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The International Price of Remote Work

Agostina Brinatti

University of Michigan

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Remote Work Conference - Stanford

October 14, 2022

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Alberto Cavallo

Harvard Business School

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Javier Cravino

University of Michigan

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Andres Drenik

UT Austin

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Remote work is integrating global labor markets

  • A large fraction of jobs can now be done remotely across borders
    • ICT-enabled service trade quadrupled since 2000, now 70% of all trade in services in the US
    • After Covid, US companies are shifting to a more flexible work-from-anywhere model
    • PWC survey: 28% of employers plan to allow remote work in another country

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  • Question: How are these remote wages set?
    • Are wages different across regions and countries?
    • Are remote wages more sensitive to international competition and shocks?

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  • This paper: new data from a globalized remote labor market

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What we do:

  • Scrape data from a large web-based job platform
    • Matches workers with employers from around the world
    • Work can be delivered online 🡪 window into a globalized market for remote work
    • Rapidly growing sector 🡪 number tripled in past decade, with $50 billion in revenues in 2020

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  • Main Findings

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    • Large wage differences across locations
      • Wages vary with workers’ locations, not employers’ locations

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    • Remote wages are highly sensitive to foreign shocks
      • Dollar wages respond little to dollar exchange rates in worker’s country
      • Wages respond strongly to foreign competitors’ wages

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Data

  • The Platform:
    • Largest online platform: millions of users, 3 million jobs worth $1 billion are posted annually
      • We focus on 100K workers that are active in our sample.
    • Specialized on remote jobs – from accountants to web developers

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12 broad and 91 narrow sectors

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A typical platform

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Job history Data

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Data

  • Job-based data collected once between 2019 and early 2020 🡪 “transacted wages”
    • 380,000 jobs from 2012 to 2020
    • Country of employee and employer

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  • Worker-based data collected in 2019, 2020, and 2021 🡪 “ask wages”

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Where are workers and employers located?

  • Workers more spread around the world 🡪 70% in non-OECD
  • Employers concentrated in developed countries 🡪 88% in OECD

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Wages vary across workers in different countries

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  • Large differences, correlated with GDP per capita in worker’s country
  • Is this driven by worker characteristics, sector, or employer’s location?

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Slope = 0.25, R2 = 0.47

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Wages and Observables

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Wages vary across workers in different countries

  • After controls, large differences remain 🡪 e.g. Indian worker receives 1/3rd of US wage
  • Smaller than differences in GDP

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Slope = 0.22 , R2 = 0.58

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Wages vary much less with employers’ country

  • Little evidence of workers charging different wages to employers in different countries

Slope = 0.07 (0.02) , R2 = 0.48

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Wages also vary across workers in different US states

  • Similar pattern across US states 🡪 slope 0.24 (0.04)

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Stylized model of remote wage determination

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Implications for wage changes

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Estimating ERPT into remote wages

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Estimating response to changes in competitors’ wages

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Remote wages are highly sensitive to foreign shocks

  • Rupee falls 10% 🡪 Dollar wage falls 2.1%, Rupee wage rises 7.9%
  • Competitor wage index rises 10% 🡪 Dollar wage rises 7.4%

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Measuring offshorability using transacted data

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Which jobs are more offshorable?

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Less wage dispersion in occupations that are more offshorable

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Main take aways

  • New data from web-based job platform to study remote wages

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  • Large wage gaps in remote wages across countries and regions
    • Worker location account for up to 1/3 of the variance in wages
    • Wages correlates with income per capita in worker’s locations

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  • Remote wages are highly sensitive to foreign shocks
    • Change in own and foreign exchange rates
    • Change in competitor’s wages
    • Similar findings obtained in the literature on price of tradable goods

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  • New measures of job offshorability based on cross-border transactions
    • Less wage dispersion in jobs that are more offshored

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Additional Slides

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Robustness

  • Ask wage data
  • Alternative sets of fixed effects
  • Condition on wage change
  • Alternative set of competitors
  • Placebo 🡪 competitors in other sectors

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Summary Statistics

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Wages and workers characteristics

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Remote vs. non-remote wages

  • Non-remote wages obtained from ICP 2011 data
  • Slope 0.2 (0.03) 🡪 similar to our results with GDP per capita

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Pricing to Market

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Equilibrium wages

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Offshoring with SOC categories

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Export Prices and GDP per-capita

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Distribution of wage changes : transacted wage data

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Distribution of wage changes : ask wage data

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Market shares by sector

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Ask (Posted) vs Transacted Wages

Binned scatterplot

  • Slope implies that for each additional dollar asked, they get $0.91
  • Intercept 🡪 average transacted wages are 2% lower than ask wage

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Labor Demand

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Labor supply