We develop a new method for estimating dynamic discrete choice models, such as Rust (1987), without distributional assumptions on error terms. Our method is tractable in that it does not require high-dimensional searches over the space of counterfactuals, and involves mainly linear programming and value function iterations. We show that the counterfactuals bounded by our method is fairly tight when applied to the Rust (1987) data. The method may therefore be useful to applied researchers in bounding parameter estimates and counterfactual outcomes in dynamic discrete choice models without distributional assumptions.

We analyze how CEO stock options compensation can be used as a commitment device in oligopolistic competition. We develop a two-stage model where shareholders choose managerial compensation to commit their managers to being aggressive in equilibrium. Our results may explain why some shareholders appear to incentivize ‘excessive’ risk taking through stock options compensation. We analyze how our results are impacted by product quality, marginal cost, product differentiation, and industry concentration. As motivation for our research, we show that there exists positive empirical correlation between industry concentration and options compensation vega within a sample of firms, as suggested by our model.

We analyze the Markov Perfect Equilibria of an infinite-horizon overlapping generations model with consumer lock-in to compare the performance of history-based and uniform pricing in growing and declining markets. Under history-based pricing, firms charge higher prices to locked-in customers and lower prices to new customers. We show that a high exit rate of consumers (sufficiently declining market) constitutes a sufficient condition for history-based pricing to generate higher average prices than uniform pricing, thereby harming consumer welfare. In contrast, a high consumer entry rate (sufficiently growing market) ensures that history-based pricing intensifies competition compared with uniform pricing.

Households still pay rent primarily with paper methods, even though electronic methods are featured more prominently among high-income, high-education, and high-rent households. These patterns may be explained either by the lack of landlord acceptance of electronic methods or by the unwillingness of tenants to pay using these methods.
The dominant methods for paying rent are cash (22 percent), check (42 percent), and money order (16 percent). Electronic methods are still rarely used, at 8 percent for bank account number payment and 7 percent for online banking bill payment, and less than 2 percent for debit and credit cards.
Compared with other large bill payments of more than $200, rental payments are much more likely to be made with paper-based methods than with electronic methods, despite the recent attempts by start-ups to make it easier for landlords to accept electronic payments. They are also much less likely to be automatic.
Check and electronic methods are more frequently used for higher-value transactions and by those with higher income and education.