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Mandatory vaccination for Covid-19 has received intense political and ethical debates, while economic literature is rare. In this study, we examine the effects of the announcements of vaccine mandates (VMs) for workers working in three sectors including health, education, and state governments on the uptake of first-dose and second-dose vaccination across 50 states in the United States of America.

We show that the VM announcements have heterogeneous effects; hence standard two-way fixed effects difference-in-differences estimators are not robust. We present evidences for the heterogeneous treatment effects using recently developed estimators of de Chaisemartin and D’Haultfœuille (2020b,c,a) in single and two-treatment settings.

In the setting of a staggered single treatment when treating all VM announcements equal, our results show that the VM announcement cause an increase of 20.6% first-dose uptake for the period from 1 July to 31 August 2021. In two-treatment settings, our results suggest that the announcement of VM for workers in health or state government sectors are the main drivers of increased first-dose vaccination. Also the VM announcement does not have significant effects on second-dose uptake.

Our results are robust with respect to the choice of differing outcome variables as well as time period after being controlled for state-level covariates of Covid-19 death, unemployment and cumulative two-dose vaccination. 

About the presenter

Dr Son Nghiem is an associate professor of health economic at the Department of Health Economics, Wellbeing and Society, Australian National University. He has more than 10years experience in applied econometrics and health economics research.

Dr Nghiem has developed a strong track record with over 100 peer-reviewed papers published in high-impact journals in health economics, public health and health services research. He has been awarded over $8m in research grants and fellowship. One of his most impactful studies is the development of the Classification of Hospital Acquired Diagnoses (CHATx) to improve the safety of patients.

The CHADx is now integrated into the Hospital-Acquired Complications by the Australian Commission on Safety and Quality in Health Care. Dr Nghiem has also developed a predictive model to estimate a risk score for trauma admissions using a machine learning approach. Recently, he led a study to predict the risk of frailty for older patients using the longitudinal study of cardiovascular admissions in Queensland.

He is conducting various research projects on cardiovascular disease, including the development of a disease progression model for heart attack using a multi-state hidden Markov model and estimation of a hospital frailty risk score and assesses its ability to predict adverse health outcomes in Australia. Currently, Dr Nghiem is leading the economic evaluation of AusPathogen – a national research project on the application of whole genome sequencing in infectious disease surveillance.