We present evidence on the labor supply of CEOs and on whether family and professional CEOs differ on this dimension. We do so through a new survey instrument that allows us to codify CEOs’ diaries in a detailed and comparable fashion and to build a bottom-up measure of CEO labor supply. The comparison of 1,114 family and professional CEOs reveals that family CEOs work 9% fewer hours relative to professional CEOs. Hours worked are positively correlated with firm performance, and differences between family and non-family CEOs account for approximately 18% of the performance gap between family and non-family firms. We investigate the sources of the differences in CEO labor supply across governance types by exploiting firm and industry heterogeneity and quasi-exogenous meteorological and sport events. The evidence suggests that family CEOs value—or can pursue—leisure activities relatively more than professional CEOs. Layperson summary

Does the “soft side” of management matter? Many managers assert that “firm culture” is strongly correlated with productivity, but there are few robust tests of this assertion. In a set of field experiments, we study driver productivity within a large US logistics company that is arguably transitioning from one relational contract to another, while leaving formal practices and incentives unchanged. We find that sites under the new contract are associated with 1/8 percent higher productivity. Our findings suggest that relational contracts have a first-order effect on productivity and that they can be altered over time.

Different agents need to make a prediction. They observe identical data, but have different models: they predict using different explanatory variables. We study which agent believes they have the best predictive ability—as measured by the smallest subjective posterior mean squared prediction error—and show how it depends on the sample size. With small samples, we present results suggesting it is an agent using a low-dimensional model. With large samples, it is generally an agent with a high-dimensional model, possibly including irrelevant variables, but never excluding relevant ones. We apply our results to characterize the winning model in an auction of productive assets, to argue that entrepreneurs and investors with simple models will be overrepresented in new sectors, and to understand the proliferation of “factors” that explain the cross-sectional variation of expected stock returns in the asset-pricing literature.

We develop a new method to measure CEO behavior in large samples via a survey that collects high-frequency, high-dimensional diary data and a machine learning algorithm that estimates behavioral types. Applying this method to 1,114 CEOs in six countries reveals two types: “leaders,” who do multifunction, high-level meetings, and “managers,” who do individual meetings with core functions. Firms that hire leaders perform better, and it takes three years for a new CEO to make a difference. Structural estimates indicate that productivity differentials are due to mismatches rather than to leaders being better for all firms.