Causal inference in Econometrics and Health Sciences

Join us for a lunchtime lecture and hear from Associate Professor Margarita Moreno-Betancur and Dr Akanksha Negi on the topic of causal inference. Each speaker will present for 20 minutes, followed by a 20 minute Q&A session at the end. For those attending in person, a light lunch will be provided after the Q&A.

Please note that in-person registration closes on midnight of Wed 15 Feb but registration for online only is still available.

Dr Akanksha Negi's abstract:

The seminar aims to provide its audience with a brief introduction to causal inference in econometrics and the methods available for studying problems therein. We will begin with the Neyman-Rubin causal model which underpins the theoretical framework for studying causality. This will be followed by a short discussion on randomized experiments which forms an experimental benchmark for observational studies. In such settings, the researcher has no control over who receives the treatment and where the assumptions of selection on observables/unobservables play a central role in the identification of causal effects. Finally, we will discuss difference-in-differences, which is the workhorse empirical strategy in econometrics for estimating causal effects with observational data. This is also a current research interest of mine.

Biography

Dr. Akanksha Negi is a Lecturer in the Department of Econometrics and Business Statistics in the Monash Business School. She completed her PhD in Economics at Michigan State University under Professor Jeffrey M. Wooldridge. Her research has focused on methods for robust and efficient estimation of treatment effects in both experimental and observational data settings. Prior to joining the PhD program, Akanksha worked for two years as a Senior Research Assistant at the International Food Policy Research Institute. She holds a Bachelor’s and Master’s in Statistics from Delhi University in India.

Assoc. Prof. Moreno-Betancur's abstract:

The ultimate goal of medical and health research is to improve patient outcomes and population health. As a result, the overwhelming majority of clinical and public health research studies ask “causal” questions, concerning the effect of treatments, policies, behaviours and other exposures on health outcomes. In many cases, especially in the current era of data deluge, these studies rely on observational (non-experimental) data to address causal questions. Unfortunately, for a long time the statistics discipline largely shunned the possibility of causal inference beyond randomised trials, and instead focused on the development of tools such as regression models without clarity regarding their usefulness and limitations for addressing the causal questions that substantive areas continued to ask. In recent decades, however, the discipline has seen the rise of a new area focused on determining the settings and approaches that could allow causal inference from observational data. In this talk, I will first provide an overview of some of the fundamental contributions of this area of statistics to enable and improve the study of causality in health research. I will then provide an overview of the methodological research my team is conducting to further advance this area.

Biography

Assoc. Prof Margarita Moreno-Betancur is co-Director of the Clinical Epidemiology and Biostatistics Unit (CEBU) at the Murdoch Children’s Research Institute (MCRI) and the University of Melbourne. She leads an integrated program of methodological and collaborative research, supported by an NHMRC Investigator Grant (2022-26) and previously an ARC DECRA (2019-22). Her methodological areas of interest are causal inference, missing data and survival analysis, and she has contributed to epidemiological research projects in a range of areas, particularly in life course and social epidemiology. She is part of the steering groups of the Victorian Centre for Biostatistics (ViCBiostat), the MCRI's LifeCourse Initiative and the Master of Biostatistics at the University of Melbourne.

Schedule

• 10:30-11:00, Registration, set up and light refreshments
• 11:00-11:10 Introductions
• 11:10-11:30, Akanksha
• 11:30-11:50, Margarita
• 11:50-12:10, Questions and discussion
• 12:15-12:45, Lunch