Measuring the success of the social safety net is notoriously difficult, and the data we do have often tells an incomplete story. The official poverty measure, for example, is widely criticized for being outdated and failing to capture the true cost of living or the value of non-cash benefits.
The Supplemental Poverty Measure (SPM) is better, as it factors in taxes, transfers, and regional cost differences. But even the SPM misses the lived reality of economic instability. It measures income at a single point in time, missing the volatility of gig work and the sudden shocks of medical bills.
Furthermore, administrative data (who is actually receiving benefits) often undercounts the true need, because, as we’ve seen, take-up rates are rarely 100%.
The data also struggles to measure the “counterfactual”—what would have happened without the safety net. It is easy to look at a family receiving SNAP and still struggling, and conclude the program “didn’t work.” But the data shows that without SNAP, that family would likely be facing severe food insecurity or homelessness.
When consuming data about poverty and the safety net, always ask what is being measured and what is being left out. Are they using the official poverty line or the SPM? Are they looking at annual income or monthly volatility? The numbers are powerful, but they require careful interpretation to avoid drawing the wrong conclusions about who needs help and why.