Knowledge that Transforms

Does public cheap talk by a biased expert benefit voters? The answer depends on the nature of democratic institutions and the extent of communication possibilities. Expert endorsements induce office-seeking parties to serve the expert’s interests, hurting voters. Expert advocacy makes policies respond to information, helping voters. Together, policy advocacy and partisan endorsements are often better than either alone. Their interaction creates a delegation benefit that makes indirect democracy superior to direct democracy and office-seeking parties better than those motivated by public interest. But voter welfare is highest when an expert captured technocratic party competes against an uninformed populist one.

We study information acquisition in dealer markets. We first identify a one-sided strategic complementarity in information acquisition: the more informed traders are, the larger market makers’ gain from becoming informed. When quotes are observable, this effect in turn induces a strategic complementarity in information acquisition amongst market makers. We then derive the equilibrium pattern of information acquisition and examine the implications of our analysis for market liquidity and price discovery. We show that increasing the cost of information can decrease market liquidity and improve price discovery.

The US Environmental Protection Agency (EPA) uses a dynamic approach to enforcing air pollution regulations, with repeat offenders subject to high fines and designation as high priority violators (HPV). We estimate the value of dynamic enforcement by developing and estimating a dynamic model of a plant and regulator, where plants decide when to invest in pollution abatement technologies. We use a fixed grid approach to estimate random coefficient specifications. Investment, fines, and HPV designation are costly to most plants. Eliminating dynamic enforcement would raise pollution damages by 164 percent with constant fines or raise fines by 519 percent with constant pollution damages.

We provide empirical evidence of a novel liquidity-based transmission mechanism through which monetary policy influences asset markets, develop a model of this mechanism, and assess the ability of the quantitative theory to match the evidence.

This paper proposes a flexible-price theory of the role of money in an economy with incomplete idiosyncratic risk sharing. When the risk premium goes up, money provides a safe store of value that prevents interest rates from falling, reducing investment. Investment is too high during booms when risk is low, and too low during slumps when risk is high. Monetary policy cannot correct this: money is superneutral and Ricardian equivalence holds. The optimal allocation requires the Friedman rule and a tax/subsidy on capital. The real effects of money survive even in the cashless limit.

Data is nonrival: a person’s location history, medical records, and driving data can be used by many firms simultaneously. Nonrivalry leads to increasing returns. As a result, there may be social gains to data being used broadly across firms, even in the presence of privacy considerations. Fearing creative destruction, firms may choose to hoard their data, leading to the inefficient use of nonrival data. Giving data property rights to consumers can generate allocations that are close to optimal. Consumers balance their concerns for privacy against the economic gains that come from selling data broadly.

We examine the channels through which a randomized early childhood intervention in Colombia led to significant gains in cognitive and socio-emotional skills among a sample of disadvantaged children aged 12 to 24 months at baseline. We estimate the determinants of parents’ material and time investments in these children and evaluate the impact of the treatment on such investments. We then estimate the production functions for cognitive and socio-emotional skills. The effects of the program can be explained by increases in parental investments, emphasizing the importance of parenting interventions at an early age.

In a regime change game, privately informed agents sequentially decide whether to attack without observing others’ previous actions. To dissuade them from attacking, a principal adopts a dynamic information disclosure policy, frequent viability tests. A viability test publicly discloses whether the regime has survived the previous attacks. When such tests are sufficiently frequent, in the unique cutoff equilibrium, agents never attack if the regime passes the latest test, regardless of their private signals. We apply this theory to demonstrate that a borrower can eliminate panic-based runs by sufficiently diffusing the rollover choices across different maturity dates.

Social network data are often prohibitively expensive to collect, limiting empirical network research. We propose an inexpensive and feasible strategy for network elicitation using Aggregated Relational Data (ARD): responses to questions of the form "how many of your links have trait k ?" Our method uses ARD to recover parameters of a network formation model, which permits sampling from a distribution over node- or graph-level statistics. We replicate the results of two field experiments that used network data and draw similar conclusions with ARD alone.

This paper estimates the effects on rural education of the send-down movement during the Cultural Revolution, when about 16 million urban youth were mandated to resettle in the countryside. Using a county-level dataset compiled from local gazetteers and population censuses, we show that greater exposure to the sent-down youths significantly increased rural children’s educational achievement. This positive effect diminished after the urban youth left the countryside in the late 1970s but never disappeared. Rural children who interacted with the sent-down youths were also more likely to pursue more-skilled occupations, marry later, and have smaller families than those who did not.