By the end of this course, participants will be able to:

• Understand theories and practices essential to impact evaluation
• Gain insight into evaluation problem: attribution, counterfactual, selection and placement biases
• Deepen understanding of causal inference
• Explain impact evaluation designs: randomized, quasi-experimental and theory-based
• Plan, operationalize and manage an impact evaluation
• Perform advanced data analysis using statistical software, accurately interpret results, and derive meaningful conclusions from empirical evidence.
• Effectively communicate evaluation findings to a diverse range of stakeholders.

Fundamentals of Monitoring, Evaluation, Accountability and Learning (MEAL) 

• Differences between Monitoring and Evaluation 
• Accountability and Learning in Monitoring and Evaluation 
• Logframe 
• Theory of Change 
• Results Framework 
• Indicators 

Introduction to Impact Evaluation 

• Defining impact evaluation 
• Purpose of Impact Evaluation 
• Forms of Impact evaluation 
• Types of Evaluation Questions 
• Evaluation Matrix 
• Internal and External Validity 

Causal Inference and Counterfactuals 

• Causal Inference 
• Critical Causal Inference Assumptions 
• Estimating Counterfactual 
• Two Counterfeit Estimates of the Counterfactual 
• Before – After Comparison 
• With – Without Comparison 
• Treatment Effects (estimated parameters) 

Impact Evaluation Research Designs 

• Experimental Designs 
• Randomized Controlled Trials (RCTs) 
• Quasi-experimental Designs 
• Difference-in-Differences (DiD) 
• Regression Discontinuity Design (RDD) 
• Propensity Score Matching (PSM) 
• Instrumental Variables (IV) 
• Theory-Based Evaluations 

Randomized Controlled Trials (RCTs) 

• Introduction to Randomized Evaluations 
• Strengths and weaknesses of Randomized Evaluations 
• Unit of Randomization 
• Random Sampling vs Random Assignment 
• Balance Checks 
• Impact Calculation 
• Randomization Designs 
• Multiple Treatment (Designs) Arms 
• Spillover effects: importance, types and measurements 

Difference-in-Differences (DiD) 

• Introduction to DiD 
• Application of DiD in Impact Evaluation 
• Assumptions and Robustness 
• Strengths and Limitations 
• Estimating Treatment Effect (ATT)  
• DiD for Repeated Cross-sectional Data 
• DiD for Panel Data  
• Practical Applications and Case Studies 

Regression Discontinuity Design (RDD) 

• Introduction to RDD 
• Application of RDD in Impact Evaluation 
• Strengths and Limitations 
• Assumptions 
• Validating RDD Assumptions 
• Types of RDD 
• Sharp RDD 
• Fuzzy RDD 
• Estimating Treatment Effect (LATE)  
• Practical Applications and Case Studies 

Propensity Score Matching (PSM) 

• Introduction to PSM 
• Key Assumptions of PSM 
• Common Support and Balance Assessment 
• Strengths and Limitations 
• Constructing Propensity Scores 
• Matching Analysis 
• Nearest-Neighbour 
• Stratification 
• Radius  
• Kernel 
• Estimating Treatment Effect (ATT)  
• Doubly Robust Estimation 
• Practical Applications and Case Studies 

Instrumental Variables (IV) 

• Introduction to IV 
• Application of IV in Impact Evaluation 
• Assumptions 
• Strengths and Limitations 
• Identifying Valid Instruments 
• Endogeneity and its implications for causal inference 
• Estimating Treatment Effect (LATE)  
• Practical Applications and Case Studies 

Theory-Based Evaluations 

• Introduction to Theory-Based Evaluation 
• Importance and benefits of Theory-Based Evaluation 
• Contribution Analysis 

Combining Methods 

• Impact Evaluation Designs + Analytical Techniques 
• Difference in Differences + Propensity Score Matching 

Implementing an Impact Evaluation  

• Operationalizing the Impact Evaluation Design  
• Sampling Techniques  
• Statistical Power 
• Hypothesis Testing 
• Sample Size Calculation 
• Sampling Weight 
• Data Collection  
• Data Analysis 
• Impact Evaluation Reports 
• Disseminating Impact Evaluation Findings 

This training course is designed for:

• Monitoring and evaluation specialists
• Independent evaluators
• Researchers
• Project coordinators and managers
• Donor staff involved in appraising projects and programmes
• Policy-makers
• Project staff in non-governmental organizations involved in monitoring and evaluation

This training in Advanced Impact Evaluation Course is delivered by our seasoned trainers who have vast experience as expert professionals in their respective fields of practice. The course employs a mix of methodologies including presentations, group exercises, case studies, and much more. Group work is an essential component of the course. The course is designed to be primarily workshop-based, in which participants can work through tasks and problems that mimic their daily activities. Instructors are there to facilitate the group work, addressing real-world concerns.

At Virgon Africa, we believe in experiential learning. We value active participation in our courses through sharing experiences, lessons, ideas and practices.