Working Papers:

The Impact of Mandatory Universal Pharmaceutical Insurance On Prescription Opioid Use: Evidence from Canada

Abstract: This paper utilizes a natural experiment and robust nonparametric estimation methods to examine the impact of mandatory universal pharmaceutical insurance on prescription opioid use. A policy evaluation of Quebec’s implementation of mandatory pharmaceutical insurance to complement the existing universal public health insurance plan, that provides physician and hospital services, is conducted using data from the Canadian National Population Health Survey (NPHS). The results show that, among the general population, the policy led to a significant increase in pharmaceutical insurance coverage and a small in magnitude but statistically significant decrease in prescription opioid use. Additionally, the analysis does not find statistical evidence that the increase in pharmaceutical insurance coverage led to a substitution effect away from over-the-counter pain medications and towards prescription opioids for pain treatment.

Predicting Rare Events: The Case of Prescription Opioid (Ab)Use

Abstract: Over the past two decades, Canada has experienced rapid growth in the consumption of prescription opioids. The growth in the consumption of these medications has brought pain relief to many people suffering from chronic and acute pain. Unfortunately, it has also led to a parallel increase in prescription opioid abuse, dependence, and overdose. In order to develop evidence-based policies that curtail prescription opioid morbidity and mortality without hindering access to necessary pain treatment, it is imperative to use statistical modeling techniques to identify the key predictors of prescription opioid use and abuse. Among the national population, prescription opioid use occurs infrequently, resulting in a highly imbalanced binary dependent variable, which can pose classification problems for the standard techniques commonly used to model prescription opioid use. The literature on prescription opioid use consists primarily of analyses that utilize a multivariate logistic regression to model prescription opioid use. This paper illustrates how nonparametric kernel methods can be used to model prescription opioid use and significantly outperform the logistic regression models at correctly classifying prescription opioid users, both in-sample and out-of-sample.

The Effects of the COVID-19 Pandemic on the Earnings Distributions of Canadian Immigrants

Abstract: As the Corona Virus (SAR-CoV2) spread across the globe in 2020, many government bodies were forced to implement restrictions to slow down the spread of the virus; this included the shutdown of non-essential businesses and services, the cancellation of in-person events and entertainment, school closures, and the start of work-from-home orders. Many sectors saw a drastic drop-in economic activity, resulting in job losses and reductions in hours worked. This paper uses Canadian microdata to analyze the labour market effects of the COVID-19 pandemic on Canadian immigrants. Trends in employment status and aggregate hours worked are examined by gender and immigrant status and we find evidence that the labour supply of immigrants, especially immigrant women, was more affected than the labour supply of their non-immigrant counterparts.