Michael Pfarrhofer, PhD

Michael Pfarrhofer, PhD


Research Interests

Bayesian econometrics, time series analysis, predictive inference, monetary economics, business cycles

Short Bio

Michael Pfarrhofer is a post-doc researcher at the University of Salzburg, and finished his PhD in economics at WU Vienna on high-dimensional time-series analysis in 2019. His research interests include econometric methods for dynamic models, mainly in the context of macroeconomics and finance. The focus of his work is on econometrics, machine learning techniques and Bayesian data analysis. He has published in the Journal of Econometrics, the Journal of Applied Econometrics, the Scandinavian Journal of Economics and the Journal of Economic Behavior and Organization.

Selected Publications

Huber, Florian, Gary Koop, Luca Onorante, Josef Schreiner, and Michael Pfarrhofer. “Nowcasting in a pandemic using non-parametric mixed frequency VARs.” Journal of Econometrics, 2021, forthcoming.  doi

Huber, Florian and Michael Pfarrhofer. “Dynamic shrinkage in time-varying parameter stochastic volatility in mean models.” Journal of Applied Econometrics, 2021, 36(3), 262-270.  doi

Hauzenberger, Niko and Michael Pfarrhofer. “Bayesian state-space modeling for analysing heterogeneous network effects of US monetary policy.” Scandinavian Journal of Economics, 2021, 123(4), 1261-1291.  doi

Hauzenberger, Niko, Michael Pfarrhofer, and Anna Stelzer. “On the effectiveness of the European Central Bank’s conventional and unconventional policies.” Journal of Economic Behavior and Organisation, 2021, 191, 822-845.  doi

Pfarrhofer, Michael. “Measuring international uncertainty using global vector Autoregressions with drifting parameters.” Macroeconomic Dynamics, 2021, forthcoming.  doi


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