Heterogeneous Complementarity and Team Design: The Case of Real Estate Agents

Workers often have unobserved characteristics, e.g., soft skills, that are important for teamwork. In this paper, we formulate and estimate a model of teamwork that imposes no functional form restrictions on the complementarity between different unobserved types of workers. Our modeling approach, which builds on the stochastic blockmodels in statistics (e.g., Bickel et al., 2013) and the econometric framework developed by Bonhomme (2021), that quantify individual contributions when only teams' outputs are observed. We apply our model to a data set from a leading Chinese real estate company; the data contain the complete history of team assignments, team performances, and detailed property characteristics. We find evidence that complementarities between different agent types are heterogeneous and cannot be captured by commonly used production functions. More specifically, workers of intermediate solo performance complement all other types of workers the most; the best solo-performing workers, however, are not the best team players. Our findings suggest that firms can improve productivity by redesigning teams without incurring additional hiring costs. Leveraging our complementarity estimates, we use counterfactual experiments to show that restructuring teams can improve overall team output by up to 28.4%.