IEG’s Summer School on Causal Inference
IEG’s Summer School 2025
We are excited to organize IEG’s Summer School on Causal Inference from May 5 to May 16, 2025. Most social science research is driven by causal questions. However, conducting randomized control trials in these domains is not always feasible due to ethical or practical concerns. As a result, quasi-experimental designs based on observational data are increasingly being used to estimate causal effects.
The Summer School aims to provide participants with conceptual knowledge and the practical skills required for applying such quasi-experimental causal inference methods. The course will include examples using real-world data and hands-on sessions in Stata so that participants can understand and apply these approaches in their research. It will be conducted by IEG’s nationally and internationally reputed faculty.
A globally renowned economist will deliver a Keynote lecture.
Additionally, shortlisted applicants for the Summer School will have the opportunity to present their ongoing research work. Although the presentation is optional, we strongly encourage all participants to take advantage of this opportunity to receive valuable feedback from IEG faculty, external experts, and other attendees at the IEG Summer School. Participants are expected to present research that applies any causal inference technique. Alternatively, they may present their empirical work and discuss potential extensions using causal inference methods. The three most distinguished papers will receive the Best Paper Award.
Details regarding the structure of the Summer School will be shared with those shortlisted.
For any further clarifications, please contact us at learning@iegindia.org
Pre-requisites
- Master's Degree in Economics from a UGC-recognized university
- Knowledge of post-graduation level econometrics
- Basic Understanding of Stata software
Format
- 28 hours of in-person modules with practical sessions and special lectures spread over the first eight working days
- A keynote lecture by a globally recognized economist
- Presentations by participants at the end of Summer School
Course Content
Introduction to Causal Inference I
- Theory of Probability
- Theory of Linear Regression
- Panel Data Regression
- Logit and Probit Models
- Discussion of published research papers and applied exercises using Stata
Introduction to Causal Inference II
- Understanding the concept of Causal Inference
- Potential Outcomes Framework
- Observational Data versus Experimental Data
- Discussion of published research papers and applied exercises using Stata
Directed Acyclic Graphs (DAGs) for Causal Inference and Instrumental Variables
- Rationale for Graph and basic elements of causal graphs
- Causation, Confounding and Selection bias using DAGs
- Collider and Backdoor Criterion, Collider Bias
- DAG with a simple regression
- Instrumental Variables
- The problem of endogeneity in the regression model
- Endogeneity test
- Two-Stage Least Squares Regression
- Discussion of published research papers and applied exercises using Stata
Propensity score matching (PSM)
- Introduction to Propensity Score Matching (PSM)
- Conducting PSM
- Matching Methods: Strengths and Limitations of PSM
- Discussion of published research papers and applied exercises using Stata
Regression Discontinuity Design (RDD)
- Introduction to RDD, Fuzzy vs Sharp RDD
- Specification Tests and Sensitivity Analysis
- Limitations of RDD
- Discussion of published research papers and applied exercises using Stata
Difference in Differences (DiD)
- Basics of DiD
- 2x2 DiD set up
- Assumptions for DiD
- Discussion of published research papers and applied exercises using Stata
Pedagogy
The workshop will adopt a highly interactive pedagogy and use technology to create an engaging learning experience. Activities will include expert-led lectures, in-depth discussions of published research papers, and hands-on practice with Stata software to develop a practical understanding of causal inference techniques.
Course Outcomes
On successful completion of this course, students will be able to:
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- Understand the principles of causal inference
- Use causal inference techniques to evaluate the effect of various programmes on outcomes.
- Model causal relations in an econometric/statistical framework
- Acquire software and technical skills to pursue research on causal inference
Target audience
Research scholars and early career economists in academia, corporate, government, and non-profit organizations.
Certification
The Institute of Economic Growth shall issue a Certificate of Participation (CoP) upon fulfilment of 100 percent attendance criteria and other parameters. Those who present their ongoing research work will get a separate certificate of presentation.
Chair of The Summer School
Prof. Sabyasachi Kar (Director, IEG)
Chair of Course Committee
Prof. Indrani Chakraborty
Course Committee
Dr. Archana Dang
Dr. Gautam Kumar Das
Dr. M. Rahul
Dr. Parma Chakravartti
Dr. Sandhya Garg
Dr. Srishti Gupta
Dr. Sukhdeep Singh
Instructors
Dr. Archana Dang
Dr. Gautam Kumar Das
Dr. M. Rahul
Dr. Oindrila De
Dr. Parma Chakravartti
Dr. Sandhya Garg
Prof. Saudamini Das
Dr. Srishti Gupta
Dr. Sunaina Dhingra
Dr. Sukhdeep Singh
Prof. Vikram Dayal
Fee Structure
The enrolment fee for the course is Rs. 2000, and the tuition fee is Rs. 6000 per head, including lunch on working days.
For those who stay on campus during the course, additional accommodation charges, including food, are Rs. 5600 per head.
Shortlisted applicants are initially required to pay the compulsory and non-refundable enrolment fee of Rs. 2000. The remaining amount must be paid closer to the summer school's starting date.
Registration and Selection
Due to the course's interactive nature, final enrolment will be limited to 20 seats. Registration concludes on 30 March 2025. Please use a Gmail account to fill out the application form. To Register, Click here.
Participants will be selected based on their academic eligibility and motivation to complete the program. The 20 registered applicants who match the minimum eligibility criteria will be selected based on a 200-word Statement of Purpose (SOP). The shortlisted candidates will be notified by email shortly afterwards. To secure their seat, participants must pay an enrolment fee of Rs. 2000 within 3 days of receiving the email. Otherwise, offers will be extended to individuals on the waiting list.
Accommodation
Participants who seek accommodation will be given boarding and lodging on the IEG campus against the payment of accommodation charges. Please note that accommodation will be subject to availability and will be given on a first-come, first-serve basis.