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On this episode of the AEI Events Podcast, AEI’s Bruce D. Meyer presents a progress report on a new data set he is developing to measure income and poverty. Dr. Meyer cites several problems with the three main data sources — surveys, tax data, and program data — currently used in income and poverty calculations. While conceding that every data set has flaws individually, he argues that aggregating the sets can lead to a greater understanding of income and poverty distribution in the United States. His new data set adjusts for discrepancies in these data. He discussed early findings showing significant overreporting of the effect of Supplemental Security Income and underreporting of the effect of public assistance in reducing poverty.
During the panel discussion that followed, experts from across the political spectrum expressed appreciation for Dr. Meyer’s work, with Ben Harris of Results for America calling it a “dizzying, overwhelming effort.” Several panelists and audience members expressed concern over the ability to match the data between sets while protecting private information. The general consensus, however, was that this new data set will underscore the safety net’s important role in the lives of low-income Americans and provide a solid base from which to frame policy priorities moving forward.
This event took place on June 28, 2018.
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