This paper examines how monetary policy actions, bank liquidity positions, and institutional heterogeneity shape interbank pricing in Rwanda. Using a bank–month panel dataset constructed from transaction-level records on the Rwanda Integrated Payment Processing System (RIPPS) for monthly data from 2018 to 2022, we estimate a dynamic fixed effects model of the interbank spread, defined as the difference between a bank’s volume-weighted borrowing rate and the Central Bank Rate (CBR). The findings show that policy rate changes are transmitted to the interbank market but with incomplete and gradual adjustment. Liquidity buffers lower funding costs in normal times, yet their stabilizing role weakens during system-wide stress, particularly evident during the COVID-19 shock, which generated a broad-based and persistent widening of spreads. Despite holding the bulk of system liquidity, domestically systemic banks do not receive preferential pricing once liquidity positions are controlled for. Robustness checks using a Basel-aligned liquidity risk index confirm that liquidity risk is consistently priced over time. These results suggest that strengthening liquidity forecasting, enhancing fine-tuning operations, improving coordination with fiscal cash-flow cycles, and adjusting corridor design to the policy stance would reinforce interbank market stability and improve the effectiveness of Rwanda’s price-based monetary policy framework.

As the foreign direct investment (FDI)-driven catch-up model of eight Central and Eastern European (CEE-8) economies approaches its limits, strengthening the export capacity of small and medium-sized enterprises (SME) may play an important role in sustaining economic convergence within the European Union (EU). Despite deep integration into EU production networks, domestic SME participation in international trade remains limited. In this context, digitalization is increasingly seen as a factor that may reduce information, coordination, and administrative barriers associated with SME cross-border trade. This study examines how different dimensions of digitalization relate to intra-EU export performance of SMEs in the CEE-8, conceptualizing digitalization across three distinct but interacting layers: firm-level digital adoption, societal digital usage, and the institutional digital environment. Using a balanced panel dataset covering 2018–2023, the analysis employs a one-way fixed-effects estimator with wild cluster bootstrap inference to address the small-cluster setting. Results indicate that societal digital usage and digital public services for businesses are strongly and positively associated with SME intra-EU export performance. Firm-level digitalization shows a more complex pattern: internal digital tools display delayed positive associations after a maturation period, while e-commerce participation is consistently negatively associated with aggregate export volumes. Robustness checks using Driscoll-Kraay standard errors and alternative functional forms confirm the stability of the core findings. The results suggest that strengthening digital foundations and reducing cross-border digital frictions can support more effective CEE-8 SME participation in the EU Single Market.

Global value chains have recently changed structurally (“servicification”)—that is, service sectors’ involvement in global value chain processes has become more intensive. We quantify services trade restrictions’ contribution to underdevelopment of global value chain servicification across Asian economies—an underexplored area. The study applies the “structural” gravity trade model and constructs panel data based on the 2025 Trade in Value Added and the Services Trade Restrictiveness Index database developed by the Organization for Economic Co-operation and Development. The empirical analysis covers five major service sectors—trade, transport, I&C, finance, and professional services. First, global value chain servicification remains relatively underdeveloped in most emerging and developing Asian economies, particularly across several service categories. Second, services trade restrictions’ presence significantly and negatively affects global value chain servicification’s extent in these economies. Third, these restrictive measures account for approximately 30–60% of servicification’s observed underdevelopment. Regarding policy implications, removing or easing such trade restrictions could substantially promote global value chain servicification, enhancing productivity and integration for emerging and developing Asian economies.

This study examines dynamic interdependencies and risk transmission among major cryptocurrencies and traditional financial assets, including Bitcoin, Ethereum, U.S. equities, and gold, over the period 2017–2024. Particular attention is given to the structural shift associated with the 2024 U.S. spot Bitcoin exchange-traded fund (ETF) approval, which marked a significant milestone in the institutionalization of cryptocurrency markets. Using daily data, the analysis distinguishes volatility-driven co-movement from structural spillover effects across markets. Dependence structures are modeled using tail-sensitive Student-t copulas applied to GARCH-filtered returns to capture nonlinear and extreme co-movements, while a vector autoregressive framework combined with generalized impulse response functions and Diebold–Yilmaz connectedness measures is employed to evaluate order-invariant shock transmission dynamics across pre- and post-ETF regimes. The results reveal three main findings. First, cryptocurrencies display strong internal dependence and short-horizon contagion, with Bitcoin consistently acting as the dominant transmitter of shocks to Ethereum over an approximately three-day transmission window. Second, linkages between cryptocurrencies and equity markets remain moderate and largely regime-dependent rather than indicative of persistent structural spillovers. Third, gold remains weakly connected throughout the sample, maintaining its role as a diversification asset. Portfolio analysis further indicates that including Bitcoin can reduce portfolio variance by 4–7% and Value-at-Risk by up to 5%, although economic gains are sensitive to transaction costs. Overall, the findings suggest that cryptocurrencies function as a partially segmented asset class, offering conditional diversification benefits despite increasing institutional adoption.

This study examines whether size-contingent employment regulations are associated with distortions in firm size distribution and whether such patterns are more consistent with productivity-based selection or with broader constraints on firm scaling. Using 2024 census data covering 86,758 formal firms in Ecuador, we combine bunching analysis, regression discontinuity design (RDD), and logistic regression to analyze firm responses at the 10- and 50-employee thresholds. We document significant bunching below the 50-employee threshold, consistent with an economically meaningful implicit regulatory tax on firm scaling. However, RDD estimates reveal no productivity discontinuity at the cutoff, indicating that the observed threshold effects are more consistent with broad-based scaling constraints than with selective filtering of low-productivity firms. Sectoral analyses show a consistent pattern of bunching across technologically diverse industries, supporting an institutional rather than technological interpretation. Conditional on threshold proximity, firm crossing is more strongly associated with sales growth than with productivity advantages. By distinguishing between compositional avoidance and local crossing, the study sheds new light on the puzzle of absent productivity selection. These findings provide the first rigorous evidence of regulatory threshold effects in Ecuador and show how size-based regulations may distort firm scaling and contribute to allocative inefficiencies.

Financial literacy represents a fundamental competence in contemporary knowledge-based economies, particularly in the context of increasingly complex corporate financing instruments. Insufficient financial literacy may lead to suboptimal debt decisions, inefficient capital structures, and heightened financial vulnerability of firms. The aim of this paper is to assess the level of financial literacy of university students in the field of corporate debt financing and to identify key determinants influencing the correctness of their responses. The empirical analysis is based on a quantitative questionnaire survey conducted among university students in the Slovak Republic (n = 403) using a convenience sampling approach. The questionnaire included 16 knowledge-based items focused on debt financing instruments, interest mechanisms, leasing, bonds, and alternative sources of financing. Data were analysed using descriptive statistics and inferential methods, primarily Pearson’s χ2 test of independence and Cramer’s V. The results reveal considerable variability in students’ performance across thematic areas. Higher success rates were observed for basic concepts of debt financing and traditional bank products, while lower performance was recorded for analytically demanding tasks, particularly those related to interest rate comparisons, capital market instruments, and alternative financing forms. Field of study emerged as the most significant determinant of financial literacy, followed by the level of study, whereas gender and region showed only marginal effects. The findings highlight the need to strengthen application-oriented financial education in higher education, with a stronger focus on practical aspects of corporate debt financing.

The Cultural and Creative Industries (CCIs) are dynamic contributors to the global economy but face inherent vulnerabilities due to their structure of small enterprises and project-based nature. This study quantifies the economic resilience of CCIs in Mexico across multiple economic cycles from 1994 to 2023, aiming to fill a gap in quantitative evidence regarding sectoral performance during shocks. Using quarterly Gross Domestic Product (GDP) data, the research applies a counterfactual analytical framework based on resistance and recovery indices. The methodology assesses how specific subsectors—arts and entertainment, research and development (R&D), and services—deviate from national growth patterns during recessions and subsequent expansions. Empirical results indicate that while CCIs generally exhibited weak resistance during the 1994 and 2000 crises, they demonstrated robust recovery capacities. Notably, the 2008 crisis saw resilient performance in the services sector, and the COVID-19 pandemic induced exceptional recovery indices (exceeding 2.0) in arts and services, likely facilitated by rapid digitalization. The study concludes that CCI resilience is contingent on the nature of the crisis. Future sustainability requires a shift from emergency survival to “ecological resilience,” supported by public policies that address financial precariousness and foster digital adaptation.

Given the context of the COVID-19 pandemic disrupting global logistics, coupled with the Russia–Ukraine war causing global energy price changes, examining both the linear and nonlinear associations between shipping cost and oil price is crucial in a global context. This study empirically exhibits the association among Global Commodity Prices Index (GPI), Oil Price (OP), Gold Future Price (GFP), and Baltic Dry Index (BDI) by employing Linear Autoregressive Distributive Lag (ARDL) as well as Nonlinear Autoregressive Distributive Lag (Nonlinear ARDL) from January 2003 to January 2023. The findings indicate that the influence of OP on BDI has a negative impact in the long run and a positive impact in the short run. Furthermore, the OP has an asymmetric effect on BDI in both the long and short terms. Finally, the predictive performance of the NARDL model outperforms the ARDL model in forecasting OP and BDI. The empirical findings derived from the ARDL and NARDL algorithms offer valuable insights for policymakers in designing public policies and for investors in portfolio construction.

South Africa’s shift to renewable energy has been characterised by significant structural changes, primarily through the Renewable Energy Independent Power Producer Procurement Programme (REIPPPP), which achieved considerable capacity by 2016. Although this green transition aligns with environmental and economic goals, gender inequities persist in labour market outcomes, particularly in technical and leadership positions. This study examines the short- and long-term impacts of renewable energy investments and important socioeconomic elements on female labour force participation (FLFP) in South Africa. Applying a bounds testing approach based on a semi-annual autoregressive distributed lag (ARDL) model, this analysis utilises data from 2003 to 2022. It includes factors such as renewable energy investments, the share of green jobs, GDP per capita, and access to modern energy services. The results indicate a statistically significant long-term equilibrium relationship. Increased renewable energy investments align with increases in FLFP, and the growth of green jobs further boosts women’s workforce participation. GDP per capita additionally has a positive impact, highlighting the macroeconomic advantages of inclusive growth. On the contrary, access to existing energy services shows a statistically insignificant negative relationship with FLFP, suggesting that merely expanding infrastructure may not effectively tackle gendered labour disparities. This study adds to the field of energy economics by providing a gender-segregated empirical evaluation and by suggesting policy actions to foster a more inclusive and fair energy transition in South Africa.

This study applies a multiple threshold nonlinear autoregressive distributed lag (MTNARDL) model to examine the asymmetric impact of real exchange rate volatility on Vietnam’s exports and imports with its three leading trading partners: China, the United States, and South Korea. By allowing trade responses to vary across different volatility regimes, the MTNARDL framework provides a flexible approach to capturing potential nonlinear adjustment dynamics that cannot be addressed by single-threshold models. Moreover, using bilateral import and export data helps reduce aggregation bias. The results indicate the presence of asymmetric long-run adjustment dynamics in the relationship between real exchange rate volatility and bilateral trade flows, while short-run effects are generally weak and less consistent across trading partners. These findings provide valuable insights into the complex effects of exchange rate volatility, enabling policymakers to more effectively design and manage policies to mitigate its impact.