We extend the literature structurally estimating social preferences by accounting for the desire to adhere to social norms. Our representative agent is strongly motivated by norms and failing to account for this causes us to overestimate how much agents care about helping those who are worse...

The theory of compensating differentials has proven difficult to test with observational data: the consequences of selection, unobserved firm and worker characteristics, and the broader macroeconomic environment complicate most analyses. Instead, we construct experimental, real-effort labor...

Despite the "1/N problem" associated with profit sharing, the empirical literature finds that sharing profits with workers has a positive impact on work team and firm performance. We examine one possible resolution to this puzzle by observing that, although the incentive to work harder under...

The theory of compensating differentials has proven difficult to test with observational data: the consequences of selection, unobserved firm and worker characteristics, and the broader macroeconomic environment complicate most analyses. Instead, we construct experimental, real-effort labor...

The theory of compensating differentials has proven difficult to test with observational data: the consequences of selection, unobserved firm and worker characteristics, and the broader macroeconomic environment complicate most analyses. Instead, we construct experimental, real-effort labor...

Despite the "1/N problem" associated with profit sharing, the empirical literature finds that sharing profits with workers has a positive impact on work team and firm performance. We examine one possible resolution to this puzzle by observing that, although the incentive to work harder under...

We extend the literature structurally estimating social preferences by accounting for the desire to adhere to social norms. Our representative agent is strongly motivated by norms and failing to account for this causes us to overestimate how much agents care about helping those who are worse...