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...

Traditionally, the literature on forecasting exchange rates with many potential predictors have primarily only accounted for parameter uncertainty using Bayesian Model Averaging (BMA). Though BMA-based models of exchange rates tend to outperform the random walk model, we show that when...

We develop an empirical nonlinear model of equilibrium unemployment and test its policy implications for a number of OECD countries. The model here sees the natural rate and the associated equilibrium path of unemployment as endogenous, pushed by the interaction of shocks and the institutional...

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...

This study performs the challenging task of examining the forecastability behavior of the stock market returns for the Dow Jones Industrial Average (DJIA) and the Dow Jones Islamic (DJIM) market indices, using non-parametric regressions. These indices represent different markets in terms of...

We develop models for examining possible predictors of growth of China’s foreign exchange reserves that embrace Chinese and global trade, financial and risk (uncertainty) factors. Specifically, by comparing with other alternative models, we show that the dynamic model averaging (DMA) and...

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 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...

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...

We develop models for examining possible predictors of the return on gold that embrace six global factors (business cycle, nominal, interest rate, commodity, exchange rate and stock price factors) and two uncertainty indices (the Kansas City Fed’s financial stress index and the U.S. Economic...