The process of political change is the focus of inquiry across the subfields of political science. Testing theories about political dynamics requires analysts to make critical statistical assumptions about the nature of the memory of our time series. Intuitively, the memory of a time series refers to the rate at which the effects of shocks to a process, such as the effect of the massive change in Congress in 1994 to the stream of policy outputs, dissipate. Assumptions about memory lie at the heart of our theories about political processes and they affect both the models we choose and the inferences we draw from them. But these assumptions are not well known, are technically difficult, and the implications of violating them have not been fully established. The purpose of this study is to relate statistical assumptions about the memory in our time series to theory and hypothesis testing. The results of the project will illustrate the properties of alternative estimators as the nature of the memory in time series varies and the conditions under which each estimator is appropriate. The evidence will be used to gauge the reliability of results that have led to theoretical debates in current applied work with a particular focus on the support for the political parties and for the President, but the implications have much broader applicability across the subfields of political science and social sciences more generally. This POWRE award will support the investigator in a Visiting Professorship to the Harvard-MIT Data Center. It will allow her to interact and collaborate with other political methodologists who will serve as her mentors during and after her year at Harvard. The Harvard-MIT Cata Center will provide valuable tools that will be pivotal for the completion of the research and will prove invaluable after she leaves Harvard and continues to explore additional time series questions. The investigator will also immerse herself in the various workshops and symposia relating to macro political theory and econometrics while working on her research. The quantitative skills that she will gain will enable her to make the needed breakthrough to successfully complete her research and, thus, enhance her visibility in the field.
