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ویرایش: Second Edition نویسندگان: Paul J. Gertler, Sebastian Martinez, Patrick Premand, Laura B. Rawlings, and Christel M.J. Vermeersch. سری: ISBN (شابک) : 9781464807800 ناشر: The World Bank Group سال نشر: 2016 تعداد صفحات: 367 زبان: English فرمت فایل : PDF (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود) حجم فایل: 6 مگابایت
در صورت تبدیل فایل کتاب Impact evaluation in practice به فرمت های PDF، EPUB، AZW3، MOBI و یا DJVU می توانید به پشتیبان اطلاع دهید تا فایل مورد نظر را تبدیل نمایند.
توجه داشته باشید کتاب ارزیابی تاثیر در عمل نسخه زبان اصلی می باشد و کتاب ترجمه شده به فارسی نمی باشد. وبسایت اینترنشنال لایبرری ارائه دهنده کتاب های زبان اصلی می باشد و هیچ گونه کتاب ترجمه شده یا نوشته شده به فارسی را ارائه نمی دهد.
Cover Half Title Title Page Copyright Page Contents Preface Acknowledgments About the Authors Abbreviations PART ONE. INTRODUCTION TO IMPACT EVALUATION Chapter 1. Why Evaluate? Evidence-Based Policy Making What Is Impact Evaluation? Prospective versus Retrospective Impact Evaluation Efficacy Studies and Effectiveness Studies Complementary Approaches Ethical Considerations Regarding Impact Evaluation Impact Evaluation for Policy Decisions Deciding Whether to Carry Out an Impact Evaluation Chapter 2. Preparing for an Evaluation Initial Steps Constructing a Theory of Change Developing a Results Chain Specifying Evaluation Questions Selecting Outcome and Performance Indicators Checklist: Getting Data for Your Indicators PART TWO. HOW TO EVALUATE Chapter 3. Causal Inference and Counterfactuals Causal Inference The Counterfactual Two Counterfeit Estimates of the Counterfactual Chapter 4. Randomized Assignment Evaluating Programs Based on the Rules of Assignment Randomized Assignment of Treatment Checklist: Randomized Assignment Chapter 5. Instrumental Variables Evaluating Programs When Not Everyone Complies with Their Assignment Types of Impact Estimates Imperfect Compliance Randomized Promotion as an Instrumental Variable Checklist: Randomized Promotion as an Instrumental Variable Chapter 6. Regression Discontinuity Design Evaluating Programs That Use an Eligibility Index Fuzzy Regression Discontinuity Design Checking the Validity of the Regression Discontinuity Design Limitations and Interpretation of the Regression Discontinuity Design Method Checklist: Regression Discontinuity Design Chapter 7. Difference-in-Differences Evaluating a Program When the Rule of Assignment Is Less Clear The Difference-in-Differences Method How Is the Difference-in-Differences Method Helpful? The “Equal Trends” Assumption in Difference-in-Differences Limitations of the Difference-in-Differences Method Checklist: Difference-in-Differences Chapter 8. Matching Constructing an Artificial Comparison Group Propensity Score Matching Combining Matching with Other Methods Limitations of the Matching Method Checklist: Matching Chapter 9. Addressing Methodological Challenges Heterogeneous Treatment Effects Unintended Behavioral Effects Imperfect Compliance Spillovers Attrition Timing and Persistence of Effects Chapter 10. Evaluating Multifaceted Programs Evaluating Programs That Combine Several Treatment Options Evaluating Programs with Varying Treatment Levels Evaluating Multiple Interventions PART THREE. HOW TO IMPLEMENT AN IMPACT EVALUATION Chapter 11. Choosing an Impact Evaluation Method Determining Which Method to Use for a Given Program How a Program’s Rules of Operation Can Help Choose an Impact Evaluation Method A Comparison of Impact Evaluation Methods Finding the Smallest Feasible Unit of Intervention Chapter 12. Managing an Impact Evaluation Managing an Evaluation’s Team, Time, and Budget Roles and Responsibilities of the Research and Policy Teams Establishing Collaboration How to Time the Evaluation How to Budget for an Evaluation Chapter 13. The Ethics and Science of Impact Evaluation Managing Ethical and Credible Evaluations The Ethics of Running Impact Evaluations Ensuring Reliable and Credible Evaluations through Open Science Checklist: An Ethical and Credible Impact Evaluation Chapter 14. Disseminating Results and Achieving Policy Impact A Solid Evidence Base for Policy Tailoring a Communication Strategy to Different Audiences Disseminating Results PART FOUR. HOW TO GET DATA FOR AN IMPACT EVALUATION Chapter 15. Choosing a Sample Sampling and Power Calculations Drawing a Sample Deciding on the Size of a Sample for Impact Evaluation: Power Calculations Chapter 16. Finding Adequate Sources of Data Kinds of Data That Are Needed Using Existing Quantitative Data Collecting New Survey Data Chapter 17. Conclusion Impact Evaluations: Worthwhile but Complex Exercises Checklist: Core Elements of a Well-Designed Impact Evaluation Checklist: Tips to Mitigate Common Risks in Conducting an Impact Evaluation Glossary Boxes 1.1 How a Successful Evaluation Can Promote the Political Sustainability of a Development Program: Mexico’s Conditional Cash Transfer Program 1.2 The Policy Impact of an Innovative Preschool Model: Preschool and Early Childhood Development in Mozambique 1.3 Testing for the Generalizability of Results: A Multisite Evaluation of the “Graduation” Approach to Alleviate Extreme Poverty 1.4 Simulating Possible Project Effects through Structural Modeling: Building a Model to Test Alternative Designs Using Progresa Data in Mexico 1.5 A Mixed Method Evaluation in Action: Combining a Randomized Controlled Trial with an Ethnographic Study in India 1.6 Informing National Scale-Up through a Process Evaluation in Tanzania 1.7 Evaluating Cost-Effectiveness: Comparing Evaluations of Programs That Affect Learning in Primary Schools 1.8 Evaluating Innovative Programs: The Behavioural Insights Team in the United Kingdom 1.9 Evaluating Program Design Alternatives: Malnourishment and Cognitive Development in Colombia 1.10 The Impact Evaluation Cluster Approach: Strategically Building Evidence to Fill Knowledge Gaps 2.1 Articulating a Theory of Change: From Cement Floors to Happiness in Mexico 2.2 Mechanism Experiments 2.3 A High School Mathematics Reform: Formulating a Results Chains and Evaluation Question 3.1 The Counterfactual Problem: “Miss Unique” and the Cash Transfer Program 4.1 Randomized Assignment as a Valuable Operational Tool 4.2 Randomized Assignment as a Program Allocation Rule: Conditional Cash Transfers and Education in Mexico 4.3 Randomized Assignment of Grants to Improve Employment Prospects for Youth in Northern Uganda 4.4 Randomized Assignment of Water and Sanitation Interventions in Rural Bolivia 4.5 Randomized Assignment of Spring Water Protection to Improve Health in Kenya 4.6 Randomized Assignment of Information about HIV Risks to Curb Teen Pregnancy in Kenya 5.1 Using Instrumental Variables to Evaluate the Impact of Sesame Street on School Readiness 5.2 Using Instrumental Variables to Deal with Noncompliance in a School Voucher Program in Colombia 5.3 Randomized Promotion of Education Infrastructure Investments in Bolivia 6.1 Using Regression Discontinuity Design to Evaluate the Impact of Reducing School Fees on School Enrollment Rates in Colombia 6.2 Social Safety Nets Based on a Poverty Index in Jamaica 6.3 The Effect on School Performance of Grouping Students by Test Scores in Kenya 7.1 Using Difference-in-Differences to Understand the Impact of Electoral Incentives on School Dropout Rates in Brazil 7.2 Using Difference-in-Differences to Study the Effects of Police Deployment on Crime in Argentina 7.3 Testing the Assumption of Equal Trends: Water Privatization and Infant Mortality in Argentina 7.4 Testing the Assumption of Equal Trends: School Construction in Indonesia 8.1 Matched Difference-in-Differences: Rural Roads and Local Market Development in Vietnam 8.2 Matched Difference-in-Differences: Cement Floors, Child Health, and Maternal Happiness in Mexico 8.3 The Synthetic Control Method: The Economic Effects of a Terrorist Conflict in Spain 9.1 Folk Tales of Impact Evaluation: The Hawthorne Effect and the John Henry Effect 9.2 Negative Spillovers Due to General Equilibrium Effects: Job Placement Assistance and Labor Market Outcomes in France 9.3 Working with Spillovers: Deworming, Externalities, and Education in Kenya 9.4 Evaluating Spillover Effects: Conditional Cash Transfers and Spillovers in Mexico 9.5 Attrition in Studies with Long-Term Follow-Up: Early Childhood Development and Migration in Jamaica 9.6 Evaluating Long-Term Effects: Subsidies and Adoption of Insecticide-Treated Bed Nets in Kenya 10.1 Testing Program Intensity for Improving Adherence to Antiretroviral Treatment 10.2 Testing Program Alternatives for Monitoring Corruption in Indonesia 11.1 Cash Transfer Programs and the Minimum Level of Intervention 12.1 Guiding Principles for Engagement between the Policy and Evaluation Teams 12.2 General Outline of an Impact Evaluation Plan 12.3 Examples of Research–Policy Team Models 13.1 Trial Registries for the Social Sciences 14.1 The Policy Impact of an Innovative Preschool Model in Mozambique 14.2 Outreach and Dissemination Tools 14.3 Disseminating Impact Evaluations Effectively 14.4 Disseminating Impact Evaluations Online 14.5 Impact Evaluation Blogs 15.1 Random Sampling Is Not Sufficient for Impact Evaluation 16.1 Constructing a Data Set in the Evaluation of Argentina’s Plan Nacer 16.2 Using Census Data to Reevaluate the PRAF in Honduras 16.3 Designing and Formatting Questionnaires 16.4 Some Pros and Cons of Electronic Data Collection 16.5 Data Collection for the Evaluation of the Atención a Crisis Pilots in Nicaragua 16.6 Guidelines for Data Documentation and Storage Figures 2.1 The Elements of a Results Chain B2.2.1 Identifying a Mechanism Experiment from a Longer Results Chain B2.3.1 A Results Chain for the High School Mathematics Curriculum Reform 2.2 The HISP Results Chain 3.1 The Perfect Clone 3.2 A Valid Comparison Group 3.3 Before-and-After Estimates of a Microfinance Program 4.1 Characteristics of Groups under Randomized Assignment of Treatment 4.2 Random Sampling and Randomized Assignment of Treatment 4.3 Steps in Randomized Assignment to Treatment 4.4 Using a Spreadsheet to Randomize Assignment to Treatment 4.5 Estimating Impact under Randomized Assignment 5.1 Randomized Assignment with Imperfect Compliance 5.2 Estimating the Local Average Treatment Effect under Randomized Assignment with Imperfect Compliance 5.3 Randomized Promotion 5.4 Estimating the Local Average Treatment Effect under Randomized Promotion 6.1 Rice Yield, Smaller Farms versus Larger Farms (Baseline) 6.2 Rice Yield, Smaller Farms versus Larger Farms (Follow-Up) 6.3 Compliance with Assignment 6.4 Manipulation of the Eligibility Index 6.5 HISP: Density of Households, by Baseline Poverty Index 6.6 Participation in HISP, by Baseline Poverty Index 6.7 Poverty Index and Health Expenditures, HISP, Two Years Later 7.1 The Difference-in-Differences Method 7.2 Difference-in-Differences When Outcome Trends Differ 8.1 Exact Matching on Four Characteristics 8.2 Propensity Score Matching and Common Support 8.3 Matching for HISP: Common Support 9.1 A Classic Example of Spillovers: Positive Externalities from Deworming School Children 10.1 Steps in Randomized Assignment of Two Levels of Treatment 10.2 Steps in Randomized Assignment of Two Interventions 10.3 Crossover Design for a Program with Two Interventions 15.1 Using a Sample to Infer Average Characteristics of the Population of Interest 15.2 A Valid Sampling Frame Covers the Entire Population of Interest B15.1.1 Random Sampling among Noncomparable Groups of Participants and Nonparticipants B15.1.2 Randomized Assignment of Program Benefits between a Treatment Group and a Comparison Group 15.3 A Large Sample Is More Likely to Resemble the Population of Interest Tables 3.1 Evaluating HISP: Before-and-After Comparison 3.2 Evaluating HISP: Before-and-After with Regression Analysis 3.3 Evaluating HISP: Enrolled-Nonenrolled Comparison of Means 3.4 Evaluating HISP: Enrolled-Nonenrolled Regression Analysis 4.1 Evaluating HISP: Balance between Treatment and Comparison Villages at Baseline 4.2 Evaluating HISP: Randomized Assignment with Comparison of Means 4.3 Evaluating HISP: Randomized Assignment with Regression Analysis 5.1 Evaluating HISP: Randomized Promotion Comparison of Means 5.2 Evaluating HISP: Randomized Promotion with Regression Analysis 6.1 Evaluating HISP: Regression Discontinuity Design with Regression Analysis 7.1 Calculating the Difference-in-Differences (DD) Method 7.2 Evaluating HISP: Difference-in-Differences Comparison of Means 7.3 Evaluating HISP: Difference-in-Differences with Regression Analysis 8.1 Estimating the Propensity Score Based on Baseline Observed Characteristics 8.2 Evaluating HISP: Matching on Baseline Characteristics and Comparison of Means 8.3 Evaluating HISP: Matching on Baseline Characteristics and Regression Analysis 8.4 Evaluating HISP: Difference-in-Differences Combined with Matching on Baseline Characteristics B10.1.1 Summary of Program Design 11.1 Relationship between a Program’s Operational Rules and Impact Evaluation Methods 11.2 Comparing Impact Evaluation Methods 12.1 Cost of Impact Evaluations of a Selection of World Bank–Supported Projects 12.2 Disaggregated Costs of a Selection of World Bank–Supported Impact Evaluations 12.3 Sample Budget for an Impact Evaluation 13.1 Ensuring Reliable and Credible Information for Policy through Open Science 14.1 Engaging Key Constituencies for Policy Impact: Why, When, and How 15.1 Examples of Clusters 15.2 Evaluating HISP+: Sample Size Required to Detect Various Minimum Detectable Effects, Power = 0.9 15.3 Evaluating HISP+: Sample Size Required to Detect Various Minimum Detectable Effects, Power = 0.8 15.4 Evaluating HISP+: Sample Size Required to Detect Various Minimum Desired Effects (Increase in Hospitalization Rate) 15.5 Evaluating HISP+: Sample Size Required to Detect Various Minimum Detectable Effects (Decrease in Household Health Expenditures) 15.6 Evaluating HISP+: Sample Size Required to Detect a US$2 Minimum Impact for Various Numbers of Clusters