Dynamic Models for Social Scientists
Harold Clarke, University of Texas at Dallas
Guy Whitten, Texas A & M University
4 - 15 August (two week course / 35 hrs)
Harold D. Clarke is Ashbel Smith Professor in the School of Economic, Political and Policy Sciences, University of Texas at Dallas, and adjunct Professor, Department of Government, University of Essex. His current research interests focus on the political economy of party support. He has published widely on this topic both in American and British journals and is Chief Editor of Electoral Studies. He is also a Principal Investigator for the 2010 British Election Study (Universityof Essex), the 2011 Political Support in Canada Study, and the 2012 Political Support in America Study. His most recent books are Performance Politics and the British Voter (Cambridge University Press, 2009), Making Political Choices: Canada and the United States (University of Toronto Press, 2009) and Affluence, Austerity and Electoral Change in Britain (Cambridge University Press, 2013).
Guy D. Whitten, Ph.D. University of Rochester, is a Professor of Political Science and the Director of the European Union Center at Texas A&M University. Dr. Whitten's primary research interests are political economy, public policy, political methodology, and comparative politics. Much of his published research has involved cross-national comparative studies of the influence of economics on government popularity and elections. His recent research in public policy includes work on the politics of defense spending in parliamentary democracies. Dr. Whitten has also published a number of influential works on the use of statistics to make inferences in political science. He is a member of the editorial boards for Electoral Studies and Political Science Research and Methods. His teaching interests are political economy, public policy, political methodology, and comparative politics.
- This is an applied course which focuses on statistical methods for conducting dynamic analyses of economic, political and social data. A variety of important models are considered including ARFIMA, Fractional Error Correction, GARCH and Dynamic Conditional Correlations, Duration Models, Markov Switching Models, Dynamic Panel Models for Time Series Cross-Sectional (TSCS) Data, VAR and Vector Error Correction. Special attention is given to specifying and analyzing State Space models of the latent dynamics of processes of interest. Both frequentist and Bayesian approaches to model specification, analysis, and interpretation are employed. The course will provide working knowledge of how to use Stata, R and Winbugs to analyze various dynamic models. Students are invited to bring their own data sets for analyses in daily lab sessions.
- The course will benefit anyone who is interested in conducting multivariate dynamic analyses of economic, political, and social processes from frequentist or Bayesian perspectives. The aim is to teach course participants how to undertake and evaluate sophisticated dynamic analyses of economic, political, and social data. The methods considered will be helpful to graduate students and faculty in the social sciences, as well as researchers working in the public and private sectors.
- Participants should be familiar with applied multiple regression analysis and with the standard Windows computing environment. Basic knowledge of the Stata, R and Winbugs programs is helpful but not required.
- Commandeur, Jacques and Siem Jan Koopman. 2007. An Introduction to State Space Time Series Analysis. Oxford: Oxford University Press.
- Asteriou, D., & Hall, S. (2011). Applied Econometrics, 2nd Edition. Palgrave MacMillan.