Jeremy Lise

The effect of coworkers on the learning and the productivity of an individual is measured combining theory and data. The theory is a frictional equilibrium model of the labor market in which production and the accumulation of human capital of an individual are allowed to depend on the human capital of coworkers. The data is a matched employer-employee dataset of US firms and workers. The measured production function is supermodular. The measured human capital function is non-linear: Workers catch-up to more knowledgeable coworkers, but are not dragged-down by less knowledgeable ones. The market equilibrium features a pattern of sorting of coworkers across teams that is inefficiently positive. This inefficiency results in low human capital individuals having too few chances to learn from mo...

We develop an empirical search-matching model which is suitable for analyzing the wage, employment and welfare impact of regulation in a labor market with heterogeneous workers and jobs. To achieve this we develop an equilibrium model of wage determination and employment which extends the current literature on equilibrium wage determination with matching and provides a bridge between some of the most prominent macro models and microeconometric research. The model incorporates productivity shocks, long-term contracts, on-the-job search and counter-offers. Importantly, the model allows for the possibility of assortative matching between workers and jobs due to complementarities between worker and job characteristics. We use the model to estimate the potential gain from optimal regulation and...

This paper makes three primary contributions. First, we demonstrate the usefulness of general equilibrium models as tools with which to draw policy implications for policies implemented in practice only as small-scale social experiments. Second, we illustrate the usefulness of social experiments as a tool to evaluate equilibrium models. In particular, we calibrate our model using only data on an experimental control group and from general data sets, and then use it to predict (in partial equilibrium) the outcomes experienced by an experimental treatment group. We find that it predicts these outcomes remarkably well. Third, we apply our methodology to the evaluation of the Canadian Self-Sufficiency Project (SSP), a policy providing generous financial incentives for Income Assistance (IA) re...