Impact Evaluation in International Development Theory, Methods, and Practice.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Glewwe, Paul
Otros Autores: Todd, Petra
Formato: Electrónico eBook
Idioma:Inglés
Publicado: : World Bank Publications, 2021.
Temas:
Economic assistance > Evaluation.
Economic impact analysis.
Économie > Études d'impact.
economic impact analysis.
Economic assistance > Evaluation
Economic impact analysis
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Front Cover
  • Contents
  • Preface
  • About the Authors and Contributors
  • Abbreviations
  • Part I The Basics of Impact Evaluation
  • Chapter 1 The Purpose of Impact Evaluation
  • Introduction
  • The difference between monitoring and evaluation
  • A definition of impact evaluation
  • Brief overview of types of impact evaluations
  • Other issues regarding impact evaluation
  • Conclusion
  • Notes
  • References
  • Chapter 2 How to Conduct an Impact Evaluation: Getting Started
  • Introduction
  • Step 1. Defining the program and the outcomes of interest
  • Step 2. Forming a theory of change to refine the evaluation questions
  • Step 3. Depicting a theory of change in a results chain (logic model)
  • Step 4. Formulating specific hypotheses for the impact evaluation
  • Step 5. Selecting performance indicators for monitoring and evaluation
  • Conclusion
  • Notes
  • References
  • Chapter 3 The Evaluation Problem
  • Introduction
  • Correlation does not imply causation
  • Potential outcomes and the evaluation problem
  • Observed outcomes and the gain from treatment
  • Parameters of interest
  • Conclusion
  • References
  • Chapter 4 Validity: Internal, External, and Trade-Offs
  • Introduction
  • Internal validity
  • External validity
  • Trade-offs and intermediate approaches
  • Conclusion
  • Notes
  • References
  • Chapter 5 Overview of Impact Evaluation Methods
  • Introduction
  • Using randomized controlled trials to evaluate program impacts
  • Impact evaluations based on nonrandomized and quasi-experimental data
  • Conclusion
  • Notes
  • References
  • Part II Experimental Methods
  • Chapter 6 Introduction to Randomized Controlled Trials
  • Introduction
  • The basic idea of a randomized controlled trial
  • How does randomization solve the evaluation problem?
  • What if some people assigned to the treatment group choose not to participate?.
  • Intention-to-treat effects
  • Intention-to-treat effects when effects spill over onto nonparticipants
  • Encouragement designs
  • Conclusion
  • Notes
  • References
  • Chapter 7 Regression Methods for Randomized Controlled Trials
  • Introduction
  • Estimating average treatment effects when no problems occur
  • Estimation when some in the treatment group are not treated
  • Complications caused by sample attrition
  • Methods for increasing precision of the estimates
  • Methods for obtaining correct standard errors
  • Other useful advice and recommendations
  • Conclusion
  • Notes
  • References
  • Chapter 8 Practical Advice for Implementing Randomized Evaluations
  • Introduction
  • Potential problems with randomized experiments, and possible solutions
  • Practical advice for randomizing into treatment and control groups
  • The use of pre-analysis plans in impact evaluations
  • Other practical advice
  • Increasing external validity
  • Conclusion
  • Notes
  • References
  • Chapter 9 Sample Size, Sample Design, and Statistical Power
  • Introduction
  • Statistical power as a criterion for choosing the sample design
  • Power and MDE calculations in more complex settings
  • Practical issues regarding power calculations
  • Further statistical issues
  • Conclusion
  • Notes
  • References
  • Chapter 10 Recommendations for Conducting Ethical Impact Evaluations
  • Introduction
  • Two frameworks for conducting ethical evaluations and research
  • Confidentiality
  • Ethics of randomized controlled trials
  • Conflicts of interest
  • Ethical research in practice
  • Conclusion
  • Notes
  • References
  • Part III Nonexperimental Methods
  • Chapter 11 Regression Methods for Nonrandomized Data: Cross-Sectional and Before-After Estimators
  • Introduction
  • Examples: Cross-sectional, before-after, and difference-in-differences estimators
  • Parameters of interest.
  • The cross-sectional estimator and sources of bias
  • The before-after estimator
  • Conclusion
  • Notes
  • References
  • Chapter 12 Regression Methods for Nonrandomized Data: The Difference-in-Differences Estimator and the Within Estimator
  • Introduction
  • The difference-in-differences estimator
  • Within estimators
  • Applications of difference-in-differences and within estimators
  • Conclusion
  • Notes
  • References
  • Chapter 13 Matching Methods
  • Introduction
  • Two simple examples
  • Cross-sectional matching
  • Implementation of propensity score matching estimators
  • Difference-in-differences matching
  • Additional topics for matching methods
  • Empirical applications of matching estimators
  • Conclusion
  • Notes
  • References
  • Chapter 14 Regression Discontinuity Methods
  • Introduction
  • Intuition for regression discontinuity methods
  • Identification of treatment effects under "sharp" and "fuzzy" data
  • Checking the validity of a regression discontinuity design
  • The Hahn, Todd, and van der Klaauw estimation method
  • Examples of regression discontinuity methods
  • Conclusion
  • Notes
  • References
  • Chapter 15 Instrumental Variables Estimation and Local Average Treatment Effects
  • Introduction
  • Two uses of instrumental variables estimation for impact evaluation analysis
  • Instrumental variables estimation of ATE and ATT
  • Using IV methods to estimate local average treatment effects
  • Conclusion
  • Notes
  • References
  • Chapter 16 Control Function Methods
  • Introduction
  • The basic idea of the control function approach
  • Methods for estimating control functions
  • Standard error calculations for control function estimation methods
  • Comparing control functions to matching methods and instrumental variables
  • Adapting the control function approach for estimating ATE(X) and ATE.
  • An application: The performance of public and private schools in Chile
  • Conclusion
  • Notes
  • References
  • Chapter 17 Quantile Treatment Effects
  • Introduction
  • The basic idea of quantile regression, with an example
  • Conditional and unconditional quantile treatment effect estimators
  • Conditional quantile treatment effect estimators
  • Unconditional quantile treatment effect estimators
  • Standard errors
  • Examples of applications
  • Conclusion
  • Notes
  • References
  • Part IV Data Collection and Project Management
  • Chapter 18 Designing Questionnaires and Other Data Collection Instruments
  • Introduction
  • General principles and recommendations
  • General advice on the design of questionnaires
  • Household questionnaires
  • Service provider questionnaires
  • Community (and price) questionnaires
  • Other data collection instruments
  • Paper questionnaires versus computer-assisted personal interviewing
  • Conclusion
  • Notes
  • References
  • Chapter 19 Data Collection and Data Management
  • Introduction
  • The steps involved in data collection and data management
  • Establish procedures for collecting and managing the data
  • Collect the data (including monitoring of data quality)
  • Further checks of data quality after the fieldwork
  • Create data files for analysis and dissemination
  • Establish a system to store, revise, and disseminate the data
  • Conclusion
  • Notes
  • References
  • Chapter 20 Survey Management
  • Introduction
  • Budgeting and developing an overall plan of activities
  • Human resources (personnel) management
  • Logistical coordination
  • Community relations
  • Lessons from unfortunate experiences
  • Conclusion
  • Note
  • References
  • Part V Related Topics
  • Chapter 21 Dissemination of Results and Working with Policy Makers
  • Introduction
  • What products should the impact evaluation deliver?.
  • Dissemination of the findings
  • Working with policy makers
  • Conclusion
  • Notes
  • References
  • Chapter 22 Qualitative Approaches, Data, and Analysis in Impact Evaluations
  • Joan DeJaeghere
  • Introduction
  • Contributions and challenges in using qualitative research in impact evaluations
  • Different purposes and types of qualitative approaches
  • The most common methods for collecting qualitative data
  • Exploratory and explanatory qualitative approaches
  • Practical suggestions for designing, gathering, and analyzing qualitative data
  • Conclusion
  • Annex 22A Questions for realist evaluations
  • References
  • Chapter 23 Cost-Benefit Analysis and Cost-Effectiveness Analysis
  • Introduction
  • Calculation of costs
  • A simple comparison of cost-benefit analysis and cost-effectiveness analysis
  • Cost-benefit analysis (valuing the benefits)
  • Cost-effectiveness analysis
  • Conclusion
  • Notes
  • References
  • Boxes
  • Box 1.1 Key organizations and agency departments that focus on impact evaluation in international development
  • Box 3.1 Requirements for answering the evaluation problem, "What is the causal impact of the program (or project or policy) on the outcomes of interest?"
  • Box 22.1 Case studies and comparative qualitative analysis: Example of Akazi Kanoze Youth Livelihoods Project (Alcid 2014)
  • Box 22.2 Longitudinal and theory-based design and analysis: Example of Learn, Earn, and Save Initiative of Youth Livelihoods Programs in Tanzania and Uganda
  • Figures
  • Figure 2.1 A results chain diagram: Basic layout and components
  • Figure 2.2 A more detailed view of what goes into a results chain (logic model)
  • Figure 2.3 Examples of a results chain's components: Education and health sectors
  • Figure 2.4 Example of a results chain: Mexico's PROGRESA program.

Ejemplares similares