Impact Evaluation Of Development Interventions

Impact evaluation is an empirical approach to estimating the causal effects of interventions, in terms of both magnitude and statistical significance. Expanded use of impact evaluation techniques is critical to rigorously derive knowledge from development operations and for development investments and policies to become more evidence-based and effective. To help backstop more use of impact evaluation approaches, this book introduces core concepts, methods, and considerations for planning, designing, managing, and implementing impact evaluation, supplemented by examples. The topics covered range from impact evaluation purposes to basic principles, specific methodologies, and guidance on field implementation. It has materials for a range of audiences, from those who are interested in understanding evidence on "what works" in development, to those who will contribute to expanding the evidence base as applied researchers.

The second edition of the Impact Evaluation in Practice handbook is a comprehensive and accessible introduction to impact evaluation for policy makers and development practitioners. First published in 2011, it has been used widely across the development and academic communities. The book incorporates real-world examples to present practical guidelines for designing and implementing impact evaluations. Readers will gain an understanding of impact evaluations and the best ways to use them to design evidence-based policies and programs. The updated version covers the newest techniques for evaluating programs and includes state-of-the-art implementation advice, as well as an expanded set of examples and case studies that draw on recent development challenges. It also includes new material on research ethics and partnerships to conduct impact evaluation. The handbook is divided into four sections: Part One discusses what to evaluate and why; Part Two presents the main impact evaluation methods; Part Three addresses how to manage impact evaluations; Part Four reviews impact evaluation sampling and data collection. Case studies illustrate different applications of impact evaluations. The book links to complementary instructional material available online, including an applied case as well as questions and answers. The updated second edition will be a valuable resource for the international development community, universities, and policy makers looking to build better evidence around what works in development.

Impact evaluation aims to answer whether and to what extent a development intervention has delivered its intended effects, thus enabling evidence-based policy making. The desire for more hard evidence of the effectiveness of development interventions has fueled a growing interest in rigorous impact evaluation in the international development community. This report discusses the fundamental challenge of impact evaluation, which is to credibly attribute the impact, if any, to the intervention concerned. It then discusses the merits and limitations of various impact evaluation methods. It also presents a survey of recent applications of impact evaluation, focusing on the typical evaluation problems looked at, methods used, and key findings. The report includes six case studies and outlines practical steps in implementing an impact evaluation.

In recent years debates on as well as funding of impact evaluations of development interventions have flourished. Unfortunately, controversy regarding the promotion and application of randomized experiments (RE) has led to a sense of polarization in the development policy and evaluation community. As some proponents claim epistemological supremacy of REs (with respect to attribution) the counter reaction among others has been rejection. Needless to say, such extreme positions are counterproductive to reaching a goal that is commonly endorsed: to learn more about what works and why in development. This paper discusses the prospects and limitations of REs from the perspective of three categories of challenges in impact evaluation: delimitation and scope, attribution versus explanation, and implementation challenges. The implicit lesson is twofold. First of all, the question 'to randomize or not to randomize' is overrated in the current debate. Limitations in scope, applicability as well as implementation will necessarily restrict the use of REs in development impact evaluation. There is a risk that the current popularity of REs in certain research and policy circles might lead to a backlash as too high expectations of REs may quicken its demise. More importantly, given the nature and scope of the challenges discussed in the paper, more energy should be devoted to developing and testing 'rigorous' mixed method approaches within a framework of theory-driven evaluation.

This report aims to support impact evaluation in the energy sector by assessing what has been produced against what might be possible. It reviews 85 impact evaluations of energy interventions in developing countries, summarizes findings on outcomes, identifies evidence gaps, and proposes ways forward. A majority of studies has so far focused on rural electrification and improved cookstoves, while most investments are in power generation and transmission. After considering the body of evidence available, directions and approaches are proposed for future impact evaluations to best contribute new evidence regarding the sector.

This publication aims to support impact evaluation in the transport sector by assessing what has been produced against what might be possible. It reviews 91 impact evaluations of transport interventions in developing countries, summarizes findings on outcomes, identifies evidence gaps, and proposes ways forward. Most of the studies reviewed find significant effects on at least one of the outcomes investigated. However, impact evaluation has given relatively little coverage to major areas of investment, such as urban and sustainable transportation, transport corridors, and efficiency enhancing measures. New methods and increasing openness of geospatial data provide scope to generate more innovative impact studies.

Public programs are designed to reach certain goals and beneficiaries. Methods to understand whether such programs actually work, as well as the level and nature of impacts on intended beneficiaries, are main themes of this book.

Developmental evaluation (DE) offers a powerful approach to monitoring and supporting social innovations by working in partnership with program decision makers. In this book, eminent authority Michael Quinn Patton shows how to conduct evaluations within a DE framework. Patton draws on insights about complex dynamic systems, uncertainty, nonlinearity, and emergence. He illustrates how DE can be used for a range of purposes: ongoing program development, adapting effective principles of practice to local contexts, generating innovations and taking them to scale, and facilitating rapid response in crisis situations. Students and practicing evaluators will appreciate the book's extensive case examples and stories, cartoons, clear writing style, "closer look" sidebars, and summary tables. Provided is essential guidance for making evaluations useful, practical, and credible in support of social change.

This book is open access under a CC BY 4.0 license. This book presents methods to evaluate sustainable development using economic tools. The focus on sustainable development takes the reader beyond economic growth to encompass inclusion, environmental stewardship and good governance. Sustainable Development Goals (SDGs) provide a framework for outcomes. In illustrating the SDGs, the book employs three evaluation approaches: impact evaluation, cost-benefit analysis and objectives-based evaluation. The innovation lies in connecting evaluation tools with economics. Inclusion, environmental care and good governance, thought of as “wicked problems”, are given centre stage. The book uses case studies to show the application of evaluation tools. It offers guidance to evaluation practitioners, students of development and policymakers. The basic message is that evaluation comes to life when its links with socio-economic, environmental, and governance policies are capitalized on.

Assessing impacts of public investments has long captured the interest and attention of the development community. This paper presents the evolution of different methods and approaches used for ex ante appraisal, monitoring, project evaluation, and impact assessment over the last five decades. Among these tools, impact assessment (IA) conducted retrospectively comes closest to providing the proof of development effectiveness. It is defined as the systematic analysis of the significant or lasting changes in people's lives brought about by a given action or series of actions in relation to a counterfactual. There are three basic types of retrospective IAs: macro-level IAs that focus on the contribution of developmental efforts to an impact goal aggregated at a sector or a system level; micro-level impact evaluations (IEs) concerned with estimating the average effect of an intervention on outcomes at the beneficiary level; and micro-level ex post impact analysis concerned with total effects of a development effort after the outputs are scaled-up. Ex post IAs have evolved and expanded over the decades in both breadth and depth of analysis in response to evolving development themes and methodological advancements. The increased emphasis on learning from evaluations has also seen responses from both quantitative and qualitative camps of the evaluation community. The paper argues that generation of robust knowledge that feeds into making developmental policies and investment decisions requires a hierarchical and cumulative approach to "improving the proof" through rigorous and a variety of impact assessment methods applied incrementally at the project, program and system level. Subjecting as many development interventions as resources allow to rigorous impact assessment based on a common framework can help build a critical body of evidence on impacts of development interventions, which can then be subjected to meta-analyses to help assimilate results across different studies and build a knowledge base on what works and what does not.