Quantitative Methods for Development Economics
Zahid Asghar, School of Economics, QAU Islamabad
Course Overview
This course is designed to introduce students to impact evaluation. Can we improve vaccination in Pakistan with small nudges? Is pollution harmful in China? Can we improve aid distribution mechanism among flood victims? Does it really matter to have an extra year of schooling for income years later? If yes, what is the magnitude of these effects? How much should you trust these results? The answer to these questions determines public policy and inform debates about development issues.
Learning Outcomes
By the end of this course, students will be familiar with tools to be applied for program evaluation and better understand research design. This includes the understanding of the statistical tools used, the ability to replicate research papers or perform their own analysis using R and interpret the results.
Instructional Method
Structure – The course has 3 main parts: revision of application of some basic techniques of regression analysis, statistical inference to introduce students to the fundamentals of statistics and causal inference. In the third part, we will study different research designs and learn about how they work and when one should use them.
Books
I will be providing students with several sets of practice questions during the course. For those students who would like to refer to a textbook during this course you have several possibilities:
Course contents
| Week | Title | Topics covered | Essential reading |
|---|---|---|---|
| 1 | Introduction to Quantitative Methods for Development Economics (and R) | Introduction to quantitative methods; description, prediction and causality; research design; R basics | Chapter 1, “Introduction”, in Imai |
| 2 | Simple, Multiple and Nonlinear Regression Models | Concepts and application to earning and smoking data, hypothesis testing and confidence interval , sampling distribution of OLS estimators | Ch4-7 “Introduction to Econometrics” Stock and Watson available here |
| Simple, Multiple and Nonlinear Regression Models | Concepts and application to earning and smoking data, hypothesis testing and confidence interval , sampling distribution of OLS estimators | Ch8 “Introduction to Econometrics” Stock and Watson here | |
| 3 | Internal and External validity | Threats to internal and external validity of regression models | Ch9 “Introduction to Econometrics” Stock and Watson |
| 4 | Regression IV (Panel data) | Data with repeated observations of the same units over time; fixed-effect models | Chapter 10, “Regression with Panel Data”, in Stock and Watson,here |
| 5 | Logit and Probit Models | Concepts and application,Non-standard standard errors; logistic regression | Chapter 11, “Introduction to Econometrics” Stock and Watson,here |
| 6 | Continued | continued | “Introduction to Econometrics” Stock and Watson |
| 7 | Regression IV (Panel data) | Data with repeated observations of the same units over time; fixed-effect models | Chapter 10, “Regression with Panel Data”, in Stock and Watson, available |
| 8 | Instrumental Variable | Does cigarette tax reduce demand for smoking? | Chapter 12, “Regression with Panel Data”, in Stock and Watson, available |
| 9 | RCTs and Difference in differences estimators | Experiments, Quasi-experiments | Ch 13 Stock and Watson and Ch 18 The Effect |
| 10 | Continued | continued | continued |
| 11 | Regression Discontinuity Designs | Regression Discontinuity Designs | ch20 from The Effect |
| 12 | continued | continued | ch20 from The Effect |
| 13 | Projects evaluations | ||
| 14 | Projects evaluations | ||
| 15 | Revision |