Presents an overview of
methods for estimating causal effects: how to answer the question of
“What is the effect of A on B?” Includes discussion of randomized designs, but
with more emphasis on alternative designs and methods for when randomization is
infeasible: matching methods, propensity scores, longitudinal treatments,
regression discontinuity, instrumental variables, and principal stratification.
Methods are motivated by examples from social sciences, policy and health
sciences.