We present a model in which managers are risk-averse and firms compete for scarce managerial talent ("alpha"). When managers are not mobile across firms, firms provide efficient compensation, which allows for learning about managerial talent and for insurance of low-quality managers. When...

This paper presents a market equilibrium model of CEO assignment, pay and incentives under risk aversion and heterogeneous moral hazard. Each of the three outcomes can be summarized by a single closed-form equation. In assignment models without moral hazard, allocation depends only on firm size...

In a labor market hierarchy, promotions are affected by the noisiness of information about the candidates. I study the hypothesis that males are more risk taking than females, and its implications for rates of promotion and abilities of survivors. I define promotion hierarchies with and without...

Measuring the value of labor-market hires for stock prices, be it underwriters when firms go public (IPOs) or chief executive officers (CEOs), is difficult due to selection. Opaque firms with higher costs of capital benefit more from prestigious underwriters, while productive firms benefit more...

We posit the problem of an autocrat who has to allocate access to the executive positions in his inner circle and define the career profile of his own insiders. Statically, granting access to an executive post to a more experienced subordinate increases political returns to the post, but is more...

We provide evidence that firms appoint independent directors who are overly sympathetic to management, while still technically independent according to regulatory definitions. We explore a subset of independent directors for whom we have detailed, micro-level data on their views regarding the...

Using a large sample of establishments drawn from the Multi-City Study of Urban Inequality (MCSUI) employer survey, we study gender differences in promotion rates and in the wage gains attached to promotions. Several unique features of our data distinguish our analysis from the previous...

Can an algorithm assist firms in their hiring decisions of corporate directors? This paper proposes a method of selecting boards of directors that relies on machine learning. We develop algorithms with the goal of selecting directors that would be preferred by the shareholders of a particular...