Precision medicines inherently fragment treatment populations, generating small-population markets, creating high-priced "niche busters" rather than broadly prescribed "blockbusters". It is plausible to expect that small markets will attract limited entry in which a small number of interdependent differentiated product oligopolists will compete, each possessing market power. Multiple precision medicine market situations now resemble game theory constructs such as the prisoners' dilemma and Bertrand competition. The examples often involve drug developer choices created by setting the cut-off value for the companion diagnostics to define the precision medicine market niches and their payoffs. Precision medicine game situations may also involve payers and patients who attempt to change the game to their advantage or whose induced behaviors alter the payoffs for the developers. The variety of games may predictably array themselves across the lifecycle of each precision medicine indication niche and so may become linked into a sequentially evolving meta-game. We hypothesize that certain precision medicine areas such as inflammatory diseases are becoming complex simultaneous multi-games in which distinct precision medicine niches compete. Those players that learn the most rapidly and apply those learnings the most asymmetrically will be advantaged in this ongoing information pharms race.
The Information Pharms Race and Competitive Dynamics of Precision Medicine: Insights from Game Theory -- by Ernst R. Berndt, Mark R. Trusheim
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How Well Do Automated Methods Perform in Historical Samples? Evidence from New Ground Truth -- by Martha Bailey, Connor Cole, Morgan Henderson, Catherine Massey
New large-scale data linking projects are revolutionizing empirical social science. Outside of selected samples and tightly restricted data enclaves, little is known about the quality of these "big data" or how the methods used to create them shape inferences. This paper evaluates the performance of commonly used automated record-linking algorithms in three high quality historical U.S. samples. Our findings show that (1) no method (including hand linking) consistently produces samples representative of the linkable population; (2) automated linking tends to produce very high rates of false matches, averaging around one third of links across datasets and methods; and (3) false links are systematically (though differently) related to baseline sample characteristics. A final exercise demonstrates the importance of these findings for inferences using linked data. For a common set of records, we show that algorithm assumptions can attenuate estimates of intergenerational income elasticities by almost 50 percent. Although differences in these findings across samples and methods caution against the generalizability of specific error rates, common patterns across multiple datasets offer broad lessons for improving current linking practice.
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The Effect of Education and School Quality on Female Crime -- by Javier Cano-Urbina, Lance Lochner
This paper estimates the effects of educational attainment and school quality on crime among American women. Using changes in compulsory schooling laws as instruments, we estimate significant effects of schooling attainment on the probability of incarceration using Census data from 1960-1980. Using data from the 1960-90 Uniform Crime Reports, we also estimate that increases in average schooling levels reduce arrest rates for violent and property crime but not white collar crime. Our results suggest small and mixed direct effects of school quality (as measured by pupil-teacher ratios, term length, and teacher salaries) on incarceration and arrests. Finally, we show that the effects of education on crime for women are unlikely to be due to changes in labor market opportunities and may be more related to changes in marital opportunities and family formation.
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Student Loan Nudges: Experimental Evidence on Borrowing and Educational Attainment -- by Benjamin M. Marx, Lesley J. Turner
We estimate the impact of student loan "nudges" on community college students' borrowing and provide the first experimental evidence of the effect of student loans on educational attainment. Nonbinding loan offers listed in students' financial aid award letters, that do not alter students' choice sets, significantly affect borrowing. Students randomly assigned to receive a nonzero loan offer were 40 percent more likely to borrow than those who received a $0 loan offer. Nudge-induced borrowing increased both GPA and credits earned by roughly 30 percent un the year of the intervention, and in the following year, increased transfers to four-year colleges by 10 percentage points (nearly 200 percent). We predict that the average student would be better off receiving a nonzero loan offer for any discount rate below 12.4 percent. Students' borrowing responses to the nudge are most consistent with a model in which nonzero offers provide information about loan eligibility, suggesting that for most students, nonzero offers are welfare enhancing. Given that over 5 million U.S. college students receive $0 loan offers, our results indicate the potential to achieve large gains in educational attainment through changes to the choice architecture around borrowing.
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The Uncovered Interest Parity Puzzle, Exchange Rate Forecasting, and Taylor Rules -- by Charles Engel, Dohyeon Lee, Chang Liu, Chenxin Liu, Steve Pak Yeung Wu
Recent research has found that the Taylor-rule fundamentals have power to forecast changes in U.S. dollar exchange rates out of sample. Our work casts some doubt on that claim. However, we find strong evidence of a related in-sample anomaly. When we include U.S. inflation in the well-known uncovered interest parity regression of the change in the exchange rate on the interest-rate differential, we find that the inflation variable is highly significant and the interest-rate differential is not. Specifically, high U.S. inflation in one month forecasts dollar appreciation in the subsequent month. We introduce a model in which a Taylor rule determines monetary policy, but in which not only monetary shocks but also liquidity shocks drive nominal interest rates. This model can potentially account for the empirical findings.
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Learning from Coworkers: Peer Effects on Individual Investment Decisions -- by Paige Ouimet, Geoffrey Tate
We use unique data on employee decisions in the employee stock purchase plans (ESPPs) of U.S. public firms to measure the influence of networks on investment decisions. Comparing only employees within a firm during the same election window and controlling for a metro area fixed effect, we find that the local choices of coworkers to participate in the firm's ESPP exert a significant influence on employees' own decisions to participate. Local coworkers' trading patterns also disseminate to colleagues through the network. In the cross-section, we find that some employees (men, younger workers) are particularly susceptible to peer influence. Generally, we find that more similar employees exert greater influence on each other's decisions and, particularly, that high (low) information employees are most affected by other high (low) information employees. However, we also find that the presence of high information employees magnifies the effects of peer networks. We trace a value-increasing investment choice through employee networks. Thus, our analysis suggests the potential of networks and targeted investor education to improve financial decision-making.
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Should we Get rid of the Natural Rate Hypothesis? -- by Olivier J. Blanchard
50 years ago, Milton Friedman articulated the natural rate hypothesis. It was composed of two sub-hypotheses: First, the natural rate of unemployment is independent of monetary policy. Second, there is no long-run trade-off between the deviation of unemployment from the natural rate and inflation. Both propositions have been challenged. The paper reviews the arguments and the macro and micro evidence against each. It concludes that, in each case, the evidence is suggestive, but not conclusive. Policy makers should keep the natural rate hypothesis as their null hypothesis, but keep an open mind and put some weight on the alternatives.
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US Exports and Employment -- by Robert C. Feenstra, Hong Ma, Yuan Xu
We examine the employment responses to import competition from China and to global export expansion from the United States, both of which have been expanding strongly during the past decades. We find that although Chinese imports reduce jobs, at both the industry level and the local commuting zone level, the global export expansion of US products also creates a considerable number of jobs. On balance over the entire 1991-2007 period, job gains due to changes in US global exports were slightly less than job losses due to Chinese imports. Using data at both the industry level and the commuting zone level, we find a net loss of around 0.2-0.3 million jobs. When we extend the analysis to 1991-2011, we find the net job effect of import and export exposure is roughly balanced at the commuting zone level.
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Moral Hazard in Health Insurance: What We Know and How We Know It -- by Liran Einav, Amy Finkelstein
We describe research on the impact of health insurance on healthcare spending ("moral hazard"), and use this context to illustrate the value of and important complementarities between different empirical approaches. One common approach is to emphasize a credible research design; we review results from two randomized experiments, as well as some quasi-experimental studies. This work has produced compelling evidence that moral hazard in health insurance exists - that is, individuals, on average, consume less healthcare when they are required to pay more for it out of pocket - as well as qualitative evidence about its nature. These studies alone, however, provide little guidance for forecasting healthcare spending under contracts not directly observed in the data. Therefore, a second and complementary approach is to develop an economic model that can be used out of sample. We note that modeling choices can be consequential: different economic models may fit the reduced form but deliver different counterfactual predictions. An additional role of the more descriptive analyses is therefore to provide guidance regarding model choice.
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Personalized Medicine When Physicians Induce Demand -- by David H. Howard, Jason Hockenberry, Guy David
Advocates for "personalized medicine" tests claim they can reduce health care spending by identifying patients unlikely to benefit from costly treatments. But most tests are imperfect, and so physicians have considerable discretion in how they use the results. We show that when physicians face incentives to provide a treatment, the introduction of an imperfect prognostic test will increase treatment rates. We study the interaction of incentives and information in physicians' choice between conventional radiotherapy and intensity modulated radiation therapy (IMRT) for Medicare patients with breast cancer. IMRT is far more costly. Patients with left-side tumors are more likely to benefit from IMRT, though it is unnecessary for the vast majority of patients. IMRT use is 18 percentage points higher in freestanding clinics, where physician-owners share in the lucrative fees generated by IMRT, than in hospital-based clinics. Patients with left-side tumors are more likely to receive IMRT in both types of clinics. However, IMRT use in patients with right-side tumors (the low benefit group) treated in freestanding clinics is actually higher than use in patients with left-side tumors (high benefit group) treated in hospital-based clinics. Prognostic information affects use but does nothing to counter incentives to overuse IMRT.
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The Use and Misuse of Patent Data: Issues for Corporate Finance and Beyond -- by Josh Lerner, Amit Seru
Patents and citations are powerful tools for understanding innovative activity inside the firm, and are increasingly use in corporate finance research. But due to the complexities of patent data collection and the changing spatial and industry composition of innovative firms, biases may be introduced. We highlight several patent-level biases induced by truncation of reported patent awards and citations, affecting estimates of time trends and patterns across technology classes and regions. We then introduce measures of patent and citation biases. When aggregated at the firm level, these survive popular methods of adjustment and are correlated with firm-level characteristics. We show that these issues can lead to problematic - and ex ante predictable - inferences, using several examples from prominent streams of finance literature that use patent data. We suggest a number of concrete steps that researchers can employ to avoid biased inferences.
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Intrinsic Openness and Endogenous Institutional Quality -- by Yang Jiao, Shang-Jin Wei
Quality of public institutions has been recognized as a crucial determinant of macroeconomic outcomes. We propose that a country's intrinsic level of openness (due to population size, geography, or exogenous trade opportunities) affects its incentives in investing in better institutions. We present a simple theory and extensive empirical evidence validating the role of intrinsic openness in determining governance quality. This suggests an indirect but important channel for globalization to improve welfare by raising the quality of governance.
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Aggregating from Micro to Macro Patterns of Trade -- by Stephen J. Redding, David E. Weinstein
We develop a new framework for aggregating from micro to macro patterns of trade. We derive price indexes that determine comparative advantage across countries and sectors and the aggregate cost of living. If firms and products are imperfect substitutes, we show that these price indexes depend on variety, average demand/quality and the dispersion of demand/quality-adjusted prices, and are only weakly related to standard empirical measures of average prices, thereby providing insight for elasticity puzzles. Of the cross-section (time-series) variation in comparative advantage, 50 (90) percent is accounted for by variety and average demand/quality, with average prices contributing less than 10 percent.
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Moral Hazard Misconceptions: the Case of the Greenspan Put -- by Gideon Bornstein, Guido Lorenzoni
Policy discussions on financial market regulation tend to assume that whenever a corrective policy is used ex post to ameliorate the effects of a crisis, there are negative side effects in terms of moral hazard ex ante. This paper shows that this is not a general theoretical prediction, focusing on the case of monetary policy interventions ex post. In particular, we show that if the central bank does not intervene by monetary easing following a crisis, this creates an aggregate demand externality that makes borrowing ex ante inefficient. If instead the central bank follows the optimal discretionary policy and intervenes to stabilize asset prices and real activity, we show examples in which the aggregate demand externality disappears, reducing the need for ex ante intervention.
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Tax Simplicity and Heterogeneous Learning -- by Philippe Aghion, Ufuk Akcigit, Matthieu Lequien, Stefanie Stantcheva
We study how strongly individuals respond to tax simplicity and how they learn about the complexities of the tax system. We focus on the self-employed, who can more easily adjust to tax incentives and whose responses directly stem from their own understanding of the tax system. We use new French tax returns data from 1994 to 2012. France serves as a good quasi-laboratory: it has three fiscal regimes - or modes of taxation - for the self-employed, which differ in their monetary tax incentives and in their tax simplicity. Two key features are that, first, these regimes are subject to eligibility thresholds; we find large excess masses (bunching) right below the latter. Second, the regimes impact different agents heterogeneously and have changed extensively over time. Taken together, these two key elements give us measures of tax responses (the bunching) as well as the variation needed to jointly estimate a value of tax simplicity and taxable income elasticities. They also give us an opportunity to study how individuals learn about and respond over time to changing policy parameters. We estimate a large value for tax simplicity of up to 650 euros per year per individual depending on the regime and activity. We also find sizable costs of tax complexity; agents are not immediately able to understand what the right regime choice is, leave significant money on the table, and learn over time. The cost of complexity is "regressive" in that it affects mostly the uneducated, low income, and low skill agents. Agents who can be viewed as more informed and knowledgeable (e.g., the more educated or high-skilled) are more likely to make the correct regime choice and to learn faster.
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Fresh Air Eases Work - The Effect of Air Quality on Individual Investor Activity -- by Steffen Meyer, Michaela Pagel
This paper shows that air quality has a significantly negative effect on the likelihood of individual investors to sit down, log in, and trade in their brokerage accounts controlling for investor-, weather-, traffic-, and market-specific factors. In perspective, a one standard deviation increase in fine particulate matter leads to the same reduction in the probability of logging in and trading as a one standard deviation increase in sunshine. We document this effect for low levels of pollution that are commonly found throughout the developed world. As individual investor trading can be a proxy for everyday cognitively-demanding tasks such as office work, our findings suggest that the negative effects of pollution on white-collar work productivity are much more severe than previously thought. To our knowledge, this is the first study to demonstrate a negative impact of pollution on a measure of white-collar productivity at the individual level in a western country.
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Are Poor Individuals Mainly Found in Poor Households? Evidence using Nutrition Data for Africa -- by Caitlin S. Brown, Martin Ravallion, Dominique van de Walle
Antipoverty policies assume that targeting poor households suffices in reaching poor individuals. We question this assumption. Our comprehensive assessment for sub-Saharan Africa reveals that undernourished women and children are spread widely across the household wealth and consumption distributions. Roughly three-quarters of underweight women and undernourished children are not found in the poorest 20% of households, and around half are not found in the poorest 40%. Countries with higher undernutrition tend to have higher shares of undernourished individuals in non-poor households. The results are consistent with intra-household inequality but other factors also appear to be at work including common health risks.
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Fast and Slow Learning From Reviews -- by Daron Acemoglu, Ali Makhdoumi, Azarakhsh Malekian, Asuman Ozdaglar
This paper develops a model of Bayesian learning from online reviews, and investigates the conditions for asymptotic learning of the quality of a product and the speed of learning under different rating systems. A rating system provides information about reviews left by previous customers. A sequence of potential customers decide whether to join the platform. After joining and observing the ratings of the product, and conditional on her ex ante valuation, a customer decides whether to purchase or not. If she purchases, the true quality of the product, her ex ante valuation, an ex post idiosyncratic preference term and the price of the product determine her overall satisfaction. Given the rating system of the platform, she decides to leave a review as a function of her overall satisfaction. We study learning dynamics under two classes of rating systems: full history, where customers see the full history of reviews, and summary statistics, where the platform reports some summary statistics of past reviews. In both cases, learning dynamics are complicated by a selection effect -- the types of users who purchase the good and thus their overall satisfaction and reviews depend on the information that they have available at the time of their purchase. We provide conditions for asymptotic learning under both full history and summary statistics, and show how the selection effect becomes more difficult to correct for with summary statistics. Conditional on asymptotic learning, the speed (rate) of learning is always exponential and is governed by similar forces under both types of rating systems, though the exact rates differ. Using this characterization, we provide the rate of learning under several different types of rating systems. We show that providing more information does not always lead to faster learning, but strictly finer rating systems always do. We also illustrate how different rating systems, with the same distribution of preferences, can lead to very fast or very slow speeds of learning.
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Socioeconomic Status and Macroeconomic Expectations -- by Sreyoshi Das, Camelia M. Kuhnen, Stefan Nagel
We show that individuals' macroeconomic expectations are influenced by their socioeconomic status (SES). People with higher income or higher education are more optimistic about future macroeconomic developments, including business conditions, the national unemployment rate, and stock market returns. The spread in beliefs between high- and low-SES individuals diminishes significantly during recessions. A comparison with professional forecasters and historical data reveals that the beliefs wedge reflects excessive pessimism on the part of low-SES individuals. SES-driven expectations help explain why higher-SES individuals are more inclined to invest in the stock market and more likely to consider purchasing homes, durable goods, or cars.
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Old-age Labor Force Participation in Germany: What Explains the Trend Reversal among Older Men? And What the Steady Increase among Women? -- by Axel Boersch-Supan, Irene Ferrari
The aim of this paper is to illustrate for Germany the factors that may explain the U-shaped pattern of older men's labor force participation - from a long declining trend that began in the early 1970s to an increasing trend starting from the late 1990s - and at the same time the steady increase in older women's labor force participation. In a first step, we provide graphical evidence of the trends of various variables which may be relevant, with the aim of investigating the presence or absence of common patterns between these factors and labor force participation. Then, through a decomposition analysis, we provide an empirical estimate of the contribution of some of these factors to the overall evolution of labor force participation. Our preliminary conclusion is that much of the change in the trend of older men's labor force participation may be explained by changes in public pension regulations, and in particular by the phasing in of actuarial adjustments for early retirement. Regarding women, whether public pension rules play a role is unclear. Most probably, the secular change of women's role in society is the main driver of the steadily increasing labor force participation among German women.
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