Measuring Tax Complexity in the United States (with Ryan Oprea and Alex Rees-Jones)

Tax complexity its clear importance to public finance, few formal and precise measures of tax complexity are currently available. We develop a new measure of tax complexity based on the number of discrete tax-form cells that an individual must consider in order to form a sufficiently accurate forecast of tax burden or marginal tax rates. We calculate our measures within the IRS Tax Model Files and use these data to characterize tax complexity from 1960 through 2012. We document how complexity evolved across time and how it was influenced by tax reforms, both on average and across income groups. We further use this analysis to characterize the nature of “complexity inequality” and its evolution across time. We additionally explore the use of our complexity measures as control variables in elasticity analysis, and examine how inference about tax elasticity is influenced by heterogeneity in complexity across people or across time.

Recommended citation: Kassirra, Dominic, Ryan Oprea, and Alex Rees-Jones (2024). "Measuring Tax Complexity in the United States" Work in progress. 1(1).