Resume

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I am Assistant Professor in Computational Social Science at the University of Exeter, United Kingdom. In my research, I am investigating political and electoral behaviour in advanced economies. Furthermore, in collaboration with the International Monetary Fund and the World Bank, I study the economics and politics of climate change.

As a quantitative scholar, I mainly use causal inference and machine learning methods. Beyond my research, I have been teaching graduate (Bsc, MSc and PhD) and undergraduate courses on causal inference, quantitative research methods, regression analysis, omputational programming, data science, machine learning as well as social policy and political economy.

Prior to my tenure at Exeter, I was a post-doc (LSE Fellow) at the Department of Methodology at the London School of Economics and Political Science. I hold a PhD from Oxford, a master's degree from LSE, and a bachelor's degree from Zeppelin University (with a semester abroad at Columbia).

I am an affiliated fellow at the Department of Methodology at LSE, the LSE Data Science Institute, and the Department of Social Policy and Intervention at the University of Oxford.

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Research

Journal articles

Furceri, D., Ganslmeier, M., & Ostry, J. D. (2023).
Are Climate Change Policies Politically Costly?
Energy Policy, 178, 113575.

Ganslmeier, M., Van Parys, J., & Vlandas, T. (2022).
Compliance with the first UK COVID-19 Lockdown and the Compounding Effects of Weather.
Scientific Reports, 12(1), 1-10.

Ganslmeier, M., Furceri, D., & Ostry, J. D. (2021).
The Impact of Weather on COVID-19 Pandemic.
Scientific Reports, 11(1), 1-7.

Vlandas, T., McArthur, D., & Ganslmeier, M. (2021).
Ageing and the Economy: A Literature Review of Political and Policy Mechanisms.
Political Research Exchange, 3(1), 1932532.

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Book chapters

Martelli, A., Campos, N. F., Ganslmeier, M., Ji, Y., & Saka, O. (2020).
On the Complementarity between Labour Market Regulation and Tax Reforms in the European Union.
In Economic Growth and Structural Reforms in Europe (pp. 280-313).
Cambridge University Press.

Saka, O., Martelli, A., Ganslmeier, M., Ji, Y., Campos, N. F., & De Grauwe, P. (2020).
Structural Reforms in Europe. Lessons from Early Experiences.
In Economic Growth and Structural Reforms in Europe (pp. 317-341).
Cambridge University Press.

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In progress / under review

Ganslmeier, M.
From Pledge to Poll: The Impact of Campaign Promises on Party Alignment
revise and resubmit, Comparative Political Studies

Ganslmeier, M., & Vlandas, T.
The Sources of Model Uncertainty in Political Science: A Machine Learning Approach
under review

Bettarelli, L., Furceri, D., Ganslmeier, M., & Schiffbauer, M.
The Economic Costs of Temperature Volatility: Evidence from US Firms.
under review

Ganslmeier, M., Klymak, M., & Vlandas, T.
Pension Benefits and Turnout: Evidence from the Public Sector in Illinois
under review

Mealy, P., & Ganslmeier, M., Godinho, C., Hallegatte, S.
Climate Policy Feasibility Frontiers: A tool for realistic and strategic climate policymaking
under review

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Further research work

Furceri, D., Ganslmeier, M., Ostry, J. D., & Yang, N. (2021).
Initial Output Losses from the Covid-19 Pandemic: Robust Determinants.

Ganslmeier, M., Deb, P., Furceri, D., Ostry, J., & Tawk, N. (2021).
Vaccinate Early and Vaccinate Broadly: On the Health and Economic Effects of COVID-19 Vaccines.

Aksoy, C., Ganslmeier, M., & Poutvaara, P. (2020).
Public Attention and Policy Responses to COVID-19 Pandemic.

Freelance

I have helped various clients to accelerate their data-driven projects on a freelance basis. If you are interested in hiring me, do not hesitate to get in touch. I speak multiple languages (R, Python, Stata, SQL, Ruby, JavaScript and HTML), and I have experience in the following techniques:

Deep Learning

Natural Language Processing

Causal Inference

Geo Mapping

Web Scraping

Descriptive Analysis