Search Results (468)

Unemployment and weak economic productivity are significant global issues, particularly in West Africa. Recently, through diverse mechanisms, remittances and foreign direct investment (FDI) have been sources of foreign capital flow that have positively influenced many less developed economies, including ECOWAS (ECOWAS stands for Economic Community of West African States). Nevertheless, these financial flows have exhibited significant inconsistencies, primarily resulting from economic downturns in migrants’ destination countries, with remarkable implications for beneficiary economies. This study, therefore, examines the effect of remittances and FDI on employment in ECOWAS. Specifically, the study assesses the effects of the inflow of remittances and FDI on employment using panel dynamic ordinary least squares (PDOLS) and also investigates the shock effects of remittances and FDI by employing Panel Vector Error Correction (PVECM), which involves variance decomposition. The results show that foreign direct investment (FDI) positively and significantly affects employment. Other variables that show a significant relationship with employment are wage rate, education expenditure, and interest rate. The variance decomposition result revealed that external shocks on remittances and FDI have short- and long-term effects on employment. The above findings imply that foreign direct investment has a far-reaching positive impact on the economy-wide management of the West African sub-region and thus calls for relevant policy options. Full article

This study proposes a novel Deep Reinforcement Learning (DRL) policy network structure for portfolio management called PortRSMs. PortRSMs employs stacked State-Space Models (SSMs) for the modeling of multi-scale continuous regime shifts in financial time series, striking a balance between exploring consistent distribution properties over short periods and maintaining sensitivity to sudden shocks in price sequences. PortRSMs also performs cross-asset regime fusion through hypergraph attention mechanisms, providing a more comprehensive state space for describing changes in asset correlations and co-integration. Experiments conducted on two different trading frequencies in the stock markets of the United States and Hong Kong show the superiority of PortRSMs compared to other approaches in terms of profitability, risk–return balancing, robustness, and the ability to handle sudden market shocks. Specifically, PortRSMs achieves up to a 0.03 improvement in the annual Sharpe ratio in the U.S. market, and up to a 0.12 improvement for the Hong Kong market compared to baseline methods. Full article

This paper examines the changing role of emissions trading systems (ETSs) within the macro-financial framework of energy markets, emphasizing price dynamics and systemic spillovers. Utilizing monthly data from seven ETS jurisdictions spanning January 2021 to December 2024 (N = 287 observations after log transformation and first differencing), which includes four auction-based markets (United States, Canada, United Kingdom, South Korea), two secondary markets (China, New Zealand), and a government-set fixed-price scheme (Germany), this research estimates a panel vector autoregression (PVAR) employing a Common Correlated Effects (CCE) model and augments it with machine learning analysis utilizing XGBoost and explainable AI methodologies. The PVAR-CEE reveals numerous unexpected findings related to carbon markets: ETS returns exhibit persistence with an autoregressive coefficient of −0.137 after a four-month lag, while increasing inflation results in rising ETS after the same period. Furthermore, ETSs generate spillover effects in the real economy, as elevated ETSs today forecast a 0.125-point reduction in unemployment one month later and a 0.0173 increase in inflation after two months. Impulse response analysis indicates that exogenous shocks, including Brent oil prices, policy uncertainty, and financial volatility, are swiftly assimilated by ETS pricing, with effects dissipating completely within three to eight months. XGBoost models ascertain that policy uncertainty and Brent oil prices are the most significant predictors of one-month-ahead ETSs, whereas ESG factors are relevant only beyond certain thresholds and in conditions of low policy uncertainty. These findings establish ETS markets as dynamic transmitters of macroeconomic signals, influencing energy management, labor changes, and sustainable finance under carbon pricing frameworks. Full article

Against the backdrop of China’s fast-growing digital economy and its financial inclusion agenda, there is still little city-level evidence on whether the e-CNY pilot accelerates financial deepening at the grassroots. Using a balanced panel of 271 prefecture-and-above cities for 2016–2022, this study employs a staggered difference-in-differences (SDID) design augmented by the synthetic control method (SCM) to rigorously identify the policy effect of the e-CNY pilot. The results show that the pilot program significantly improves urban financial inclusion, contributing to more equitable access to financial services and supporting inclusive socio-economic development. Mechanism analysis suggests that the effect operates mainly through two channels, a merchant-coverage channel and a transaction-scale channel, with the former contributing the majority of the overall effect. Incorporating a migration-based mobility index shows that most studies’ focus on the merchant-coverage effect is amplified in cities under tight mobility restrictions but wanes where commercial networks are already saturated, whereas the transaction-scale channel is largely insensitive to mobility shocks. Heterogeneity tests further indicate stronger gains in non-provincial capital cities and in the eastern and central regions. Overall, the study uncovers a “penetration-inclusion” network logic and provides policy insights for advancing sustainable financial inclusion through optimized terminal deployment, merchant incentives, and diversified scenario design. Full article

This paper analyzes how two major economic downturns—a recession and a stagflation—affected convergence in the European Union (EU). Absolute and conditional convergence rates are estimated using ordinary least squares (OLS) semilog regressions based on cross-sectional data from 2004 to 2022. The study tests two hypotheses: there was no absolute convergence in the EU during either the recession or the stagflation period, and conditional convergence occurred during the recession but not during stagflation. The regression results indicate that neither hypothesis can be rejected. External variables—economic openness, inflation, and investment—were more influential during stable periods, whereas internal variables—debt, unemployment, and the control of corruption—had a greater impact during crises. These findings suggest that the EU was more institutionally prepared for the stagflation due to mechanisms developed after the financial crisis, but these tools proved less effective in addressing supply-side shocks. Full article

This paper considers the impact of Central Bank Digital Currencies (CBDCs) on the world’s financial systems with a special emphasis on G20 economies. Using quarterly macro-financial data for the period of 2000 to 2024, collected from the IMF, BIS, World Bank, and Atlantic Council, a Global Vector Autoregression (GVAR) model is applied to 20 G20 countries. The results reveal significant heterogeneity across economies: CBDC shocks intensify emerging market financial instability (e.g., India, Brazil), while more digitally advanced countries (e.g., UK, Japan) experience stabilization. Retail CBDCs increase disintermediation risks in more fragile banking systems, while wholesale CBDCs improve cross-border liquidity. This article contributes to the literature by providing the first GVAR-based estimation of CBDC spillovers globally. Full article

This study examined the dynamic interconnectedness and portfolio implications within the cryptocurrency ecosystem, focusing on five representative digital assets across the core functional categories: Layer 1 cryptocurrencies (Bitcoin (BTC) and Ethereum (ETH)), decentralized finance (Uniswap (UNI)), stablecoins (Dai), and crypto infrastructure tokens (Maker (MKR)). Using the Extended Joint Connectedness Approach within a Time-Varying Parameter VAR framework, the analysis captured time-varying spillovers of return shocks and revealed a heterogeneous structure of systemic roles. Stablecoins consistently acted as net absorbers of shocks, reinforcing their defensive profile, while governance tokens, such as MKR, emerged as persistent net transmitters of systemic risk. Foundational assets like BTC and ETH predominantly absorbed shocks, contrary to their perceived dominance. These systemic roles were further translated into portfolio design, where connectedness-aware strategies, particularly the Minimum Connectedness Portfolio, demonstrated superior performance relative to traditional variance-based allocations, delivering enhanced risk-adjusted returns and resilience during stress periods. By linking return-based systemic interdependencies with practical asset allocation, the study offers a unified framework for understanding and managing crypto network risk. The findings carry practical relevance for portfolio managers, algorithmic strategy developers, and policymakers concerned with financial stability in digital asset markets. Full article

The enforcement of the European Union Deforestation Regulation (EUDR) may reduce the supply of natural rubber to the European Union (EU), potentially leading to price increases due to the inelastic nature of rubber demand. This study assesses the potential financial implications for smallholder producers in Ghana, considering both the opportunities and risks associated with the evolving regulatory environment under EUDR and local market access conditions. A cost–benefit analysis (CBA) was conducted to evaluate the impact of different EUDR-related export decline scenarios on the net present value (NPV) of a standard 4-hectare plantation. The results suggest that even a minor 2.5% decline in global exports to the EU could increase the NPV by 17% for an independent compliant producer. However, a simulated COVID-19-like crisis in the fifth year of production leads to a 20% decline in NPV, reflecting vulnerability to external shocks. Based on these findings, the study identifies two priorities. This first is improving the coordination and harmonization of compliance efforts across the value chain to enable more producers to benefit from potential EUDR-related price increases. The recent creation of the Association of Natural Rubber Actors of Ghana (ANRAG) presents an opportunity to support such collective mechanisms. Second, minimizing losses during demand shocks requires the Tree Crops Development Authority (TCDA) to establish clear rules and transparent reporting for authorizing unprocessed rubber exports when factories reduce purchases due to low international prices—thus preserving market access for vulnerable producers. Together, these approaches would ensure that the potential benefits of the EUDR are realized inclusively, remain stable despite market downturns, and do not undermine value addition in domestic processing factories. Full article

Global financial markets have experienced significant volatility during crises, particularly COVID-19 and the Russia–Ukraine conflict, prompting questions about how regional markets respond to such shocks. Previous research highlights the influence of crises on stock market volatility, focusing on individual events or global markets, but less is known about the comparative dynamics within the Gulf Cooperation Council (GCC) markets. Our study investigated volatility and asymmetric behavior within GCC stock markets during both crises. Furthermore, the econometric model E-GARCH(1,1) was applied to the daily frequency data of financial stock market returns from 11 March 2020 to 31 July 2023. This study examined volatility fluctuation patterns and provides a comparative assessment of GCC stock markets’ behavior during crises. Our findings reveal varying degrees of market volatility across the region during the COVID-19 crisis, with Qatar and the UAE exhibiting the highest levels of volatility persistence. In contrast, the Russia–Ukraine conflict has had a distinct effect on GCC markets, with Oman exhibiting the highest volatility persistence and Kuwait having the lowest volatility persistence. This study provides significant insights for policymakers and investors in managing risk and enhancing market resilience during economic and geopolitical uncertainty. Full article

This study investigates the systemic tail dependence among biodiversity, clean energy, and financial transition assets using a novel partial correlation-based network approach. Analyzing eleven indices from 2019 to 2025, we capture dynamic connectedness across normal and extreme market conditions. Empirical findings indicate that clean energy assets form a central hub of connectedness, while biodiversity-linked instruments increasingly influence systemic behavior under stress. Events such as the COVID-19 vaccine rollout, the Russia–Ukraine war, and El Niño intensify these dynamics. Compared to the traditional Generalized Forecast Error Variance Decomposition (GFEVD) framework, our approach better detects short-term shocks, offering actionable insights for climate-aware investment and risk management. Full article

Housing prices have recently risen sharply in many countries, primarily linked to the global credit cycle. Although various factors play a role, the ability of developing countries to navigate this cycle and maintain autonomous monetary policies is crucial. This paper introduces a dynamic macroeconomic model featuring a housing production sector within an imperfect banking framework. It captures key housing and economic dynamics in advanced and emerging economies. The analysis shows domestic liquidity policies, such as bank capital requirements, reserve ratios, and currency devaluation, can stabilize investment and production. However, their effectiveness depends on foreign interest rates and liquidity. Stabilizing housing prices and risk-free bonds is more effective in high-interest environments, while foreign liquidity shocks have asymmetric impacts. They can boost or lower the effectiveness of domestic policy, depending on the country’s level of financial development. These findings have several policy implications. For example, foreign capital controls would be adequate in the short term but not in the long term. Instead, governments would try to promote the development of local financial markets. Controlling debt should be a target for macroprudential policy as well as promoting saving instruments other than real estate, especially during low interest rates. Full article

This study investigates the impact of geopolitical risk, firm characteristics, and macroeconomic variables on the performance of non-financial firms listed on the Egyptian Stock Exchange. The study analyzes a panel dataset consisting of 182 Egyptian firms over the period 2014–2023. Using the panel Generalized Method of Moments (GMM) regression technique, the study examines the effect of geopolitical risk on the return on assets. This study controls for firm characteristics such as liquidity, leverage, and growth opportunities and controls for macroeconomic variables such as inflation and GDP. This empirical evidence investigates the moderating role of FinTech on such relationship. The results reveal a significant and negative relationship between geopolitical risk and firms’ performance. Liquidity, growth opportunities, and inflation show positive and significant impacts. In contrast, leverage and GDP demonstrate significant negative relationships. Remarkably, FinTech moderates the relationship significantly and positively. Therefore, investors ought to proceed with prudence when positioning cash within elevated political volatility. The significant positive moderating effect of FinTech on this connection provides a vital strategic insight: enterprises with enhanced FinTech integration may demonstrate increased resilience to geopolitical shocks. Full article

The agricultural products trade network is essentially a complex adaptive system formed by nonlinear interactions between countries. Based on the complex system theory, this study reveals the dynamic self-organization law of the RCEP regional agricultural products trade network by using the panel data of RCEP agricultural products export trade from 2000 to 2023, combining social network analysis (SNA) and the temporal exponential random graph model (TERGM). The results show the following: (1) The RCEP agricultural products trade network presents a “core-edge” hierarchical structure, with China as the core hub to drive regional resource integration and ASEAN countries developing into secondary core nodes to deepen collaborative dependence. (2) The “China-ASEAN-Japan-Korea “riangle trade structure is formed under the RCEP framework, and the network has the characteristics of a “small world”. The leading mode of South–South trade promotes the regional economic order to shift from the traditional vertical division of labor to multiple coordination. (3) The evolution of trade network system is driven by multiple factors: endogenous reciprocity and network expansion are the core structural driving forces; synergistic optimization of supply and demand matching between economic and financial development to promote system upgrading; geographical proximity and cultural convergence effectively reduce transaction costs and enhance system connectivity, but geographical distance is still the key system constraint that restricts the integration of marginal countries. This study provides a systematic and scientific analytical framework for understanding the resilience mechanism and structural evolution of regional agricultural trade networks under global shocks. Full article

This study examines the long-term financial sustainability of commercial banks, emphasizing the crucial role of credit risk management. Given that the core function of credit creation inherently exposes banks to credit risk, this analysis evaluates how five key bank-specific risk variables, namely expected credit losses (ECL_BS), impairment gains or losses (ECL_IS), non-performing loans (NPLs), common equity tier 1 capital (CET1), and leverage (LEV) affect long-term financial sustainability. Applying a panel error correction model on data from listed South African banks spanning 2006 to 2023, the study reveals a stable long-term relationship, with approximately 74% of short-term deviations corrected over time, indicating convergence towards equilibrium. By taking into account the significance of major exogeneous shocks such as the 2009–2010 global financial crisis and the COVID-19 pandemic, as well as regulatory framework changes, the results reveal persistent relationships between credit risk factors and banks’ long-term financial sustainability in both short and long horizons. Notably, expected credit losses, and impairment gains and losses exert significant negative influence on long-term financial sustainability, while higher CET1 and NPLs exhibit positive effects. The study findings are framed within four complementary theoretical perspectives—the resource-based view, institutional theory, industrial organisation, and the dynamic capabilities framework—highlighting the multidimensional drivers of financial resilience. Thus, the study’s originality lies in its integrated approach to assessing credit risk, offering a holistic model for evaluating its influence on long-term financial sustainability. This integrated framework provides valuable, actionable insights for financial regulators, bank executives, policymakers, and banking practitioners committed to strengthening credit risk frameworks and aligning banking sector stability with broader sustainable development goals. Full article

This study examines the role of supervisory frameworks in shaping the risk management behavior of Greece’s four systemic banks during the period of 2015–2024. It explores how regulatory reforms under Capital Requirements Regulation II, Basel III, and European Central Bank oversight influenced capital adequacy, asset quality, and liquidity metrics. Employing a quantitative methodology, this study analyzes secondary data from Pillar III disclosures, annual financial reports, and supervisory statements. Key risk indicators (capital adequacy ratio, non-performing exposure ratio, liquidity coverage ratio, and risk-weighted assets) are evaluated in conjunction with regulatory interventions, such as International Financial Reporting Standards 9 transitional relief, the Hercules Asset Protection Scheme, and European Central Bank liquidity measures. The findings reveal that enhanced supervision contributed to improved resilience and regulatory compliance. International Financial Reporting Standards 9 transitional arrangements were pivotal in maintaining capital thresholds during stress periods. Supervisory flexibility and extraordinary European Central Bank support measures helped banks absorb shocks and improve risk governance. Differences across banks highlight the impact of institutional strategy on regulatory performance. This study offers a rare longitudinal assessment of supervisory influence on bank risk behavior in a high-volatility Eurozone context. Covering an entire decade (2015–2024), it uniquely links institutional strategies with evolving regulatory frameworks, including crisis-specific interventions such as International Financial Reporting Standards 9 relief and asset protection schemes. The results provide insights for policymakers and regulators on how targeted supervisory interventions and transitional mechanisms can enhance banking sector resilience during protracted crises. Full article