Course Lecturer, Institute for the Study of International Development, McGill University, Fall 2022 

• INTD 356 - Quantitative Methods for Development  (syllabus)

• Lecture slides: 

INTRODUCTION

1. What is impact evaluation?

2. What is causal inference?

PART I: FUNDAMENTALS OF STATISTICS

3. Describing data

4. Probability and distributions

5. Sample estimation and hypothesis test

6. Simple linear regression

7. Multiple linear regression

8. Regression: categorical data

9. Log, interaction, and fixed effect

10. Log, interaction, and fixed effect (cont.)

PART II: IMPACT EVALUATION METHODS AND CAUSAL INFERENCE

11. Randomized controlled trials

12. Randomized controlled trials: case study  

13. Randomized controlled trials: case study

14. Difference-in-differences method

15. Difference-in-differences method: case study

16. Difference-in-differences method: case study

17. Regression discontinuity

18. Regression discontinuity: case study

19. Instrumental variables

20. Instrumental variable method: case study

21. Matching

22. Matching: case study

23. The importance of a rigorous design

24. Policy implication

Sample assignments: 

• • Sample mid-term test 1

  • Sample mid-term test 2

  • Sample practice questions

  • Impact Evaluation Proposal instruction & requirements