Impact Evaluation Techniques: RCTs, Quasi-Experimental Methods & CBA Course

Introduction

Impact evaluation is essential for determining whether programs and policies achieve their intended outcomes and deliver value for money. This course provides participants with advanced knowledge and practical skills in rigorous evaluation techniques, including Randomized Controlled Trials (RCTs), quasi-experimental methods, and Cost-Benefit Analysis (CBA).

Participants will explore how RCTs are designed and implemented to establish causal relationships between interventions and outcomes. The course highlights when and how to use randomization effectively, ensuring credible and unbiased results that support evidence-based decision-making.

Quasi-experimental methods are critical where randomization is not feasible. Participants will learn techniques such as difference-in-differences, regression discontinuity, propensity score matching, and instrumental variables to estimate impact using observational data.

The course also focuses on Cost-Benefit Analysis, enabling participants to assess whether the benefits of a program outweigh its costs. Participants will learn how to quantify benefits, discount future values, and interpret economic efficiency for strategic planning and resource allocation.

Emerging trends such as big data integration, machine learning for causal inference, and real-time evaluation systems are incorporated. Participants will understand how modern tools enhance impact evaluation accuracy, scalability, and responsiveness in dynamic environments.

By the end of the course, participants will be able to design and implement rigorous impact evaluations, apply advanced analytical techniques, and generate actionable insights that improve program effectiveness, accountability, and long-term sustainability.

Who Should Attend

• Monitoring and Evaluation Officers and Managers
• Impact Evaluation Specialists
• Data Analysts and Statisticians
• Program and Project Managers
• Policy Analysts and Advisors
• NGO and Development Practitioners
• Donor-Funded Project Staff
• Researchers and Academicians
• Government and Public Sector Practitioners
• Economists and Financial Analysts
• Internal Audit and Compliance Officers
• Consultants in Development and Evaluation

Duration

10 Days

Course Objectives

• Develop a comprehensive understanding of impact evaluation principles and methodologies, including RCTs and quasi-experimental approaches.
• Equip participants with skills to design and implement Randomized Controlled Trials that generate credible causal evidence.
• Strengthen participants’ ability to apply quasi-experimental methods such as difference-in-differences and propensity score matching effectively.
• Enhance knowledge of Cost-Benefit Analysis techniques to assess economic efficiency and inform resource allocation decisions.
• Build capacity to identify appropriate evaluation designs based on program context, data availability, and ethical considerations.
• Provide participants with practical skills to analyze data, interpret results, and draw valid conclusions from impact evaluations.
• Improve competencies in handling biases, confounding variables, and threats to validity in evaluation studies.
• Enable participants to integrate advanced tools, including statistical software and machine learning techniques, in impact analysis.
• Strengthen skills in communicating complex evaluation findings clearly to policymakers, donors, and stakeholders.
• Empower participants to design monitoring systems that complement impact evaluation frameworks for continuous learning.
• Foster critical thinking in assessing evaluation quality, reliability, and applicability of findings to decision-making processes.
• Enhance participants’ ability to generate evidence-based recommendations that improve program design, implementation, and sustainability.

Comprehensive Course Outline

Module 1: Introduction to Impact Evaluation

• Concepts and importance of impact evaluation
• Difference between monitoring and evaluation
• Causality and attribution challenges
• Overview of evaluation designs

Module 2: Theory of Change & Evaluation Design

• Linking programs to outcomes
• Designing evaluation frameworks
• Identifying indicators and outcomes
• Aligning evaluation with objectives

Module 3: Randomized Controlled Trials (RCTs)

• Principles of randomization
• Designing RCTs for programs
• Sampling and assignment methods
• Ethical considerations in RCTs

Module 4: Implementing RCTs

• Field implementation strategies
• Data collection and management
• Monitoring compliance and attrition
• Ensuring validity and reliability

Module 5: Quasi-Experimental Methods Overview

• Need for quasi-experimental designs
• Strengths and limitations
• Selection of appropriate methods
• Addressing bias and confounding

Module 6: Difference-in-Differences (DiD)

• Concept and assumptions
• Model estimation techniques
• Application in program evaluation
• Interpreting DiD results

Module 7: Propensity Score Matching (PSM)

• Matching techniques and algorithms
• Balancing covariates
• Assessing match quality
• Application in impact evaluation

Module 8: Regression Discontinuity Design (RDD)

• Principles of cutoff-based evaluation
• Designing RDD studies
• Estimation and interpretation
• Validity checks

Module 9: Instrumental Variables (IV)

• Addressing endogeneity issues
• Identifying valid instruments
• Estimation techniques
• Interpreting IV results

Module 10: Cost-Benefit Analysis (CBA)

• Principles of economic evaluation
• Identifying costs and benefits
• Discounting and net present value
• Decision-making using CBA

Module 11: Data Management & Analysis

• Data collection strategies
• Cleaning and preparation
• Using statistical software
• Ensuring data quality

Module 12: Advanced Analytical Tools

• Regression modeling for evaluation
• Sensitivity analysis
• Robustness checks
• Handling complex datasets

Module 13: Emerging Trends in Impact Evaluation

• Big data and real-time evaluation
• Machine learning for causal inference
• Digital monitoring systems
• Innovative evaluation approaches

Module 14: Reporting & Communication

• Writing impact evaluation reports
• Visualizing results
• Communicating findings to stakeholders
• Policy briefs and presentations

Module 15: Case Studies & Best Practices

• Real-world evaluation examples
• Lessons learned from global programs
• Group discussions and peer learning
• Benchmarking practices

Module 16: Practical Exercises & Action Planning

• Designing an impact evaluation study
• Applying RCT and quasi-experimental methods
• Conducting cost-benefit analysis
• Developing implementation plans

Training Approach

The instructor led trainings are delivered using a blended learning approach and comprises of presentations, guided sessions of practical exercise, web-based tutorials and group work. Our facilitators are seasoned industry experts with years of experience, working as professional and trainers in these fields.

All facilitation and course materials will be offered in English. The participants should be reasonably proficient in English.

Certification

Upon successful completion of the training, participants will be awarded a certificate of completion by Steady Development Center.

Training Venue

The training will be held online. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, tutorials and all required training manuals. Any other personal expenses are catered by the participant.
For registration and further enquiries, contact us on:

• Tel: +254 701 180 097
• Email: training@steadytrainingcenter.com

Tailor-Made Option

This course can be customized to suit the specific needs of your organization and be delivered on-line to any convenient location.

Terms Of Payment

Upon agreement by both parties’ payment should be made to Steady Development Center’s official account at least 3 working days before training begins to facilitate adequate preparation.

Our Upcoming Training Schedule