Macroeconomics of Labor Market Sorting

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Suppose one day all workers in the U.S. were randomly reallocated across all existing jobs. Would there be any effect on output? It seems likely that the answer is ``yes''. This suggests that aggregate output and productivity depend on the actual allocation of individual workers to particular jobs. This project extends the state-of-the-art theory of sorting of workers across jobs to include the ability of workers to search for better jobs while employed. It then shows that, using only routinely available matched employer-employee data on wages and labor market transition rates, it is possible to recover the output of any observed employer-employee match and the consequences for output, productivity, and wages of moving any worker to any firm in the economy. The proposed model and measurement method will be used to provide substantive empirical answers to a number of classic but yet unanswered economic questions. The intellectual merit of the project lies in the following. (1) The PI develops an assortative matching model with on-the-job search and proves its nonparametric identification. (2) The PI draws on the recent advances in computer science to develop algorithms to implement the proposed identification strategy in practice given the potential limitations of existent data sets. (3) The PI will provide the theoretical methodology for answering important empirical questions in the context of an equilibrium model. (4) The PI will provide substantive answers to these questions. The project will have a broad impact. (1) It will provide a new model and empirical methodology for studying sorting in the labor market. (2) It will develop and and make publicly available the computational tools that enable this study. (3) New empirical findings obtained using these tools will provide a better understanding of fundamental economic issues and have a potential to substantially impact the design and evaluation of existing public policies. Fundamentally, the PI shows how the US government, using the data it already has access to, can to overcome frictions in the labor market and improve allocation of workers to jobs. This may eventually result in a substantial improvement in economic competitiveness of the United States. The results will also inform optimal design of policies, such as unemployment insurance. (4) It will provide training to graduate and postgraduate students in the development and applications of these tools and methods. (5) The results of this research will be presented at prominent national and international academic and policy conferences and seminars. They are also likely to become a standard entry on the reading lists in advanced courses.