Utilizing a machine learning technique known as random forests, we study whether regional output growth uncertainty helps to improve the accuracy of forecasts of regional output growth for 12 regions of the UK using monthly data for the period from 1970 to 2020. We use a stochastic volatility...

We examine the predictive value of El Niño and La Niña weather episodes for the subsequent realized variance of 16 agricultural commodity prices. To this end, we use high‐frequency data covering the period from 2009 to 2020 to estimate the realized variance along realized skewness, realized...

This paper develops a New-Keynesian Dynamic Stochastic General Equilibrium (NKDSGE) model for forecasting the growth rate of output, inflation, and the nominal short-term interest rate (91 days Treasury Bill rate) for the South African economy. The model is estimated via maximum likelihood...

This paper compares the forecasting ability of five alternative types of models in predicting four key macroeconomic variables, namely, per capita growth rate, the CPI inflation, the money market rate, and the growth rate of the nominal effective exchange rate for the South African economy....

This paper uses the dynamic factor model framework, which accommodates a large cross-section of macroeconomic time series, for forecasting regional house price inflation. In this study, we forecast house price inflation for five metropolitan areas of South Africa using principal components...