Econometrics and Causal Inference

Seminar speaker Dr. Shreshti Rawat is an accomplished PhD scholar in the field of development economics. Her teaching experience at prestigious institutions and her notable L. K. Deshpande Young Labour Economist Award is a testament to her expertise.

The seminar focused on the complexities of extracting causal relationships from observational data, a crucial aspect of empirical economics research. Dr Rawat delved into the fundamental principles of econometrics and causal inference, highlighting researchers' significant challenges when establishing causal linkages between variables in non-experimental (observational) studies.

The seminar explored fundamental issues that can lead to misleading results if not addressed, which included endogeneity, selection bias, skewed findings, omitted variables, and measurement errors, among others. Dr Rawat emphasised that addressing these challenges through rigorous statistical methods is crucial for deriving reliable causal insights from empirical data. This, in turn, informs evidence-based policy decisions and enhances our understanding of economic phenomena. 

Dr Rawat highlighted the ongoing advancements in methodology and interdisciplinary collaboration aimed at improving the robustness and credibility of causal inference in economic research, ultimately contributing to developing sound economic theories and effective policy interventions.

This was followed by an interactive Q&A session, where students had the golden opportunity to engage with the speaker and gain further insights. Hosts Agrani Jain and Chahat Gupta thanked Professor Devangana Jha for her efforts that made the event possible. The event concluded on a high note, leaving all participants with a wealth of knowledge and meaningful experiences to take with them.