The Impact of Political Uncertainty: A Robust Control Approach

In this paper, we examine how candidate uncertainty affects the policy platforms chosen in a uni-dimensional, two candidate Downsian spatial model. The candidates, we assume, do not know the true distribution of voters. Following the robust control literature, candidates respond to this uncertainty by applying a max-min operator to their optimization problem. This approach, consistent with findings within the behavioral economics literature, protects the candidate by ensuring that her expected utility never falls too far, regardless of the true voter distribution. We show that this framework produces policy convergence between the two candidates but there is a multiplicity of possible policy platforms upon which the candidates could settle, some of which could be quite distant from the median voter. These results are robust to the timing of the game and the level of uncertainty faced by the candidates. We argue that our model explains drift, which is our term for changing political beliefs over time. While drift may be caused by shifting attitudes or demographics, we show that drift could also be the result of candidate uncertainty.