Spring 2021 - 60879 - PA 397C - Advanced Empirical Methods for Policy Analysis

Evaluation Design-Wb
Overview Many courses teach you how to analyze data, but few courses teach you how to ensure that you have the right data to analyze in the first place. And few courses teach you how to interpret results in a way that makes appropriately qualified claims about generality, causality, and the potential effects of future interventions. This course emphasizes fundamental issues including sampling, causality, generalizability, significance, and effect size. We examine research designs that are meant to enhance causal inference, including randomized experiments, regression discontinuity, propensity score matching, and “crossover” longitudinal designs with fixed effects and instrumental variables. Prerequisites We assume acquaintance with basic statistical inference including differences between means (e.g., t tests), differences between proportions (e.g., chi-square tests), and linear regression. Previous familiarity with Stata will be helpful but is not required.
Instruction Mode
Internet