  Human dynamics and sociophysics suggest statistical models that may explain
and provide us with better insight into social phenomena. Contextual and
selection effects tend to produce extreme values in the tails of rank-ordered
distributions of both census data and district-level election outcomes. Models
that account for this nonlinearity generally outperform linear models. Fitting
nonlinear functions based on rank-ordering census and election data therefore
improves the fit of aggregate voting models. This may help improve ecological
inference, as well as election forecasting in majoritarian systems.
  We propose a generative multiplicative decrease model that gives rise to a
rank-order distribution, and facilitates the analysis of the recent UK EU
referendum results. We supply empirical evidence that the beta-like survival
function, which can be generated directly from our model, is a close fit to the
referendum results, and also may have predictive value when covariate data are
available.
