The Citizens for Tax Justice (CTJ) and Institute on Taxation and Economic Policy (ITEP), amongst other progressive organizations, have put forth the claim that our tax code is nearly flat on the basis that “regressive” consumption taxes in state/local tax codes offset federal and (to a lesser extent) state income tax progressivity.
The problem with almost all of these analysis is that they all invariably hinge on the fact that their reported ratios between consumption and income is greater than 1 at lower income levels. In other words, they are counting consumption taxes in the numerator that are not included in the income base (the denominator).
ITEP claims, in their description, that they’re correlating consumption patterns in the BLS’s Consumer Expenditure Survey to reported income. The problem with this approach is that the BLS CEX consistently indicates that the ratio between consumption to “income” exceeds 1 just shy of the 50th percentile on down (the bottom is >2x)
ITEP further papers over these flaws by effectively hiding non-linearity at negative numbers in their models (e.g., consumption 20x negative income).
Some money quotes on their model:
Our procedure for imputing consumption onto individual tax records can be thought of as involving two distinct steps: (i) econometrically estimating the necessary relationships for each of the desired consumption items from the Consumer Expenditure Survey (CES); and (ii) using the resulting regression coefficients to simulate consumption on the merged data file for non-dependents. Implicit in this approach is reliance on the strong separability of a utility function over different categories of consumption; i.e., we used a “utility tree” approach to estimate several systems of share equations.
Next, total non-durable consumption expenditures were imputed in a similar manner: separate ordinary least squares (OLS) regressions were estimated from the CES on both samples with a similar set of predictor variables. Coefficients from these equations were then used to impute mean (non-durable) consumption expenditures to each household and a normally distributed error term with a mean of zero and a standard deviation equal to the standard error of the regression was added to each imputed amount. Two sets of adjustments were then made to the imputed amounts.
First, the particular functional form used was unstable at very low levels of income resulting in extraordinary amounts of imputed consumption for several records. For nondurable consumption, our OLS specification included two terms, 1/Y and 1/Y2, where Y is total family income, that presented problems at both ends of the income distribution. For very low incomes, the nonlinearity introduced by 1/Y and 1/Y2 caused estimates of mean consumption to approach infinity. This was handled by constraining consumption for these records to be no more than 1.5 times income. This limit was based on analysis of the CES data independent of the imputation process.
Second, the tax return data that formed the basis of the income information for filers contained income amounts far outside the range observed on the CES and caused problems when our regression coefficients were used. Our approach was to assume that the estimated equation was valid for incomes within the range of the CES and to fit a spline function for the portion of income in excess of this amount for those households (about 2.5%) with reported incomes outside the range of that reported in the CES.
Without getting into the weeds with respect to how their model works (they don’t disclose nearly enough information or data to do this), I can reproduce their consumption tax numbers very closely by simply using the BLS CEX consumption to pre-tax income ratios and a flat consumption tax. In other words, you don’t need to assume that the poor are paying higher effective rates as a proportion of their consumption (e.g., on “sin” taxed goods) to get higher effective taxes as a percentage of this very limited definition of “income” on the poor. It’s quite clearly almost entirely a byproduct of methodological flaws that vastly overstate spending-to-income at low incomes and vastly understate spending-to-income at upper incomes.