan. Regional policy should therefore place greater emphasis on land productivity, irrigation efficiency, climate resilience, investment quality, processing, logistics, and agri-food value-chain development.
This study examines whether the 2022 tightening of sanctions against Russia and Belarus was associated with lower real GDP growth in European sanctioning economies. Most of the sanctions literature examines the impact on targeted states, whereas the macroeconomic costs for sanctioning economies have received far less systematic attention. Using annual panel data for 60 countries over 2016–2024, drawn from IMF, World Bank, and UN Comtrade databases, the analysis applies a difference-in-differences framework with country and year fixed effects, supported by parallel-trends diagnostics, placebo tests, and formal sensitivity analysis. The results indicate that, in the post-2022 period (2022–2024), real GDP growth in the sanctioning group was lower by approximately 1.47 percentage points relative to the control group; given a positive pre-treatment signal in 2021, this differential may represent an upper bound on the sanctions-related component. The negative differential was robustly stronger in more open economies. Within the sanctioning group, greater pre-2022 export dependence was associated with a more negative post-2022 growth change, whereas energy vulnerability showed no statistically significant heterogeneity. Overall, the findings indicate uneven short-run growth differentials associated with the sanctions episode, with stronger differentials in highly open economies.
Mozambique has prioritized soybean within its agricultural strategy, yet smallholder yields remain far below attainable levels and the share of that shortfall attributable to inefficient use of existing inputs has not been quantified. This study estimates farm-level technical efficiency (TE) and its determinants for 926 smallholder soybean farmers drawn from the 2023 Integrated Agricultural Survey covering Zambezia, Tete, Manica and Niassa, the provinces supplying the great majority of national output. A translog stochastic production frontier with a half-normal inefficiency term was fitted by maximum likelihood in a single step, with the variance of the inefficiency term parameterized as a function of farm and household characteristics. Approximately 72% of the residual variation separating farmers from the frontier was attributable to technical inefficiency rather than to random noise. Mean TE was 0.40 (range 0.02 to 0.81), an efficiency gap of about 60 percentage points, corresponding to a proportional output increase of approximately 147% from better use of existing inputs. Returns to scale over the continuous inputs entering the frontier were decreasing (approximately 0.74). Land was the dominant continuous frontier input and irrigation shifted the frontier upward. Farmers in the Central zone were more efficient than those in the North (0.43 against 0.36). The sex of the household head and region were the only determinants significant on both the coefficient and bootstrap tests, while credit access, though largest in marginal effect, was supported by the bootstrap interval alone. The findings support geographically targeted extension and gender-sensitive support.
Evidence on the fiscal consequences of population ageing rests largely on projections and regional panels. We examine how ageing relates to growth and the primary fiscal balance across sixty-nine economies from 1990 to 2024. Because cross-sectional dependence is pervasive and slope homogeneity rejected, inference rests on outlier-robust common correlated effects and augmented mean-group estimators, with system generalised method of moments (GMM) used as a robustness check. First, ageing has no robust average effect on growth or the balance once slopes differ and common global movements are removed, and no convex fiscal profile survives. Second, the fiscal cost of ageing is concentrated in economies at earlier stages of the demographic transition, where a one-point rise in old-age dependency is associated with a primary balance weaker by about 1.2 percentage points of GDP, an ordering that survives every specification we estimate. Third, publicly financed health care carries that weight: one percentage point of GDP of such spending is associated with a balance weaker by 1.5 to 1.9 percentage points, while privately financed care shows no such association. The demographic push on that spending is itself weakly estimated and appears only with a lag. Containing such spending requires building health-financing and revenue capacity during the transition.
Both researchers and policymakers increasingly recognize the importance of creative industries within the broader economy. While previous studies have primarily examined their innovation activities and knowledge diffusion through labor mobility and relatedness, considerably less attention has been devoted to their structural position within intersectoral production networks. This study examines the structural embeddedness of creative industries in the EU-27 by constructing weighted directed relatedness networks from aggregated input–output tables for 2010 and 2022. The findings show that creative industries occupy highly connected and structurally central positions within European production networks, suggesting that they may support coordination during value-chain adjustment and economic adaptation. Creative industries also maintain strong relationships with education, scientific research and development, information and communication, and professional service sectors, highlighting their integration within knowledge-intensive economic activities. The study further reveals a pronounced disassortative network structure, indicating that highly connected sectors tend to be linked to less-connected industries. By shifting the analytical perspective from spatial concentration to structural embeddedness, the study contributes to the relatedness and creative industries literature through an input–output network framework that provides new insights into the organization of European production networks.
This study examines the relationship between financial inclusion and economic growth, focusing specifically on the role of financial sector development in South Asia. The research encompasses annual data from five developing economies in South Asia: Bangladesh, India, Pakistan, Nepal, and Sri Lanka, during the period from 2000 to 2024. Multidimensional indicators of financial inclusion, economic growth, and financial sector development were generated using principal component analysis, while the panel autoregressive distributed lag–pooled mean group technique was applied to evaluate both long-run and short-run dynamics. The findings indicate that growth of the financial sector contributes significantly to economic development, providing its position as a major force behind economic expansion. The results suggest that financial sector development may represent a potential transmission channel linking financial inclusion and economic growth. The study highlights the importance of strengthening inclusive financial systems and financial sector institutions to achieve sustainable economic growth in South Asia, and offers policy recommendations for enhancing financial access, financial literacy, innovation, and financial market efficiency.
Post-2020 changes in cross-country log GDP per capita dispersion are directionally consistent across macroeconomic data systems but concentrated in a few country trajectories. Using the IMF WEO 1980–2024 baseline, a provisional 2025 extension, and a 167-country WEO–WDI–PWT panel for 2000–2023, the analysis compares sigma, level inequality, weighting, contributions, mobility, and horizon. Sigma rises by 0.018–0.024 across the sources. Paired country-resampling intervals support sign stability, not broad-based widening. The top five contributors account for 60.3–66.9% of the variance increase and the top ten for 86.6–96.3%; positive residuals remain after joint exclusion. The WEO 2020–2024 increase was exceeded by only two of the 36 preceding four-year changes, although sigma in 2024 remained below its 2000 level. Gini and Theil decline or remain approximately flat, while fixed-quartile separation and persistent ranks locate the change within a durable hierarchy. The contribution is an integrated diagnostic of scale, weighting, concentration, persistence, and horizon; it neither measures global interpersonal inequality nor establishes a structural reversal of long-run convergence.
This paper examines how innovation heterogeneity is associated with employment structure among firms in Sub-Saharan Africa (SSA). While innovation is often promoted as a pathway to job creation, its employment implications remain contested, particularly in contexts marked by resource constraints, weak infrastructure and uneven skills supply. Using firm-level data from the World Bank Enterprise Survey and the Innovation Follow-up Survey, the study investigates five types of innovation (product, process, organisational, incremental and radical) across five employment outcomes, including total, permanent, temporary, skilled and unskilled employment. Kernel propensity-score matching is used to reduce observable selection bias, with nearest-neighbour matching applied as a robustness check. The findings show that innovation is not uniformly related to employment. While product innovation is mainly linked to permanent and total employment, process innovation is associated with broader employment outcomes. Organisational innovation is more strongly connected to structured, skill-oriented employment than to unskilled employment. Incremental innovation shows the most inclusive employment pattern, whereas radical innovation is largely skill-selective and does not translate into broad-based employment gains. These empirical findings suggest that employment-oriented innovation policy in Sub-Saharan Africa should support adaptive innovation, while complementing advanced innovation with skills development.
This study investigates how institutional quality conditions the relationship between energy transition and environmental sustainability in nine CIS economies over the period 1996–2024, drawing on annual panel data sourced from the World Development Indicators. In the empirical framework, carbon dioxide emissions are specified as the dependent variable, while industrial output, foreign direct investment (FDI), renewable energy consumption, economic growth, trade openness, overall energy use, and an institutional quality index are included as key determinants of environmental pressure. Methodologically, the paper employs second-generation panel econometric techniques, commencing with cross-sectional dependence diagnostics and panel unit root tests, and proceeding to long-run estimation through FMOLS and CCR. The robustness of these estimates is reinforced using Driscoll-Kraay standard errors, while the System-GMM estimator is applied to address heteroskedasticity, serial correlation, cross-sectional dependence, and endogeneity concerns. The results indicate that industrial activity, energy consumption, and FDI significantly increase CO2 emissions, whereas greater reliance on renewable energy and stronger institutional quality help to alleviate environmental degradation. Under more rigorous specifications, trade openness and economic growth are found to reduce emissions, pointing to emerging decoupling patterns within CIS countries. Importantly, the interaction between renewable energy and institutional quality reveals a pronounced complementary effect, suggesting that stronger governance frameworks amplify the environmental benefits of energy transition. Taken together, the findings underscore that environmental sustainability across CIS economies is jointly determined by structural, economic, and institutional factors, with institutional quality serving as a critical lever for advancing progress toward SDG 13.
Achieving environmental sustainability, particularly the targets outlined in Sustainable Development Goal 13 (Climate Action), is a critical global imperative. This investigation analyzes the heterogeneous effects of artificial intelligence (AI), tourism intensity, tourism expenditure, the Gross Domestic Product (GDP) share contributed by tourism, natural resource rents, and environmental policy stringency on the ecological footprints of advanced countries from 2000 to 2022. Using a robust analytical framework featuring advanced econometric methods, specifically the Method of Moments Quantile Regression (MMQR) and an innovative machine learning approach—Panel Quantile-on-Quantile Kernel-Based Regularized Least Squares (PQQKRLS)—the research elucidates complex, nonlinear interdependencies. Key empirical results show that AI adoption significantly mitigates ecological footprints across all quantile distributions. Conversely, heightened tourism intensity and increased tourism expenditure are associated with greater environmental degradation. The analysis further indicates a U-shaped tourism–ecological footprint relationship, suggesting that tourism’s economic contribution may initially reduce ecological pressure but may increase it again beyond a certain expansion threshold. These conclusions underscore the necessity for advanced nations to adopt synergistic policy frameworks that strategically leverage AI technologies, promote sustainable tourism practices, and reinforce rigorous environmental governance to advance climate action and ecological sustainability.
