The Ohio State University

Many questions central to political science, such as the issue of stability and change in the United States party system, revolve around the degree of persistence or memory in a political process. Fractional integration techniques, which allow researchers to investigate dynamic behavior that falls between the stationary and integrated alternatives, provide more precise ways to test hypotheses about the degree of persistence than current modeling strategies. Hypotheses: Choices about the treatment of the time series properties of the data and model specification may influence the substantive conclusions drawn about the dynamics of important political processes. Methods: Fractional integration methods are discussed and compared with common univariate diagnostic tests. A transfer function model of macropartisanship using fractional integration techniques is contrasted with traditional ARMA and ARIMA methods. Results: Fractional integration techniques offer a more flexible way to model a time series. Using fractional integration techniques, we find that macropartisanship is dominated by a strong permanent component, but also contains transitory dynamics in response to changes in economic evaluations and a measure of presidential approval. Our empirical work shows the importance of taking seriously the time series properties of data to ensure valid inferences about the dynamics of political processes.

By downloading these Materials, I agree to the following:

1. I will not use the Materials to
   1. obtain information that could directly or indirectly identify subjects.
   2. produce links among the Distributor's datasets or among the Distributor's data and other datasets that could identify individuals or organizations.
   3. obtain information about, or further contact with, subjects known to me except where the use and/or release of such identifying information has no potential for constituting an unwarranted invasion of privacy and/or breach of confidentiality.
2. I agree not to download any Materials where prohibited by applicable law.
3. I agree not to use the Materials in any way prohibited by applicable law.
4. I agree that any books, articles, conference papers, theses, dissertations, reports, or other publications that I create which employ data reference the bibliographic citation accompanying this data. These citations include the data authors, data identifier, and other information accord with the Recommended Standard (http://thedata.org/citation/standard) for social science data.
5. THE DISTRIBUTOR MAKES NO WARRANTIES, EXPRESS OR IMPLIED, BY OPERATION OF LAW OR OTHERWISE, REGARDING OR RELATING TO THE DATASET

BY CLICKING THE "I AGREE" CHECKBOX BELOW, I CONFIRM THAT I HAVE READ AND UNDERSTOOD EACH AND EVERY TERM SET FORTH IN THE TERMS AND CONDITIONS FOR THE USE OF DATA FOUND ABOVE, AND I AGREE TO BE BOUND BY ALL OF SUCH TERMS AND CONDITIONS.

IF I DO NOT UNDERSTAND OR AGREE TO ALL OF THE TERMS AND CONDITIONS, I MUST NOT DOWNLOAD THE MATERIALS.