The coronavirus has deleteriously affected a great majority of countries in the world. Developed societies such as the United States and the majority of Western countries have had the highest rates of mortality because of the pandemic. Sub-Saharan Africa, on the other hand, has been the...

The structure of a national economy is generally correlated with the stage of economic development. In economic history, it was demonstrated a trend from a first stage when agriculture predominated to last stage when the sector of services is the largest. In this context, the complex...

This study re-examines the long-run relationship among foreign direct investment (FDI), renewable energy consumption (RE) and economic growth (GDP) for 9 Middle East and North Africa (MENA) countries over the period 1990–2015 using a newly developed cointegration test by McNown et al. (2018),...

This study re-examines the long-run relationship among foreign direct investment (FDI), renewable energy consumption (RE) and economic growth (GDP) for 9 Middle East and North Africa (MENA) countries over the period 1990–2015 using a newly developed cointegration test by McNown et al. (2018),...

We address the issue of estimation and inference in dependent nonstationary panels of small cross-section dimensions. The main conclusion is that the best results are obtained applying bootstrap inference to single-equation estimators. SUR estimators perform badly, or are even unfeasible, when...

We address the issue of panel cointegration testing in dependent panels, showing by simulations that tests based on the stationary bootstrap deliver good size and power performances even with small time and cross-section sample sizes and allowing for a break at a known date. They can thus be an...

The Common Correlated Effects (CCE) approach by Pesaran2006 is a popular method for estimating panel data models with interactive effects. Due to its simplicity, i.e. unobserved common factors are approximated with cross-section averages of the observables, the estimator is highly flexible and...

Forecasting the vote share for the upcoming US presidential elections involves multiple pivotal economic and non-economic factors. Critical macroeconomic forces such as the rate of economic growth, tax burden, inflation, and unemployment significantly influence the votes gained or lost by the...

Non-Gaussian state-space models arise in several applications, and within this framework the binary time series setting provides a relevant example. However, unlike for Gaussian state-space models — where filtering, predictive and smoothing distributions are available in closed form — binary...

The outcome of the US presidential election is one of the most significant events that impacts trade, investment, and geopolitical policies on the global stage. It also sets the direction of the world economy and global politics for the next few years. Hence, it is of prime importance not just...