We propose and implement an estimator for identifiable features of correlated random coefficient models with binary endogenous variables and nonadditive errors in the outcome equation. It is suitable, e.g., for estimation of the average returns to college education when they are heterogeneous...

A fundamental identification problem in program evaluation arises when idiosyncratic gains from participation and the treatment decision depend on each other. Imbens and Angrist (1994) were the first to exploit a monotonicity condition in order to identify an average treatment effect parameter...

We study the effects of improvements in eBay's rating mechanism on seller exit and continuing sellers' behavior. Following a large sample of sellers over time, we exploit the fact that the rating mechanism was changed to reduce strategic bias in buyer rating. That improvement did not lead to...

We study the effects of improvements in eBay's rating mechanism on seller exit and continuing sellers' behavior. Following a large sample of sellers over time, we exploit the fact that the rating mechanism was changed to reduce strategic bias in buyer rating. That improvement did not lead to...

We study the effects of improvements in market transparency on eBay on seller exit and continuing sellers' behavior. An improvement in market transparency by reducing strategic bias in buyer ratings led to a significant increase in buyer valuation especially of sellers rated poorly prior to the...

We study the effects of improvements in market transparency on eBay on seller exit and continuing sellers' behavior. An improvement in market transparency by reducing strategic bias in buyer ratings led to a significant increase in buyer valuation especially of sellers rated poorly prior to the...

We study the effects of improvements in market transparency on eBay on seller exit and continuing sellers’ behavior. An improvement in market transparency by reducing strategic bias in buyer ratings led to a significant increase in buyer valuation especially of sellers rated poorly prior...