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Using Social Media to Measure Labor Market Flows

Author

Listed:
  • Dolan Antenucci
  • Michael Cafarella
  • Margaret Levenstein
  • Christopher Ré
  • Matthew D. Shapiro

Abstract

Social media enable promising new approaches to measuring economic activity and analyzing economic behavior at high frequency and in real time using information independent from standard survey and administrative sources. This paper uses data from Twitter to create indexes of job loss, job search, and job posting. Signals are derived by counting job-related phrases in Tweets such as "lost my job." The social media indexes are constructed from the principal components of these signals. The University of Michigan Social Media Job Loss Index tracks initial claims for unemployment insurance at medium and high frequencies and predicts 15 to 20 percent of the variance of the prediction error of the consensus forecast for initial claims. The social media indexes provide real-time indicators of events such as Hurricane Sandy and the 2013 government shutdown. Comparing the job loss index with the search and posting indexes indicates that the Beveridge Curve has been shifting inward since 2011. The University of Michigan Social Media Job Loss index is update weekly and is available at http://econprediction.eecs.umich.edu/.

Suggested Citation

  • Dolan Antenucci & Michael Cafarella & Margaret Levenstein & Christopher Ré & Matthew D. Shapiro, 2014. "Using Social Media to Measure Labor Market Flows," NBER Working Papers 20010, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:20010
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    References listed on IDEAS

    as
    1. Miles Kimball & Helen Levy & Fumio Ohtake & Yoshiro Tsutsui, 2006. "Unhappiness after Hurricane Katrina," NBER Working Papers 12062, National Bureau of Economic Research, Inc.
    2. Régis Barnichon & Bart Hobijn & Ayşegül Şahin, 2010. "Which industries are shifting the Beveridge curve?," Working Paper Series 2010-32, Federal Reserve Bank of San Francisco.
    3. Steven L. Scott & Hal R. Varian, 2015. "Bayesian Variable Selection for Nowcasting Economic Time Series," NBER Chapters, in: Economic Analysis of the Digital Economy, pages 119-135, National Bureau of Economic Research, Inc.
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    More about this item

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • J60 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - General

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