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Jan Prüser

Biographic Data

ID9567366
NAMEJan Prüser
GIVEN NAMESJan
FAMILY NAMEPrüser
SIGNATUREPRÜSER J
AFFILIATIONSTU Dortmund University
ORCID0000-0001-7435-7334
VERIFIEDYes
TOTAL WORKS4
TOTAL CITATIONS0
WORKS AS AUTHOR4
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2020
LATEST PUBLICATION YEAR2024
H-INDEX0
  • Nonlinearities in macroeconomic tail risk through the lens of big data quantile regressions

    Open Access•Jan Prüser, Florian Huber•ARTICLE•Journal of Applied Econometrics•2024

    Modeling and predicting extreme movements in GDP is notoriously difficult, and the selection of appropriate covariates and/or possible forms of nonlinearities are key in obtaining precise forecasts. In this paper, our focus is on using large datasets in quantile regression models to forecast the conditional distribution of US GDP growth. To capture possible nonlinearities, we include several nonlinear specifications. The resulting models will be …

  • A Comparison of Approaches to Select the Informativeness of Priors in BVARs

    Jan Prüser, Christoph Hanck•ARTICLE•Jahrbucher fur Nationalokonomie…•2021

    Vector autoregressions (VARs) are richly parameterized time series models that can capture complex dynamic interrelationships among macroeconomic variables. However, in small samples the rich parametrization of VAR models may come at the cost of overfitting the data, possibly leading to imprecise inference for key quantities of interest such as impulse response functions (IRFs). Bayesian VARs (BVARs) can use prior information to shrink the model …

  • Regional composition of national house price cycles in the US

    Open Access•Jan Prüser, Thomas C Schmidt et al.•ARTICLE•Regional Science and Urban…•2021

  • On the Time‐Varying Effects of Economic Policy Uncertainty on the US Economy

    Open Access•Jan Prüser, Alexander Schlösser•ARTICLE•Oxford Bulletin of Economics and…•2020

    We study the impact of Economic Policy Uncertainty (EPU) on the US Economy by using a VAR with time‐varying coefficients. The coefficients are allowed to evolve gradually over time which allows us to discover structural changes without imposing them a priori . We find three different regimes, which match the three major periods of the US economy, namely the Great Inflation, the Great Moderation and the Great Recession. The initial impact on real …

No prominent works on this page.

  • On the Time‐Varying Effects of Economic Policy Uncertainty on the US Economy

    Open Access•Jan Prüser, Alexander Schlösser•ARTICLE•Oxford Bulletin of Economics and…•2020

    We study the impact of Economic Policy Uncertainty (EPU) on the US Economy by using a VAR with time‐varying coefficients. The coefficients are allowed to evolve gradually over time which allows us to discover structural changes without imposing them a priori . We find three different regimes, which match the three major periods of the US economy, namely the Great Inflation, the Great Moderation and the Great Recession. The initial impact on real …

  • A Comparison of Approaches to Select the Informativeness of Priors in BVARs

    Jan Prüser, Christoph Hanck•ARTICLE•Jahrbucher fur Nationalokonomie…•2021

    Vector autoregressions (VARs) are richly parameterized time series models that can capture complex dynamic interrelationships among macroeconomic variables. However, in small samples the rich parametrization of VAR models may come at the cost of overfitting the data, possibly leading to imprecise inference for key quantities of interest such as impulse response functions (IRFs). Bayesian VARs (BVARs) can use prior information to shrink the model …

  • Regional composition of national house price cycles in the US

    Open Access•Jan Prüser, Thomas C Schmidt et al.•ARTICLE•Regional Science and Urban…•2021

  • Nonlinearities in macroeconomic tail risk through the lens of big data quantile regressions

    Open Access•Jan Prüser, Florian Huber•ARTICLE•Journal of Applied Econometrics•2024

    Modeling and predicting extreme movements in GDP is notoriously difficult, and the selection of appropriate covariates and/or possible forms of nonlinearities are key in obtaining precise forecasts. In this paper, our focus is on using large datasets in quantile regression models to forecast the conditional distribution of US GDP growth. To capture possible nonlinearities, we include several nonlinear specifications. The resulting models will be …

Monetary Policy and Economic Impact (4 works) · Econometrics (3 works) · Market Dynamics and Volatility (3 works) · Artificial Intelligence (2 works) · Bayesian probability (2 works) · Computer Science (2 works) · Economics (2 works) · Forecasting Techniques and Applications (2 works) · Great recession (2 works) · Keynesian economics (2 works)

Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae