7th Vienna Workshop on High Dimensional Time Series
in Macroeconomics and Finance
IHS, Vienna | 28-29 May 2026
Conference Agenda
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
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Daily Overview |
| 8:30am - 9:00am |
Registration |
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| 9:00am - 10:00am |
P1: Plenary 1 - Roberto Casarin Location: Lecture Room E02 Chair: Leopold Sögner, Institute for Advanced Studies |
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| 10:00am - 10:30am |
Coffee Break: Coffee Break |
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| 10:30am - 12:00pm |
PS-1A Location: Lecture Room E02 Learning Nonlinear Factor Models with Unknown Monotone Links from Incomplete and Noisy Data 1: Technical University of Munich, Germany; 2: Virginia Tech, United States of America Non-Gaussian Structural Dynamic Factor Models: Identification, Estimation, and Applications 1: University of Warsaw, Poland; 2: University of Notre Dame, USA; 3: Bank of England and King’s College London, UK Factor-based imputation of missing values using cross-section averages 1: Lund University, Sweden; 2: Örebro University |
PS-1B Location: Lecture Room SR 101 Estimation and Inference for Cointegrated Systems of Multi-Factor Production Functions: Modelling the Joint Behavior of GDP and Emissions 1: Department of Economics, Analytics and Operations Research, University of Klagenfurt; 2: Institute for Advanced Studies, Vienna Beyond the Oracle Property: Adaptive LASSO in Cointegrating Regressions with Local-to-Unity Regressors TU Wien, Austria Practical estimation methods for high-dimensional multivariate stochastic volatility models McGill University, Canada |
| 12:00pm - 1:30pm |
Lunch Break |
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| 1:30pm - 3:00pm |
PS-2A Location: Lecture Room E02 Incorporating Micro Data into Macro Models Using Pseudo VARs 1: University of Strathclyde, United Kingdom; 2: Federal Reserve Bank of Cleveland, United States of America Bayesian modelling of VAR precision matrices using stochastic block networks 1: University of Salzburg, Austria; 2: University of Strathclyde, Great Britian; 3: Bocconi University, Italy Nonlinear Autoregressive Models for Functional Time Series with Bayesian Additive Regression Trees 1: University College Dublin, Ireland; 2: University of Texas Health Science Center at Houston; 3: NEOMA Business School; 4: Erasmus University Rotterdam; 5: Michigan State University |
PS-2BA Location: Lecture Room SR 101 Predicting Energy Demand with Tensor Factor Models 1: University of Bologna, Italy; 2: European Investment Bank Forecasting El Niño/Southern Oscillation (ENSO) using High Dimensional Factor Models 1: University of L'Aquila, Italy; 2: Einaudi Institute for Economics and Finance; 3: Univeristy of Rome Tor Vergata Dynamic Clustering in Multi-Factor Copulas with Hidden Markov Models Erasmus University Rotterdam, Netherlands, The |
| 3:00pm - 3:45pm |
Poster 1 Location: Lecture Room E02 Let the Tree decide: FABART \\ A Non-Parametric Factor Model 1: Banco de España, Spain; 2: University College Dublin Inflation Forecasting with Large Language Models: A Real-Time Evaluation Against Central Bank Projections SGH Warsaw School of Economics, Poland Envelope Matrix Autoregressive Models SIUC, United States of America Density nowcasts for U.S. GDP by probabilistic neural networks Department of Artificial Intelligence and Systems Engineering, Budapest University of Technology and Economics BIS Time-series Regression Oracle 1: Bank for International Settlements, Switzerland; 2: Saarland University Gradient-Boosted Panel MIDAS Trees 1: Erasmus University Rotterdam, Netherlands, The; 2: Tinbergen Institute, Netherlands, The Central bank independence and the transmission of external shocks in small open economies Central Bank of Ireland, Ireland How to certify positivity of a given signed mixture of statistical densities. 1: University College Cork, Netherlands, The; 2: University of Trento, Italy Forecast Combination with Random Subspaces: Accuracy Gains and Interpretability Halle Institute for Economic Research (IWH), Germany Bilinear Time Variation for High Dimensional TVP-VARs 1: Örebro University School of Business; 2: Fondazione ENI Enrico Mattei Robust Tests of Forecast Accuracy for Factor-Augmented Regressions with an Application to the Novel EA-MD-QD Dataset 1: University of Bologna, Italy; 2: University of Freiburg, Germany; 3: BI Norwegian Business School, Norway |
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| 3:45pm - 5:15pm |
PS-3A Location: Lecture Room E02 Implied Factors: The Linear Skeleton of Machine Learning Forecasts 1: UQAM, Canada; 2: Bank of Canada; 3: ECB Optimal Predictor Selection for Macroeconomic Time Series using Variable Importance in Random Forests ETH Zürich, Switzerland Mapping the Design Space of High-Dimensional Macroeconomic Nowcasting 1: Institute for Advanced Studies (IHS), Vienna, Austria; 2: Vienna University of Economics and Business (WU), Vienna, Austria; 3: Vienna Graduate School of Finance (VGSF), Vienna, Austria Chronos-2: From Univariate to Universal Forecasting Boston College, United States of America |
PS-3B Location: Lecture Room SR 101 Power Priors for VARs 1: Bocconi University, Italy; 2: Bocconi University, Italy; 3: Universita Cattolica del Sacro Cuore A Dynamic Horseshoe Process Prior for High-dimensional time-varying parameter models Vienna University of Economics and Business, Austria Scenario Analysis with Multivariate Bayesian Machine Learning Models 1: Vienna University of Economics and Business, Austria; 2: Oesterreichische Nationalbank Adaptive Targeted Predictors for Large-Scale Macroeconomic Forecasting KOF ETH Zürich, Switzerland |
| 5:30pm - 6:30pm |
P2: Plenary 2 - Melanie Schienle Location: Lecture Room E02 |
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| 7:00pm - 9:00pm |
Dinner Location: Glacis Beisl |
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