79 citations · 86 across the 7 of their papers we have counts for
7 papers
Simple Macroeconomic Forecast Distributions for the G7 Economies
Friederike Becker, Fabian Krüger, Melanie Schienle
We present a simple method for predicting the distribution of output growth and inflation in the G7 economies. The method is based on point forecasts published by the International…
Modeling Spatial Extremal Dependence of Precipitation Using Distributional Neural Networks
Christopher Bülte, Lisa Leimenstoll, Melanie Schienle
In this work, we propose a simulation-based estimation approach using generative neural networks to determine dependencies of precipitation maxima and their underlying uncertainty…
Direction Augmentation in the Evaluation of Armed Conflict Predictions
Johannes Bracher, Lotta Rüter, Fabian Krüger +2
In many forecasting settings, there is a specific interest in predicting the sign of an outcome variable correctly in addition to its magnitude. For instance, when forecasting arme…
Robust Knockoffs for Controlling False Discoveries With an Application to Bond Recovery Rates
Konstantin Görgen, Abdolreza Nazemi, Melanie Schienle
We address challenges in variable selection with highly correlated data that are frequently present in finance, economics, but also in complex natural systems as e.g. weather. We d…
Predicting Value at Risk for Cryptocurrencies With Generalized Random Forests
Rebekka Buse, Konstantin Görgen, Melanie Schienle
We study the prediction of Value at Risk (VaR) for cryptocurrencies. In contrast to classic assets, returns of cryptocurrencies are often highly volatile and characterized by large…
How have German University Tuition Fees Affected Enrollment Rates: Robust Model Selection and Design-based Inference in High-Dimensions
Konstantin Görgen, Melanie Schienle
We use official data for all 16 federal German states to study the causal effect of a flat 1000 Euro state-dependent university tuition fee on the enrollment behavior of students d…
Nonparametric regression with nonparametrically generated covariates
Enno Mammen, Christoph Rothe, Melanie Schienle
We analyze the statistical properties of nonparametric regression estimators using covariates which are not directly observable, but have be estimated from data in a preliminary st…