2N Modeling Heterogeneity in Cross-sectional and Panel Data
Daniel Stegmueller, Nuffield College, University
of Oxford
23 July - 3 August (two week course / 35 hrs)
Detailed Course Outline [PDF]
THIS COURSE IS NOW FULLY BOOKED AND WE ARE OPERATING A WAITING LIST
Course Content
This course introduces a range of recently developed methods that deal with heterogeneity. Heterogeneity refers to differences between groups, such as individuals and countries, which are due to omitted or unobserved factors. Commonly employed approaches try to correct for such factors. We will take a different approach and build explicit models for heterogeneity between individuals or groups allowing us to answer questions such as: Does the effect of income on redistribution preferences differ between different subgroups of individuals? Does the effect of parties’ policy on vote choice differ between individuals? What are the individual level dynamics of partisan identification? Do different subgroups of a population follow different patterns of attitude or preference change? Do unemployment and poverty dynamics differ between (unobserved) subgroups? The models presented in this course will help you answers such questions. Among others, we will discuss:
(1) Heterogeneity in cross sectional data:
• Multilevel models for heterogeneity between groups (countries, organization etc.)
• Latent class or finite mixture regression models for effect heterogeneity between subgroups
(2) Heterogeneity in panel data:
• Fixed and random effects models for panel data with linear as well as categorical outcomes
• Nonparametric random effects models for panel data: relaxing the common assumption of normal distributed random effects
• Dynamic linear models, dynamic nonlinear models: modeling state-dependence (for example the persistence of preferences) and individual heterogeneity
• Mixed markov models and mixed latent markov models: modeling transitions processes through time (such as dynamics of partisanship)
Course Objectives
We will discuss a framework for a wide range of models relevant for applied research in political science, sociology, and economics. You will learn the models’ theoretical properties, but we will spend a substantial amount of time on their estimation, presentation and interpretation.
Course Prerequisites
You should be familiar with basic matrix algebra and probability theory. A basic familiarity with data management (with Stata or R) is helpful but not strictly necessary.
Example Reading
Neundorf, Anja; Stegmueller, Daniel & Scotto, Thomas. The Individual-Level Dynamics of Bounded Partisanship. Public Opinion Quarterly, 2011, 75, p. 458-482.
McAtee, Andrea & Wolak, Jennifer. Why People Decide to Participate in State Politics. Political Research Quarterly, 2011, 64, p. 45-58
Imai, Kosuke & Tingley, Dustin. 2012. A Statistical Method for Empirical Testing of Competing Theories. American Journal of Political Science, 56, p. 218-236.