Dr Michael Ganslmeier

Michael Ganslmeier

About

I am an Assistant Professor in Data Science at the Department of Information Studies at University College London. My research addresses two central challenges in empirical science. First, I develop and apply methods to estimate causal effects in settings where randomized experiments are not feasible, using observational data from real-world contexts. Second, I study how quantitative findings depend on assumptions and modeling choices, and develop frameworks to assess their robustness. Together, my work aims to re-anchor scientific credibility in its foundational principles, at a time when science faces unprecedented pressure in an increasingly polarizing environment.

Jobs

Assistant Professor in Data Science, University College London (since 2026)
Data Scientist & Consultant, World Bank (since 2023)
Assistant Professor in Computational Social Science, University of Exeter (2024-2025)
Postdoctoral Fellow, Department of Methodology, London School of Economics (2022-24)

Degrees

Doctor, University of Oxford
Master, London School of Economics
Semester Abroad, Columbia University
Bachelor, Zeppelin University

Download my Resume

Collaborations

I have had the privilege of working for and collaborating with the following esteemed organizations:

Research & Publications

Publications

Estimating the Extent and Sources of Model Uncertainty in Political Science (2025)
- Authors: Michael Ganslmeier, Tim Vlandas
- Funded by: All Souls College / Economic and Social Research Council (ESRC)
- Published in: Proceedings of the National Academy of Sciences
- Replication files: Github
On the Limits of Justified Model Spaces (2025)
- Authors: Michael Ganslmeier, Tim Vlandas
- Funded by: All Souls College / Economic and Social Research Council (ESRC)
- Published in: Proceedings of the National Academy of Sciences
From Pledge to Poll: The Impact of Campaign Promises on Party Alignment (2025)
- Authors: Michael Ganslmeier [Job Market Paper]
- Funded by: All Souls College / Economic and Social Research Council (ESRC)
- Published in: Comparative Political Studies
- Replication files: Harvard Dataverse
Are Climate Change Policies Politically Costly? (2023)
- Authors: Davide Furceri, Michael Ganslmeier, Jonathan D. Ostry
- Funded by: All Souls College / Economic and Social Research Council (ESRC)
- Published in: Energy Policy
Compliance with the First UK COVID-19 Lockdown (2022)
- Authors: Michael Ganslmeier, Jonathan Van Parys, Tim Vlandas
- Funded by: YouGov
- Published in: Scientific Reports (Nature)
The Impact of Weather on COVID-19 Pandemic (2021)
- Authors: Michael Ganslmeier, Davide Furceri, Jonathan D. Ostry
- Published in: Scientific Reports (Nature)
Ageing and the Economy: A Literature Review of Political and Policy Mechanisms (2021)
- Authors: Tim Vlandas, Daniel McArthur, Michael Ganslmeier
- Published in: Political Research Exchange
On the Complementarity between Labour Market Regulation and Tax Reforms in the European Union (2020)
- Authors: Angelo Martelli, Nauro F. Campos, Michael Ganslmeier, Yuemei Ji, Orkun Saka
- Funded by: Economic and Social Research Council (ESRC)
- Published in: Cambridge University Press
Structural Reforms in Europe. Lessons from Early Experiences (2020)
- Authors: Orkun Saka, Angelo Martelli, Michael Ganslmeier, Yuemei Ji, Nauro F. Campos, Paul De Grauwe
- Funded by: Economic and Social Research Council (ESRC)
- Published in: Cambridge University Press

Research in Progress

Empirical Identification of Feasible and Strategic Climate Policies
- Authors: Penny Mealy, Michael Ganslmeier, Stephane Hallegatte
- Funded by: World Bank
- Status: Revise and Resubmit at Nature Climate Change
When Habit Prevails: A Causal Test of Policy Feedback Theory Using a Pension Reform
- Authors: Michael Ganslmeier, Margaryta Klymak, Tim Vlandas
- Funded by: All Souls College / Economic and Social Research Council (ESRC)
- Status: Revise and Resubmit at Political Science Research and Methods
The Economic Costs of Temperature Volatility
- Authors: Luca Bettarelli, Davide Furceri, Michael Ganslmeier, Marc Schiffbauer
- Funded by: World Bank / International Monetary Fund
- Status: Under review
Firm-Level Climate Change Adaptation: Micro Evidence from 134 Nations
- Authors: Claudia Berg, Luca Bettarelli, Davide Furceri, Michael Ganslmeier, Arti Grover, Megan Lang, Marc Schiffbauer
- Funded by: World Bank
- Status: Under review
Political Integration and Trust in Foreigners
- Authors: Barry Eichengreen, Michael Ganslmeier, Orkun Saka
- Status: In progress
Racing Ahead? The Matthew Effect Without Feedback Loops
- Authors: Michael Ganslmeier
- Status: In progress

See Resume for Full List

Software

Below is a selection of software that I have been developing as part of my research and policy collaborations.

sensiverse

An R package for sensitivity and model uncertainty analysis in the social sciences. It offers tools to explore large model spaces, quantify robustness, and visualize uncertainty.

PNAS Paper | Github | Tutorial

Global Weather Map

An interactive climate data visualization platform built for the World Bank. It maps temperature, precipitation, and extreme event trends using high-resolution ERA5 weather data.

Open Global Weather Map Tool

Portfolio

Feel free to check out the results of some of my past research projects.

From Pledge to Poll:
The Impact of Campaign Promises on Party Alignment

Empirical Identication of Feasible and Strategic Climate Policies

Pension Benefits and Turnout: Evidence from the Public Sector in Illinois.

Compliance with the First UK COVID-19 Lockdown and the Compounding Effects of Weather

The Sources of Model Uncertainty in Political Science:
A Machine Learning Approach

The Economic Costs of Temperature Volatility

Skills

I have helped various clients accelerate their data-driven projects. If you are interested in hiring me as a consultant, advisor, or freelancer, feel free to get in touch. I speak/know how to use R, Python, Stata, SQL, Ruby, JavaScript, HTML/CSS, ArcGIS, Shell, Bash, REST API, AWS, TensorFlow, and many more.

Deep and Machine Learning

Experience in neural networks, predictive modeling, and frameworks like Keras, TensorFlow and PyTorch.

Natural Language Processing

Proficient in text mining, sentiment analysis, and NLP libraries like spaCy and transformers.

Causal Inference

Expertise in analyzing causal relationships using econometrics and advanced statistics.

Geospatial Analysis

Competence in geospatial data analysis and GIS tools like ArcGIS and satellite imagery processing.

Web Scraping

Experienced in building scalable scrapers with Python's BeautifulSoup and Scrapy, and R's rvest and RSelenium.

Descriptive Analysis

Expert in creating dashboards and visualizations for actionable insights.

Teaching

I have taught multiple courses at the undergraduate, master and doctoral level at University College London, London School of Economics, University of Exeter and University of Oxford. You can access the course descriptions via the links provided.