3L Dynamic Models for Social Scientists
Harold Clarke, University of Texas at Dallas
8 - 19 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 in journals such as the American Journal of Political Science, American Political Science Review, and British Journal of Political Science. He is chief editor of Electoral Studies. He has been a principal investigator for the 2001, 2005 and 2010 British Election Study (University of Essex and University of Texas at Dallas), the 2011 Political Support in Canada Study, and the 2012 Political Support in America Study. His most recent books are Affluence, Austerity and Electoral Change in Britain (Cambridge University Press, 2013) and Austerity and Political Choice in Britain (Palgrave Macmillan, 2015).
- 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 the standard Windows operating environment. Basic knowledge of a major statistical software package such as Stata 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.
- Becketti, Sean. 2013. Introduction to Time Series Using Stata. College Station, TX: Stata Press.
- Box-Steffensmeier, Janet et al. 2014. Time Series Analysis for the Social Sciences. New York: Cambridge University Press.
- Pfaff, Bernhard. 2006. Analysis of Integrated and Cointegrated Time Series With R. New York Springer.