Multiple media outlets have reported claims from scholars and commentators that the expanded Child Tax Credit (CTC) from 2021 reduced child poverty by one-third, keeping “3.8 million children out of poverty.” (A few examples: here, here, here, and here.) The implication is that the recent rollback of temporary pandemic CTC expansions will plunge millions of children back into poverty. However, the evidence supporting these claims comes from simulated and imputed data, raising questions about the actual impact of the expanded CTC on child poverty.

A group of researchers at Columbia University started producing a monthly poverty rate shortly after the pandemic hit, supplementing the annual measure used by the US Census Bureau. The Census Bureau’s annual poverty measure is significantly time-lagged, which makes the Columbia group’s monthly rate useful for assessing current poverty trends. However, the Columbia researchers base their monthly poverty rate on statistically simulated measures of income, not the actual situation on the ground. Based on the sheer number of assumptions that go into the Columbia poverty measure, it severely limits any assessment of policy changes like the expanded CTC.

In an ideal world, the US Census Bureau (or another
statistical agency) would ask households each month how much income they have (including
money they receive form CTC payouts) and compare it to a poverty threshold. This
would allow researchers to assess how increased CTC payments affected the
poverty rate as they phased in. Such a monthly survey exists (the monthly CPS),
but it has some limitations that make it a less than ideal source of monthly
income data.

Recognizing these limitations but driven by the need for a timely poverty measure, economists Jeehoon Han, Bruce Meyer and Jim Sullivan from the University of Chicago and Notre Dame developed a poverty measure that uses the monthly CPS data on income, rather than simulated measures like those used by the Columbia team. The benefit of using reported income from the monthly survey (unlike the Columbia measure) is that it asks respondents to report all income, specifically:

Total combined income during the past 12 months . . . of all members [of the family]. This includes money from jobs, net income from business, farm or rent, pensions, dividends, interest, social security payments and any other money income received . . . by members of [the family] who are 15 years of age or older.

Monthly payments to families through the expanded CTC started in July 2021, and respondents should have reported these payments on the monthly survey because they represented a source of cash income. This makes the Chicago/Notre Dame poverty measure useful to assess the CTC’s effect on poverty. Han, Meyer, and Sullivan highlight the short-term poverty reduction of the expanded CTC, although they note “we still do not see the sharp decline in the poverty rate for children that had been forecasted.”

Contrast this with Columbia’s poverty rate, which simulates income rather than uses what respondents report on the monthly survey. The researchers “apply combined-sample multiple imputation (CSMI) techniques to export the association of observable characteristics and poverty in the ASEC [annual survey] to the updated composition and labor market characteristics of the monthly files.” There are plausible reasons for choosing to simulate income in this way rather than use the monthly reported income, but it is important to recognize the difference.

Both methods have their own strengths and weaknesses. Respondents likely underreport their income on the monthly survey, resulting in the Chicago/Notre Dame measure understating poverty reductions from the expanded CTC. The Columbia team’s estimates likely overstate the effects of the CTC given their assumptions and imputations. Even policy scholars are confused. In recent commentary, Niskanen Center’s Director of Poverty and Welfare Policy, Sam Hammond conflated the US Census Bureau’s annual poverty measure with the Chicago/Notre Dame monthly poverty rate, mistakenly believing that their monthly poverty rate does not account for CTC payments, even though it likely does.

Estimating the effects (or potential effects) of the expanded CTC on poverty can help inform the policy debate, but we must acknowledge the uncertainty of the data and resist attempts to oversell the benefits of a particular policy. In reality, analyzing the impacts of the CTC on poverty using simulated data is little more than speculative.

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