Successful Impact Evaluations: Lessons from DFID and 3Ie
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A Note on the Impact Evaluation of Public Policies: the Counterfactual Analysis
A note on the impact evaluation of public policies: the counterfactual analysis Massimo Loi and Margarida Rodrigues 2012 Report EUR 25519 EN 1 European Commission Joint Research Centre Institute for the Protection and Security of the Citizen Contact information Forename Surname Address: Joint Research Centre, Via Enrico Fermi 2749, TP 361, 21027 Ispra (VA), Italy E-mail: [email protected] Tel.: +39 0332 78 5633 Fax: +39 0332 78 5733 http://ipsc.jrc.ec.europa.eu/ http://www.jrc.ec.europa.eu/ Legal Notice Neither the European Commission nor any person acting on behalf of the Commission is responsible for the use which might be made of this publication. Europe Direct is a service to help you find answers to your questions about the European Union Freephone number (*): 00 800 6 7 8 9 10 11 (*) Certain mobile telephone operators do not allow access to 00 800 numbers or these calls may be billed. A great deal of additional information on the European Union is available on the Internet. It can be accessed through the Europa server http://europa.eu/. JRC74778 EUR 25519 EN ISBN 978-92-79-26425-2 ISSN 1831-9424 doi:10.2788/50327 Luxembourg: Publications Office of the European Union, 2012 © European Union, 2012 Reproduction is authorised provided the source is acknowledged. Printed in Italy Contents 1. Introduction ............................................................................................................................. 4 2. Basic concepts ........................................................................................................................ -
Randomised Control Trials for the Impact Evaluation of Development Initiatives: a Statistician’S Point of View
ILAC Working Paper 13 Randomised Control Trials for the Impact Evaluation of Development Initiatives: A Statistician’s Point of View Carlos Barahona October 2010 Institutional Learning and Change (ILAC) Initiative - c/o Bioversity International Via dei Tre Denari 472°, 00057 Maccarese (Fiumicino ), Rome, Italy Tel: (39) 0661181, Fax: (39) 0661979661, email: [email protected] , URL: www.cgiar-ilac.org 2 The ILAC initiative fosters learning from experience and use of the lessons learned to improve the design and implementation of agricultural research and development programs. The mission of the ILAC initiative is to develop, field test and introduce methods and tools that promote organizational learning and institutional change in CGIAR centers and their partners, and to expand the contributions of agricultural research to the achievement of the Millennium Development Goals. Citation: Barahona, C. 2010. Randomised Control Trials for the Impact Evaluation of Development Initiatives: A Statistician’s Point of View . ILAC Working Paper 13, Rome, Italy: Institutional Learning and Change Initiative. 3 Table of Contents 1. Introduction ........................................................................................................................ 4 2. Randomised Control Trials in Impact Evaluation .............................................................. 4 3. Origin of Randomised Control Trials (RCTs) .................................................................... 6 4. Why is Randomisation so Important in RCTs? ................................................................. -
3Ie Impact Evaluation Glossary
Impact Evaluation Glossary Version No. 7 Date: July 2012 Please send comments or suggestions on this glossary to [email protected]. Recommended citation: 3ie (2012) 3ie impact evaluation glossary. International Initiative for Impact Evaluation: New Delhi, India. Attribution The extent to which the observed change in outcome is the result of the intervention, having allowed for all other factors which may also affect the outcome(s) of interest. Attrition Either the drop out of participants from the treatment group during the intervention, or failure to collect data from a unit in subsequent rounds of a panel data survey. Either form of attrition can result in biased impact estimates. Average treatment effect The average value of the impact on the beneficiary group (or treatment group). See also intention to treat and treatment of the treated. Baseline survey and baseline data A survey to collect data prior to the start of the intervention. Baseline data are necessary to conduct double difference analysis, and should be collected from both treatment and comparison groups. Before versus after See single difference. Beneficiary or beneficiaries Beneficiaries are the individuals, firms, facilities, villages or similar that are exposed to an intervention with beneficial intentions. Bias The extent to which the estimate of impact differs from the true value as result of problems in the evaluation or sample design (i.e. not due to sampling error). 1 Blinding A process of concealing which subjects are in the treatment group and which are in the comparison group, which is single-blinding. In a double blinded approach neither the subjects nor those conducting the trial know who is in which group, and in a triple blinded trial, those analyzing the data do not know which group is which. -
Impact Evaluation in Practice Second Edition Please Visit the Impact Evaluation in Practice Book Website at .Org/Ieinpractice
Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Impact Evaluation in Practice Second Edition Please visit the Impact Evaluation in Practice book website at http://www.worldbank .org/ieinpractice. The website contains accompanying materials, including solutions to the book’s HISP case study questions, as well as the corresponding data set and analysis code in the Stata software; a technical companion that provides a more formal treatment of data analysis; PowerPoint presentations related to the chapters; an online version of the book with hyperlinks to websites; and links to additional materials. This book has been made possible thanks to the generous support of the Strategic Impact Evaluation Fund (SIEF). Launched in 2012 with support from the United Kingdom’s Department for International Development, SIEF is a partnership program that promotes evidence-based policy making. The fund currently focuses on four areas critical to healthy human development: basic education, health systems and service delivery, early childhood development and nutrition, and water and sanitation. SIEF works around the world, primarily in low-income countries, bringing impact evaluation expertise and evidence to a range of programs and policy-making teams. Impact Evaluation in Practice Second Edition Paul J. Gertler, Sebastian Martinez, Patrick Premand, Laura B. Rawlings, and Christel M. J. Vermeersch © 2016 International Bank for Reconstruction and Development / The World Bank 1818 H Street NW, Washington, DC 20433 Telephone: 202-473-1000; Internet: www.worldbank.org Some rights reserved 1 2 3 4 19 18 17 16 The fi nding, interpretations, and conclusions expressed in this work do not necessarily refl ect the views of The World Bank, its Board of Executive Directors, the Inter- American Development Bank, its Board of Executive Directors, or the governments they represent. -
Impact Evaluation of Development Interventions a Practical Guide Howard White David A
IMPACT EVALUATION OF DEVELOPMENT INTERVENTIONS A Practical Guide Howard White David A. Raitzer ASIAN DEVELOPMENT BANK IMPACT EVALUATION OF DEVELOPMENT INTERVENTIONS A Practical Guide Howard White David A. Raitzer ASIAN DEVELOPMENT BANK Creative Commons Attribution 3.0 IGO license (CC BY 3.0 IGO) © 2017 Asian Development Bank 6 ADB Avenue, Mandaluyong City, 1550 Metro Manila, Philippines Tel +63 2 632 4444; Fax +63 2 636 2444 www.adb.org Some rights reserved. Published in 2017. Printed in the Philippines. ISBN 978-92-9261-058-6 (print), 978-92-9261-059-3 (electronic) Publication Stock No. TCS179188-2 DOI: http://dx.doi.org/10.22617/TCS179188-2 The views expressed in this publication are those of the authors and do not necessarily reflect the views and policies of the Asian Development Bank (ADB) or its Board of Governors or the governments they represent. ADB does not guarantee the accuracy of the data included in this publication and accepts no responsibility for any consequence of their use. The mention of specific companies or products of manufacturers does not imply that they are endorsed or recommended by ADB in preference to others of a similar nature that are not mentioned. By making any designation of or reference to a particular territory or geographic area, or by using the term “country” in this document, ADB does not intend to make any judgments as to the legal or other status of any territory or area. This work is available under the Creative Commons Attribution 3.0 IGO license (CC BY 3.0 IGO) https://creativecommons.org/licenses/by/3.0/igo/. -
USAID Technical Note on Impact Evaluation
VERSION 1.0 | SEPTEMBER 2013 TECHNICAL NOTE Impact Evaluations Monitoring and Evaluation Series INTRODUCTION This Note This Note defines impact evaluations, explains when they should be defines impact commissioned according to USAID policy and describes different designs for quasi-experimental and experimental impact evaluations. The USAID evaluations Automated Directives System (ADS) 203 defines impact evaluations as and discusses those that measure the change in a development outcome that is attributable to a defined intervention. Impact evaluations are based on models of cause and effect design and and require a credible and rigorously defined counterfactual to control for factors key planning other than the intervention that might account for the observed change. considerations. Decisions about whether an impact evaluation would be appropriate, and what type of impact evaluation to conduct, are best made early during the project design phase. Some impact evaluation designs can only be implemented if comparison groups are established and baseline data is collected before an intervention begins. Although they are most effective and sometimes only possible when planned before program implementation, impact evaluations can sometimes be used to measure changes that occur either during or after program implementation. In most cases, an expert should be consulted in advance to determine whether an impact evaluation will be feasible. Technical Notes are published by the This note outlines key considerations that USAID staff and evaluators should Bureau for Policy, take into account when planning for and designing impact evaluations. Those Planning and Learning commissioning an evaluation should include the evaluator when making and provide key decisions about an intervention’s targeting and implementation, and consider concepts and issues related to logistics, time and cost. -
Randomized Controlled Trials: Strengths, Weaknesses and Policy Relevance
Randomized Controlled Trials: Strengths, Weaknesses and Policy Relevance Anders Olofsgård Rapport 2014:1 till Expertgruppen för biståndsanalys (EBA) This report can be downloaded free of charge at www.eba.se. Hard copies are on sale at Fritzes Customer Service. Address: Fritzes, Customer Service, SE-106 47 Stockholm Sweden Fax: 08 598 191 91 (national) +46 8 598 191 91 (international) Tel: 08 598 191 90 (national) +46 8 598 191 90 (international) E-mail: [email protected] Internet: www.fritzes.se Printed by Elanders Sverige AB Stockholm 2014 Cover design by Julia Demchenko ISBN 978-91- 38-24114-1 Foreword Sweden’s international aid is strategically managed by the Government mainly through so called results strategies. In the guidelines for these strategies it is stated that “decisions about the future design of aid are to a great extent to be based on an analysis of the results that have been achieved.”1 This demands precision in how expected results are formulated and how results are measured and reported. Results can be stated in terms of outputs, outcomes or impacts. Outputs are goods or services that result directly from interventions and are generally easy to measure and report (for example, an organised seminar on sustainability, a built road, or a number of vaccinations). Outcomes and impacts are results caused by outputs, that is, the part of the change in a state or a condition (“sustainability”, better functioning markets, or an eradicated disease) that can be attributed to the intervention. These results are in general more difficult to measure than outputs, amongst other things because the observed change rarely depends solely on the intervention. -
Impact Evaluation Methods in Public Economics: a Brief Introduction to Randomized Evaluations and Comparison with Other Methods
Impact Evaluation Methods in Public Economics: A Brief Introduction to Randomized Evaluations and Comparison with Other Methods The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Pomeranz, Dina. "Impact Evaluation Methods in Public Economics: A Brief Introduction to Randomized Evaluations and Comparison with Other Methods." Public Finance Review (January 2017). (Was Harvard Business School Working Paper, No. 16-049, October 2015. Spanish version available at http://www.hbs.edu/ faculty/Supplemental%20Files/Metodos-de-Evaluacion-de- Impacto_50067.pdf.) Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:25757697 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#OAP Impact Evaluation Methods in Public Economics Dina Pomeranz Working Paper 16-049 Impact Evaluation Methods in Public Economics Dina Pomeranz Harvard Business School Working Paper 16-049 Copyright © 2015 by Dina Pomeranz Working papers are in draft form. This working paper is distributed for purposes of comment and discussion only. It may not be reproduced without permission of the copyright holder. Copies of working papers are available from the author. Impact Evaluation Methods in Public Economics A Brief Introduction to Randomized Evaluations and Comparison with Other Methods Dina Pomeranz September 2015 Recent years have seen a large expansion in the use of rigorous impact evaluation tech- niques. Increasingly, public administrations are collaborating with academic economists and other quantitative social scientists to apply such rigorous methods to the study of public finance. -
IFPRI's Evaluation of PROGRESA in Mexico: Norm, Mistake, Or Exemplar?
IFPRI’s evaluation of PROGRESA in Mexico: Norm, Mistake, or Exemplar? William N. Faulkner Published in Evaluation, Volume 20, Number 2, April 2014. SAGE Publications. 1 Abstract: During the early stages of implementing their new flagship anti-poverty program, Progresa, Mexican officials contracted an evaluation team from the International Food Policy Research Institute (IFPRI). This article critically revisits the narrative of this evaluation’s methodology using an approach informed by science studies, finding a number of significant omissions and ambiguities. By profiling the available information on these facets of the evaluation against, first, the intellectual background of randomised control trials (RCTs) in international development evaluation, and second, the political context of the project, the analysis attempts to extract lessons for today’s evaluation community. These lessons result in two invitations: (1) for the proponents of RCTs in the field of international development evaluation to critically and reflexively consider the problematic framing of the methodology in this case study and what the implications might be for other similar projects; (2) for evaluators critical of how RCTs have been presented in the field to narrow a greater portion of their analyses to specific case studies, known econometric issues with familiar labels, and living institutions with names. Keywords: Conditional Cash Transfers; Randomised-Control Trials; Meta-Evaluation. 2 Glossary of Abbreviations Abbreviation Definition CCT Conditional Cash Transfer -
Impact Evaluation of Development Interventions-A Practical Guide
IMPACT EVALUATION OF DEVELOPMENT INTERVENTIONS A Practical Guide Howard White David A. Raitzer ASIAN DEVELOPMENT BANK IMPACT EVALUATION OF DEVELOPMENT INTERVENTIONS A Practical Guide Howard White David A. Raitzer ASIAN DEVELOPMENT BANK Creative Commons Attribution 3.0 IGO license (CC BY 3.0 IGO) © 2017 Asian Development Bank 6 ADB Avenue, Mandaluyong City, 1550 Metro Manila, Philippines Tel +63 2 632 4444; Fax +63 2 636 2444 www.adb.org Some rights reserved. Published in 2017. Printed in the Philippines. ISBN 978-92-9261-058-6 (print), 978-92-9261-059-3 (electronic) Publication Stock No. TIM179188-2 DOI: http://dx.doi.org/10.22617/TIM179188-2 The views expressed in this publication are those of the authors and do not necessarily reflect the views and policies of the Asian Development Bank (ADB) or its Board of Governors or the governments they represent. ADB does not guarantee the accuracy of the data included in this publication and accepts no responsibility for any consequence of their use. The mention of specific companies or products of manufacturers does not imply that they are endorsed or recommended by ADB in preference to others of a similar nature that are not mentioned. By making any designation of or reference to a particular territory or geographic area, or by using the term “country” in this document, ADB does not intend to make any judgments as to the legal or other status of any territory or area. This work is available under the Creative Commons Attribution 3.0 IGO license (CC BY 3.0 IGO) https://creativecommons.org/licenses/by/3.0/igo/. -
Causal Inference and Selection Bias: M&E Vs. IE
Causal inference and Selection Bias: M&E vs. IE Malathi Velamuri Victoria University of Wellington Workshop on Impact Evaluation of Public Health Programs July 11-15, 2011 – Chennai Causal Analysis Seeks to determine the effects of particular interventions or policies, or estimate behavioural relationships Three key criteria for inferring a cause and effect relationship: (a) covariation between the presumed cause(s) and effect(s); (b) temporal precedence of the cause(s); and (c) exclusion of alternative explanations for cause-effect linkages. • What is effect of scholarships on school attendance & performance (test scores)? • Does access to piped water reduce prevalence of diarrhea among children? • Does promotion of condom use and distribution of free condoms reduce transmission of STIs? • Can rural ICTs be an effective tool to bridge the digital divide? Why are causal answers needed? • Association is not causation Ex: Does use of traditional fuels and cooking stoves cause respiratory illness? • Perceived wisdom is not always correct • Policymakers need to know the relative effectiveness of particular policy changes or interventions for prioritizing public actions • Provide greater accountability in the use of aid and greater rigour in the assessment of development outcomes • Increases transparency/ accountability – promotes good governance M&E Vs. IE M&E plays an important role in the management of programmes Management tool Objective: To ensure that resources going into the programme are being utilized, services are being accessed, activities are occurring in a timely manner, and expected results are being achieved. Monitoring is concerned with routine tracking of service and programme performance using input, process and outcome information collected on a regular and ongoing basis from policy guidelines, routine record-keeping, regular reporting and surveillance systems, (health) facility observations and client surveys. -
Impact Evaluations
VERSION 1.0 | SEPTEMBER 2013 TECHNICAL NOTE Impact Evaluations Monitoring and Evaluation Series INTRODUCTION This Note This Note defines impact evaluations, explains when they should be defines impact commissioned according to USAID policy and describes different designs for quasi-experimental and experimental impact evaluations. The USAID evaluations Automated Directives System (ADS) 203 defines impact evaluations as and discusses those that measure the change in a development outcome that is attributable to a defined intervention. Impact evaluations are based on models of cause and effect design and and require a credible and rigorously defined counterfactual to control for factors key planning other than the intervention that might account for the observed change. considerations. Decisions about whether an impact evaluation would be appropriate, and what type of impact evaluation to conduct, are best made early during the project design phase. Some impact evaluation designs can only be implemented if comparison groups are established and baseline data is collected before an intervention begins. Although they are most effective and sometimes only possible when planned before program implementation, impact evaluations can sometimes be used to measure changes that occur either during or after program implementation. In most cases, an expert should be consulted in advance to determine whether an impact evaluation will be feasible. Technical Notes are published by the This note outlines key considerations that USAID staff and evaluators should Bureau for Policy, take into account when planning for and designing impact evaluations. Those Planning and Learning commissioning an evaluation should include the evaluator when making and provide key decisions about an intervention’s targeting and implementation, and consider concepts and issues related to logistics, time and cost.