PSC 585 Dynamic Models: Structure, Computation and Estimation

Political Science Field: Positive Theory
Typically offered every other year

Tasos Kalandrakis
Fall 2013

Course Syllabus

TR 14:00-15:15, F 10:00-12:00 Dynamic considerations are becoming increasingly important in the study of such political processes as legislative policy making, the impact of the political cycle on macroeconomic performance, the stability of international systems, the conduct of war, and regime change. The course develops the theory of dynamic models in decision and game theoretic environments, develops numerical methods for the computation of these models, and culminates with a thorough treatment of statistical estimation of dynamic models. The goal of the course is to equip graduate students with analytical, numerical, and statistical tools that can be used in their future research on applied topics, and specific applications will be considered at some length. Some familiarity with a programming language (such as Matlab or R) is a plus, but the dedicated student should be able to acquire basic programming skills needed for the course.

Tasos Kalandrakis
Spring 2011 — T 14:00-16:40

Course Syllabus

The course provides theoretical and computational tools for the analysis and estimation of models of strategic interaction with an emphasis on dynamic games. In the first half of the course theory and numerical methods for dynamic programming, general dynamic games, and Markov chains are covered in some detail. In the second half we focus on issues of identification and estimation with an emphasis on efficient numerical algorithms. Non-parametric methods are discussed when applicable. Applications include but are not limited to models of bargaining, voting, and the non-parametric estimation of voter preferences. Some familiarity with a programming language is a plus, but the dedicated student should be able to acquire basic programming skills needed for the course.

John Duggan, Tasos Kalandrakis
Spring 2008

Course Syllabus

Dynamic considerations are becoming increasingly important in the study of such political processes as stability of international systems, the conduct of war, legislative policy making, regime change, and the impact of political variables on economic growth and industry dynamics. We provide theoretical and computational tools for the study of such applications. The course covers the basics of dynamic programming and general dynamic games and the main results on Markov chains. The main focus is the study of stochastic games with an emphasis on numerical analysis of simple (i.e., finite) models illustrated in a number of applications. The goal of the course is to equip graduate students with analytical and numerical tools that can be used in their future research on applied topics. Some familiarity with a programming language (such as Matlab or R) is a plus, but the dedicated student should be able to acquire basic programming skills needed for the course.