Taking account of uncertainty in modelling individual health and health behaviours
Speaker: Audrey Laporte
Date: February 16th
Time: 11 AM – 1 PM
Location: HSB 100 (155 College Street)
It is well known that uncertainty is a key consideration in theoretical health economics analysis. The literature has shown that uncertainty is a multifaceted concept, with the individual’s optimal response depending on the formal nature of the uncertainty and the time horizon involved. A model which considers the case of a serious illness, i.e., one that permanently reduces the individual’s stock of health is introduced and is used to illustrate the effect of the introduction of a vaccine. Uncertainty with regards to the cumulative effect on health capital of on-going health behaviours will also be explored. After setting out the models for the deterministic and stochastic (i.e. uncertainty) cases, diagrams are used to illustrate how the introduction of uncertainty may be expected to alter the optimal lifetime trajectory for the individual predicted by the model.
Prof. Audrey Laporte is an Associate Professor of Health Economics and the Director of the Canadian Centre for Health Economics in the Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health, University of Toronto and an Adjunct Senior Scientist at the Institute for Clinical Evaluative Sciences. She currently serves as Treasurer on the Board of the International Health Economics Association and on the Scientific Board of the American Health Econometrics Workshop Group.
Prof. Laporte has published extensively in the health economics and health services research literatures. Part of her program of research focusses on applications of theoretical and empirical economic dynamics to health-related questions. Her work has also considered the determinants of heath at the individual level and in particular drivers of health behaviours. Her work in this area aims to explore the empirical implications of dynamic theory not just in terms of informing the equations to be estimated but the implications for the properties of the statistical methods themselves.