I am an economist and a professional forecaster for RWI – Leibniz Institute of Economic Research in Essen, Germany at the division Macroeconomics and Public Finance.

I am part of the junior faculty of the Ruhr Graduate School of Economics and a research fellow of DocMA - an interdisciplinary research project in which algorithms process huge amounts of newspaper articles and texts of social media in order to recognize patterns.

On this page you will find my research, forecasts, replication codes, and previous teaching materials.


  • Applied Macroeconomics
  • Forecasting
  • Econometrics
  • Bayesian Methods
  • Teaching


  • PhD in Economics, 2015

    Hamburg Graduate School of Economics at the University of Hamburg

  • MSc in Economics, 2011

    University of Bonn

  • BSc Economics and Management, 2008

    University of Magdeburg


Improving inference and forecasting in VAR models using cross-sectional information

We propose a flexible prior for vectorautoregressions (VARs) which can exploit the panel structure of macroeconomic time series and at the same time provide shrinkage towards zero in order to address overfitting concerns. The prior is flexible as it allows for parameter pooling across both a country dimension (two countries are completely alike) and/or variable dimension (dynamics of two variables across countries are alike). The usefulness of our approach is demonstrated via a Monte Carlo study and an empirical application using a large euro area data set. We find that cross country information helps deliver sharper parameter inference that improves point and density forecasts as well as structural analysis through lower estimation uncertainty. Also it is beneficial to have both pooling and shrinkage instead of only pooling.

The investment narrative: Improving private investment forecasts with media data

In this paper we use newspaper articles to generate time series that are related to corporate investment and look at their ability to predict its dynamics.

Monetary policy uncertainty and inflation expectations

In this paper we study whether inflation expectations in the U.S. react to changes in monetary policy uncertainty (MPU) as measured through the volatility of monetary policy shocks. We find that while they did, the importance of MPU has diminished and that it has different effects on short versus long-term inflation expectations.



Joint Economic Forecast 2020-2022

Bi-annual forecast for the German and the world economy prepared on behalf of the Federal Ministry for Economic Affairs and Energy

Big Data in the macroeconomic analysis forecasting investments and exports with unconventional data sources and methods.

In this project we evaluate whether unconventional data sources such as satellite images, newspaper articles, web articles or monitoring truck, ship, and train movement can help predict the economic developments, in particular with regard to Investments and Exports.

Business Cycle Analysis

Analysis and forecasting of the of the German and the world economy with a special emphasis on the Euro Area.

Joint Economic Forecast 2016-2020

Bi-annual forecast for the German and the world economy prepared on behalf of the Federal Ministry for Economic Affairs and Energy

Scientific advisory for the Federal Ministry of Economics and Technology

Advisory for the German delegation in the EU Output gap working group

The macroeconomic effects of uncertainty

A collection of my economic research on uncertainty in international economic context


The effects of COVID-19 on the Italian economy

This is an excerpt from our 2020 spring economic forecast

Presenting at the Eighth Italian Congress of Econometrics and Empirical Economics

I will attend the ICEEE 2019 in Lecce, Italy and present on Friday, the 25-th. I have created a calendar file (.ics) with the program for easier navigating there.