Knowledge that Transforms

Abstract The seller of an asset has the option to buy hard information about the value of the asset from an intermediary. The seller can then disclose this information before selling the asset in a competitive market. We study how the intermediary designs and sells hard information to robustly maximize the intermediary's revenue across all equilibria. Even though the intermediary could use an accurate test that reveals the asset’s value, we show that robust revenue maximization leads to a noisy test with a continuum of possible scores. In addition, the intermediary always charges the seller for disclosing the test score to the market, but not necessarily for running the test. This enables the intermediary to robustly appropriate a significant share of the surplus resulting from the asset sale.

Abstract Skepticism about the quality of health systems and their consequent underuse are thought to contribute to high rates of mortality in the developing world. The perceived quality of health services may be especially critical during epidemics, when people choose whether to cooperate with response efforts and frontline health workers. Can improving the perceived quality of health care promote community health and ultimately help to contain epidemics? We leverage a field experiment in Sierra Leone to answer this question in the context of the 2014 West African Ebola crisis. Two years before the outbreak, we randomly assigned two interventions to government-run health clinics—one focused on community monitoring, and the other conferred nonfinancial awards to clinic staff. Prior to the Ebola crisis, both interventions increased clinic utilization and patient satisfaction. Community monitoring additionally improved child health, leading to 38% fewer deaths of children under age five. Later, during the crisis, the interventions also increased reporting of Ebola cases by 62%, and community monitoring significantly reduced Ebola-related deaths. Evidence on mechanisms suggests that both interventions improved the perceived quality of health care, encouraging patients to report Ebola symptoms and receive medical care. Improvements in health outcomes under community monitoring suggest that these changes partly reflect a rise in the underlying quality of administered care. Overall, our results indicate that promoting accountability not only has the power to improve health systems during normal times, but can also make them more resilient to emergent crises.

Abstract U.S. income inequality has varied inversely with union density over the past 100 years. But moving beyond this aggregate relationship has proven difficult, in part because of limited microdata on union membership prior to 1973. We develop a new source of microdata on union membership dating back to 1936, survey data primarily from Gallup (N ≈ 980,000), to examine the long-run relationship between unions and inequality. We document dramatic changes in the demographics of union members: when density was at its mid-century peak, union households were much less educated and more nonwhite than other households, whereas pre-World War II and today they are more similar to nonunion households on these dimensions. However, despite large changes in composition and density since 1936, the household union premium holds relatively steady between 10 and 20 log points. We use our data to examine the effect of unions on income inequality. Using distributional decompositions, time series regressions, state-year regressions, as well as a new instrumental-variable strategy based on the 1935 legalization of unions and the World War II–era War Labor Board, we find consistent evidence that unions reduce inequality, explaining a significant share of the dramatic fall in inequality between the mid-1930s and late 1940s.

Abstract This article describes a new fact, then analyzes its causes and consequences: in most countries, import tariffs and nontariff barriers are substantially lower on dirty than on clean industries, where an industry’s “dirtiness” is defined as its carbon dioxide (CO2) emissions per dollar of output. This difference in trade policy creates a global implicit subsidy to CO2 emissions in internationally traded goods and contributes to climate change. This global implicit subsidy to CO2 emissions totals several hundred billion dollars annually. The greater protection of downstream industries, which are relatively clean, substantially accounts for this pattern. The downstream pattern can be explained by theories where industries lobby for low tariffs on their inputs but final consumers are poorly organized. A quantitative general equilibrium model suggests that if countries applied similar trade policies to clean and dirty goods, global CO2 emissions would decrease and global real income would change little.

Abstract Consideration set models generalize discrete-choice models by relaxing the assumption that consumers consider all available options. Determining which options were considered has previously required either survey data or restrictions on how attributes affect consideration or utility. We provide an alternative route. In full-consideration models, choice probabilities satisfy a symmetry property analogous to Slutsky symmetry in continuous-choice models. This symmetry breaks down in consideration set models when changes in characteristics perturb consideration. We show that consideration probabilities are constructively identified from the resulting asymmetries. We validate our approach in a lab experiment where consideration sets are known and then apply our framework to study a “smart default” policy in Medicare Part D, wherein consumers are automatically reassigned to lower-cost prescription drug plans with the option of opting out. Full-consideration models imply that such a policy will be ineffective because consumers will opt out to avoid switching costs. Allowing for inattention, we find that defaulting all consumers to lower-cost options produces negligible welfare benefits on average, but defaulting only consumers who would save at least $300 produces large benefits.

Abstract Long-term nominal interest rates are surprisingly sensitive to high-frequency (daily or monthly) movements in short-term rates. Since 2000, this high-frequency sensitivity has grown even stronger in U.S. data. By contrast, the association between low-frequency changes (at 6- or 12-month horizons) in long- and short-term rates, which was also strong before 2000, has weakened substantially. This puzzling post-2000 pattern arises because increases in short rates temporarily raise the term premium component of long-term yields, leading long rates to temporarily overreact to changes in short rates. The frequency-dependent excess sensitivity of long-term rates that we observe in recent years is best understood using a model in which (i) declines in short rates trigger “rate-amplifying” shifts in investor demand for long-term bonds, and (ii) the arbitrage response to these demand shifts is both limited and slow. We study, theoretically and empirically, how such rate-amplifying demand can be traced to mortgage-refinancing activity, investors who extrapolate recent changes in short rates, and investors who “reach for yield” when short rates fall. We discuss the implications of our findings for the validity of event study methodologies and the transmission of monetary policy.

Abstract In October 2010, the state government of Andhra Pradesh, India, issued an emergency ordinance, bringing microfinance activities in the state to a complete halt and causing a nationwide shock to the liquidity of lenders, especially those with loans in the affected state. We use this massive dislocation in the microfinance market to identify the causal impacts of a reduction in credit supply on consumption, earnings, and employment in general equilibrium in rural labor markets. Using a proprietary district-level data set from 25 separate, for-profit microlenders matched with household data from the National Sample Survey, we find that district-level reductions in credit supply are associated with significant decreases in casual daily wages, household wage earnings, and consumption. We find a substantial consumption multiplier from credit that is likely driven by two channels—aggregate demand and business investment. We calibrate a simple two-period, two-sector model of the rural economy that incorporates both channels and show that the magnitude of our wage results is consistent with the model’s predictions.

Abstract Proposition 209 banned race-based affirmative action at California public universities in 1998. Using a difference-in-differences research design and a newly constructed longitudinal database linking all 1994–2002 University of California applicants to their educational experiences and wages, I show that ending affirmative action caused underrepresented minority (URM) freshman applicants to cascade into lower-quality colleges. The “mismatch hypothesis” implies that this cascade would provide net educational benefits to URM applicants, but their degree attainment declined overall and in STEM fields, especially among less academically qualified applicants. URM applicants’ average wages in their twenties and thirties subsequently declined, driven by declines among Hispanic applicants. These declines are not explained by URM students' performance or persistence in STEM course sequences, which were unchanged after Prop 209. Ending affirmative action also deterred thousands of qualified URM students from applying to any UC campus. Complementary regression discontinuity and institutional value-added analyses suggest that affirmative action’s net educational and wage benefits for URM applicants exceed its net costs for on-the-margin white and Asian applicants.

Government programs are often offered on an optional basis to market participants. We explore the economics of such voluntary regulation in the context of a Medicare payment reform, in which one medical provider receives a single, predetermined payment for a sequence of related healthcare services, instead of separate service-specific payments. This "bundled payment" program was originally implemented as a 5-year randomized trial, with mandatory participation by hospitals assigned to the new payment model; however, after two years, participation was made voluntary for half of these hospitals. Using detailed claim-level data, we document that voluntary participation is more likely for hospitals that can increase revenue without changing behavior ("selection on levels") and for hospitals that had large changes in behavior when participation was mandatory ("selection on slopes"). To assess outcomes under counterfactual regimes, we estimate a stylized model of responsiveness to and selection into the program. We find that the current voluntary regime generates inefficient transfers to hospitals, and that alternative (feasible) designs could reduce these inefficient transfers and raise welfare. Our analysis highlights key design elements to consider under voluntary regulation.

Abstract We implement a new survey of firms, focusing on their higher-order macroeconomic expectations. The survey provides a novel set of stylized facts regarding the relationship between first-order and higher-order expectations of economic agents, including how they adjust their beliefs in response to a variety of information treatments. We show how these facts can be used to calibrate key parameters of noisy-information models with infinite regress as well as to test predictions made by this class of models. We also consider a range of extensions to the basic noisy-information model that can potentially better reconcile theory and empirics. Although some extensions like level-k thinking are unsuccessful, incorporating heterogeneous long-run priors can address the empirical shortcomings of the basic noisy-information model.