Professor Dr Gregor von Schweinitz

Professor Dr Gregor von Schweinitz
Current Position

since 10/17

Assistant Professor of Economics, esp. Quantitative Macroeconomics

Leipzig University

since 5/14

Head of the Research Group Volatility, Growth and Financial Crisis

Halle Institute for Economic Research (IWH) – Member of the Leibniz Association

since 1/11

Economist in the Department of Macroeconomics

Halle Institute for Economic Research (IWH) – Member of the Leibniz Association

Research Interests

  • dynamic macroeconomics
  • European and international economic policy: in particular financial crises
  • risk modelling and analysis

Gregor von Schweinitz is Assistant Professor of Economics at Leipzig University since October 2017 and a member of the Department of Macroeconomics since 2011. His research focuses on quantitative macroeconomics.

Gregor von Schweinitz earned a diploma from TU Dresden, University of Strasbourg and Technical University of Munich. He received his PhD from Martin Luther University Halle-Wittenberg.

Your contact

Professor Dr Gregor von Schweinitz
Professor Dr Gregor von Schweinitz
Mitglied - Department Macroeconomics
Send Message +49 345 7753-744

Publications

Recent Publications

cover_journal-of-financial-stability.gif

Does Machine Learning Help us Predict Banking Crises?

Johannes Beutel Gregor von Schweinitz

in: Journal of Financial Stability, forthcoming

read publication

cover_DP_2019-13.jpg

Fiscal Policy and Fiscal Fragility: Empirical Evidence from the OECD

Makram El-Shagi Gregor von Schweinitz

in: IWH Discussion Papers, No. 13, 2019

Abstract

In this paper, we use local projections to investigate the impact of consolidation shocks on GDP growth, conditional on the fragility of government finances. Based on a database of fiscal plans in OECD countries, we show that spending shocks are less detrimental than tax-based consolidation. In times of fiscal fragility, our results indicate strongly that governments should consolidate through surprise policy changes rather than announcements of consolidation at a later horizon.

read publication

cover_journal-of-macroeconomics.jpg

On the Empirics of Reserve Requirements and Economic Growth

Jesús Crespo Cuaresma Gregor von Schweinitz Katharina Wendt

in: Journal of Macroeconomics, 2019

Abstract

Reserve requirements, as a tool of macroprudential policy, have been increasingly employed since the outbreak of the great financial crisis. We conduct an analysis of the effect of reserve requirements in tranquil and crisis times on long-run growth rates of GDP per capita and credit (%GDP) making use of Bayesian model averaging methods. Regulation has on average a negative effect on GDP in tranquil times, which is only partly offset by a positive (but not robust effect) in crisis times. Credit over GDP is positively affected by higher requirements in the longer run.

read publication

 

Refereed Publications

cover_journal-of-financial-stability.gif

Does Machine Learning Help us Predict Banking Crises?

Johannes Beutel Gregor von Schweinitz

in: Journal of Financial Stability, forthcoming

read publication

cover_macroeconomic-dynamics.jpg

Optimizing Policymakers’ Loss Functions in Crisis Prediction: Before, Within or After?

Peter Sarlin Gregor von Schweinitz

in: Macroeconomic Dynamics, forthcoming

Abstract

Early-warning models most commonly optimize signaling thresholds on crisis probabilities. The expost threshold optimization is based upon a loss function accounting for preferences between forecast errors, but comes with two crucial drawbacks: unstable thresholds in recursive estimations and an in-sample overfit at the expense of out-of-sample performance. We propose two alternatives for threshold setting: (i) including preferences in the estimation itself and (ii) setting thresholds ex-ante according to preferences only. Given probabilistic model output, it is intuitive that a decision rule is independent of the data or model specification, as thresholds on probabilities represent a willingness to issue a false alarm vis-à-vis missing a crisis. We provide simulated and real-world evidence that this simplification results in stable thresholds and improves out-of-sample performance. Our solution is not restricted to binary-choice models, but directly transferable to the signaling approach and all probabilistic early-warning models.

read publication

cover_journal-of-macroeconomics.jpg

On the Empirics of Reserve Requirements and Economic Growth

Jesús Crespo Cuaresma Gregor von Schweinitz Katharina Wendt

in: Journal of Macroeconomics, 2019

Abstract

Reserve requirements, as a tool of macroprudential policy, have been increasingly employed since the outbreak of the great financial crisis. We conduct an analysis of the effect of reserve requirements in tranquil and crisis times on long-run growth rates of GDP per capita and credit (%GDP) making use of Bayesian model averaging methods. Regulation has on average a negative effect on GDP in tranquil times, which is only partly offset by a positive (but not robust effect) in crisis times. Credit over GDP is positively affected by higher requirements in the longer run.

read publication

Working Papers

cover_DP_2019-13.jpg

Fiscal Policy and Fiscal Fragility: Empirical Evidence from the OECD

Makram El-Shagi Gregor von Schweinitz

in: IWH Discussion Papers, No. 13, 2019

Abstract

In this paper, we use local projections to investigate the impact of consolidation shocks on GDP growth, conditional on the fragility of government finances. Based on a database of fiscal plans in OECD countries, we show that spending shocks are less detrimental than tax-based consolidation. In times of fiscal fragility, our results indicate strongly that governments should consolidate through surprise policy changes rather than announcements of consolidation at a later horizon.

read publication

cover_DP_2019-02.jpg

An Evaluation of Early Warning Models for Systemic Banking Crises: Does Machine Learning Improve Predictions?

Johannes Beutel Sophia List Gregor von Schweinitz

in: IWH Discussion Papers, No. 2, 2019

Abstract

This paper compares the out-of-sample predictive performance of different early warning models for systemic banking crises using a sample of advanced economies covering the past 45 years. We compare a benchmark logit approach to several machine learning approaches recently proposed in the literature. We find that while machine learning methods often attain a very high in-sample fit, they are outperformed by the logit approach in recursive out-of-sample evaluations. This result is robust to the choice of performance measure, crisis definition, preference parameter, and sample length, as well as to using different sets of variables and data transformations. Thus, our paper suggests that further enhancements to machine learning early warning models are needed before they are able to offer a substantial value-added for predicting systemic banking crises. Conventional logit models appear to use the available information already fairly effciently, and would for instance have been able to predict the 2007/2008 financial crisis out-of-sample for many countries. In line with economic intuition, these models identify credit expansions, asset price booms and external imbalances as key predictors of systemic banking crises.

read publication

cover_DP_2018-09.jpg

Did the Swiss Exchange Rate Shock Shock the Market?

Manuel Buchholz Gregor von Schweinitz Lena Tonzer

in: IWH Discussion Papers, No. 9, 2018

Abstract

The Swiss National Bank abolished the exchange rate floor versus the Euro in January 2015. Based on a synthetic matching framework, we analyse the impact of this unexpected (and therefore exogenous) shock on the stock market. The results reveal a significant level shift (decline) in asset prices in Switzerland following the discontinuation of the minimum exchange rate. While adjustments in stock market returns were most pronounced directly after the news announcement, the variance was elevated for some weeks, indicating signs of increased uncertainty and potentially negative consequences for the real economy.

read publication
Mitglied der Leibniz-Gemeinschaft LogoTotal-Equality-LogoWeltoffen Logo