• 2023
• Working Paper

Consider a leader’s decision whether to persist with an unsuccessful R&D project or to terminate the project in favor of a new project with an uncertain value. How does that decision affect the effort exerted by the manager assigned to the project? To study this question we build and analyze an equilibrium, infinite-horizon model which embeds a search problem with an agency problem. We assess the policy value of a leader’s persistence instrument under conditions of complete and incomplete information. Among other things, we find that persistence takes advantage of a manager’s incentive to gain access to future, potentially higher-payoff projects to induce effort on the current project. Furthermore, when the leader has superior information about the value of the current project, the manager may choose to delay effort to better take advantage of the information signal provided by the leader’s persistence choice.

• January 2023
• Case

In September 2019, Zaoui & Co.’s close-knit team of professionals convened for their annual off-site. In its nine years of operation, the boutique investment bank founded by the brothers Michael (HBS ’83) and Yoel Zaoui (Stanford GSB ’88), had garnered a track record for advising on several significant transactions across Europe. At the retreat, the firm’s leaders were debating whether to (a) continue as a small boutique focused on mergers and acquisitions (M&A) advisory services, (b) grow aggressively in M&A advisory, or (c) diversify into principal investing. Each alternative presented strategic and organizational challenges and opportunities. Whichever path they elected to pursue would significantly influence what kind of firm Zaoui & Co. would become.

• January 2023
• Article

Firm-induced migration typically entails firms relocating workers to fill value-creating positions at destination locations. But such relocated workers are often exposed to external employment opportunities at their destinations, possibly triggering turnover. We conceptualize the firm-induced migration path, consisting of the relocated workers’ place of origin and destination, as relevant in determining worker performance and post-relocation turnover. Using a unique dataset from a large Indian technology firm that hires talent from both large cities and smaller towns, we document robust econometric patterns by exploiting the firm’s randomized assignment of workers to production centers across the country. These production centers are located in the largest technology cluster in India (Bangalore), smaller technology clusters, and non-cluster locations. We find that the firm-induced migration path shapes both worker performance and turnover. Compared to workers from large cities, workers from smaller towns achieve higher performance when relocated to Bangalore than to other production centers, but are also more likely to join competing firms. Fine-grained data on employment and human-capital-augmentation opportunities at workers’ destination locations, and on socioeconomic conditions in workers’ places of origin, help us rule in an abductive explanation: across firm-induced migration paths, differences in external labor-market opportunities between workers’ places of origin and their destinations, as well as intrafirm skill-development opportunities at the destination, are related to heterogeneous human-capital outcomes.