We propose an easy-to-implement framework for combining quantile forecasts, applied to forecasting GDP growth. Using quantile regressions, our combination scheme assigns weights to individual forecasts from different indicators based on quantile scores. Previous studies suggest distributional...

This research article presents a comparative analysis between logistic regression as a traditional method, artificial neural networks (ANNs), and decision tree as machine learning techniques for predicting credit risk. It meticulously examines and evaluates these three methods, elucidating their...

Previous research on the globalization-welfare state nexus has typically been conducted within a linear monotonic framework, focusing on two primary hypotheses. The efficiency hypothesis predicts that globalization shrinks the welfare state's size. In contrast, the compensation hypothesis argues...

We study how the threat of entry affects service quantity and quality of general prac- titioners (GPs). We leverage Germany’s needs-based primary care planning system, in which the likelihood of new GPs reduces by 20 percentage points when primary care coverage exceeds a cut-off. We compile...