Nearly six decades after its inception, the Supplemental Nutrition Assistance Program (SNAP), formerly known as the Food Stamp Program, has become the largest food and nutrition assistance program in the U.S. SNAP’s primary objective is to alleviate food insecurity by helping low-income families afford nutritious diets.
In 2019, the United States Department of Agriculture (USDA) reported that nearly 36 million individuals received SNAP benefits in an average month that year, with monthly household benefits around $260. SNAP has become an important “automatic stabilizer” in the U.S. safety net, expanding during bad economic times to help Americans. Today, due to the Covid-19 pandemic, SNAP caseloads have increased by an unprecedented 17 percent—between 6 to 7 million recipients—from just February to May 2020. It took almost 18 months to record similar increases in caseloads during the Great Recession.
Over the years, SNAP has come under political pressure to reform the program along many dimensions, including proposals to cut costs and restricting the types of eligible food items. While proposals to restructure the program must be based on credible research on SNAP’s effectiveness at reducing food insecurity and its effects on health or nutrition-related outcomes, my research has found that proposals framed as helping to make SNAP an anti-obesity program are often based on faulty data.
In studying SNAP's impacts, including on recipients’ health, we cannot merely compare recipients to income-eligible non-recipients because the former choose to participate in SNAP for reasons that we may not observe. Also, most studies on SNAP's effectiveness rely on self-reported participation in economic surveys, and there's evidence suggesting that between 20 to 50 percent of SNAP recipients do not report receiving benefits in survey data. These obstacles pose considerable challenges to researchers and can yield misleading results if not addressed. As a result, my collaborators and I have developed statistical methods to overcome these challenges by leveraging information on the determinants of participation and factors that help predict accurate reporting of SNAP receipt. For instance, survey respondents who have an adult present during the interview and those who are patient and friendly with interviewers provide more accurate benefit receipt responses. Using these methods, I find that SNAP participation is not associated with the probability of becoming obese or overweight. Research addressing participation quality also finds that SNAP meets its primary objective—it reduces food insecurity in households with children by about 6 to 11 percentage points.
As we look ahead to recovering from the economic fallouts of the coronavirus pandemic, the SNAP program stands out in our country’s safety net due to its ability to respond quickly and expand to meet the needs of millions of Americans. As such, efforts to strengthen the SNAP program, including the recent increases to the maximum benefit amounts that took effect on October 1, 2020, are welcome news.
Augustine Denteh is an assistant professor in the Department of Economics at Tulane University. His broad research interests are in applied econometrics and health economics, where he is interested in employing innovative econometric tools to study how public policies affect people’s health and wellbeing. In particular, he works on impact evaluation, measurement error models, the economics of obesity, and food and nutrition programs. Denteh is also interested in techniques for generalizability in health policy using statistical machine learning approaches for causal inference.