Combined Distributional Effects of the One Big Beautiful Bill Act and of Tariffs

This Appendix explains how we calculate the numbers in this report. The results can be replicated by running this R code.

The Budget Lab has previously presented estimates of the distributional impact of tariffs. Information on our overall tariff methodology can be found here. Our prior distributional methodology is based in part on Clausing and Lovely (2024): The Budget Lab calculates the consumption shares, relative to income, of each category of good exposed to tariffs by income decile using the Consumer Expenditure Survey (CEX), then uses this result to distribute our aggregate price-effect calculation across different consumption units. For this report, however, we needed to modify our methodology to produce an “apples-to-apples" comparison to CBO’s estimates. There are two main changes required to harmonize the concepts in our prior distributional approach with those of CBO.

The first change is that we shift to ranking households by an income measure that adjusts for family size. CBO ranks households by equivalized income after taxes transfers, dividing income by the square root of family size. Our prior estimates used published CEX distributional data, which do not adjust for household size when constructing income percentiles.

The second change is that we use a broader measure of after-tax-and-transfer income when calculating the percent change in resources due to tariffs. The measure of after-tax-and-transfer income used in our prior analyses is taken directly from the CEX, which is known to have issues with income underreporting at both the low and high ends of the income distribution. (In fact, previously TBL did not report tariff distributional effects at the first income decile for this very reason). CBO, on the other hand, corrects for these issues in their distributional work. Therefore, to harmonize our tariff estimates with CBO’s, we take their after-tax-and-transfer income estimates as the baseline against which relative effects are measured. Relative to our prior analyses, this change reduces the measured regressivity of tariffs.

To implement these changes, we begin with the “Additional Data for Researchers” files from CBO’s most recent Distribution of Household Income report. These files report estimated average fiscal income and its components for each quintile. To impute consumption for each quintile, we rank consumption units in the 2019 CEX by equivalized after-tax-and-transfer income and calculate each quintile’s share of total consumption.² We then distribute 2019 personal consumption expenditures (PCE) to each quintile in those proportions and calculate average consumption. To this quantity, we apply our estimates of the quintile-specific tariff-driven percent change in PCE price index, an estimate which accounts for compositional differences in spending patterns across income groups. This step generates gross tariff burden in dollars. Finally, we divide this quantity by after-tax-and-transfer income to generate a relative measure of distributional impact. We validate this process by multiplying the dollar-amount gross tariff burdens by the ratio of projected 2026 PCE to 2019 PCE and comparing to our estimates of 2026 gross tariff revenue, finding a difference of about 2%.

We also account for two additional factors affecting the net distributional impact of tariffs for the first time in TBL’s analysis on this topic. These factors are related to the inflation indexing rules for government benefits and taxes:

1. Higher transfer benefits. Tariffs, a type of indirect tax, create a wedge between the level of producer prices and of consumer prices. This wedge can either be resolved in the form of higher consumer prices (“pass-forward”) or lower nominal market incomes (“pass-backward”). While these scenarios are economically equivalent in the long run, our tariff analysis assumes the Fed accommodates the tariffs and allows the price level to rise—that is, the pass-forward scenario—since in this case the wedge mechanically is a one-time effect on the price level.
   
   When the price level rises, certain government transfer benefits rise automatically due to cost-of-living adjustments. In other words, the burden of tariff-driven price hikes is offset to the extent that consumption is funded by indexed transfer benefits. Because these benefits make up a larger fraction of income for lower-income households, this dynamic reduces the regressivity of tariffs. We account for this dynamic by adjusting each quintile’s OASDI, SSI, and SNAP income proportionally to the PCE price level impact.
    
2. Lower individual income taxes. The same logic applies to individual income taxes, since most provisions are indexed to inflation. In the pass-forward scenario, nominal market incomes are unchanged, but tax brackets, the standard deduction, etc. are higher, and individual income taxes fall as a result. To estimate this effect in Tax-Simulator, we run a scenario where the inflation index and Social Security benefits are increased by the estimated PCE price level change, scored against a scenario where the OBBBA tax law applies.

The inclusion of these factors represents a new, permanent feature of Budget Lab tariff distribution methodology, not a change made specifically for this analysis in order to harmonize our concepts with those of CBO. The net effect of these two factors is to reduce the net burden of tariffs across all income groups and slightly reduce their regressivity.