What you'll learn
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Learn the most important and popular tools for program evaluation: Randomization, Instrumental Variable, Difference-in-Difference, Regression Discontinuity Design, and Matching
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Conduct Data analysis with these tools using STATA and R
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Use real world data sets for practical application of all models, such as for the Health Insurance Subsidy Program
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Reproduce some well known work of the most established experts in the field, including of noble laureates to learn best practices
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Read, understand, and evaluate empirical studies on program evaluation
What you'll learn
-
Learn the most important and popular tools for program evaluation: Randomization, Instrumental Variable, Difference-in-Difference, Regression Discontinuity Design, and Matching
-
Conduct Data analysis with these tools using STATA and R
-
Use real world data sets for practical application of all models, such as for the Health Insurance Subsidy Program
-
Reproduce some well known work of the most established experts in the field, including of noble laureates to learn best practices
-
Read, understand, and evaluate empirical studies on program evaluation
What is Impact Evaluation?
Organizations, firms, and government bodies work on different projects, programs and policies that aim to make the lives of people better. As we design and deliver programs across fields such as education, health, poverty, and law, it is critical to then understand how these impact the people we serve.
By using impact evaluation, we can identify what works and what doesn’t, and make the necessary changes to achieve the outcomes we seek. It’s a powerful tool that helps us hold ourselves accountable and continuously improve, so we can better serve the needs of our communities.
With impact evaluation, you can:
- Use evidence-based decision-making
- Make the most of your resources
- Demonstrate the value of your work
- Secure funding for your projects
- Make a real impact.
What is Impact Evaluation?
Organizations, firms, and government bodies work on different projects, programs and policies that aim to make the lives of people better. As we design and deliver programs across fields such as education, health, poverty, and law, it is critical to then understand how these impact the people we serve.
By using impact evaluation, we can identify what works and what doesn’t, and make the necessary changes to achieve the outcomes we seek. It’s a powerful tool that helps us hold ourselves accountable and continuously improve, so we can better serve the needs of our communities.
With impact evaluation, you can:
- Use evidence-based decision-making
- Make the most of your resources
- Demonstrate the value of your work
- Secure funding for your projects
- Make a real impact.
Course Description
The increasing demand for impact evaluation skills across various sectors has led us to design a well-rounded course especially for professionals working in social sciences and policy making. This course will cover important econometric evaluation tools and techniques most in use today, without getting too technical.
This course is designed to help you understand research design and to think clearly with data. You will learn impact evaluation tools by working with real life world applications, and even learn to replicate the results of the most prominent publications like Card and Krueger (1994).
The main software we will be using for the course will be STATA and R. All programs/slides will remain available for each topic after the training.
If you are a beginner in this field and worried you might not be able to enroll – don’t worry! We will happily host extra sessions and make up classes (free of cost!) to catch you up and help build the necessary foundations for you to succeed.
Course Content
Week 1:
Program/Impact Evaluation Overview
- Definition and key concepts
- Purpose and benefits of impact evaluation
- Different types of impact evaluation
- Challenges and Best practices
Week 2:
Difference in Differences Estimators, Instrumental Variable
- Purpose and Use in causal inference
- Assumptions and Limitations
- Data Preparation, Identifying Treatment and Control Groups
- Regression Model and breaking down DiD and IV analysis
- Examples, Applications, Policy Implementations
Demo and assignments using Stata and R
Week 3:
Regression Discontinuity Design, Matching and Randomization
- Purpose and Use in causal inference
- Assumptions and Limitations
- Data Preparation, Identifying Treatment and Control Groups
- Regression Models and breaking down RDD and Matching/Randomization analysis
- Examples, Applications, Policy Implementations
Demo and assignments using Stata and R
Week 4:
Case Studies and Applications
- Real-life examples of impact evaluation studies
- Applications of impact evaluation in different sectors: Health Insurance Subsidy Program and other data
- Practical exercises and group discussions
Trainer
Dr. Zahid Asghar, Professor at Quaid-i-Azam University, is an applied econometrician and statistician with special interests in development economics and making sense of data through Data visualization. He has conducted a large number of trainings on data analytics using Excel, STATA, R and EVIEWS. Dr. Zahid has published on topics such as gender, food security and other socio-economic issues, both in national and international peer reviewed journals.