The conduct of inflation targeting is heavily dependent on accurate inflation forecasts. Non-linear models have increasingly featured, along with linear counterparts, in the forecasting literature. In this study, we focus on forecasting South African infl ation by means of non-linear models and...

This paper employs classical bivariate, factor augmented (FA), slab and spike variable selection (SSVS)-based, and Bayesian semiparametric shrinkage (BSS)-based predictive regression models to forecast the US real private residential fixed investment series over an out of sample period of 1983Q1...

Information on economic policy uncertainty (EPU) does matter in predicting oil returns especially when accounting for omitted nonlinearities in the relationship between these two variables via a time-varying coefficient approach. In this work, we compare the forecastability of standard, Bayesian...

Evidence in favour of the monetary model of exchange rate determination for the South African Rand is at best mixed. A co-integrating relationship between the nominal exchange rate and fundamentals forms the basis of the monetary model. With the econometric literature suggesting that it is the...

This paper evaluates the ability of Bayesian shrinkage-based dynamic predictive regression models estimated with hierarchical priors (Adaptive Jefferys, Adaptive Student-t, Lasso, Fussed Lasso and Elastic Net priors) and non-hierarchical priors (Gaussian, Lasso-LARS, Lasso-Landweber) in...

This paper is the ?rst one to analyze the ability of linear and nonlinear monetary policy rule specifications as well as nonparametric and semiparametric models in forecasting the nominal interest rate setting that describes the South African Reserve Bank (SARB) policy decisions. We augment the...