Associate Professor in Quantitative Political Science
Telephone: +44 (0)24 765 72959
Advice and Feedback Hours (during term time only, not in reading weeks): please sign up using this link or make an appointment via email.
Room: E2.19, Social Sciences Building
Dr Andreas Murr is Associate Professor in Quantitative Political Science, Course Director for the BA in Politics and Sociology, and Chair of the Academic Conduct Panel.
He joined Warwick from the University of Oxford, where he was Departmental Lecturer in Quantitative Methods.
He received a PhD in Government in 2013 and an MA in Public Opinion and Polling in 2009 from the University of Essex.
His research interests include political behaviour, public opinion, and political methodology.
Andreas is member of the Editorial Board of Electoral Studies.
He is also Co-Convenor of the Political Methodology Specialist Group of the Political Studies Association.
Murr, Andreas & Michael Lewis-Beck. 2022. Citizen Forecasts of the 2021 German Election. PS: Political Science & Politics.
Murr, Andreas. 2021. Do Party Leadership Contests Predict British General Elections?. Electoral Studies.
Murr, Andreas; Mary Stegmaier & Michael Lewis-Beck. 2021. Vote Expectations Versus Vote Intentions: Rival Forecasting Strategies. British Journal of Political Science.
Murr, Andreas & Michael Lewis-Beck. 2021. Citizen Forecasting 2020: A State-by-State Experiment. PS: Political Science & Politics.
Leiter, Debra; Andreas Murr; Ericka Rascón & Mary Stegmaier. 2018. Social Networks and Citizen Election Forecasting: The More Friends the Better. International Journal of Forecasting.
Murr, Andreas. 2016. The Wisdom of Crowds: What do Do Citizens Forecast for the 2015 British General Election? Electoral Studies.
Murr, Andreas. 2015. The Wisdom of Crowds: Applying Condorcet's Jury Theorem to Forecasting U.S. Presidential Elections. International Journal of Forecasting.
Murr, Andreas. 2015. The Party Leadership Model: An Early Forecast of the 2015 British General Election. Research & Politics.
Traunmüller, Richard; Andreas Murr & Jeff Gill. 2015. Modeling Latent Information in Voting Data with Dirichlet Process Priors. Political Analysis.
Murr, Andreas. 2011. "Wisdom of crowds"? A decentralised election forecasting model that uses citizens' local expectations. Electoral Studies.
Murr, Andreas. 2017. "Wisdom of Crowds" in Kai Arzheimer; Jocelyn Evans & Michael Lewis-Beck (editors). The Sage Handbook of Electoral Behaviour.
Fisher, Steve & Andreas Murr. 2020. Crunching decades of leadership election results suggests Labour should pick Keir Starmer. Prospect Magazine.
Murr, Andreas & Steve Fisher. 2019. The Party Leadership Model predicts a Conservative overall majority. Elections Etc.
Murr, Andreas; Mary Stegmaier & Michael Lewis-Beck. 2019. Citizen forecasting 2019: a big win for the Conservatives. LSE's British Politics and Policy Blog.
Murr, Andreas; Mary Stegmaier & Michael Lewis-Beck. 2019. Why vote expectations are a better tool for predicting election results than vote intentions. LSE's British Politics and Policy Blog.
Murr, Andreas; Mary Stegmaier & Michael Lewis-Beck. 2017. How did the U.K. election forecasts do? Monkey Cage – The Washington Post.
Murr, Andreas; Mary Stegmaier & Michael Lewis-Beck. 2017. New British election forecast: Conservatives gain 31 seats and have 77% chance of controlling a majority. Monkey Cage – The Washington Post.
Murr, Andreas; Mary Stegmaier & Michael Lewis-Beck. 2016. Using citizen forecasts we predict that with 362 electoral votes, Hillary Clinton will be the next president. LSE's American Politics and Policy Blog..
Murr, Andreas; Steve Fisher & Paul Whiteley. 2015. The State and Future of Political Methodology. The Plot.
Murr, Andreas. 2015. Members of Parliament Accurately Predict Who Becomes Prime Minister. The Plot.
Murr, Andreas. 2015. Citizens Forecast a Hung Parliament with the Conservatives as the Largest Party. LSE's British Politics and Policy Blog.
Cranmer, Skyler; Jeff Gill, Natalie Jackson, Andreas Murr & Dave Armstrong. 2014. hot.deck: Multiple Hot-deck Imputation. R package version 1.0.