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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