A stochastic differential equation approach to the analysis of the UK 2016 EU referendum polls

TL;DR

This paper introduces a stochastic differential equation model to analyze UK EU referendum polls, demonstrating its ability to fit poll data and predict outcomes effectively.

Contribution

The paper presents a novel stochastic differential equation approach for modeling and analyzing referendum poll data, with empirical validation and predictive capabilities.

Findings

Beta distribution fits the poll data well

Model has strong predictive power

Provides insights into social dynamics during the referendum

Abstract

Human dynamics and sociophysics suggest statistical models that may explain and provide us with better insight into social phenomena. Here we propose a generative model based on a stochastic differential equation that allows us to analyse the polls leading up to the UK 2016 EU referendum. After a preliminary analysis of the time series of poll results, we provide empirical evidence that the beta distribution, which is a natural choice when modelling proportions, fits the marginal distribution of this time series. We also provide evidence of the predictive power of the proposed model.