Andreas Murr

The University of Warwick · Department of Politics & International Studies

When analyzing data, researchers are often less interested in the parameters of statistical models than in functions of these parameters such as predicted values. Here we show that Bayesian simulation with Markov-Chain Monte Carlo tools makes it easy to compute these quantities of interest with their uncertainty. We illustrate how to produce custom...

When assessing election forecasts, two important criteria emerge: their accuracy (precision) and lead time (distance to event). Curiously, in both 2010 and 2015 the most accurate forecasts came from models having the longest lead time—albeit at most 12 months. Can we increase the lead time further, supposing we tolerate a small decrease in accuracy...

Party leadership elections predict British general elections. Because Members of Parliament usually want to get re-elected and know their colleagues, they are motivated and able to vote in leadership contests for the colleague who is most likely to deliver electoral victory. Therefore, the party with the more popular leader among MPs typically wins...

Are ordinary citizens better at predicting election results than conventional voter intention polls? The authors address this question by comparing eight forecasting models for British general elections: one based on voters' expectations of who will win and seven based on who voters themselves intend to vote for (including ‘uniform national swing m...

National election forecasting has become most developed for vote and seat shares as well as winners of elections. These election outcomes are usually forecasted by voter intention polls, structural models, or a combination of the two. For voter turnout, election forecasts come almost exclusively from likelihood-to-vote polls. We develop a structura...

Most citizens correctly forecast which party will win a given election, and such forecasts usually have a higher level of accuracy than voter intention polls. How do citizens do it? We argue that social networks are a big part of the answer: much of what we know as citizens comes from our interactions with others. Previous research has considered o...

Most citizens correctly forecast which party will win the election, and groups of citizens forecast even better than individual citizens. Using Condorcet's jury theorem , I explain why individual citizens are better than chance at forecasting, and why in turn groups of citizens forecast better than individual citizen. The so-called 'wisdom of crowd...

Are ordinary citizens better at predicting election results than conventional voter intention polls? We address this question by comparing predictive models for British elections: one based on voters' expectations of who will win and others based on who voters themselves intend to vote for (including " cube rule " and uniform national swing models)...

Most citizens correctly forecast which party will win the election, usually with greater accuracy than voter intention polls. How do they do it? We argue that social networks are a big part of the answer: much of what we know as citizens comes from our communication with others. Previous research has considered only indirect characteristics of soci...

Who do you think will win in your constituency? Most citizens correctly answer this question, and groups are even better at answering it. Combining individual forecasts results in the ‘wisdom of crowds’ explained by Condorcet's jury theorem. This paper demonstrates the accuracy of citizen forecasts in seven British General Elections between 1964 an...

British political parties select their leaders to win elections. The winning margin of the party leader among the selectorate reflects how likely they think she is to win the General Election. The present research compares the winning margins of party leaders in their party leadership elections and uses the results of this comparison to predict tha...

Increasingly, professional forecasters rely on citizen forecasts when predicting election results. Following this approach, forecasters predict the winning party to be the one which most citizens have said will win. This approach predicts winners and vote shares well, but related research has shown that some citizens forecast better than others. Ex...

We apply a specialized Bayesian method that helps us deal with the methodological challenge of unobserved heterogeneity among immigrant voters. Our approach is based on generalized linear mixed Dirichlet models (GLMDMs) where random effects are specified semiparametrically using a Dirichlet process mixture prior that has been shown to account for u...

Many studies report the “wonders of aggregation” and that groups (often) yield better decisions than individuals. Can this “wisdom of crowds”-effect be used to forecast elections? Forecasting models in first-past-the-post systems need to translate vote shares into seat shares by some formula; however, the seat–vote ratio alters from election to ele...