Suchergebnisse

In the literature on electoral politics full convergence of policy platforms is usually regarded as socially optimal. The reason is that risk-averse voters prefer a sure middle-of-the-road policy to a lottery of two extremes with the same expectation. In this paper we study the normative implications of convergence in a simple model of electoral competition, in which parties are uncertain about voters' preferences. We show that if political parties have incomplete information about voters' preferences, the voters may prefer some degree of policy divergence. The intuition is that policy divergence enables voters to correct policies that are based on a wrong perception of their desires.

In a multiperiod setting, decision-makers can learn about the consequences of their decisions through experimentation. In this paper we examine how in a two-party system polarization and political instability affect learning through experimentation. We distinguish two cases: the decision to be made is not salient and does not affect the outcome of the following elections (exogenous elections) and the decision is salient and the election outcome depends on it (endogenous elections). We show that while the possibility of learning increases activism, the existence of political instability distorts learning. Furthermore, in contrast to the existing literature, we demonstrate that, when elections are exogenous, polarization between political parties does not always decrease active learning. In the case with endogenous elections we find that electoral concerns may induce candidates not to experiment, even if the majority of voters prefers activism.