Search Results (763)

The concept of virtual water is currently one of the most important issues in water resource management, especially in a context marked by structural water scarcity. Beyond the analysis of virtual water flows, which has been widely studied in the literature, this study aims to better understand the relationship between virtual water exports and economic growth. This paper analyzes the dynamic relationship between Morocco’s economic growth and agricultural virtual water exports to the European Union over the period of 1986–2023. An ARDL model was used based on annual data to test cointegration and estimate short- and long-term effects, controlling for gross fixed capital formation and agricultural value added. The bounds test confirms the existence of a stable long-term relationship between the variables. The results suggest that export specialization may be associated with foreign earnings and agricultural activity while also coinciding with greater pressure on resources and potential adaptation costs, especially for blue water resources. However, estimates indicate that in the long term, investment is positively and significantly associated with growth, while virtual water exports are associated with a negative effect on GDP, suggesting that export gains may be offset by increasing water constraints and sectoral trade-offs, and that agricultural value added mainly influences short-term dynamics. The results highlight the importance of integrating water footprint and virtual water trade concepts, as well as climate constraints, into agricultural and trade strategy planning while strengthening policies on water efficiency, innovation, and governance. Full article

The future of Earth depends on the investment choices of companies and individuals. Over the past decade, investment decisions of individuals have been intensely studied by researchers in developed countries. Yet, very few studies focused on these investment decisions in developing countries using an experimental approach. This study adopts an experimental approach to examine the impact of ESG awareness on the sustainable investment decisions of undergraduate students in Egypt. In the experiment, subjects were asked to watch a video on investment basics (control) and investment and ESG basics (treatment). After that, the subjects were asked to choose between two choices, one sustainable (ESG choice) and one unsustainable with and without a return difference. After controlling for demographic characteristics, personal traits, financial knowledge, and risk tolerance, the results indicate that ESG awareness increases the probability of making sustainable investment decisions. Moreover, the findings indicate that sustainable investing among individuals is conditional on higher or equal returns than conventional investing. The study provides practical insights for professionals and policy recommendations. Full article

This study investigates the cross-border consequences of large-scale military attacks on Ukraine’s critical energy infrastructure and their implications for European energy resilience. Unlike prior research focused primarily on national-level disruption, this paper conceptualizes wartime infrastructure destruction as a source of systemic spillover risk within interconnected electricity systems. We develop an analytical framework integrating three dimensions: shock probability, structural vulnerability, and recovery capacity. Using evidence from 2022–2026 and comparative assessment of selected European Network of Transmission System Operators for Electricity (ENTSO-E) countries, we identify substantial asymmetries in exposure and resilience. Moldova appears highly vulnerable due to structural dependence and limited flexibility, whereas Poland demonstrates stronger resilience supported by diversification and institutional capacity. The findings show that shocks originating in Ukraine propagate through electricity trade flows, balancing constraints, and price volatility. The results highlight that large-scale attacks on the energy system threaten not only immediate regional security but also the long-term energy sustainability of the interconnected European network. The paper contributes to the literature by linking war-induced infrastructure damage with sustainable energy governance and by proposing resilience tools such as digital twins and blockchain coordination. The results are relevant for policymakers, transmission operators, and crisis management institutions across Europe. Full article

This paper investigates the role of cross-border trade in shaping participation in global value chains (GVCs) in developing and emerging economies over the period 2000–2022. It tests the central hypothesis that greater trade intensity enhances integration into fragmented global production systems. Using panel data methods, the analysis examines the effects of trade openness alongside foreign direct investment, logistics performance, GDP per capita, and domestic value added. The results provide strong evidence that trade openness is the dominant driver of GVC participation, with a robust and economically meaningful elasticity. Domestic value added is also positively associated with GVC integration, suggesting that deeper global engagement can coincide with increased domestic value creation. GDP per capita exerts a weaker but significant effect, while foreign direct investment and logistics performance do not show direct statistical significance in the preferred specification. These findings highlight trade as the primary transmission mechanism linking national economies to global production networks, while also pointing to a complementary role of domestic capabilities. At the same time, increased reliance on cross-border trade may heighten exposure to external shocks, underscoring a key policy trade-off. The study concludes that effective GVC integration requires balancing openness with strategies that strengthen resilience and value capture. Full article

Foreign-exchange decisions rest on hierarchically organized evidence whose latent structure is inadequately captured by Euclidean representations. Reinforcement-learning agents trained on flat embeddings inherit stability guarantees that do not transfer to the manifold supporting the latent state. We address both limitations through a hybrid architecture in which a schema-constrained structured chain-of-thought is embedded into a Poincaré ball, transported to a qubit register via angle encoding, and processed by an L-layer hardware-efficient variational ansatz on a state-vector backend. The circuit exposes two read-outs to the policy, namely, a scalar Pauli-Z observable and a projected quantum kernel inducing a fidelity-based similarity over magnet-price attractors, the latter identified via kernel-weighted recurrence density and finite-time Lyapunov statistics. The Lipschitz constraint on the action-value function is lifted from the hyperbolic geodesic distance to a joint metric on ${\mathbb{B}}_{\kappa }^n\times \mathbb{P}\left(\mathcal{H}\right)$. A stability theorem yields an explicit bound depending on the read-out operator norm, on the depth–width product of the ansatz, and on the curvature–Hilbert balance. The pipeline is evaluated on nine major FX crosses over a 2015–2025 out-of-sample window, with rolling-origin walk-forward retraining and broker-published transaction costs. The system attains $2.55\%$ pair-averaged non-compounded monthly P&L and $8.83\%$ maximum drawdown, with Sharpe $1.78$, Calmar $3.43$, and Probabilistic Sharpe Ratio exceeding $0.95$ on every cross. The gain remains significant under a deflated-Sharpe-ratio test with $N_{\mathrm{trials}}=42$ correction. Block-wise ablations exhibit strictly monotone degradation: removing the projected kernel costs $-4.15$ p.p. on annualized P&L, the joint Lipschitz penalty $-6.42$ p.p., the attractor module $-7.64$ p.p., and the hyperbolic embedding $-8.40$ p.p. The quantum block thereby instantiates a structurally non-classical, geometry-aware regularizer identifiable through ablation rather than asymptotically advantageous. Full article

This review examines the relationship among foreign direct investment (FDI), trade openness, and economic growth, with emphasis on the channels through which external integration influences development outcomes. The literature generally suggests that FDI can raise growth through capital accumulation, technology transfer, productivity gains, and stronger linkages with domestic firms, while trade openness can promote growth by expanding market access, increasing competition, and improving resource allocation. However, the evidence is not uniform: some studies report that trade openness is the main driver of growth, while others find that FDI has a stronger effect, or that both variables matter only under favorable macroeconomic, institutional, and financial conditions. This review synthesizes theoretical arguments and empirical findings, identifies major transmission mechanisms and conditional factors, and highlights the policy environment needed for FDI and trade liberalization to translate into sustained economic growth. Full article

This study examines the role of governance and institutional quality in shaping FDI inflows across twelve South and Central Asian economies from 2002 to 2023. The analysis incorporates key macroeconomic determinants, including trade openness, economic growth, population, inflation, six governance dimensions, and a composite institutional quality index constructed through principal component analysis. Driscoll–Kraay standard errors, Feasible Generalized Least Squares (FGLS), and Method of Moments Quantile Regression (MMQR) techniques are employed to capture heterogeneity and distributional effects. The findings show that trade openness, economic growth, and population consistently stimulate FDI inflows, whereas inflation discourages foreign investment. More importantly, the study reveals a counterintuitive institutional effect: stricter governance mechanisms-including stronger rule of law, regulatory quality, and anti-corruption measures-can temporarily constrain FDI inflows by increasing compliance costs, administrative complexity, and adjustment burdens for foreign investors in transitional economies. This suggests that institutional strengthening operates as a double-edged process, promoting long-term economic credibility while potentially discouraging short-term foreign capital inflows. The study therefore highlights the importance of balancing institutional reforms with procedural efficiency and investor-friendly implementation strategies in South and Central Asia. Full article

Air transport is a key driver of economic development, tourism, and regional connectivity, yet its growth generates increasing environmental costs. Grounded in the catalytic effects framework and the sustainability trade-off perspective, this exploratory study examines the economic and sustainability dimensions of air traffic recovery and growth at Belgrade Nikola Tesla Airport during 2019–2024, a period encompassing a pandemic shock and record post-pandemic expansion. Descriptive statistical analysis and Pearson correlation analysis were applied to six annual data points, supplemented by an approximate CO₂ emission estimation. Passenger traffic increased from 6.16 to 8.37 million (+35.9%), and the destination network expanded from 99 to 135 routes. A positive co-movement was observed between passenger traffic and foreign tourist arrivals (r = 0.970; p = 0.001). No detectable association was found between passenger traffic and annual GDP growth rate (r = 0.143; p = 0.79). Estimated CO₂ emissions grew proportionally from 0.831 to 1.130 million tonnes, consistent with the proportional growth pattern generated by the fixed-factor estimation framework applied. The passengers-per-movement ratio improved from 87.5 to 97.2, indicating a proximate improvement in operational efficiency. These preliminary findings provide exploratory evidence relevant to Sustainable Development Goals 8 and 9 and may inform future research and policy discussions on the sustainability dimensions of airport development. Full article

This paper examines changes in the macroeconomic indicators of the member countries of the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) following their accession to the agreement. This study aims to identify shifts in the structural comparability of national economies and to assess the processes of macroeconomic convergence in the context of sustainable development. To achieve this objective, reference pools of CPTPP member countries are constructed, and their digital profiles are developed based on key macroeconomic indicators and grouped into three blocks: (1) indicators of economic growth and the state of the real sector, including GDP (constant 2015 US$), GDP growth, annual %, gross capital formation, % of GDP, unemployment, total % of total labor force, and national estimate; (2) indicators of foreign economic activity and trade openness, including exports of goods and services, % of GDP, imports of goods and services, % of GDP, external balance on goods and services (% of GDP), foreign direct investment, net inflows, % of GDP, and trade, and % of GDP; (3) indicators of financial and macroeconomic stability including inflation, consumer prices, annual %, central government debt, % of GDP, and gross savings, and % of GDP. Based on the digital profiles, similarities/differences in the economies were examined by applying linear discriminant analysis (LDA). The empirical framework covers two periods: (1) 2013–2017 (pre-accession) years and (2) 2019–2023 (post-accession) years. The results indicate that the economies of member countries in 2013–2017 exhibited a high degree of heterogeneity. In contrast, the 2019–2023 period demonstrates a tendency toward partial convergence of macroeconomic parameters, as evidenced by a reduction in distances between country profiles in the discriminant space. While interpreting the results, it is acknowledged that the 2019–2023 period coincided with the effects of the global crisis caused by the COVID-19 pandemic, which significantly impacted international trade dynamics. For most countries, this period was characterized by a decline in several macroeconomic indicators and investment activity, an increase in debt burdens, and enhanced heterogeneity in economic dynamics, which was taken into account when interpreting macroeconomic convergence processes within the CPTPP. The scientific novelty of the study lies in its application of an approach based on the analysis of the structural similarity of the macroeconomic profiles of CPTPP countries, which complements traditional assessments of the effects of economic and trade integration. The practical significance of the findings is associated with their potential use in evaluating the prospects for CPTPP expansion and in modeling alternative scenarios of participation and sustainable development within international trade agreements under conditions of global economic transformation. Full article

The paper seeks to determine whether renewable energy is a future pathway for society or rather a temporary stage leading towards sustainable sources of energy. It evaluates the factors that affect the use of renewable energy in Malaysia through modelling their long-term relationship and short-term causalities. Time-series data collected from 1970 to 2021 is used in the Johansen cointegration test and Vector Error Correction Model (VECM) to determine the association among renewable energy consumption, per capita GDP, foreign direct investments (FDI), carbon dioxide (CO₂) emissions, oil prices, trade openness, and urbanisation. There is evidence of a strong positive long-term association between renewable energy consumption and per capita GDP. However, there is evidence of a negative long-term relationship between renewable energy and FDI, CO₂ emissions, oil prices, and urbanisation. There is a positive relationship between renewable energy consumption and trade openness in the long term. In addition, short-term causality analysis shows the existence of a feedback loop between renewable energy consumption, economic growth, and FDI. Overall, the paper provides empirical evidence for the carbon-neutral target set by Malaysia in 2050. Full article

This study examines the impact of climate change on the performance of Egypt’s fish foreign trade during the period from 1995 to 2022. The analysis incorporates a set of climate indicators, including average surface air temperature, relative humidity, rainfall, carbon dioxide emissions, methane emissions, and nitrous oxide emissions, in addition to fish trade indicators represented by exports, imports, total trade volume, trade balance, and export-to-import coverage ratio. The study employs the Autoregressive Distributed Lag (ARDL) model to investigate both the short-run and long-run relationships between climate change variables and fish foreign trade performance in Egypt. Unit root tests confirmed that the variables were integrated at mixed orders I(0) and I(1), supporting the suitability of the ARDL methodology. The findings reveal the existence of a statistically significant long-run equilibrium relationship between climate change indicators and Egyptian fish exports. In particular, nitrous oxide emissions exerted a significant negative effect on fish exports in the long run, while rainfall showed a positive short-run effect. The results also indicate that approximately 57% of short-run disequilibria are corrected annually toward the long-run equilibrium. In contrast, no long-run cointegration relationship was found between climate variables and fish imports, total fish trade volume, or the fish trade balance, indicating that climate impacts on these indicators are mainly short-term in nature. The study concludes that climate change represents an important determinant of Egypt’s fish trade performance through its effects on productivity, environmental quality, and trade competitiveness. The findings highlight the need for integrated adaptation and mitigation policies to strengthen the sustainability and resilience of Egypt’s fisheries sector under changing climatic conditions. Full article

Geopolitical conflicts continue to disrupt global energy supply chains, causing sharp changes in energy prices. These changes reshape the cost structure and efficiency levels of grain circulation. Based on panel data from 30 Chinese provinces covering 2011–2022, this study constructs a proxy for grain circulation efficiency using a resource misallocation framework and counterfactual decomposition. We employ panel threshold regression and double machine learning methods to systematically examine the nonlinear impact of energy price levels on grain circulation efficiency and to reveal regional differences. The findings are as follows: (1) Energy price levels exhibit a significant single-threshold effect. When energy prices remain within a low range, rising prices exert a positive technology push effect; beyond the threshold, a cost-squeeze suppression dominates. (2) The eastern region shows the highest tolerance for price increases, whereas the western region has the lowest tolerance, with the central region falling in between. (3) Double machine learning feature importance analysis reveals that research and experimental development investment and economic development are the dominant factors affecting agricultural product circulation efficiency in the eastern region; water consumption and capital stock are the key factors in the central region; and energy prices, foreign trade dependence, and infrastructure are the most sensitive factors in the western region. This study provides empirical evidence for designing differentiated regional circulation policies and enhancing the resilience of the grain circulation system. Full article

The Gulf Cooperation Council (GCC) countries consistently rank among the highest per capita CO₂ emitters globally, yet rigorous empirical analysis of the structural drivers of these emissions in the post-Paris Agreement era remains scarce. This study investigates the determinants of CO₂ emissions per capita across six GCC economies—Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates—over the period 2015–2022, using pooled ordinary least squares (OLSs) and country fixed effects (FEs) panel regression models with country-clustered standard errors. The focal explanatory variable is energy use per capita, complemented by GDP per capita, trade openness, urbanization, foreign direct investment (FDI), and industry value added as controls. A quadratic income term explicitly tests the environmental Kuznets curve (EKC) hypothesis. Results consistently show that energy use is the dominant driver of emissions. The EKC hypothesis is supported in the FE framework. The implied turning point of approximately USD 85,500 per capita (constant 2015 USD) is already exceeded by Qatar (panel mean: USD 114,835) and approached by the UAE (USD 71,434), while Bahrain (USD 55,681), Kuwait (USD 51,531), Saudi Arabia (USD 61,232), and Oman (USD 38,591) remain on the EKC’s rising slope, consistent with their continued emissions’ growth trajectories. Urbanization exerts a significant positive within-country effect on emissions. Trade openness reduces emissions in cross-sectional specifications, while FDI is systematically insignificant. These findings support energy efficiency reforms, renewable energy expansion, and low-carbon urban planning as the most effective policy levers for GCC decarbonization. Full article

This paper examines how remittances-to-GDP are conditionally associated with GDP growth upswings and downturns in four lower-middle-income countries (LMICs) in mainland Southeast Asia—Cambodia, Laos, Myanmar, and Vietnam (CLMV)—over 2000–2021, conditional on other external inflows including foreign direct investment (FDI), official development assistance (ODA), and trade openness. Employing a nonlinear Autoregressive Distributed Lag (N-ARDL) model with a Dynamic Fixed Effects (DFE) estimator, this study estimates short- and long-run regime-differentiated associations between GDP growth regimes and remittances to GDP, controlling for foreign direct investment (FDI), official development assistance (ODA), and trade openness. GDP growth is decomposed into above- and below-median regimes, allowing the model to examine whether remittance dynamics differ across growth upswings and downturns. Panel estimates are complemented with dynamic multipliers that trace conditional adjustment paths over different horizons. The results reveal a high-growth-driven regime pattern rather than formal statistical evidence of unequal high- and low-growth coefficients. In the long run, above-median growth significantly reduces remittances to GDP (${\widehat{\theta }}_1=-0.130$, very strong evidence), consistent with the household insurance motive; below-median growth has no significant long-run association (${\widehat{\theta }}_2=-0.127$, no evidence). In the short run, above-median growth is positively associated with remittances (${\widehat{\tilde{\beta }}}_1^{+}=0.033$, very strong evidence), while below-median growth again shows no significant short-run response (${\widehat{\tilde{\beta }}}_1^{-}=0.051$, no evidence). Formal Wald tests do not reject equality between the high- and low-growth coefficients in either horizon; therefore, the findings should be interpreted as a regime-differentiated significance pattern within a nonlinear specification, not as formal proof of coefficient asymmetry. Taken together, these responses are consistent with a one-sided counter-cyclical interpretation of remittances: remittances to GDP decline when domestic growth is above the median, while no significant adjustment is observed during below-median growth episodes. The pattern documented here is therefore driven by the high-growth regime and should not be read as evidence of an active counter-cyclical surge during downturns. Trade openness and ODA exhibit significant positive short-run co-movement with remittances, whereas FDI shows a strong positive long-run association with remittances to GDP. The novelty of this study lies in providing new panel evidence on regime-differentiated remittance–growth associations for CLMV within a nonlinear N-ARDL and dynamic multiplier framework, while transparently reporting that formal Wald tests do not reject equality between high- and low-growth coefficients. Policy implications center on facilitating reliable remittance channels—reducing transfer costs and expanding financial inclusion—without assuming that remittance inflows automatically rise during downturns. Full article

This study investigates the short-term and long-term impacts of gross domestic product (GDP), inflation, foreign capital flows, trade balance and interest rate on stock market performance in Saudi Arabia for the period 1990–2023. The autoregressive distributed lag (ARDL) approach and error correction model (ECM) are employed to empirically examine the short-run and long-run relationships. The ARDL-ECM technique is effective for analyzing cointegration and assessing adjustment processes. Additionally, impulse response function (IRF) analysis based on the vector autoregression (VAR) model, estimated using these macroeconomic indicators, is applied in this paper. This study provides novel insights and addresses emerging gaps in the literature concerning Saudi Arabia as a developing economy. The long-term relationship in the bounds test results confirms its existence. In the long run, inflation and interest rate exert a statistically significant negative effect on stock market performance, while the trade balance has a significant positive impact. GDP and foreign capital inflows do not exhibit statistically significant long-run effects. Short-run dynamics indicate persistence in stock market performance along with significant effects from inflation and interest rate changes, while GDP and foreign capital inflows remain statistically insignificant in the long-run scenario. Forecast error variance decomposition (FEVD) results show that approximately 68.5% of the variation in market performance is explained by its own shocks, followed by foreign capital flows (16.3%) and inflation (8.4%). While foreign capital flow does not exhibit statistical significance in the ARDL long-run estimates, its contribution in variance decomposition highlights its role as an important source of external shocks. These findings are relevant to various stakeholders, including investors and policymakers. Additionally, policy emphasis should be placed on controlling inflation and maintaining stable interest rates while improving trade balance conditions. Although foreign capital flow does not show a direct long-run effect, its role in influencing market variability suggests the need for a stable and well-regulated investment environment. Full article