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The purpose of this paper is to empirically examine whether the massive spreads and fatalities of the COVID-19 pandemic in the USA, the country with the most advanced medical technology in the world, are symptomatic of leadership failure. The authors posit that when political leaders, such as the President of the USA, in conjunction with a group of state governors and city mayors, employed conspiracy theories and disinformation to achieve their political goals, they contributed to the massive spreads and fatalities of the virus, and they also undermined the credibility of the Centers for Disease Control and Prevention (CDC) and the health-care professionals in providing the pertinent control guidelines and true scientific-based medical information.

The authors conducted a review of current studies that address the handling of global infectious diseases to build a better understanding of the issue of pandemics. They then employed a theoretical framework to link the massive spreads and fatalities of the COVID-19 pandemic to political leaders, such as President Trump and the group of obsequious state governors and city mayors, who propagated conspiracy theories and disinformation through social media platforms to downplay the severity of the virus. The authors compared the massive spreads and fatalities of the COVID-19 pandemic in the USA under President Trump to President Obama who handled H1N1, Ebola, Zika and Dengue. More importantly, the authors compared President Trump's handling of the COVID-19 pandemic to other political leaders in advanced countries where there were no concerted efforts to spread conspiracy theories and disinformation about the health risks of COVID-19 pandemic.

The authors' theoretical analysis alluded to the fact that political leaders, such as President Trump, who are engulfed in self-deceptions, self-projections and self-aggrandizements would engage in self-promotion and avoid accountability for their missteps in handling global pandemic shocks. In contrast, political leaders in other advanced countries did not downplay the severity thus their ability to curtail the spreads and fatalities of the COVID-19 pandemic.

The theoretical viewpoints presented in this paper along with the derivations of the spreads–fatalities curtailment coefficients and the spread–fatality upsurge coefficients under Presidents Obama and Trump, respectively, may not be replicable. Given this plausible limitation, future research may need to provide a deep analysis of the amplifications of conspiracy theories and disinformation because they are now deeply rooted in the political economy of the USA. Furthermore, since scientists and medical professionals may not be able to forecast future epidemics or pandemics with pin-point accuracy nor predict how political leaders would disseminate health risks information associated with different pathogens, it is imperative that future research addresses the positive or adverse effects of conspiracy theories and disinformation that are now easily propagated simultaneously through different social media platforms, which are currently protected under Section 230 of the Communications Decency Act. The multiplier effects of conspiracy theories and disinformation will continue to amplify the division about the authenticity of COVID-19 pandemic and the emergence or reemergence of other pathogens in the foreseeable future.

The authors derived the unique spreads-fatalities curtailment coefficients to demonstrate how President Obama used effective collaboration and coordination at all levels of government in conjunction with medical experts to curtail the spreads and fatalities associated with H1N1, Ebola, Zika and Dengue. They further derived the spreads-fatalities upsurge coefficients to highlight how President Trump contributed to the spreads and fatalities of COVID-19 pandemic through his inability to collaborate and coordinate with state governors, city mayors and different health-care agencies at the national and international levels.

The purpose of this paper is to investigate the income inequality dynamics in each of the 50 states of USA over the period 1981-2011.

The paper estimates an augmented Kuznets curve panel Vector AutoRegression in per capita income, economic freedom, educational attainment, unemployment, and population ageing along with evaluating generalized impulse responses functions (GIRF) and generalized forecast-error variance decompositions (GFEVD).

All the variables are integrated of order one and are panel cointegrated. Kuznets’ hypothesized inverted U-shaped relationship between inequality and growth is not supported by the data. Unemployment and population ageing have statistically significant positive effects on inequality in the long-run; education has statistically significant negative impact; economic freedom has statistically insignificant positive effect. Long-run bidirectional causality exists among the variables. GFEVD show that excluding income inequality itself, variation in income inequality is more influenced by perturbations in per capita income, educational attainment, and unemployment. GIRF corroborate the results of the GFEVD.

This paper fulfills an identified need to study the causal relationship between inequality and its determining factors without assuming the a priori exogeneity or endogeneity of the underlying variables.

The purpose of this paper is to examine the dynamic and long-run relationships among public debt, FDI and output growth in five individual Caribbean countries over the period 1975–2015.

Zivot and Andrews (1992) unit root test with structural break is used to examine the stationarity of the variables and then the autoregressive distributed lag bounds testing procedure is used to ascertain existence of cointegration among them. Finally, order-invariant generalized forecast error variance decomposition (GFEVD) is used to establish the strength of the causal relationship between the examined variables.

The results confirm that the examined variables are cointegrated. FDI, domestic investment, trade openness, human capital (HC) and institutional quality were found to have significantly positive effects on economic growth, while higher public debt and inflation rates hampered growth. GFEVD revealed unidirectional Granger causality running from FDI to economic growth in two countries; unidirectional causality from growth to FDI in two other countries; and bidirectional causality between growth and FDI in one other country. The results also indicate one-way causality from output growth to public debt in three countries and bidirectional causality between these two variables in two other countries.

The implication is that the Caribbean Governments may need to adopt effective debt management as a major policy and intensify efforts at utilizing loans obtained judiciously for human and capital projects that have direct positive net present value but, to secure strong and inclusive growth, these strategies must be linked to policies that enhance macroeconomic stability and the quality of their institutions, encourage capital inflows and domestic investments vis-à-vis domestic savings, and increase HC and trade earnings.

In contrast to extant studies of the public debt–FDI–output growth nexus, this study controls for the possibility of structural breaks in unit root tests along with performing bounds test for cointegration, variance decomposition analysis, Granger causality tests, and CUSUM and CUSUMSQ tests for the stability of the dynamic output growth model. This is a unique contribution to the existing literature, and highlights the originality value of this paper.