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Emerging the U.S. Firm Size Distribution Using 4.2 Billion Individual Tax Records

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  • Joseph A.E. Shaheen

    (George Mason University, Fairfax, VA, USA)

Abstract

The firm size distribution describes important economic and labor properties of any economy. Government entities must expend enormous resources in data collection, cleaning, and analysis in order to construct this and other important distributions describing the aggregate properties large economies. In the U.S., this process can be cumbersome and relies on querying multiple databases and utilizing significant computational resources. I show that construction of the U.S. firm size distribution is plausible using only individual income tax records (W2s) drawn directly from Internal Revenue Service tax records (micro data) and that the emergent distribution is statistically identical to what is reported by the United States Census Bureau. The methodology represents an incremental advance for population-scale studies in economic analysis—specifically firm and labor analysis. Finally, this paper acts as a re-validation of earlier work in fitting the firm size distribution.

Suggested Citation

  • Joseph A.E. Shaheen, 2019. "Emerging the U.S. Firm Size Distribution Using 4.2 Billion Individual Tax Records," Proceedings of the 12th International RAIS Conference, April 3-4, 2019 9JS, Research Association for Interdisciplinary Studies.
    • Handle: RePEc:smo:cpaper:9js
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    References listed on IDEAS

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    3. Reed, William J., 2001. "The Pareto, Zipf and other power laws," Economics Letters, Elsevier, vol. 74(1), pages 15-19, December.
    4. Evans, David S, 1987. "Tests of Alternative Theories of Firm Growth," Journal of Political Economy, University of Chicago Press, vol. 95(4), pages 657-674, August.
    5. Evans, David S, 1987. "The Relationship between Firm Growth, Size, and Age: Estimates for 100 Manufacturing Industries," Journal of Industrial Economics, Wiley Blackwell, vol. 35(4), pages 567-581, June.
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    Keywords

    firm size; labor; taxation; data policy; economic analysis; data science;
    All these keywords.

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