Consumers do not purchase prescription drugs in a standard marketplace setting; instead, they rely on physicians to select an appropriate drug on their behalf. This potential agency problem is amplified by the fact that different consumers pay different prices for the same drug, depending on the copayments required by their insurance plan. There is a prevalent public concern that physicians are overly influenced by pharmaceutical company promotion, but little is actually known about how they choose which drugs to prescribe.

This dissertation investigates the extent to which agency and information problems affect prescribing, and consequently, patient outcomes. I use individual-level data on prescription drug purchases by employees and retirees in twenty-nine Fortune 500 firms from 2003-2007 to construct a sample of patients receiving first-time prescriptions for chronic drugs. In

the first two chapters, I estimate how initial prescriptions respond to three factors of patient utility: the copays set by individual health plans, large-scale copay shocks induced by patent expirations, and the predicted price-sensitivity of an individual patient. In the third chapter, a smaller sample with physician identifiers is used to measure the range of physician prescribing (number of drugs used) within a class, and its impact on patient outcomes.

In Chapter 1, I study the responses of physicians and patients to variation in the cost of drugs, and assess the welfare and health consequences of asymmetric and imperfect information in the prescription drug market. I focus on statins (cholesterol-lowering drugs) which are currently the most prescribed category of prescription drugs in the United States. Demand for drugs that treat chronic conditions depends on the initial prescriptions written by a physician, and on the subsequent decisions of patients to continue the prescription or stop. I show that the continuation decision is relatively sensitive to co-payment prices. Initial prescriptions, by comparison, are relatively insensitive to co-payment prices, suggesting that physicians either don't know the prices their patients are paying, or fail to take prices into consideration. I use the event of the highly publicized expiration of the patent for Zocor (simvastatin) to test between these explanations. Insurance plans have much lower co-pays for off-patent drugs: my analysis suggests that physicians are aware of this fact, and substantially increased prescriptions for Zocor and its generic equivalents following the patent expiration. Interestingly, the increases were larger for lower-income and healthier patients, suggesting that physicians correctly perceive the adherence elasticity of their patients and adjust their initial prescriptions accordingly, but only in response to a large and universal price change.

In Chapter 2, I study the prescribing responses to ten patent expirations occurring between 2004 and 2007 in four drug classes: antidepressants, statins, calcium channel blockers, and beta blockers. Four of the patent-losing drugs (including Zocor) experienced significant increases in prescribing rates, while three experienced statistically significant decreases. Understanding what drives this variation can inform how pharmaceutical advertising, health plans, and patient costs affect physician decisions. I identify two factors that explain much of the variation in these responses: the size of the copay drop upon expiration (i.e. the difference in copays of the brand and generic versions of the drug), and the current prevalence of generic prescribing in the drug class. Results suggest that physicians are more likely to increase their prescribing of a drug, after it becomes available as a generic, if it previously had a higher copay, on average. However, there is a baseline tendency to reduce prescribing of a patent-losing drug, likely driven by the cessation of its advertising, and this tendency grows stronger with the existing rate of generic prescribing in a class.

In Chapter 3, which is coauthored with Geoffrey Joyce and Neeraj Sood, we measure the range of physician prescribing within the ten most prevalent therapeutic classes, the factors affecting the broadness of this range, and its impact on patient outcomes. Physicians prescribe more broadly than commonly perceived. In 8 of 10 classes, the median physician prescribes at least 3 different drugs despite the small number of initial prescriptions observed per doctor (median=7). Physicians treating patients with a greater range of comorbid conditions and varied formulary designs prescribe a broader range of drugs within a class. Though narrow prescribers are more likely to prescribe highly advertised drugs, few physicians prescribe these drugs exclusively. Narrow prescribing has modest effects on medication adherence and out of pocket costs in some drug classes.

Compared to other disciplines, one of the distinctive features of Economics is the impossibility of doing experiments to study empirically relevant questions. In this dissertation, I use two episodes from the past where the unique features of the institutional environment created quasi-experiments that help us understand relevant issues relate to cartels and neighborhood effects. In the fist two chapters, I use the Chilean nitrate industry between the War of the Pacific and the start of the First World War (1880-1914) to shed light on the effects of entry for cartels and the importance of learning for effective cartel organization. The Chilean nitrate industry was very important at the time: Chilean nitrate was the main commercial fertilizer used in the world. Also, it was the main industry of Chile, the only country where it is found, where it represented 70% of exports and 45% of government revenues. Importantly, there was no antitrust legislation and no domestic consumer surplus to protect in Chile. Thus, cartels could be freely formed by nitrate producers. Moreover, these cartels were completely public: Their decisions were publicly discussed by the press and the public and they would be formed by the signature of a public contract. I collected from handwritten archival records an original data set of monthly output and inputs that covers 35 years of this industry, period over which 5 cartels were organized. In the third chapter, I introduce a novel new dataset to study neighborhood effects that uses a massive program of forced-displacement of population within the city of Santiago in the context of the Chilean dictatorship in the early 1980s.

Chapter 1 studies the effect of cartels on entry, and the long-term effect of cartel-induced entry for the evolution of industry productivity. Intuitively, as cartels artificially increase prices entry becomes more attractive and less productive firms may decide to enter. Because of data limitations, previous researchers have not quantified the extensive margin mechanism. My analysis has 3 steps. First, I evaluate if nitrate cartels caused more entry of new firms. I find that cartels generated an additional entry of 4 plants per year or about 5\% of the initial number of plants in my main period of interest. Second, I estimate the productivity of all the plants in the industry to analyze if firms that entered during cartel periods where less productive. I find that there is a sizable gap in average productivity between entrants during competition and cartel periods: If the median-sized plant in the industry had received this productivity gap its revenue would have increases by one-third. Third, I conduct two counterfactual simulations. The first, studies the effect of entry on cartel profits by estimating incumbent cartel members counterfactual profits if they had been able to prevent any additional entry. I find their counterfactual profits would have been 40% larger had there been no entry. The second counterfactual studies the effect of having a cartel on entry. Specifically, what would the number of new firms and their productivity have been, if during the Fourth and Fifth Cartels there had been competition? I find that 18% of the plants that entered in the data would have not entered. This translates into an increase on mean plant productivity of 3%.

Chapter 2 studies the degree to which experience helps firms to organize successful cartels. Unlike in most of the previous literature on cartels, in the nitrate cartels issues related to monitoring and enforcement were of secondary importance with respect to the challenge of allocating the collusive surplus among the colluding firms. I document that cartel contracts gradually became more complete, generated a smoother transition from competition to collusion, and that producers eventually discarded inefficient methods of market share allocation, associated to larger production costs, in favor of better alternatives. In particular, I am able to estimate that the time method used during the Second Cartel directly caused higher production costs of about 10%, while the trial method implemented during the Third Cartel caused higher costs of approximately 20%.

Finally, Chapter 3 describes a novel large dataset that combines archival records and administrative data to study a natural experiment that occurred during the Chilean dictatorship between 1979 and 1985, when the government mandated the relocation of a large number of slums in the city of Santiago, Chile. Some features of the program's implementation make it of unique interest to study the broad effects of neighborhoods on social mobility and inequality: the unit of treatment was the slum, participation was mandatory and compliance was very high, since the policy was implemented during a highly repressive dictatorial government. In addition, and only some of the slums were removed from their original location creating two groups of families: movers and non-movers, which allows me to identify a causal displacement effect. The dataset comprises data for more than 26,000 households that were part of this program (out of a total of 40,000 households) and more than 58,000 of their children, providing the potential for causal estimation of the long-term and inter-generational effects of moving to a high-poverty neighborhood on education, mortality, income, and crime.