First IEG Winter School on Causal Inference
November 25 – December 4, 2024
We are excited to organise IEG’s first Winter School on Causal Inference from November 25 to December 4, 2024. Most social science research is driven by causal questions. However, conducting randomised 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 is increasingly being used to estimate causal effects.
The goal of the Winter School is to provide participants with both the conceptual knowledge and the practical skills required for the application of causal inference methods. The course will include examples using real-world data with hands-on sessions in Stata, so that participants can understand and apply these approaches in their own research. The course will be conducted by IEG’s nationally and internationally reputed faculty.
Prof. Rohini Somanathan, a globally renowned economist, will make a Keynote presentation.
Additionally, shortlisted applicants for the Winter School will have the opportunity to attend a special workshop at IEG on “Towards a Resilient Economy” to be held on the 6th and 7th of December, 2024. Extended Boarding and lodging will be provided on campus for those candidates attending the Resilient Economy workshop, free of cost, from the 5th to the 8th of December, 2024. The Resilient Economy workshop will include a poster session for the Winter School participants where the select few will be able to present their ongoing research findings. Details regarding the workshop will be shared with those shortlisted.
Contact:
For any further clarifications please contact us at iegws@iegindia.org
Pre-requisites
- Master's Degree in Economics from a UGC recognized university.
- Participants need to have knowledge of post-graduation level econometrics.
- Stata software will be used in the practical session, so some basic understanding of the software is desirable.
Format
- 32-hours in-person modules with practical sessions spread over 8 working days.
- Four lectures each day (three class discussions + one practical session using Stata software).
Course Content
Introduction to Causal Inference I
- Theory of Probability
- Theory of Linear 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 basics 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 pedagogy will be highly interactive with an effective use of technology.
- Lectures
- Published paper discussions.
- Hands on with Stata software
Course Outcomes
On successful completion of this course, students will be able to:
- 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, early career economists in academia, corporate sector, government sector, and non-profit organisations.
Certification
Institute of Economic Growth shall issue a Certificate of Participation (CoP) on fulfilment of 100 percent attendance criteria, and other parameters.
Chair of The Winter School
Prof. Chetan Ghate (Director, IEG)
Chair of Course Committee
Prof. Sabyasachi Kar
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
Enrolment fees for the course is Rs. 1000. Tuition fees is Rs. 5000 per head and includes lunch. For those who want to stay on campus during the course, additional accommodation charges (including bed, breakfast and dinner) is Rs. 4000 per head. A limited number of the selected candidates will get full waivers on tuition fees and accommodation charges on a first-come-first-serve basis.
Shortlisted applicants are initially required to pay the compulsory and non-refundable enrolment fee of Rs.1000. The remaining amount will need to be paid closer to the date of the Winter School.
Registration and Selection
Due to the course's interactive nature, final enrolment will be limited to 20 seats only. Registration concludes on September 15, 2024. To fill out the application form use your gmail account or create a new gmail account. To Register Click here.
Participants would be assessed on their academic experience and motivation to complete the program, as demonstrated in the application form. The first 20 registered candidates who match the eligibility criteria and the assessments will be shortlisted. These candidates will be notified by email shortly afterwards. To secure their seat, participants must pay an enrolment fee of Rs. 1000 within 5 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. Those who wish to attend the Resilient Economy workshop will receive free boarding and lodging during the duration of the workshop.
