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.

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.