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 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...

We use quantile random forests (QRF) to study the efficiency of the growth forecasts published by three leading German economic research institutes for the sample period from 1970 to 2017. To this end, we use a large array of predictors, including topics extracted by means of...

We study the efficiency of growth and inflation forecasts published by three leading German economic research institutes during a period of time ranging from 1970 to 2017. To this end, we examine whether the information used by the research institutes when they formed their forecasts helps to...

We use a machine-learning algorithm known as boosted regression trees (BRT) to implement an orthogonality test of the rationality of aggregate stock-market forecasts. The BRT algorithm endogenously selects the predictor variables used to proxy the information set of forecasters so as to maximize...

We study the predictability of stock returns using an iterative model-building approach known as quantile boosting. Examining alternative return quantiles that represent normal, bull and bear markets via recursive quantile regressions, we trace the predictive value of extensively studied...

This paper proposes an iterative model-building approach known as quantile boosting to trace out the predictive value of realized volatility and skewness for gold futures returns. Controlling for several widely studied market- and sentiment-based variables, we examine the predictive value of...

We revisit the sources of the bias in Federal Reserve forecasts and assess whether a precautionary motive can explain the forecast bias. In contrast to the existing literature, we use forecasts submitted by individual FOMC members to uncover members' implicit loss function. Our key finding is...

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...