Search Results (473)

This study investigates the determinants of GDP per capita across 26 European Union member states over the period of 2006–2024, with a particular focus on entrepreneurship, institutional quality, and macroeconomic factors. Given the presence of long-run income differences across EU countries, the analysis explicitly accounts for structural heterogeneity in economic development and institutional capacity. To ensure robust estimation in the presence of cross-sectional dependence and slope heterogeneity, the study employs advanced panel econometric techniques, including tests for cross-sectional dependence, unit roots, and cointegration. Long-run relationships and short-run dynamics are estimated using the Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL) model, complemented by robustness checks based on the Augmented Mean Group (AMG) and Common Correlated Effects Mean Group (CCEMG) estimators. In addition, the Method of Moments Quantile Regression (MMQR) is applied to capture heterogeneity across different points of the income distribution, thereby reflecting long-run income disparities among EU member states. The empirical results confirm the existence of a stable long-run equilibrium relationship among the variables. The baseline CS-ARDL estimates indicate that institutional quality, entrepreneurial activity, trade openness, and government expenditure exert positive and statistically significant effects on GDP per capita, while financial development exhibits a negative effect and foreign direct investment remains insignificant. In the short run, entrepreneurship and trade openness contribute positively to GDP per capita, whereas government expenditure and credit expansion generate contractionary effects. The robustness analysis using AMG and CCEMG estimators largely supports these findings, as the direction of the coefficients remains consistent across alternative specifications, although some variation in statistical significance is observed due to differences in the treatment of cross-sectional dependence and unobserved common factors. The MMQR results further reveal substantial heterogeneity across the income distribution, indicating that the effects of key determinants vary depending on countries’ long-run income levels. In particular, trade openness and institutional quality exert stronger positive effects in lower-income quantiles, while the adverse effects of excessive financial development are more pronounced in higher-income quantiles. Overall, the findings underscore the importance of promoting productive entrepreneurship, strengthening institutional frameworks, facilitating trade integration, and ensuring efficient financial intermediation to enhance GDP per capita within the European Union. The results also highlight the need for differentiated policy approaches that explicitly account for long-run income heterogeneity, structural differences, and varying institutional capacities across EU member states. Full article

This study examines the time–frequency dynamics between CO₂ emissions and their determinants—oil prices, renewable energy deployment, and climate policy uncertainty—in Türkiye from 1987Q2 to 2024Q1. We integrate a rolling-window Nonlinear Autoregressive Distributed Lag (NARDL) model with wavelet coherence analysis to capture evolving asymmetric effects and multi-scale transmission mechanisms. Our findings reveal pronounced, persistent asymmetries. Oil price decreases stimulate CO₂ emissions substantially more than equivalent price increases reduce them, yielding a negative asymmetry effect. Renewable energy demonstrates a stable, negative long-run relationship with emissions, with wavelet analysis indicating this effect concentrates over medium-to-long-term horizons, underscoring its structural decarbonization role. Climate policy uncertainty exerts fragmented, episodic influences, disrupting short-to-medium-term emission trajectories. Rolling-window estimates confirm these asymmetric relationships shift markedly around structural breaks, including the 2001 domestic crisis and the 2008 global financial crisis. The study concludes that effective decarbonization requires temporally calibrated policies: counter-cyclical carbon pricing to offset oil price asymmetries, and credible long-term frameworks to sustain renewable energy investments. Methodologically, the results demonstrate the value of combining time-domain and frequency-domain techniques to diagnose complex, evolving interactions in the energy–environment nexus. Full article

The deployment of agricultural inputs considerably influences national agrarian output, which is a key driver of economic growth. This study contributes to the literature by examining how changes in crop yield growth reflect resource allocation in agricultural production. Data spanning 1994 to 2019, obtained from the World Bank, were used to examine the impact of agricultural input productivity on agricultural output. The 26-year time-series data were employed for the Organization for Economic Co-operation and Development (OECD) and Latin American Caribbean (LAC). The findings from the Autoregressive Distributed Lag model, along with the Vector Error Correction Model, reveal a negative but significant long-term impact of agricultural land use on crop yields in OECD, and a negative and insignificant impact in LAC countries. Moreover, agricultural land use showed a positive but insignificant short-run effect on crop yield in OECD countries, while a negative and insignificant short-run effect was observed in LAC countries. This study highlights disparities in agricultural productivity drivers between OECD and LAC regions. By linking productivity dynamics with input utilization, the analysis provides policy-relevant insights for improving sustainability, food security, and agricultural productivity. Full article

A strong transportation infrastructure is critical in advancing ICT trade by facilitating the efficient movement of goods and services. This efficiency enhances supply chains and attracts greater foreign direct investment, ultimately supporting technological development and boosting the economy. This article evaluates the relationship between transportation infrastructure (TI), information and communication technology trade openness (ICT trade), foreign direct investment (FDI), and economic growth (GDP) in Saudi Arabia from 1990 to 2023. Using the Autoregressive Distributed Lag (ARDL) model, we found that ICT trade has a statistically significant positive effect on long-run GDP growth. However, in the short run, ICT trade has a positive but non-significant impact on GDP growth. Additionally, the results show that TI has a statistically significant negative effect on short-run GDP growth. Moreover, the non-linear Threshold Regression model results show a threshold value for information and communication technology trade openness (ICT trade) of approximately 0.4051. Specifically, the findings indicate that increased ICT trade reduces the negative impact on economic growth beyond a certain threshold. This study is highly significant for Saudi Arabian decision-makers, as it highlights the roles of transportation infrastructure and ICT trade in attracting FDI and bolstering the economy. Full article

This study examines the asymmetric responses of stock market indices in Türkiye and Kazakhstan to oil price shocks during the 2010–2025 period. Using the Nonlinear Autoregressive Distributed Lag (NARDL) model, the study decomposes the nonlinear effects of oil price fluctuations on financial markets. Empirical findings reveal that in Türkiye, a net oil importer, the stock market exhibits a dual-sensitivity: while exchange rate dynamics (2.34) remain the dominant driver, oil price increases (−0.12) exert a direct and statistically significant negative pressure. In contrast, Kazakhstan, a net oil exporter, shows a high vulnerability to oil price decreases (−1.05) at the 1% significance level, confirming a strong asymmetric structure (p = 0.0122). Furthermore, the error correction speed is significantly higher in Türkiye (28%) than in Kazakhstan (4%), indicating divergent market efficiency and recovery mechanisms. These results demonstrate that financial market reactions to external shocks differ fundamentally based on energy trade structures. The findings suggest that oil-importing countries must prioritize exchange rate stability, while oil-exporting nations must develop specific policy buffers against the persistent downside risks of global energy cycles. Full article

The present study examines the relationship between environmental, economic, and bioenergy impacts of renewable energy in Egypt, spanning from 1990 to 2023. The study utilizes three distinct models, concluding that all variables remain stationary at I(0) and I(1). Therefore, analysis is conducted using the Autoregressive Distributed Lag (ARDL) approach. Model 1 captures the relationship between bioenergy production and GDP per capita, as well as the significant impact of capital formation on economic growth. Models 2 and 3 of the study have CO₂ emissions as the dependent variable, which indicates that renewable energy, urbanization, GDP per capita, and bioenergy production have a significant impact. Moreover, the short-run analysis conducted using the Error Correction Model (ECM) reveals the model’s long-run convergence. The study’s findings also support the environmental Kuznets curve (EKC) hypothesis, and the interaction term between bioenergy and GDP per capita is found to contribute to carbon dioxide emissions. To achieve a low-carbon and growth-oriented economy, policymakers should encourage investment in renewable energy, as it enhances technological efficiency and fosters sustainable agricultural growth. Full article

This study investigates whether fluctuations in the real exchange rate give rise to symmetric or asymmetric J-curve effects in manufacturing trade between Türkiye and Germany, thereby positioning the analysis within and contributing to the broader scholarly discourse on exchange rate–trade balance dynamics. Using monthly data for the period 2013M01–2025M07, the paper first estimates a linear Autoregressive Distributed Lag (ARDL) model for the bilateral manufacturing trade balance and subsequently extends the framework to a nonlinear ARDL (NARDL) specification, which explicitly incorporates symmetry and asymmetry by decomposing real exchange rate changes into positive (depreciation) and negative (appreciation) partial sums. The linear ARDL results provide no evidence of a conventional J-curve and suggest that the aggregate impact of the real exchange rate is weak and often statistically insignificant. In contrast, the NARDL estimates uncover pronounced long-run and cumulative short-run asymmetries: real depreciations of the Turkish lira are associated with a persistent improvement in the bilateral manufacturing trade balance, whereas appreciations exert weak and statistically insignificant effects, a finding that remains robust when a real effective exchange rate measure is employed. Overall, the evidence indicates that Türkiye–Germany manufacturing trade does not conform to the standard J-curve pattern. These findings suggest that trade policy should adopt an asymmetric stance toward exchange rate movements: since depreciations yield persistent trade balance improvements while appreciations produce negligible effects, policies designed to support export competitiveness should prioritize the management of depreciation episodes rather than assuming symmetric adjustment dynamics. Full article

This study examines selected factors influencing white maize price movements in South Africa over the period 1994–2024. Given the importance of white maize for food security, understanding the drivers of producer price dynamics is essential for effective policy formulation and managing price stability. Annual time-series data are analysed using an Autoregressive Distributed Lag (ARDL) modelling framework, complemented by bounds testing, an error-correction model, Toda–Yamamoto causality and structural break tests. The bounds test confirms the existence of a stable long-run cointegrating relationship between maize prices and the selected explanatory variables. In the short run, imports and fuel prices exert significant upward pressure on maize producer prices, while lagged fuel prices and rainfall reduce prices. In the long run, imports and fuel prices remain statistically significant determinants, whereas maize production, exports, the exchange rate, and rainfall are insignificant. Complemented with the structural break tests that identify regime shifts in the early 2000s, 2012, and 2021, causality results indicate that imports, rainfall and fuel prices lead to Granger causality in maize producer prices. Collectively the findings reinforce the conclusion that white maize prices in South Africa are governed by long-run structural relationships, while short-run price movements reflect temporary adjustments rather than permanent shifts in market fundamentals. An integrated, long-horizon analysis that jointly incorporates climatic, trade, and macroeconomic determinants within an ARDL framework is provided by the study. Therefore, the findings have important implications for climate-risk management, transport cost containment, trade and price-stabilisation policies. Full article

This paper investigates the interaction between fiscal policy and non-performing loans (NPLs), a nexus often overlooked in banking stability literature. By proposing a generalized theoretical framework that augments the industrial organization (IO) theory of banking with liquidity preference theory, this study explains why a fiscal contraction (an improvement in the primary balance from deficit toward surplus) can decrease NPLs in a bank’s portfolio. Using bank-level quarterly data from Guyana (2009: Q4 to 2024: Q4) and a Panel Autoregressive Distributed Lag Pooled Mean Group (ARDL-PMG) model, we find that a fiscal contraction reduces NPLs in the long run. Specifically, a one-percentage-point improvement in the seasonally adjusted primary balance (as a % of GDP) is associated with a 0.473 percentage point decrease in NPLs in the long run. This finding contrasts with the existing literature, which often suggests that fiscal consolidations increase credit risk. In the short run, however, the results indicate a divergent effect where fiscal contractions lead to a temporary increase in NPLs, with a coefficient of 0.103, likely because of immediate pressure on borrower debt-service capacity. This study contributes to the literature by extending the IO theory of banking to the fiscal policy–NPL relationship in a developing, resource-rich economy. Notably, while higher oil prices and bank efficiency significantly lower NPLs, traditional macroeconomic drivers such as GDP growth, inflation, and the real effective exchange rate—as well as the COVID-19 pandemic—are found to be statistically insignificant in this framework. Full article

Optimal dividend policy remains a key topic of debate in corporate finance, particularly in emerging markets where investor preferences and macroeconomic volatility affect decision making. This study therefore examines the relationship between dividend policy and the Johannesburg Stock Exchange (JSE) market index over the period 2000 to 2020. The study uses firm-level dividend data to construct a market-capitalization-weighted aggregate dividend index. The paper further employs an Autoregressive Distributed Lag (ARDL) and error correction model to assess the long-run equilibrium relationship and short-run adjustments. The results show evidence of a long-run relationship between dividends and the JSE index price. In the short run, dividend payments exhibit negative effect on index prices while lagged dividends have a significant positive effect on index implying delayed market response. These findings suggest that South African investors place more confidence and emphasis on capital gains rather than dividend distributions. This study contributes evidence on the aggregate dividend dynamics within the context of an emerging market and offers practical insights for managers, investors and policy makers. Full article

We propose a fully nonparametric empirical autoregressive copula framework for univariate time series, designed to capture nonlinear and asymmetric serial dependence while exactly preserving the empirical marginal distribution. The method decouples marginal behavior from temporal dependence by (i) constructing a shape-preserving empirical marginal via monotone interpolation and mapping observations to the unit interval, and (ii) estimating the lag–lead dependence through a nonparametric conditional AR(1) copula density on ${(0,1)}^2$. To ensure stable estimation near the boundaries, we employ reflection-based kernel methods that mitigate edge effects and yield well-behaved conditional densities on the unit support. Forecasts are obtained from the implied conditional predictive density: we compute point forecasts either as conditional modes (maximum a posteriori) on the copula scale or as conditional means, and then back-transform exactly using the empirical quantile function, guaranteeing marginal fidelity and support-respecting predictions. Empirically, we evaluate the approach on three CBOE volatility indices (VIX, VXD, and RVX) and benchmark it against linear ARMA models, copula-based parametric competitors, and state-space/heteroskedasticity baselines (Local level, TVP–AR, and ARMA–GARCH). The results highlight that modeling the full conditional transition density nonparametrically can deliver competitive—often best or near-best—forecast accuracy across horizons, particularly in the presence of pronounced volatility regimes and asymmetric adjustments. Full article

This paper examines the impact of public debt servicing on private investment in Egypt within the debt overhang hypothesis. While existing research largely focuses on the debt–growth relationship, limited attention has been given to how debt servicing burdens affect private capital formation. Using annual data from 1990 to 2023, the study employs an Autoregressive Distributed Lag (ARDL) model to estimate short-run and long-run dynamics between private sector gross fixed capital formation and key mac-roeconomic variables. Results provide statistically significant evidence of a long-run debt overhang effect, whereby debt servicing exerts a persistent negative impact on private investment. Short-run effects appear temporarily expansionary but dissipate as servicing pressures accumulate. The analysis focuses on Egypt-where debt servicing pressures have repeatedly intensified in response to external shocks and exchange rate adjustments-but offers broader implications for emerging market and developing economies. The paper contributes to the literature by identifying repayment capacity as the key transmission channel through which public debt affects private investment. In contexts characterized by liquidity constraints, external vulnerabilities, and refinancing risks, debt servicing burdens-rather than debt levels alone-constitute the binding con-straint on private capital formation. Accordingly, the findings emphasize the im-portance of assessing debt sustainability through servicing obligations and repayment pressures. Full article

The volatility of oil prices has a considerable impact on the economies of oil-exporting countries, making it critical to understand how price variations affect labour markets and unemployment. This study investigates the distinct role of labour market institutions in moderating the effects of oil price volatility on unemployment. Using the Cross-Sectionally Augmented Autoregressive Distributed Lag Model (CS-ARDL) on a panel dataset of nine African oil-exporting countries from 1994 to 2024, the study establishes a strong negative link between oil price changes and unemployment. Furthermore, the results show that real GDP growth leads to a reduction in unemployment in the long run, while the labour market institutional index has a negative impact on unemployment. Interacting the oil price with the labour market institutional index causes a further reduction in unemployment. These results suggest that good labour market institutions and macroeconomic stability are essential for reducing unemployment. While increases in oil prices directly stimulate a reduction in unemployment in African oil-exporting countries, this impact is reinforced by the presence of good labour market institutions in an economy. Therefore, the results suggest that countries with strong labour market institutions are more resilient in reducing the negative impact of oil price volatility on employment. As such, policymakers must prioritise labour market institutional reforms to enhance countries’ capacity to absorb oil price shocks and reduce unemployment during periods of oil prosperity and shield against employment declines when oil prices drop. Furthermore, the creation of oil stabilisation funds in these countries may serve a similar purpose. Contribution/originality: Against a background of inconclusive empirical evidence in the literature and a dearth of research on African countries, this study investigates the role of labour market institutions (LMIs) in the oil price–unemployment nexus in African oil-exporting countries. While highly dependent on oil revenue, these countries record persistent structural unemployment. Therefore, the study provides critical evidence to guide the formulation of policies necessary to deal with external shocks and facilitate structural shifts required for employment growth. Existing studies consider general institutional variables such as democratic accountability and the rule of law and do not assess the effect of labour market institutions. The current study fills in this gap by assessing the distinct role of labour market institutions that are specifically designed to regulate only work-related activities, such as quality of labour regulations, adequacy of social protection and unemployment benefits. Furthermore, this study employed the cross-sectionally augmented autoregressive distributed lag (CS-ARDL) for econometric estimations. Compared to previous studies, this is a more appropriate method that accounts for unobserved common factors such as oil price shocks affecting all oil-exporting countries simultaneously. Full article

This study investigates the forward discount puzzle by examining the dynamic relationships among excess returns arising from interest rate parity deviations, interest rate differentials, and the USD/JPY exchange rate. The empirical analysis employs correlation analysis, the Autoregressive Distributed Lag (ARDL) cointegration test, and variance decomposition together with impulse response functions derived from a Toda–Yamamoto augmented Vector Autoregressive (VAR) model, using data spanning January 2001 to September 2025. The correlation results indicate that the spot exchange rate is negatively related to both the swap rate and the interest rate differential. Impulse response analysis shows that the USD/JPY rate responds positively to swap rate shocks in the medium to long run, while responding negatively to interest rate differential shocks in the short run. Variance decomposition results are consistent with the impulse response analysis and underscore the dominant bilateral linkage between the exchange rate and the swap rate. The long-run ARDL estimates further reveal that the swap rate is positively associated with dollar appreciation, whereas both the interest rate differential and relative output are negatively related. Overall, although short-run arbitrage appears temporarily, the cointegration and dynamic results provide robust evidence that the forward discount puzzle persists for a substantial period rather than interest rate parity holding. Full article

The global transport sector stands at a critical juncture where economic growth imperatives intersect with urgent environmental sustainability challenges. This paper investigates the impact of air freight transport, digitalisation, energy consumption, economic growth, and regulatory quality on CO₂ emissions in Gulf Cooperation Council (GCC) countries. Despite the region’s strategic importance in global air freight networks and rapid digital transformation, empirical evidence on how these factors collectively influence environmental sustainability remains limited. GCC countries provide a unique context for examining the digitalisation–transport–environment nexus. Using panel data from six GCC member states spanning 1999–2022, this study employs a second-generation autoregressive distributed lag (CS-ARDL) model to analyse short- and long-run relationships while accounting for cross-sectional dependence and heterogeneity. The empirical model designates CO₂ emissions as the dependent variable, while the digitalisation indicator, air freight transport, and energy consumption serve as principal explanatory variables. The empirical findings indicate that energy consumption and economic growth are significant drivers of CO₂ emissions in GCC countries, while digitalisation is associated with lower emissions. Regulatory quality exhibits a weaker but non-negligible negative influence. Moreover, air freight transport does not display a significant long-run effect on emission in the GCC context. These findings are robust across multiple panel estimators. The research provides evidence-based guidance for GCC national vision programmes, green aviation initiatives, and digital transformation strategies, contributing to a sustainable development discourse in resource-rich economies. Full article