This paper measures the impact of vertically integrated and exclusive software on industry structure and welfare in the sixth-generation of the US video game industry (2000–2005). I specify and estimate a dynamic model of both consumer demand for hardware and software products, and software demand for hardware platforms. I use estimates to simulate market outcomes had platforms been unable to own or contract exclusively with software. Driven by increased software compatibility, hardware and software sales would have increased by 7 percent and 58 percent and consumer welfare by $1.5 billion. Gains would be realized only by the incumbent, suggesting exclusivity favored the entrant platforms.

We embed a field experiment in a nationwide recruitment drive for a new health care position in Zambia to test whether career benefits attract talent at the expense of prosocial motivation. In line with common wisdom, offering career opportunities attracts less prosocial applicants. However, the trade-off exists only at low levels of talent; the marginal applicants in treatment are more talented and equally prosocial. These are hired, and perform better at every step of the causal chain: they provide more inputs, increase facility utilization, and improve health outcomes including a 25 percent decrease in child malnutrition.

We evaluate the consequences of narrow hospital networks in commercial health care markets. We develop a bargaining solution, "Nash- in-Nash with Threat of Replacement," that captures insurers' incentives to exclude, and combine it with California data and estimates from Ho and Lee (2017) to simulate equilibrium outcomes under social, consumer, and insurer- optimal networks. Private incentives to exclude generally exceed social incentives, as the insurer benefits from substantially lower negotiated hospital rates. Regulation prohibiting exclusion increases prices and premiums and lowers consumer welfare without significantly affecting social surplus. However, regulation may prevent harm to consumers living close to excluded hospitals.

Bayesian Learning and the Pricing of New Information: Evidence from Prediction Markets by David S. Lee and Enrico Moretti. Published in volume 99, issue 2, pages 330-36 of American Economic Review, May 2009

In the single-IV model, researchers commonly rely on t-ratio-based inference, even though the literature has quantified its potentially severe large-sample distortions. Building on Stock and Yogo (2005), we introduce the tF critical value function, leading to a standard error adjustment that is a smooth function of the first-stage F-statistic. For one-quarter of specifications in 61 AER papers, corrected standard errors are at least 49 and 136 percent larger than conventional 2SLS standard errors at the 5 percent and 1 percent significance levels, respectively. tF confidence intervals have shorter expected length than those of Anderson and Rubin (1949), whenever both are bounded.