Bayesian analysis of individual decisions in health and labour economics
Grant number: FT170100124 | Funding period: 2018 - 2023
This project aims to exploit emerging Bayesian Markov chain Monte Carlo methods to develop new approaches to modelling economic decision making. These methods will generate insights into two current and important policy debates. This includes (i) marijuana, alcohol and tobacco use and legalisation of marijuana use; and (ii) parental leave policies, maternity leave decisions and mothers' labour market dynamics. Although policies play an important role in observed health and labour market behaviours, their exact effects on individuals' decisions and outcomes are often difficult to quantify due to the complex nature of the decision process. Outcomes from the project will include new evidence of..View full description
Related publications (1)
Food Price Elasticities for Policy Interventions: Estimates from a Virtual Supermarket Experiment in a Multistage Demand Analysis with (Expert) Prior Information
Liana Jacobi, Nhung Nghiem, Andres Ramirez-Hassan, Tony Blakely
Food price elasticities (PEs) are essential for evaluating the impacts of food pricing interventions to improve dietary and health..