We resuscitated the mixed-frequency vector autoregression (MF-VAR) developed in Schorfheide and Song (2015, JBES) to generate macroeconomic forecasts for the U.S. during the COVID-19 pandemic in real time. The model combines eleven time series observed at two frequencies: quarterly and monthly....

Forecasting the number of Olympic medals for each nation is highly relevant for different stakeholders: Ex ante, sports betting companies can determine the odds while sponsors and media companies can allocate their resources to promising teams. Ex post, sports politicians and managers can...

Purpose: This study aims to examine the effect of the COVID-19 pandemic in comparison to the global financial crisis (GFC) on the gross domestic product (GDP) growth rate of China.Design/methodology/approach: Empirical analyses are conducted through alternative methods such as ordinary least...

Background: Forecasting nonlinear stochastic systems most often is quite difficult, without giving in to temptations to simply simplify models for the sake of permitting simple computations.Objective: Here, two basic algorithms, Adaptive Simulated Annealing (ASA) and path-integral codes...

We test the predictive accuracy of forecasts of the number of COVID-19 fatalities produced by several forecasting teams and collected by the United States Centers for Disease Control and Prevention during the first and second waves of the epidemic in the United States. We find three main...

The aim of this paper is to evaluate current quarterly nowcasts of the gross domestic product in Bosnia and Herzegovina based on the flow of available monthly economic indicators that are available during the same quarter. The nowcasting performance indicates that it is worthwhile to include a...