{shortcode-4baa096ab267aef81c82bd520fabb26b6b930d74}

Political scientist Zach Parolin announced that the 2024 Census will implement a monthly, “close to real-time” poverty measurement using a methodology he developed during the Covid-19 pandemic at a Harvard Center for Population and Development Studies talk Thursday afternoon.

The methodology uses data from the Panel Study of Income Dynamics and Current Population Survey Annual Social and Economic Supplement to generate poverty estimates from two weeks prior. The projections will offer more timely data than current estimates, which have a more than nine-month delay, Parolin said.

“For the first year of the pandemic, we did not know the poverty rate of that year until September of the following year,” Parolin said. “If poverty estimates are to inform somewhat real-time policy-making decisions, that’s obviously insufficient.”

Parolin — an assistant professor of political and social science at Bocconi University in Milan, Italy — said that the methodology accounts for taxes and transfers, including stimulus checks and expanded unemployment benefits, and can evaluate the success of government support programs seeking to reduce poverty.

Parolin added that the new monthly estimates pass several strong and weak “validation tests” and are “not just a statistical artifact.” In months where Parolin’s methodology identified higher monthly poverty rates, Parolin said, researchers also observed higher rates of food insufficiency.

Parolin also said the Census Bureau was adopting his team’s methodology for future censuses.

“They’re implementing this in-house with the idea of starting their own monthly poverty measure in 2024,” he said.

Alongside the monthly estimates, Parolin said the annual poverty estimate remains useful.

“Monthly poverty estimates are a supplement to — and not a substitute for — the typical annual poverty estimates,” he said.

During the talk, Parolin also discussed the “intergenerational persistence of poverty” and its effects during the Covid-19 pandemic.

“U.S. counties with the highest pre-pandemic poverty rates have a Covid-related death rate that is twice that of the lowest poverty counties,” he said. “The strongest predictor — for any given sector — of whether an individual lost a job or not was the economic situation they had inherited at the start of the pandemic.”

Parolin discussed the impact of pandemic-era policy interventions on lowering poverty rates.

In 2020, Congress passed the Cares Act, a stimulus package that provided checks and an additional $600 per week for those receiving unemployment benefits, which Parolin said “massively prevented what could have been a large spike in poverty.”

Parolin went on to speak about how policy lessons and other data from the pandemic could be applied to prepare for and mitigate future economic downturns.

“The pandemic does have profound implications for the ways we think about poverty in the U.S., implications for the ways we think about the consequences of poverty, measurement, and for understanding which policies work — and which do not,” he said.