The Inner Beauty of Firms

Abstract

Using millions of task assignments from salon management software, I find significant establishment-level dispersion in labor productivity and internal task specialization and a strong association between the two that is unexplained by establishment size. The 25% most specialized salon-quarters are on average 68% more productive than the bottom 25%. To rationalize these facts, I identify and estimate a model where competing firms assign tasks to workers with multidimensional skills in light of firm-specific organization costs. I show that accounting for task specialization can qualitatively change the productivity implications of economic shocks. Without internal reorganization, immigration of low-wage workers into Los Angeles County provides a competitive advantage to less productive salons, replacing specialized with generalist jobs and reducing labor productivity by 1.0%. With internal reorganization, all types of salons adjust to incorporate immigrant skills, prices fall and market shares rise at most salons, and specialized jobs are created increasing labor productivity by 1.4%.

Type
Presentations
  • Cowles Models and Measurement at Yale SOM
  • Southwestern Economic Theory Conference
  • ZEW Research with and within Organisations
  • MIT Sloan
  • Society for Institutional and Organizational Economics (SIOE)
  • Stanford Institute for Theoretical Economics
  • Duke Fuqua Junior Strategy Conference
  • UGA Terry College of Business
  • UPenn Labor, Firms and Macro Workshop
  • Society of Economic Dynamics
  • Harvard Business School
  • University of Chicago Booth
  • Cornell
  • Boston University
  • UNC Chapel Hill
  • Washington University St. Louis Olin
  • University of Wisconsin Madison
  • Claremont McKenna
  • Southern Economic Association Annual Meeting
  • Occidental College
  • GLO Global Conference
  • Urban Economics Association European Meeting
Awards
  • ZEW With and Within Orgs. Early Career Researcher Best Paper Prize
  • Oliver E. Williamson Best Conference Paper Award (SIOE)