Brexit: Tracking and disentangling the sentiment towards leaving the EU

On 23 June 2016 the UK held a referendum so to decide whether to stay or leave the European Union. The uncertainty surrounding the outcome of this referendum had major consequences in terms of public policy, investment decisions, and currency markets. We discuss some subtleties entailed in smoothing and disentangling poll data at the light of the problem of tracking the dynamics of the intention to Brexit, and propose a multivariate singular spectrum analysis method that produces trendlines on the unit simplex. The trendline yield via multivariate singular spectrum analysis is shown to bear a resemblance with that of local polynomial smoothing, and singular spectrum analysis presents the nice feature of disentangling directly the dynamics into components that can be interpreted as changes in public opinion or sampling error. Merits and disadvantages of some different approaches to obtain smooth trendlines on the unit simplex are contrasted, both in terms of local polynomial smoothing and
of multivariate singular spectrum analysis.