A fundamental question in the analysis of democratic governance is how the performance of politicians is linked to voters' decisions. This proposal requests support for theoretical and experimental research on such electoral accountability. In particular, the project will examine two mechanisms, learning, where voters use past performance as an indication of politicians' underlying characteristics, and sanctioning, where voters reward politicians for good performance and punish them for poor performance, by which accountability can be achieved. Each of these views leads to distinct conclusions about how institutions affect accountability. As such, understanding each mechanism's distinct role and their interaction has important implications both for the scholarly study of democratic governance and for the design of institutions to improve accountability.
The theoretical analysis will show that the standard view of sanctioning is incomplete-in an important sense, it mischaracterizes how sanctioning works. Given this, the experiments will test the hypothesis that in a wide variety of natural models of accountability, sanctioning and learning operate simultaneously and that learning can dominate sanctioning. The project characterizes how and when that occurs.
This project has important broader impacts for political science and for policy makers. There are a number of areas, such as term limits, district magnitude, and transparency of policy-making, where the policy implications of models of political accountability depend on whether one focuses on sanctioning or learning. If both mechanisms are actually operative, existing policy conclusions may be incorrect or incomplete. This research also provides opportunities to enhance the training of graduate students through involvement in the construction, design, implementation, and analysis of experiments. Finally, the experimental data collected will be made publicly available so that other researchers can explore further questions related to electoral accountability.
