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Michael Pfarrhofer

@mpfarrho.bsky.social

AP @wuvienna.bsky.social‬, Bayesian econometrics and empirical macroeconomics (monetary, business cycles, now/forecasting) mpfarrho.github.io

30 Followers  |  23 Following  |  4 Posts  |  Joined: 17.11.2024  |  1.6634

Latest posts by mpfarrho.bsky.social on Bluesky

➡️ Nonparametric observation equation, specified via Gaussian process for each series
➡️ Factors modeled with a VAR (straightforward computation and interpretation)
➡️ Applications: (1) forecasting with FRED-QD, (2) extracting drivers of global inflation dynamics and measuring international asymmetries

11.09.2025 10:45 — 👍 0    🔁 0    💬 0    📌 0
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New working paper "A Bayesian Gaussian Process Dynamic Factor Model" with T. Chernis (BMA), N. Hauzenberger (Uni Strathclyde), and H. Mumtaz (QMUL): arxiv.org/abs/2509.04928

Proposes a dynamic factor model where the latent factors are linked to observed variables with unknown nonlinear functions.

11.09.2025 10:45 — 👍 0    🔁 0    💬 1    📌 0
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📆 Join us on Mar 19 at our economics research seminar with Michael Pfarrhofer (@mpfarrho.bsky.social), who will present "General Seemingly Unrelated Local Projections"

More info and abstract:
www.jku.at/en/departmen...

17.03.2025 16:08 — 👍 7    🔁 3    💬 0    📌 0
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Scenario analysis with multivariate Bayesian machine learning models We present an econometric framework that adapts tools for scenario analysis, such as conditional forecasts and generalized impulse response functions, for use with dynamic nonparametric multivariate m...

"Scenario analysis with multivariate Bayesian machine learning models"
▶️ Conditional forecasts, generalized IRFs in dynamic nonparametric models
▶️ Applications: Macroeconomic stress testing; macroeconomic risk and financial conditions; financial shock transmission
arxiv.org/abs/2502.08440

13.02.2025 10:00 — 👍 0    🔁 0    💬 1    📌 0
Interpretable Bayesian machine learning for assessing the effects of climate news shocks on firm-level returns We propose a Bayesian Asset Pricing framework that uses machine learning to capture nonlinear interactions between firm exposures to climate change risks and a

“Interpretable Bayesian machine learning for assessing the effects of climate news shocks on firm-level returns,” at ssrn.com/abstract=513... where we:
▶️ use a Bayesian asset pricing framework & machine learning
▶️ have text-based climate risk indicators
▶️ find asymmetric impacts across firms

12.02.2025 20:31 — 👍 0    🔁 0    💬 0    📌 0
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You want to do your #PhD in #Economics at one of Europe’s largest & most modern business & economics universities. Join us at WU Wien #Vienna 🇦🇹. Click here: econjobmarket.org/positions/11...

31.01.2025 17:01 — 👍 3    🔁 1    💬 0    📌 0
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📣 NEW: Handbook of Research Methods and Applications in #Macroeconomic Forecasting by Michael P. Clements & Ana Beatriz Galvão

Chapter 14 is #OpenAccess at: doi.org/10.4337/9781...

More info: www.e-elgar.com/shop/isbn/97...

@mpfarrho.bsky.social @danilocascaldi.bsky.social #Econometrics

29.11.2024 09:39 — 👍 5    🔁 2    💬 0    📌 3

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