Impact Evaluation

In recent years interest in rigorous impact evaluation has grown tremendously in policy-making economics public health social sciences and international relations. Evidence-based policy-making has become a recurring theme in public policy alongside greater demands for accountability in public policies and public spending and requests for independent and rigorous impact evaluations for policy evidence. Frölich and Sperlich offer a comprehensive and up-to-date approach to quantitative impact evaluation analysis also known as causal inference or treatment effect analysis illustrating the main approaches for identification and estimation: experimental studies randomization inference and randomized control trials (RCTs) matching and propensity score matching and weighting instrumental variable estimation difference-in-differences regression discontinuity designs quantile treatment effects and evaluation of dynamic treatments. The book is designed for economics graduate courses but can also serve as a manual for professionals in research institutes governments and international organizations evaluating the impact of a wide range of public policies in health environment transport and economic development.