State and Local Sales Taxes (Marginal Increase in the Sales Tax Rate)
Introduction
Sales taxes are the second largest source of tax revenue for state and local governments in the United States. Forty-five states and the District of Columbia levy a statewide sales tax on most goods and some services, and counties, cities and special districts frequently add their own rate on top.
Gaarder and Henry de Frahan (2025) estimate the welfare costs of various changes to state sales tax rates. The analysis combines NielsenIQ Retail Scanner Data (weekly sales, prices and volumes from approximately 38,000 stores in 48 states over 2006–2016) with a county-level panel of sales tax rates built from Thomson Reuters OneSource. The estimation sample keeps Food, Drug and Mass Merchandiser stores, where NielsenIQ coverage is highest, and the 263 best-selling product modules (the top quartile of 2008 sales), giving a balanced panel of module-store pairs across 22,626 stores in 2,180 counties observed at six-month frequency. Because sales tax bases are set state by state, with extensive exemptions, the paper hand-collected the taxability status of each of the 263 modules in each of the 48 states for every year of the sample.
Identification comes from staggered changes in state, county and city sales tax rates: 2,974 rate changes between 2008 and 2014. The average increase was 0.54 percentage points and the average decrease 0.66 percentage points. The paper finds that pass-through of the tax to consumer prices is essentially complete, suggesting that consumers bear the full incidence of these tax changes. A one percent increase in the tax-inclusive price reduced quantity sold by about 0.5 percent, with the adjustment complete 18 to 24 months after the change. Instrumenting the consumer price with the tax change gives a demand elasticity of 0.453, the causal input to the MVPF estimates.
Using the taxable product modules represented in their NielsenIQ sample, the paper estimates the MVPF of a marginal increase in the sales tax rate for the average U.S. state. The paper separately estimates the MVPF of moving from no tax to the current sales tax rates (equivalent to eliminating state sales taxes) and the MVPF of a 5 percentage point increase in the sales tax rate.
MVPF = 1.0
Net Cost
Net cost has two components, and is expressed per dollar of revenue the tax increase would mechanically collect.
The mechanical component is +$1.000: raising the rate collects the additional tax on every unit consumers were already buying across the taxable markets in the reform.
The fiscal externality is −$0.027: The higher tax-inclusive price reduces the quantity sold, shrinking the base on which the tax is levied. Its size is the sales-weighted product of the demand elasticity and the existing tax wedge across taxable markets,
where cm defines a market (county – product module), \zeta_{cm} is market cm’s share of sales and \varepsilon^D = 0.453 is the estimated demand elasticity under log-linear (isoelastic) demand. Because pass-through is complete and supply perfectly elastic, the producer price does not move and the whole quantity response is a demand response.
Net cost is therefore $1.000 − $0.027 = $0.973 per dollar mechanically collected: the government keeps about 97 cents of every statutory dollar. The paper posits two reasons for the small offset: Initial tax rates are modest, so the wedge the elasticity is multiplied by is small; and demand for the best-selling packaged goods in the sample is inelastic at the relevant prices.
Willingness to Pay
Willingness to pay is the combined amount consumers and firms would pay to avoid the tax increase: $1.000 per dollar of mechanically raised revenue. For a marginal change in the sales tax rate, the envelope theorem eliminates the first-order effects of behavioral responses on consumer and firm welfare.
The split between consumers and firms is governed by the pass-through rate. Consumers lose \rho of each mechanical dollar and firms lose the remainder through the fall in the producer price. The paper estimates pass-through of 1.034 (SE 0.028), which suggests consumers bear the entire burden.
MVPF Summary
Dividing willingness to pay by net cost gives $1.000 / $0.973 = 1.028. Equivalently, in the closed form the paper derives for the case of complete pass-through,
Every additional dollar of revenue raised through a marginal increase in sales taxes imposes about $1.03 of welfare loss on consumers and firms — roughly 3 cents more than the revenue collected. The same figure applies to a marginal cut: each dollar of revenue forgone delivers about $1.03 of private benefit.
The result is robust to relaxing the model assumptions:
- This is the point-identified estimate under iso-elastic demand. Under the most flexible specification considered (an eighth-order polynomial), the MVPF is bounded between 1.009 and 1.036.
- Allowing imperfect competition, the paper backs out a conduct parameter of 0.002 from the observed pass-through and the bounds are essentially unchanged.
- Under imperfect salience the envelope theorem no longer holds, because consumers are buying more of the taxed good than they would if they attended fully to the tax. The paper reports that at a salience parameter of 0.25 the MVPF of a marginal increase falls to between 1.001 and 1.009 under the most flexible demand shape.
The paper also computes the MVPF state by state. Bounds for an individual state are somewhat wider than for the average state, but for 40 of the 44 states in the sample the marginal MVPF can be bounded below 1.05 even under the most flexible demand shape; across all individual states the estimates run from 1.003 to 1.065.
References
Gaarder, Ingvil and Lancelot Henry de Frahan (2025). “The Welfare Effect of Marginal and Nonmarginal Changes in Sales Taxes in the U.S.” Becker Friedman Institute Working Paper No. 2025-83. https://bfi.uchicago.edu/working-papers/the-welfare-effect-of-marginal-and-nonmarginal-changes-in-sales-taxes-in-the-u-s/
Policy Features
- Category
- Taxes
- Sub-Category
- Local Taxes/Subsidies
- Beneficiary Type(s)
- Adults
- Country of Implementation
- United States
- Year of Implementation
- 2006-2016
- Empirical Method
- Difference in Differences
- Research Type
- Primary
- Peer Reviewed
- No