Graduate Research



David Wan, MABE (2018)


What Are Socioeconomic Determinants of Cannabis Use Behaviour and How Does Medical Marijuana Legalization Impact its Consumption?

Abstract

As recreational cannabis consumption is legalized in Canada, policymakers are concerned about how the legal regime change may impact marijuana use behaviour and how people of different socioeconomic status (SES) may change their behaviour. This paper examines how marijuana use behaviour (defined as participation and use intensity) differ across socioeconomic status. Suitable Canadian data was unavailable, so the paper uses US data from the National Survey on Drug Use and Health (NSDUH). Identification comes from variation across jurisdictions with medical marijuana legalization (MML) and jurisdictions without MML. MML dimension allows the examination of the difference in user behaviour after legalization. The paper uses a linear probability model (LPM) and a finite mixture model (FMM) to estimate the marginal effects of MML, income, and education on the probability of marijuana use and the frequency of marijuana use (conditional on any use). The results suggest individuals living in a jurisdiction with MML are 50% more likely to use marijuana and use 3% to 6% more marijuana when compared to individuals living in a jurisdiction without MML. A negative gradient between income and marijuana participation was found, with the lowest income group being 50% more likely to use marijuana relative to the highest income group. The association between income and marijuana use intensity depended on the type of user and the income bracket. Lower income individuals used 3% to 17% more than the highest income individuals. There was no clear education gradient with respect to marijuana use participation, with college graduates reducing the likelihood of use. However, a negative gradient between education and marijuana use intensity was found, with higher levels of education being associated with lower levels of marijuana use.

Yingying Xiao, MABE (2017)

Is Prescription Drug Insurance Associated with Decreased Rates of Obesity?

Abstract

An individual’s health-related behaviour may change in response to ex ante moral hazard of health insurance. This paper looks at whether there is ex ante moral in Canada resulting from prescription drug insurance. Data come from the 2013-2014 Canadian Community Health Survey. The association between having prescription drug insurance and body mass (as a proxy for health), being obese, and two behaviours affecting body mass (physical activity and health food choices) is estimated using four linear models. The results suggest having prescription drug insurance is associated with a higher BMI and a higher probability of being obese. However, there is no evidence to suggest having prescription drug insurance is associated with decreased physical activity or decreased probability of making healthy food choices.

Tannaz Mahootchi, PhD (2015)

Modelling and Analysis of Value-Based Healthcare Delivery

Abstract

Healthcare reforms are emerging in order to control the increasing healthcare expenditures and to improve the health outcomes. In the context of the “Value-based Healthcare Delivery” reform, Michael Porter defines value as a patient’s health outcome per dollar spent. Porter’s proposal is comprised of organizing care around a medical condition (or around patient segments for primary care). Specifically, care will be provided by a dedicated, multidisciplinary team of providers, an Integrated Practice Unit (IPU). The IPU is jointly accountable for the health outcomes of patients and the costs of providing care during the full cycle of care. This dissertation is the first to design a dynamic incentives contract between the healthcare purchaser and the IPU, who is accountable for the health outcomes of a patient over the care cycle. The optimal contract can coordinate the objectives of the purchaser and the IPU and maximize social welfare. In addition, this is the first study to characterize the collaboration dynamics among the IPU members under different contractual agreements. The insights from this study can strengthen the work relationship of the providers within an IPU.

Jacob Loree, MABE (2015)


State Level Income Inequality and Individual Self-Reported Health Status: Evidence from the United States

Abstract

The relative income hypothesis theorizes an individual’s income, relative to the income of their peers, may adversely affect their health. There is empirical evidence to support the relative income hypothesis, showing a negative statistical relationship between income inequality and health. The literature is unsettled on the relevant level of geography to measure income inequality, as well as other control variables in the estimation. This paper contributes to this literature by asking how state level income inequality affects the probability of an individual having excellent or very good self-reported health. The relative income hypothesis is tested using individual level data from the Current Population Survey in the United States, and is supplemented with state level income inequality data and state level healthcare spending data from 1996-2009. A logit model with clustered standard errors (at the state level) is employed, with marginal effects reported. Results suggest no statistically significant marginal effects within the full sample. However, if the analysis sample is restricted to the five most equal states or the least equal states, there is a statistically significant relationship between income inequality and health. The most equal states exhibit a positive (but small) relationship between inequality and health, while the five least equal exhibit a negative (but small) relationship. While a statistically significant association is found for the most/least equal states, the point estimates are not economically significant. The results are robust to the specific income inequality measure, lag structure of income inequality, or time period of analysis. The results do not support the relative income hypothesis. The implication is the effect of income inequality on health may be overstated.