This paper develops a simple model of firm entry, competition, and exit in oligopolistic markets. It features toughness of competition, sunk entry costs, and market-level demand and cost shocks, but assumes that firms' expected payoffs are identical when entry and survival decisions are made. We prove that this model has an essentially unique symmetric Markov-perfect equilibrium, and we provide an algorithm for its computation. Because this algorithm only requires finding the fixed points of a finite sequence of contraction mappings, it is guaranteed to converge quickly.

Using a sample of U.S. firms during the 1989–2015 period, we study whether the efficiency with which managers generate revenue is sensitive to monitoring by institutional shareholders. We find that institutional ownership is positively related to managerial efficiency. Our identification relies on a discontinuity in ownership around the Russell 1000/2000 Index threshold and suggests that the positive effect of institutional ownership on managerial efficiency is causal. Furthermore, we document that monitoring by institutions helps improve managerial efficiency, and that an exogenous increase in institutional ownership leads to higher pay-for-performance sensitivity. Finally, we find consistent results after excluding from our sample forced CEO turnovers, suggesting that institutional shareholders force incumbent managers to exert greater effort rather than influence the replacement of less efficient CEOs. Taken together, our findings highlight the important role played by institutional shareholders in getting the most out of corporate executives.

This study investigates how adopting new performance measures affects the decision process through which supervisors make subjective adjustments. In our setting, the Chinese government substituted economic value added (EVA) for return on equity (ROE) in the performance score formula it uses to evaluate State-Owned Enterprises (SOEs). In accordance with the Chinese government's objective to increase the capital efficiency of SOEs, supervisors shifted the weight in subjective adjustment decisions from ROE to EVA after EVA adoption. Consistent with EVA adoption creating fairness concerns, however, supervisors did not penalize SOEs for performing poorly on EVA when they performed well on ROE, and accomplished this by shifting the weight from EVA back to ROE. Additional analyses suggest that personal preferences motivated supervisors to make these lenient subjective adjustments. Overall, our findings indicate that adopting new performance measures creates fairness concerns that motivate supervisors to consider their personal preferences in subjective adjustment decisions.

We study public policies designed to improve access and reduce costs for in vitro fertilization (IVF). High out-of-pocket prices can deter potential patients from IVF, while active patients have an incentive to risk costly high-order pregnancies to improve their odds of treatment success. We analyze IVF's rich choice structure by estimating a dynamic model of patients' choices within and across treatments. Policy simulations show that insurance mandates for treatment or hard limits on treatment aggressiveness can improve access or costs, but not both. Insurance plus price-based incentives against risky treatment, however, can together improve patient welfare and reduce medical costs.

This paper presents a new approach to the measurement of the effects of spatial mismatch that takes advantage of matched employeremployee administrative data integrated with a person-specific job accessibility measure, as well as demographic and neighborhood characteristics. We focus on a group of job searchers for plausibly exogenous reasons: lower-income workers with strong labor force attachment separated during a mass layoff. Our results support the spatial mismatch hypothesis. We find that better job accessibility significantly decreases the duration of joblessness among lower-income displaced workers, especially for blacks, women, and older workers.

Agents in two-sided matching games vary in characteristics that are unobservable in typical data on matching markets. We investigate the identification of the distribution of unobserved characteristics using data on who matches with whom. In full generality, we consider many-to-many matching and matching with trades. The distribution of match-specific unobservables cannot be fully recovered without information on unmatched agents, but the distribution of a combination of unobservables, which we call unobserved complementarities, can be identified. Using data on unmatched agents restores identification.