Handbook on Impact Evaluation: Quantitative Methods and Practices - Exercises 2009

Bangladesh, 2009

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BGD_2009_HIEQMP_v01_M

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S. Khandker, G. Koolwal and H. Samad

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Author(s)	S. Khandker, G. Koolwal and H. Samad (World Bank)
Date	2009-01-01
Country	Bangladesh
Language	English
Description	STATA exercises in the context of evaluating major microcredit programs in Bangladesh, such as the Grameen Bank.
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Handbook on Impact Evaluation: Quantitative Methods and Practices

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Author(s)	Shahidur Khandker , Gayatri B. Koolwal , Hussain Samad (World Bank)
Date	2009-10-01
Country	World
Language	English
Table of contents	PART 1. METHODS AND PRACTICES 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 PART 2. STATA EXERCISES 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
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