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Handbook on Impact Evaluation: Quantitative Methods and Practices

by: Shahidur R. Khandker, Gayatri B. Koolwal, Hussain A. Samad
Price: $39.95   *Geographic discounts available!

Available; printed on demand. Books(s) will be printed when order is received.

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: World Bank Training Series
English; Paperback; 260 pages; 7x10
Published October 13, 2009 by World Bank
ISBN: 978-0-8213-8028-4; SKU: 18028

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. Has the Grameen Bank, for example, succeeded in lowering consumption poverty among the rural poor in Bangladesh? Can conditional cash transfer programs in Mexico and Latin America improve health and schooling outcomes for poor women and children? Does a new road actually raise welfare in a remote area in Tanzania, or is it a "highway to nowhere?"

This book reviews quantitative methods and models of impact evaluation. It begings by reviewing the basic issues pertaining to an evaluation of an intervention to reach certain targets and goals. It then focuses on the experimental design of an impact evaluation, highlighting its strengths and shortcomings, followed by discussions on various non-experimental methods. The authors also cover methods to shed light on the nature and mechanisms by which different participants are benefiting from the program.

For researchers interested in learning how to use these models with statistical software, the book also provides STATA exercises in the context of evaluating major microcredit programs in Bangladesh, such as the Grameen Bank. The framework presented in this book can be very useful for strengthening local capacity in impact evaluation among technicians and policymakers in charge of formulating, implementing, and evaluating programs to alleviate poverty and underdevelopment.


1. Introduction

2. Basic Issues of Evaluation
Summary • Learning Objectives • Introduction: Monitoring versus Evaluation • Monitoring • Setting Up Indicators within an M&E Framework • Operational Evaluation • Quantitative versus Quantitative Impact Assessments • Quantitative Impact Assessment: Ex Post versus Ex Ante Impact Evaluations • The Problem of the Counterfactual • Basic Theory of Impact Evaluation: The Problem of Selection Bias • Different Evaluation Approaches to Ex Post Impact Evaluation • Overview: Designing and Implementing Impact Evaluations • Questions

3. Randomization
Summary • Learning Objectives • Setting the Counterfactual • Statistical Design of Randomization • Calculating Treatment Effects • Randomization in Evaluation Design: Different Methods of Randomization • Concerns with Randomization • Randomized Impact Evaluation in Practice • Difficulties with Randomization • Questions

4. Propensity Score Matching
Summary • Learning Objectives • PSM and Its Practical Uses • What Does PSM Do? • PSM Method in Theory • Application of the PSM Method • Critiquing the PSM Method • PSM and Regression-Based Methods • Questions

5. Double Difference
Summary • Learning Objectives • Addressing Selection Bias from a Different Perspective: Using Differences as Counterfactual • DD Method: Theory and Application • Advantages and Disadvantages of Using DD • Alternative DD Models • Questions

6. Instrumental Variable Estimation
Summary • Learning Objectives • Introduction • Two-Stage Least Squares Approach to IVs • Concerns with IVs • Sources of IVs • Question

7. Regression Discontinuity and Pipeline Methods
Summary • Learning Objectives • Introduction • Regression Discontinuity in Theory • Advantages and Disadvantages of the RD Approach • Pipeline Comparisons • Questions

8. Measuring Distributional Program Effects
Summary • Learning Objectives • The Need to Examine Distributional Impacts of Programs • Examining Heterogeneous Program Impacts: Linear Regression Framework • Quantile Regression Approaches • Discussion: Data Collection Issues

9. Using Economic Models to Evaluate Policies
Summary • Learning Objectives • Introduction • Structural versus Reduced-Form Approaches • Modeling the Effects of Policies • Assessing the Effect of Policies in a Macroeconomic Framework • Modeling Household Behavior in the Case of a Single Treatment: Case Studies on School Subsidy Programs • Conclusions

10. Conclusions


11. Introduction to Stata
Data Sets Used for Stata Exercise • Beginning Exercise: Introduction to Stata • Working with Data Files: Looking at the Content • Changing Data Sets • Combining Data Sets • Working with .log and .do Files

12. Randomized Impact Evaluation
Impacts of Program Placement in Villages • Impacts of Program Participation • Capturing Both Program Placement and Participation • Impacts of Program Participation in Program Villages • Measuring Spillover Effects of Microcredit Program Placement • Further Exercises

13. Propensity Score Matching Technique
Propensity Score Equation: Satisfying the Balancing Property • Average Treatment Effect Using Nearest-Neighbor Matching • Average Treatment Effect Using Stratification Matching • Average Treatment Effect Using Radius Matching • Average Treatment Effect Using Kernel Matching • Checking Robustness of Average Treatment Effect • Further Exercises

14. Double-Difference Method
Simplest Implementation: Simple Comparison Using "ttest" • Regression Implementation • Checking Robustness of DD with Fixed-Effects Regression • Applying the DD Method in Cross-Sectional Data • Taking into Account Initial Conditions • The DD Method Combined with Propensity Score Matching

15. Instrumental Variable Method
IV Implementation Using "ivreg" Command • Testing for Endogeneity: OLS versus IV • IV Method for Binary Treatment: "treatreg" Command • IV with Fixed Effects: Cross-Sectional Estimates • IV with Fixed Effects: Panel Estimates

16. Regression Discontinuity Design
Impact Estimation Using RD • Implementation of Sharp Discontinuity • Implementation of Fuzzy Discontinuity • Exercise

  • Shipping Weight: 1.2 lbs (0.54 kgs)

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