In Chapter 1, I describe the hospice industry in California and highlight the key institutional details, then estimate a structural model of hospice choice by patients. Hospices are firms that give palliative care to dying patients. There is no price competition because Medicare pays hospices a fixed per-day rate for each patient, so hospices compete on reputation. I define a hospice's reputation as a stock of its past quality choices. Thus, a hospice can build up its reputation stock over time by consistently choosing high quality. The reputation stock also partially depreciates every period, meaning that a hospice which repeatedly shirks on quality will lose its reputation over time. To study reputation and hospice choice in this setting, I build and estimate a demand model of hospices using yearly hospice-level data from California for 2002-2018. Each consumer makes a discrete choice from a set of hospices in her market, taking into account hospices' reputations and characteristics. The demand estimates show that reputation plays a significant role in consumer choice and depreciates at an annual rate of 53%.
In Chapter 2, I build a dynamic oligopoly model of hospices choosing quality to compete on reputation against rivals. This is used to recover the hospice cost function. I use my model and estimates to conduct the following policy counterfactuals. As reputation becomes more persistent - for instance, through the creation of an online hospice rating system - hospices choose higher quality. Hospices also choose higher quality as Medicare prices increase, but the response depends on how differentiated they are in characteristics from rivals. Finally, a hybrid per-day per-visit hospice reimbursement scheme achieves the same quality with nearly 30% lower spending than the current per-day Medicare scheme.
In Chapter 3 (joint work with Rena Conti), we study market dynamics in the pharmaceutical industry after loss of market exclusivity by a branded drug. Branded drug manufacturers often respond to generic entry by releasing an Authorized Generic (AG), which is chemically identical to the branded drug but without the brand label attached. This is used to price discriminate between consumers, with the branded drug charging high price and AG charging low price to compete with generics. Using total drug sales and revenue data on US for 2004-2016, we build a stylized structural model to study entry and pricing decisions. We estimate a random-coefficients discrete choice demand model and find significant heterogeneity in brand valuation and price sensitivity among consumers. Then we build a dynamic structural model of generic entry, AG release, and pricing. Combined with calibrated entry-cost parameters, this is used to conduct policy counterfactuals. First, we study the impact of various demand-side policies (such as improving consumer valuation of non-branded drugs and increasing price-sensitivity) on market outcomes. Second, we show that a faster generic approval rate leads to greater generic entry, lower likelihood of AG being released, and lower prices. Third, we find that banning AGs leads to greater generic entry but also higher industry prices overall.
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/48472 |
| Date | 22 March 2024 |
| Creators | Alam, Rubaiyat |
| Contributors | Rysman, Marc |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
| Rights | Attribution 4.0 International, http://creativecommons.org/licenses/by/4.0/ |
Page generated in 0.0027 seconds