Three Essays in Applied Micro-Econometrics

This thesis, comprised of three chapters, demonstrates how econometric methods can be used to inform policy-relevant questions relating to two international epidemics: the prescription opioid epidemic and the COVID-19 pandemic. Over the past two decades, Canada has experienced rapid growth in the consumption of prescription opioids. The increase 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. 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 modelling techniques to identify the critical predictors of prescription opioid use and abuse. Chapter 1 illustrates how the existing literature on prescription opioid use consists primarily of analyses that use multivariate logistic regression to model prescription opioid use. Then we demonstrate how nonparametric kernel methods can be used to model prescription opioid use and significantly outperform the logistic regression models from the perspective of correctly classifying prescription opioid users, both in-sample and out-of-sample. Chapter 2 utilizes a natural experiment and exploits robust nonparametric estimation methods to examine the impact of mandatory universal pharmaceutical insurance on prescription opioid use. 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 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. Moving from one crisis to another, i.e., from the Canadian prescription opioid epidemic to the global COVID-19 pandemic, we refocus attention on the labour market impacts of the latter. 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. Chapter 3 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.

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