Philipp Christian Broniecki

Postdoctoral Fellow - Institutt for Statsvitenskap
Image of Philipp Christian Broniecki
Norwegian version of this page
Room 941
Visiting address Gullhaug torg 1 0484 Oslo
Postal address Postboks 1097 Blindern 0317 Oslo

Academic interests

  • European Union politics
  • Legislative politics
  • Data science




I am a political scientist (postdoctoral researcher) in the Department of Political Science at the University of Oslo and a member of the Strategy of Recorded Voting in the European Parliament (StREP) project. Previously, I was a Senior Research Officer at the ESRC Business and Local Government Data Research Centre at the University of Essex, where I have been involved in public policy advise with the Essex Centre for Data Analytics.

In research legislative politics/legislative institutions with a focus on the European Union. My interests include political negotiations such as the infamous early agreement system in the European Union and its consequences for representation and political power. My work also relates to the determinants of bargaining failure, the consequences of increased politicization of EU politics, the parliamentary behavior of Euroskeptic representatives to the European Parliament, and improving measurement methods for concepts such as policy influence and support for integration.

Methodologically, I focus on Bayesian statistics, machine learining, deep learning and methods for causal inference with observational data. Currently, I participate in a project on using machine learning techniques to better estimate subnational public opinion. Furthermore, I take part in an effort that applies quantitative text analysis to leverage data from open-ended survey questions collected by development organisations, in a project on forecasting conflict escalation from big data, and an analysis of peace agreement texts to identify common strategies of mediators, their success, and determinants of the negotiation agenda.

As a member of the ESRC Business and Local Government Data Research Centre, I have instructed members of local government institutions such as law enforcement in R, Python, introductory and advanced statistics. Furthermore, I have experience teaching quantitative methods at undergraduate and postgraduate levels and I advice local government institutions, human rights/civil liberties NGOs and civil society charities on research methodology.


  • Broniecki, Philipp; Leemann, Lucas & Wuest, Reto (2021). Improved Multilevel Regression with Poststratification through Machine Learning (autoMrP). Journal of Politics. ISSN 0022-3816. 84(1), p. 597–601. doi: 10.1086/714777. Full text in Research Archive

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Published Oct. 5, 2020 5:19 PM - Last modified Dec. 14, 2020 3:06 PM