Data and Code for: IT and Urban Polarization

Principal Investigator(s):  View help for Principal Investigator(s) Jan Eeckhout, Universitat Pompeu Fabra; Christoph Hedtrich, Uppsala University; Roberto Pinheiro, Federal Reserve Bank of Cleveland

Version:  View help for Version V1

Name File Type Size Last Modified
  Aberdeen_sample 04/26/2024 05:01:PM
  Analysis 04/26/2024 05:00:PM
  Auxiliary_data 04/26/2024 05:01:PM
  Matlab 04/26/2024 05:30:PM
  Structural_Estimation 09/26/2024 08:23:AM
README_Final.pdf application/pdf 412.7 KB 07/15/2025 12:13:PM

Project Citation: 

Eeckhout, Jan, Hedtrich, Christoph , and Pinheiro, Roberto. Data and Code for: IT and Urban Polarization. Nashville, TN: American Economic Association [publisher], 2025. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2025-12-05. https://doi.org/10.3886/E201464V1

Project Description

Summary:  View help for Summary We show that differential IT investment across cities has been a key driver of job and wage polarization since the 1990s. Using a novel data set, we establish two stylized facts: IT investment is highest in firms in large and expensive cities, and the decline in routine cognitive occupations is most prevalent in large and expensive cities. To explain these facts, we propose a model mechanism where the substitution of routine workers by IT leads to higher IT adoption in large cities due to a higher cost of living and higher wages. We estimate the spatial equilibrium model to trace out the effects of IT on the labor market between 1990 and 2015. The decline in IT prices alone accounts for about 30 percent of the stronger displacement of routine cognitive jobs in expensive locations.

Scope of Project

Subject Terms:  View help for Subject Terms IT Investment; Job Polarization; Spatial Sorting; Urban Wage Premium
JEL Classification:  View help for JEL Classification
      D21 Firm Behavior: Theory
      J24 Human Capital; Skills; Occupational Choice; Labor Productivity
      J31 Wage Level and Structure; Wage Differentials
      R23 Urban, Rural, Regional, Real Estate, and Transportation Economics: Regional Migration; Regional Labor Markets; Population; Neighborhood Characteristics
Geographic Coverage:  View help for Geographic Coverage United States Metropolitan Areas
Time Period(s):  View help for Time Period(s) 1/1/1980 – 12/31/2015
Universe:  View help for Universe Employed Individuals 25 years old or older
Data Type(s):  View help for Data Type(s) census/enumeration data; survey data

Methodology

Data Source:  View help for Data Source
  • IPUMS data from the Census 1980, 1990, 2000.
  • IPUMS data from the American Community Survey 2005-2011, and 2014-2016.
  • 2015 Aberdeen Ci Technology (CiTDS) data.
  •  2015 National Establishment Time Series (NETS) data.
Unit(s) of Observation:  View help for Unit(s) of Observation Individuals, Firms, MSAs
Geographic Unit:  View help for Geographic Unit Metropolitan Statistical Areas (MSAs)

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Published Versions

V1 [2025-12-05]

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