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Bartik Instruments: What, When, Why, and How

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Listed:
  • Paul Goldsmith-Pinkham
  • Isaac Sorkin
  • Henry Swift

Abstract

The Bartik instrument is formed by interacting local industry shares and national industry growth rates. We show that the Bartik instrument is numerically equivalent to using local industry shares as instruments in a GMM estimator and discuss how different asymptotics imply different identifying assumptions. We argue that in most applications the identifying assumption is in terms of industry shares. Finally, we show how to decompose the Bartik instrument into the weighted sum of the just-identified instrumental variables estimators. These weights measure how sensitive the parameter estimate is to each instrument. We illustrate our results through four applications: estimating the inverse elasticity of labor supply, estimating local labor market effects of Chinese imports, estimating the fiscal multiplier using defense spending shocks, and using simulated instruments to study the effects of Medicaid expansions.

Suggested Citation

  • Paul Goldsmith-Pinkham & Isaac Sorkin & Henry Swift, 2018. "Bartik Instruments: What, When, Why, and How," NBER Working Papers 24408, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:24408
    Note: CF CH EFG ITI LS
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    References listed on IDEAS

    as
    1. Jaeger, David A & Ruist, Joakim & Stuhler, Jan, 2018. "Shift-Share Instruments and the Impact of Immigration," CEPR Discussion Papers 12701, C.E.P.R. Discussion Papers.
    2. Jerry A. Hausman & Whitney K. Newey & Tiemen Woutersen & John C. Chao & Norman R. Swanson, 2012. "Instrumental variable estimation with heteroskedasticity and many instruments," Quantitative Economics, Econometric Society, vol. 3(2), pages 211-255, July.
    3. Timothy J. Bartik, 1991. "Who Benefits from State and Local Economic Development Policies?," Books from Upjohn Press, W.E. Upjohn Institute for Employment Research, number wbsle.
    4. Simon Galle & Andrés Rodríguez-Clare & Moises Yi, 2017. "Slicing the Pie: Quantifying the Aggregate and Distributional Effects of Trade," NBER Working Papers 23737, National Bureau of Economic Research, Inc.
    5. Sarah R. Cohodes & Daniel S. Grossman & Samuel A. Kleiner & Michael F. Lovenheim, 2016. "The Effect of Child Health Insurance Access on Schooling: Evidence from Public Insurance Expansions," Journal of Human Resources, University of Wisconsin Press, vol. 51(3), pages 727-759.
    6. Bound, John & Holzer, Harry J, 2000. "Demand Shifts, Population Adjustments, and Labor Market Outcomes during the 1980s," Journal of Labor Economics, University of Chicago Press, vol. 18(1), pages 20-54, January.
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    More about this item

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • J0 - Labor and Demographic Economics - - General
    • J2 - Labor and Demographic Economics - - Demand and Supply of Labor

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