Project Participants

Labor Market Sorting: Identification and Implications


 

Abstract:

Building on cutting-edge advances in economics and in machine learning, we develop a method to measure latent firm and worker characteristics in the data. This reveals the consequences for wages, output and productivity from moving any individual worker to any individual firm in the economy and enables providing answers to questions such as: Does the market allocate workers to the right jobs? Can this allocation be improved? Do large employers pay higher wages because they employ better workers? What are the sources of large wage differences across industries, occupations, or regions? Fundamentally, we show how the Danish government, using the data it already has access to, can overcome frictions in the labor market and improve allocation of workers to jobs.

Type:

Private (National)

Funder:

Carlsbergfondet

Status:

Running

Start Date:

01-02-2020

End Date:

31-01-2022

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