The Patient Protection and Affordable Care Act of 2010 (ACA) led to the largest health insurance expansion in the U.S. since Medicare and Medicaid were introduced in 1965. This dissertation studies the causal effects of the ACA on pharmaceutical prices, demand, and innovation using a difference-in-differences framework with continuous treatment intensity. The identification strategy exploits plausibly exogenous variation in medical conditions’ exposure to different ACA provisions, arising from their differential prevalence across age groups.1 1 The major provisions of the ACA include the phaseout of the Medicare Part D coverage gap, Medicaid expansion, the establishment of (subsidized) health insurance exchanges, the individual mandate, and the employer mandate. Hereafter, I refer to the last 4 provisions collectively as “the ACA non-Medicare provisions.” For pharmaceutical prices, I find that the ACA non-Medicare provisions incentivized firms to increase prices for brand-name drugs targeting medical conditions more prevalent among adult workers aged 19 to 64. Specifically, a one standard deviation increase in exposure to these provisions would lead to a 0.079 percent increase in brand-name prices per prescription. While this effect may seem modest, for the medical condition with the highest exposure (essential hypertension), the brand-name price per prescription would increase by 1.455 percent. In 2015, this corresponded to a $109.363 increase, or 85.4 percent of the mean price per prescription of $128.061. Conversely, manufacturers of brand-name drugs targeting the elderly (aged 65 and over) reduced prices, likely to circumvent manufacturer discounts mandated by the phaseout of the Medicare Part D coverage gap. Specifically, a one standard deviation increase in policy exposure would lead to a 0.050 percent decrease in brand-name prices per prescription. While this effect may seem modest, for the medical condition with the highest exposure (essential hypertension), the brand-name price per prescription would decrease by 1.012 percent. In 2015, this corresponded to a $76.081 decrease, or 59.4 percent of the mean price per prescription of $128.061. For pharmaceutical utilization, I find no evidence that per capita prescriptions responded to the ACA, suggesting that individual drug consumption is highly inelastic to insurance coverage. However, the ACA affected market participation by reducing the number of buyers aged 18 and under, particularly for medical conditions more prevalent in this group. Specifically, a one standard deviation increase in disease prevalence among individuals aged 18 and under would lead to a 0.037 percent decline in total prescriptions for this group. While this effect may seem modest, for the most prevalent condition in this group (asthma), the ACA would reduce their total prescriptions by 0.557 percent. In 2015, this corresponded to a reduction of 10.009 million prescriptions, or nearly 16 times the mean total prescriptions for this age group (0.636 million prescriptions). No statistically significant effects were found on total prescriptions for adult workers aged 19 to 64 or the elderly aged 65 and over. For pharmaceutical innovation, I find that the ACA incentivized firms to reallocate R&D budgets from medical conditions more prevalent among other age groups toward those more common among adult workers aged 19 to 64. Within the 19 to 64 age range, I find that the ACA non-Medicare provisions encouraged firms to shift R&D budgets from medical conditions more prevalent among younger workers (aged 19 to 45) toward those more common among older workers aged (46 to 64). Specifically, a one standard deviation increase in exposure to the ACA non-Medicare provisions would lead to an additional 4.614 preclinical trial initiations per quarter, approximately 1.4 times the mean of 3.368 trials. While this effect is already economically significant, for the medical condition with the highest exposure (essential hypertension), the quarterly preclinical trial initiations would increase by 88.087 trials, approximately 26 times the mean of 3.368 trials. The ACA also increased clinical R&D, primarily through the continuation of “on-the-shelf” clinical projects targeting the elderly (aged 65 and over), rather than through increased preclinical trial initiations targeting adult workers (aged 19 to 64).2 2 “On-the-shelf” projects are R&D projects that a company has developed but has chosen not to pursue further, due to various reasons like lack of funding, or market uncertainty.