Handbook on Impact Evaluation: Quantitative Methods and Practices

This book reviews quantitative methods and models of impact evaluation. The formal literature on impact evaluation methods and practices is large, with a few useful overviews. Yet there is a need to put the theory into practice in a hands-on fashion for practitioners. This book also details challenges and goals in other realms of evaluation, including monitoring and evaluation (M&E), operational evaluation, and mixed-methods approaches combining quantitative and qualitative analyses. This book is organized as follows. Chapter two reviews the basic issues pertaining to an evaluation of an intervention to reach certain targets and goals. It distinguishes impact evaluation from related concepts such as M&E, operational evaluation, qualitative versus quantitative evaluation, and ex-ante versus ex post impact evaluation. Chapter three focuses on the experimental design of an impact evaluation, discussing its strengths and shortcomings. Various non-experimental methods exist as well, each of which are discussed in turn through chapters four to seven. Chapter four examines matching methods, including the propensity score matching technique. Chapter five deal with double-difference methods in the context of panel data, which relax some of the assumptions on the potential sources of selection bias. Chapter six reviews the instrumental variable method, which further relaxes assumptions on self-selection. Chapter seven examines regression discontinuity and pipeline methods, which exploit the design of the program itself as potential sources of identification of program impacts. Specifically, chapter eight presents a discussion of how distributional impacts of programs can be measured, including new techniques related to quantile regression. Chapter nine discusses structural approaches to program evaluation, including economic models that can lay the groundwork for estimating direct and indirect effects of a program. Finally, chapter ten discusses the strengths and weaknesses of experimental and non-experimental methods and also highlights the usefulness of impact evaluation tools in policy making.