This study examines the asymmetric effects of fiscal policy on economic growth in Uganda using annual data from 1983 to 2020 obtained from the Uganda Revenue Authority and the World Bank. Employing the Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) tests, the results reveal a mixture of I(0) and I(1) variables, justifying the use of the NARDL bounds testing approach to cointegration. The findings confirm a long-run cointegrating relationship among the variables and demonstrate significant asymmetric effects of fiscal policy, particularly government expenditure and tax revenue on economic growth in the long run, while short-run asymmetry is mainly observed in tax revenue, with overall fiscal responses appearing symmetric. These results imply that positive and negative fiscal shocks have differing impacts on growth over time, leading to the recommendation that fiscal policy be strategically directed toward productive investments, improved private sector support, and the creation of an enabling environment to accelerate sustainable economic growth and facilitate the attainment of middle-income status.
Applied Economics and Finance (AEF) would like to acknowledge the following reviewers for their assistance with peer review of manuscripts for this issue. Many authors, regardless of whether AEF publishes their work, appreciate the helpful feedback provided by the reviewers. Their comments and suggestions were of great help to the authors in improving the quality of their papers. Each of the reviewers listed below returned at least one review for this issue.Reviewers for Volume 13, Number 1 Erdal Gumus, Eskisehir Osmangazi University, TurkeyGetamesay Bekele Meshesha, Ethiopian Civil Service University, EthiopiaIgor Matyushenko, School of Foreign Economic Relations and Touristic Business, UkraineInam Ullah, Allama Iqbal Open University , PakistanLucas Rentschler, Utah State University, USALuis Alberiko Gil-Alana, University of Navarra, SpainMarcos Roberto Vasconcelos, Universidade Estadual de Maringá – Programa de Pós-graduação em Ciências Econômicas (Maringá State University – Postgraduate Program in Economic Sciences), BrazilPayal Chadha, University of Wales Prifysgol Cymru, KuwaitSaudin TERZIC, University Vitez, Bosnia and HerzegovinaShaoshu LI, Cornell University , USASzabolcs Blazsek, Mercer University, Macon, GuatemalaWolday D. Abrha, University of Tennessee at Chattanooga, USA Nikki GibbsEditorial AssistantOn behalf of,The Editorial Board of Applied Economics and FinanceRedfame Publishing9450 SW Gemini Dr. #99416Beaverton, OR 97008, USAURL: http://aef.redfame.com
This study examines the relationship between investor sentiment and stock market volatility in the West African Economic and Monetary Union (WAEMU) using data from the West African Regional Stock Exchange (BRVM). Based on daily data spanning the period 2010–2022, five volatility models are estimated and compared: Generalized Autoregressive Conditional Heteroskedasticity [GARCH(1,1)], Exponential Generalized Autoregressive Conditional Heteroskedasticity [EGARCH(1,1)], Asymmetric Power ARCH [APARCH(1,1)], Fractionally Integrated Generalized Autoregressive Conditional Heteroskedasticity [FIGARCH(1,d,1)] and the RiskMetrics model. The empirical results indicate a high degree of volatility persistence, pronounced asymmetric effects, and the presence of long-memory dynamics in BRVM stock returns. Among the competing specifications, the EGARCH model with an asymmetric Student’s t distribution provides the best overall performance in terms of model fit and forecasting accuracy. Furthermore, the inclusion of an investor sentiment index leads to an improvement in volatility forecasts, highlighting the relevance of behavioral factors in explaining market risk dynamics. These findings suggest that investor sentiment plays an important role in volatility dynamics in emerging African stock markets, while also underscoring the need for caution in interpreting sentiment-based measures due to potential methodological limitations.
Strategic supply chains have become a central concern for economic policy as geopolitical fragmentation, export controls, and industrial subsidies reshape global trade. This study evaluates how recent U.S. trade and industrial policies have affected the effective availability of semiconductor inputs—a critical determinant of productivity, innovation, and economic resilience. Using detailed bilateral trade data from UN Comtrade (2020–2024), the paper constructs a CES-based import aggregator that adjusts observed trade flows for tariffs, export controls, and geopolitical risk. The empirical results show that while nominal semiconductor imports recovered after the pandemic, policy-adjusted effective availability experienced significant volatility following the introduction of import controls and targeted tariffs. Dependence on East Asian suppliers—particularly Japan, South Korea, and the Netherlands—remains structurally high, especially for advanced equipment and lithography inputs. However, diversification toward allied and regional partners partially offset policy-induced access constraints by 2024. The findings highlight three applied insights. First, industrial policy can stabilize supply access without full reshoring when substitution elasticities are sufficiently high. Second, targeted restrictions impose short-run costs on effective availability but may accelerate long-run diversification. Third, resilience depends more on supplier substitutability and policy coordination than on import volume alone. These results inform ongoing debates on industrial policy effectiveness, strategic trade management, and supply-chain resilience in advanced and emerging economies.
This study develops a hybrid Bayesian modeling framework to estimate the probability of large-scale foreign divestment from U.S. Treasury securities and to assess the stability of the U.S. dollar’s reserve-currency status. The model integrates a Mixture Density Network (MDN) with Hamiltonian Monte Carlo (HMC) sampling to approximate the conditional distribution of reserve holdings given observed macroeconomic fundamentals and an inferred latent variable representing geopolitical alignment. Principal component analysis and hierarchical regularization are applied to ensure parsimony and mitigate overfitting in a small-sample environment. The empirical hazard rate is defined as the annual probability of a 10 percent contraction in foreign U.S. Treasury holdings—a threshold consistent with historical reserve reallocations during the sterling’s decline and central-bank portfolio adjustment behavior. Results indicate an estimated 6–12 percent annual probability at a 95 percent confidence interval, implying that a 10 percent drawdown could occur roughly once every 8–16 years under current macro-financial conditions. While Gaussian mixture components likely understate extreme tail risks, the findings highlight the resilience of U.S. reserve status and suggest that any future transition would be gradual, multi-decade, and contingent on structural geopolitical realignments rather than cyclical shocks.
