Oral Capps Jr., PhD is Executive Professor, Regents Professor, and Co-Director of the Agribusiness, Food, and Consumer Economics Research Center in the Department of Agricultural Economics at Texas A&M University. He is a nationally and internationally recognized leader in demand analysis, specializing in working with large databases. This project was funded through a Healthy Eating Research special rapid-response research opportunity focused on COVID-19 and the federal nutrition programs, to inform decision-making regarding innovative policies and/or programs during and after the COVID-19 pandemic. These findings were recently published in the journal PLOS ONE.

Macroeconomic factor effects on food assistance program participation’ is quite a mouthful. What are macroeconomic factors and what questions were you seeking to answer with this analysis?

Macroeconomic factors are events or conditions that broadly impact the U.S. economy. Some factors are economic stressors, such as the unemployment rate, while others serve as predictors of economic performance, such as disposable personal income.

This research aimed to identify and assess the impacts of selected macroeconomic factors on participation in key food assistance programs administered by the USDA Food and Nutrition Service (FNS)—the Supplemental Nutrition Assistance Program (SNAP), the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), and the National School Lunch Program (NSLP). We also wanted to use our understanding of macroeconomic factors to quantify the impact of COVID-19 on participation in SNAP, WIC, and NSLP, and forecast program participation using econometric models.

So, how did these macroeconomic factors affect participation in WIC, SNAP, and NSLP participation during the COVID-19 pandemic?

We hypothesized that economic stress is positively related to participation in food assistance programs. In other words, greater economic stress (e.g., decreased disposable income, increased number of claims for unemployment insurance) may lead to increased participation in SNAP, WIC, and NSLP. We also hypothesized that economic performance is negatively related to participation in food assistance programs. In other words, greater economic performance may lead to lower participation in SNAP, WIC, and NSLP.

In this study, we considered 11 macroeconomic factors, some of which are economic stressors and others that are predictors of economic performance. Learn more about each of these indicators in the full paper.

Economic StressorsPredictors of Economic Performance
– Kansas City Financial Stress Index
– St. Louis Financial Stress Index
– Number of initial claims for unemployment insurance
– Unemployment rate
– Ratio of total consumer credit outstanding to disposable personal income
– Manufacturers’ new orders of durable goods and non-defense capital goods
– Real disposable personal income
– Real M2 money stock
– Housing starts
– Case-Shiller Home Price Index
– University of Michigan Consumer Sentiment Index

We found that different sets of macroeconomic factors affect each of the food assistance programs. There was no one common factor across SNAP, WIC, and NSLP participation:

  • Macroeconomic factors affecting SNAP participation are: (1) the Kansas City and St. Louis Financial Stress Indices; (2) the number of initial claims for unemployment insurance; (3) manufacturers’ new orders of durable goods; (4) housing starts; and (5) consumer sentiment. 
  • Macroeconomic factors affecting WIC participation are: (1) the Kansas City and St. Louis Financial Stress Indices; (2) real disposable personal income; (3) real M2 money stock; (4) housing starts; (5) consumer sentiment; (6) the ratio of total consumer credit owed to disposable personal income; and (7) manufacturers’ new orders of durable goods.
  • Macroeconomic factors affecting the number of participants in the NSLP are: (1) the number of initial claims for unemployment insurance; and (2) the unemployment rate.

Interestingly, we found that changes in macroeconomic conditions that influence SNAP, WIC, and NSLP participation continue to affect participation levels anywhere from 1 month to 12 months later.

We also used our models to quantify how much COVID-19 impacted program participation. Holding all other factors steady, SNAP participation rose between 2% and 4% due to the presence of COVID-19, while WIC participation rose between 0.4% and 0.6%. NSLP participation fell between 69% and 74% due to the presence of COVID-19 likely due to the restrictions on attending school during the pandemic. 

What is the significance of these findings? Why is it important to discuss economics in the context of nutrition and food assistance programs?

This work shows how the current economic state of the country has the potential to increase or decrease participation in nutrition assistance programs. This could influence program operations and prompt agencies to increase outreach in times of economic stress to ensure that those eligible for these programs are enrolled. Additionally, FNS staff and analysts should consider these econometric modeling efforts to reduce forecasting errors, especially regarding SNAP and WIC participation numbers. In turn this would decrease the likelihood of budgeting misallocations. This econometric analysis then provides a baseline for forecast accuracy concerning participation levels in key food nutrition assistance programs.

Because we quantify the impact of COVID-19 on level of participation in SNAP, WIC, and the NSLP, we provide knowledge to analysts to help them better prepare for future pandemics or other major shocks to the economy.

Where do we go from here? What are the next steps needed to facilitate change or progress?

For future endeavors, we plan to repeat this analysis for various states and/or regions. We also plan to conduct this analysis for other major nutrition assistance programs such as the School Breakfast Program and the Child and Adult Care Food Program. The chief recommendation to the FNS is to consider the impacts of a number of macroeconomic variables in lieu of a few on participation in various food and nutrition assistance programs and to employ our quantitative models for forecasting purposes. 

Thanks to Dr. Oral Capps, Jr. for discussing his findings with us. To learn more, read the full study