Knowledge Diffusion Within and Across Firms

We develop a large-firm sorting model to study the way knowledge diffuses within and across firms. We build on \citet{shimer2000assortative} and allow for workers within a firm to influence each other's knowledge. In particular, we extend the framework to allow for a given worker's human capital to influence the future path of their coworker's human capital, and vice versa. In contrast to standard sorting models, a firm's type is no longer exogenous; it is given by the distribution of human capital of its workers. Firms are created by workers spinning off and recruiting their own employees which is an important driver of knowledge diffusion. We then use micro wage data and job mobility patterns from the LEHD (the LEHD covers all private sector jobs in the US), as well as startup patterns from the Integrated LBD, to separately estimate the knowledge diffusion process and the degree of worker complementarities in production. The data yield 5 new facts: (1) the number of coworkers has an [X] effect on an individual's wage, (2) the lowest wage coworker has an [X] effect on an individual's wage, (3) the highest wage coworker (superstar) has an [X] effect on an individual's wage, (4) workers with [X] individual wages and [X] coworker wages are more likely to start their own business (explicitly controlling for access to credit), and (5) there are [X] sorting patterns, i.e. workers with higher wages are more likely to move to firms that pay [X] average wages. We use fact (5) to estimate worker complementarities in production and we use facts (1) through (4) to discipline the knowledge diffusion process. We then use the estimated model to study various counterfactuals, including the way labor market distortions, such as firing taxes, impede mobility and affect the diffusion of knowledge.