Research and Data Analysis

Econometrics of Development and Policy Evaluation Training Course

Introduction

Econometrics of Development and Policy Evaluation Training Course is designed to empower development professionals, policy analysts, researchers, and decision-makers with advanced skills in econometric modeling, causal inference, and impact evaluation. In today's data-driven world, understanding how to design, estimate, and interpret econometric models is vital for assessing the effectiveness of public policies and development interventions. This hands-on training leverages real-world case studies and development datasets to bridge theory and practice in applied econometrics.

Participants will gain expertise in statistical techniques for program evaluation, including Difference-in-Differences, Instrumental Variables, Regression Discontinuity, and Randomized Controlled Trials. With a focus on evidence-based policymaking, the course integrates tools from Stata, R, and Python to ensure participants are fully equipped to conduct robust evaluations and generate insights that influence policy reform and developmental progress.

Programme Curriculum

Econometrics of Development and Policy Evaluation Training Course

Introduction

Course Objectives

Understand key concepts of applied econometrics in development contexts.
Apply causal inference techniques to real-world development data.
Master difference-in-differences and fixed effects models.
Evaluate policies using randomized control trials (RCTs).
Explore quasi-experimental methods for policy analysis.
Conduct regression discontinuity design (RDD) evaluations.
Use instrumental variables (IV) to handle endogeneity.
Develop policy impact evaluation frameworks.
Analyze development economics data using statistical software.
Use machine learning methods to support econometric evaluations.
Interpret and report empirical research findings.
Design and implement monitoring and evaluation (M&E) plans.
Enhance decision-making through evidence-based policy analysis.

Target Audiences

Policy analysts and government planners
Development economists and researchers
Monitoring & Evaluation specialists
NGO and donor agency staff
Social scientists and data analysts
Graduate students in economics or public policy
International development consultants
Think tanks and research institutions

Course Duration: 10 days

Course Modules

Module 1: Introduction to Development Econometrics

Importance of econometrics in development
Overview of policy evaluation approaches
Key terminologies and concepts
Introduction to causal inference
Software setup: Stata, R, Python
Case Study: Evaluating education interventions in sub-Saharan Africa

Module 2: Data Sources and Management

Types of development data (surveys, admin, experimental)
Data cleaning and wrangling
Handling missing data
Data visualization for diagnostics
Ethics in development data
Case Study: Working with DHS and World Bank datasets

Module 3: Introduction to Causal Inference

Concept of counterfactual
Treatment and control groups
Selection bias
Estimating Average Treatment Effects (ATE)
Limitations of observational studies
Case Study: Evaluating microcredit programs in India

Module 4: Difference-in-Differences (DiD)

DiD estimator fundamentals
Parallel trends assumption
Implementation in Stata/R
Robust standard errors
Interpreting interaction terms
Case Study: Impact of a health policy reform

Module 5: Instrumental Variables (IV)

IV estimation and assumptions
Relevance and exclusion restriction
Two-Stage Least Squares (2SLS)
Weak instruments problem
IV diagnostics and tests
Case Study: Compulsory schooling laws and wages

Module 6: Regression Discontinuity Design (RDD)

Sharp vs. fuzzy RDD
Running variable and cutoff
Bandwidth selection
Visualizing discontinuities
Sensitivity analyses
Case Study: Evaluating school grants by test score cutoff

Module 7: Propensity Score Matching (PSM)

Matching vs. randomization
Estimating propensity scores
Balance checks and common support
Matching algorithms (nearest neighbor, kernel)
Limitations of PSM
Case Study: Impact of vocational training programs

Module 8: Randomized Controlled Trials (RCTs)

Experimental design basics
Random assignment techniques
Sample size and power
Implementation challenges
Ethical considerations in RCTs
Case Study: Kenya deworming experiment

Module 9: Panel Data Analysis

Fixed vs. random effects
Panel vs. pooled OLS
Time-invariant variables
Within and between estimators
Clustered standard errors
Case Study: Poverty dynamics using household panel data

Module 10: Time Series in Development

Stationarity and trends
ARIMA and VAR models
Forecasting development indicators
Seasonality adjustment
Structural breaks
Case Study: GDP forecasting in fragile economies

Module 11: Machine Learning for Policy Evaluation

Supervised learning basics
Feature selection in policy data
Causal trees and forests
Comparing ML vs. traditional models
Overfitting and cross-validation
Case Study: Targeting cash transfers using ML

Module 12: Monitoring and Evaluation Frameworks

Theory of change
Logframes and KPIs
Baseline and endline surveys
Continuous data monitoring
Data for adaptive management
Case Study: M&E system for maternal health program

Module 13: Writing Policy Briefs and Reports

Structuring evaluation reports
Writing for non-technical audiences
Data storytelling techniques
Visualizations for impact
Peer review and feedback loops
Case Study: Turning econometric results into policy briefs

Module 14: Cost-Benefit and Cost-Effectiveness Analysis

Understanding CBA vs. CEA
Monetizing benefits and costs
Discount rates and NPV
Sensitivity analysis
Integrating into evaluation studies
Case Study: Education subsidy program CBA

Module 15: Capstone Project and Peer Review

Select a real development program
Apply appropriate econometric tools
Prepare a report and presentation
Peer feedback and critique
Certificate evaluation and feedback
Case Study: Capstone peer-reviewed by development experts

Training Methodology

Interactive lectures with real-world examples
Hands-on exercises with statistical software
Group work and peer-learning activities
Analysis of real development datasets
Case study presentations and discussions
Final capstone project with expert feedback

Bottom of Form

Register as a group from 3 participants for a Discount

Send us an email: info@fineskilltrainingcenter.org or call +254769199797

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to Fineskill Training Center account, as indicated in the invoice so as to enable us prepare better for you.

Skills & Software Covered

Econometrics policy evaluation development impact analysis

Programme Fee

Duration: 10 Days

Method: Online or Physical

Online Price: $2,000

Physical Price: $3,000

Certification: Accredited Certificate

View Available Dates 📄 Download Course Outline (PDF)

Available Sessions

Location

Month

Year

Oct 19 2026

19 Oct — 30 Oct 2026

💻 Online / Virtual session

Online $2,000