Advanced Econometric Methods for Impact Evaluation of Social Protection Training Course

INTRODUCTION

Advanced Econometric Methods for Impact Evaluation of Social Protection Training Course provides a rigorous exploration of sophisticated econometric methods for accurately evaluating the causal impact of social protection programs. Recognizing that robust evidence is critical for effective policy design, resource allocation, and accountability, this program equips participants with the analytical tools to go beyond simple comparisons and uncover true program effects. Participants will delve into theoretical underpinnings, practical application, and critical interpretation of results from cutting-edge evaluation techniques. This course is ideal for experienced researchers, M&E specialists, data scientists, policy analysts, and academics seeking to deepen their quantitative skills for rigorous impact assessment in the social protection sector.

DURATION

5 days

TARGET AUDIENCE

This course is specifically designed for professionals with a strong foundational understanding of econometrics and statistics, working in:

  • Research institutions and universities focusing on development economics and social policy.
  • Monitoring and evaluation departments of government ministries and international organizations.
  • Data science teams in NGOs and development agencies.
  • Policy analysis units requiring rigorous evidence for decision-making.
  • Ph.D. students and post-doctoral researchers in economics, public policy, and related fields.

OBJECTIVES

Upon completion of this course, participants will be able to:

  • Critically assess the theoretical underpinnings and assumptions of advanced impact evaluation methods.
  • Apply a range of econometric techniques to estimate causal impacts of social protection programs.
  • Understand the strengths and limitations of different evaluation designs for various program contexts.
  • Interpret complex econometric results and draw robust policy conclusions.
  • Design and implement rigorous impact evaluations using appropriate data and software.

MODULES

Module 1: Causal Inference and the Evaluation Problem

  • Review of fundamental concepts in causal inference and the counterfactual framework.
  • Understanding sources of bias in impact evaluation (e.g., selection bias, omitted variable bias).
  • Discussion of the ideal randomized controlled trial (RCT) and its practical challenges.
  • Introduction to the different types of evaluation questions (attribution vs. contribution).
  • Ethical considerations in designing and implementing impact evaluations.

Module 2: Randomized Controlled Trials (RCTs) in Practice

  • Deep dive into the design and implementation of RCTs for social protection programs.
  • Discuss issues of randomization unit, sample size calculation, and power analysis.
  • Explore strategies for managing attrition and non-compliance in RCTs.
  • Understand methods for analyzing RCT data, including intention-to-treat and treatment-on-treated effects.
  • Case studies and practical examples of successful RCTs in social protection.

Module 3: Regression Discontinuity Design (RDD)

  • Theoretical foundations of Regression Discontinuity Design for evaluating programs with eligibility thresholds.
  • Discuss sharp vs. fuzzy RDD and appropriate estimation strategies.
  • Explore bandwidth selection, functional form, and manipulation testing.
  • Practical application of RDD using real-world social protection program data.
  • Limitations and common pitfalls in applying RDD.

Module 4: Difference-in-Differences (DiD) and Panel Data Methods

  • Understanding the assumptions and application of Difference-in-Differences for staggered program rollout.
  • Extending DiD to multiple time periods and groups (fixed effects models).
  • Discuss event study designs and common trends assumption testing.
  • Explore the use of panel data for controlling for unobserved heterogeneity.
  • Practical exercises using panel data from social protection interventions.

Module 5: Instrumental Variables (IV) and Quasi-Experimental Approaches

  • Theory and application of Instrumental Variables for addressing endogeneity bias.
  • Discuss conditions for a valid instrument and tests for weak instruments.
  • Explore other quasi-experimental methods: synthetic control methods and propensity score matching (PSM) revisited.
  • Understanding the strengths and limitations of IV and other quasi-experimental designs.
  • Case studies illustrating the use of IV in social protection evaluation.

Module 6: Advanced Topics in Treatment Effects Estimation

  • Introduction to heterogeneous treatment effects and subgroup analysis.
  • Discuss quantile regression for understanding impacts across the distribution.
  • Explore methods for analyzing spillover effects and general equilibrium impacts.
  • Understanding mediation analysis and pathways of impact.
  • Introduction to machine learning techniques for prediction and causal inference.

Module 7: Data Management and Software Applications

  • Best practices for managing complex administrative and survey data for impact evaluation.
  • Techniques for data cleaning, merging, and variable construction.
  • Hands-on application of econometric methods using statistical software (e.g., Stata, R, Python).
  • Discuss programming best practices for reproducibility and transparency.
  • Troubleshooting common data and software challenges in impact evaluation.

Module 8: Communicating and Utilizing Impact Evaluation Findings

  • Strategies for effectively communicating complex econometric results to non-technical audiences.
  • Discuss the importance of robust sensitivity analysis and reporting limitations.
  • Explore pathways for translating research findings into actionable policy recommendations.
  • Understand the ethical responsibilities of evaluators in disseminating results.
  • Case studies on how rigorous impact evaluations have influenced social protection policy.

CERTIFICATION

  • Upon successful completion of this training, participants will be issued with Macskills Training and Development Institute Certificate

TRAINING VENUE

  • Training will be held at Macskills Training Centre. We also tailor make the training upon request at different locations across the world.

AIRPORT PICK UP AND ACCOMMODATION

  • Airport pick up and accommodation is arranged upon request

TERMS OF PAYMENT

Payment should be made to Macskills Development Institute bank account before the start of the training and receipts sent to info@macskillsdevelopment.com

 

Advanced Econometric Methods For Impact Evaluation Of Social Protection Training Course in Kenya
Dates Fees Location Action
07/07/2025 - 11/07/2025 $4,000 Johannesburg
Physical Class Online Class
14/07/2025 - 18/07/2025 $1,500 Mombasa
Physical Class Online Class
21/07/2025 - 25/07/2025 $1,250 Nairobi
Physical Class Online Class
04/08/2025 - 08/08/2025 $2,900 Kigali
Physical Class Online Class
11/08/2025 - 15/08/2025 $1,500 Mombasa
Physical Class Online Class
25/08/2025 - 29/08/2025 $1,250 Nairobi
Physical Class Online Class
01/09/2025 - 05/09/2025 $2,900 Kigali
Physical Class Online Class
15/09/2025 - 19/09/2025 $1,500 Mombasa
Physical Class Online Class
22/09/2025 - 26/09/2025 $1,250 Nairobi
Physical Class Online Class
06/10/2025 - 10/10/2025 $4,000 Johannesburg
Physical Class Online Class
13/10/2025 - 17/10/2025 $4,950 Instanbul
Physical Class Online Class
27/10/2025 - 31/10/2025 $1,250 Nairobi
Physical Class Online Class
03/11/2025 - 07/11/2025 $4,950 Dubai
Physical Class Online Class
17/11/2025 - 21/11/2025 $1,500 Mombasa
Physical Class Online Class
24/11/2025 - 28/11/2025 $1,250 Nairobi
Physical Class Online Class
01/12/2025 - 05/12/2025 $4,000 Johannesburg
Physical Class Online Class
08/12/2025 - 12/12/2025 $1,250 Nairobi
Physical Class Online Class