We use a machine-learning approach known as Boosted Regression Trees (BRT) to reexamine the usefulness of selected leading indicators for predicting recessions. We estimate the BRT approach on German data and study the relative importance of the indicators and their marginal effects on the...

We use a Panel Smooth Transition Regression (STR) model to study nonlinearities in the expectation-formation process in the U.S. stock market. To this end, we use data from the Livingston survey to investigate how the importance of regressive and extrapolative expectations fluctuates over time...

We use a Panel Smooth Transition Regression (STR) model to study nonlinearities in the expectation-formation process in the U.S. stock market. To this end, we use data from the Livingston survey to investigate how the importance of regressive and extrapolative expectations fluctuates over time...

We use a Panel Smooth Transition Regression (STR) model to study nonlinearities in the expectationformation process in the US stock market. To this end, we use data from the Livingston survey to investigate how the importance of regressive and extrapolative expectations fluctuates over time as...

Economic theory predicts that, in a small open economy, the dynamics of the real price of gold should be linked to real interest rates and the rate of change of the real exchange rate. Using data for Australia, we use a real-time forecasting approach to analyze whether real interest rates and...

We use Bayesian additive regression trees to reexamine the efficiency of growth and inflation forecasts for Germany. To this end, we use forecasts of four leading German economic research institutes for the sample period from 1970 to 2016. We reject the strong form of forecasts efficiency and...