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Measuring a contract's breadth: A text analysis

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  • Bryan McCannon
  • Joshua Hall
  • Yang Zhou

Abstract

We use a computational linguistic algorithm to measure the topics covered in teacher contracts. Topic modeling metrics are used to assess a contract's expansiveness. Our topic, diversity measurement, is then related to the prevalence of support staff. If more specialized services are provided, then contracts should be broader as they cover more employment relationships. We confirm a strong, statistically significant relationship and, thus, have a valid measurement of contract breadth.

Suggested Citation

  • Bryan McCannon & Joshua Hall & Yang Zhou, 2023. "Measuring a contract's breadth: A text analysis," American Journal of Economics and Sociology, Wiley Blackwell, vol. 82(1), pages 5-14, January.
    • Handle: RePEc:bla:ajecsc:v:82:y:2023:i:1:p:5-14
    DOI: 10.1111/ajes.12486
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    References listed on IDEAS

    as
    1. Joshua C. Hall & Donald J. Lacombe & Joylynn Pruitt, 2017. "Collective bargaining and school district test scores: evidence from Ohio bargaining agreements," Applied Economics Letters, Taylor & Francis Journals, vol. 24(1), pages 35-38, January.
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    4. McCannon, Bryan C., 2020. "Wine Descriptions Provide Information: A Text Analysis," Journal of Wine Economics, Cambridge University Press, vol. 15(1), pages 71-94, February.
    5. Matthew Gentzkow & Jesse M. Shapiro, 2010. "What Drives Media Slant? Evidence From U.S. Daily Newspapers," Econometrica, Econometric Society, vol. 78(1), pages 35-71, January.
    6. Carlo Schwarz, 2018. "ldagibbs: A command for topic modeling in Stata using latent Dirichlet allocation," Stata Journal, StataCorp LP, vol. 18(1), pages 101-117, March.
    7. Dyer, Travis & Lang, Mark & Stice-Lawrence, Lorien, 2017. "The evolution of 10-K textual disclosure: Evidence from Latent Dirichlet Allocation," Journal of Accounting and Economics, Elsevier, vol. 64(2), pages 221-245.
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