Gregor Zens

Gregor Zens

Research Scholar
IIASA

Gregor Zens

I am affiliated with the International Institute for Applied Systems Analysis (IIASA), where I am part of the Population and Just Societies (POPJUS) program. Previously, I worked at the Bocconi Institute for Data Science and Analytics (BIDSA) with Daniele Durante and at the Institute for Statistics and Mathematics at WU Vienna with Sylvia Frühwirth-Schnatter. I obtained my PhD in economics with a focus on Bayesian econometrics at WU Vienna, under the supervision of Jésus Crespo Cuaresma and Sylvia Frühwirth-Schnatter and have also served as a statistical consultant for the International Bank of Reconstruction and Development and the International Finance Corporation within the World Bank Group.


Research Focus

My research focuses on developing and applying statistical methods for high-dimensional and structured data, motivated by questions in human mobility, demography, and the social sciences more broadly. Methodologically, I am particularly interested in Bayesian statistics, with an emphasis on computational techniques, scalable inference, and interpretable modeling. I collaborate closely with economists, sociologists, demographers, and climate scientists, and translate my work into practice through open-source R packages. Below are some of my current and past projects.


Preprints and Selected Work in Progress

  • Scalable Variable Selection and Model Averaging for Latent Regression Models Using Approximate Variational Bayes.
    with Mark F.J. Steel (University of Warwick)
    [arXiv]

  • Dynamic Count Models with Flexible Innovation Processes for Irregular Maritime Migration.
    with Jakub Bijak (University of Southampton)
    [arXiv]

  • Bayesian Matrix Factor Models for Demographic Analysis Across Age and Time.
    [arXiv]

  • Low-Rank Bilinear Autoregressive Models for Three-Way Criminal Activity Tensors.
    with Daniele Durante (Bocconi University), Eleonora Patacchini (Cornell University) and Carlos Díaz (Universidad Católica del Uruguay)
    [arXiv]

  • Hidden in Plain Sight: Influential Sets in Linear Regression Models.
    with Nikolas Kuschnig (WU Vienna) and Jésus Crespo Cuaresma (WU Vienna)
    [updated pdf, WP]


Peer-Reviewed Publications

Journal Articles

  • Model Uncertainty in Latent Gaussian Models with Univariate Link Function.
    M.F.J. Steel and G. Zens (2025).
    Bayesian Analysis.
    [journal, arXiv, R package]

  • Flexible Bayesian Modeling of Age-Specific Counts in Many Demographic Subpopulations.
    G. Zens (2025).
    Journal of the Royal Statistical Society, Series A (Statistics in Society).
    [journal, arXiv]

  • Subnational Variations in the Quality of Household Survey Data in Sub-Saharan Africa.
    V. Seidler, E. C. Utazi, A. B. Finaret, S. Luckeneder, G. Zens, … & P. Webb (2025).
    Nature Communications, 16(1), 3771.
    [journal, explorer]

  • The Short-Term Dynamics of Conflict-Driven Displacement: Bayesian Modeling of Disaggregated Data from Somalia.
    G. Zens and L. Thalheimer (2025).
    The Annals of Applied Statistics, 19(1), 286-301.
    [journal, pdf]

  • Interrelated Drivers of Migration Intentions in Africa: Evidence from Afrobarometer Surveys.
    R. Hoffman and G. Zens (2024).
    Environmental Development, 52, 101096.
    [journal]

  • Ultimate Pólya Gamma Samplers - Efficient MCMC for possibly imbalanced binary and categorical data.
    G. Zens, S. Frühwirth-Schnatter & H. Wagner (2024).
    Journal of the American Statistical Association, 119(548), 2548–2559.
    [journal, arXiv, R package]

  • The Heterogeneous Impact of Monetary Policy on the US Labor Market.
    G. Zens, M. Böck & T.O. Zörner (2020).
    Journal of Economic Dynamics and Control, 119, 103989.
    [journal]

  • Land and Poverty: The Role of Soil Fertility and Vegetation Quality in Poverty Reduction.
    M. P. Heger, G. Zens & M. Bangalore (2020).
    Environment and Development Economics, 25(4), 315-333.
    [journal]

  • Bayesian Shrinkage in Mixture-of-Experts Models: Identifying Robust Determinants of Class Membership.
    G. Zens (2019).
    Advances in Data Analysis and Classification, 13(4), 1019-1051.

Discussions

  • Discussion on Model Uncertainty and Missing Data: An Objective Bayesian Perspective by García-Donato et al.
    M.F.J. Steel & G. Zens (2025+).
    Bayesian Analysis, To Appear.

  • Discussion on Sparse Bayesian Factor Analysis When the Number of Factors Is Unknown by Frühwirth-Schnatter et al.
    A. Avalos-Pacheco, R. de Vito, & G. Zens (2025).
    Bayesian Analysis, 20(1): 213-344.
    [journal]


Software


Newspapers, Blogs, General Audience

(In German only, sorry!)


Presentations at Conferences, Seminars and Workshops


Awards, Fellowships, Travel Grants


Academic Visits


Teaching & Thesis Supervision

I have taught several undergraduate courses on econometrics, data science methods, economic development, economic growth, and macroeconomic theory, and I have delivered graduate-level lectures on macroeconometric methods with a focus on Bayesian computation. I supervise Bachelor’s and Master’s theses and regularly mentor PhD students in summer programs. Examples of past thesis topics include “The importance of digitized government-to-person (G2P) payments for women’s financial inclusion in developing countries” and “Nowcasting GDP growth in Austria via the construction of a daily economic sentiment index using Google Trends”.


Contact

zens [at] iiasa.ac.at
International Institute for Applied Systems Analysis
Population and Just Societies Program
Schlossplatz 1, 2361 Laxenburg, Austria