Whether Supplemental Nutrition Assistance Program (SNAP) benefits are adequate to provide food security for eligible households is an important and timely policy question. While the nominal value of SNAP benefits is fixed across states (except for Hawaii and Alaska), variation in food prices across geographic areas is dramatic, and the real value of SNAP benefits varies widely across the U.S. Our research provides new evidence on geographic variation in the adequacy of SNAP benefits to purchase the Thrifty Food Plan (TFP).
The objective of the study was to determine relationship between neighborhood food store availability, store choice and food purchasing habits among Supplemental Nutrition Assistance Program (SNAP) participating households. The study sample consisted of SNAP households (n=1581) and low income households participating in the USDA's National Household Food Acquisition and Purchase Survey (FoodAPS) a nationally representative cross-sectional survey of American households with household food purchases and acquisitions data.
The Supplemental Nutrition Assistance Program (SNAP) is the largest nutritional safety net in the United States. Prior research has found that participants have higher consumption shortly after receiving their benefits, followed by lower consumption towards the end of the benefit month. This “SNAP benefit cycle” has been found to have negative effects on beneficiaries.
We tested the hypothesis that high costs of living, such as from high housing rents, reduce the healthfulness of food acquisitions.
Higher food prices may aggravate household food insecurity and hurt diet quality. Using a sample of low-income households from the National Household Food Acquisition and Purchase Survey (FoodAPS), this study examines whether local food prices affect food insecurity and nutritional quality of foods acquired, and how households use competent consumer behaviors to mitigate any adverse effects of price. Financial management practices, nutrition literacy, and conscientious food shopping practices were considered for consumer competency.
We employ multilevel models with neighborhood and state effects (fixed effects and random effects) to analyze the associations between household characteristics, neighborhood characteristics, regional attributes and dietary quality. We use data from the USDA National Household Food Acquisition and Purchase Survey. Our dependent variable is a Healthy Eating Index that incorporates dollars spent and amount of food in several categories. Key explanatory variables at the household level include variables household financial condition, housing burden, home ownership, car access, household size.
This paper examines the relationship between SNAP participation and prices paid for food items. To test this relationship, we develop an expensiveness index following the method of Aguiar and Hurst (2007) and use the FoodAPS data set. Using both the ordinary least squares method and controlling for endogeneity using an instrumental variables approach, we found SNAP participation did not hold a statistically significant relationship with the prices paid for food items when we controlled for consumer behavior and food market variables.
Policymakers are pursing initiatives to increase food access for low-income households. However, due in part to previous data deficiencies, there is still little evidence supporting the assumption that improved food store access will alter dietary habits, especially for the poorest of U.S. households. This article uses the new National Household Food Acquisition and Purchase Survey (FoodAPS) to estimate consumer food outlet choices as a function of outlet type and household attributes in a multinomial mixed logit.
In our update for the calendar year 2014, we find that 15.8% of seniors are marginally food insecure, 8.8% are food insecure, and 3.4% are very low food secure. This translates into 10.2 million, 5.7 million, and 2.2 million seniors, respectively. From 2001 to 2014, the fraction of seniors experiencing the marginal food insecurity, food insecurity, and very low food security increased by 47%, 68%, and 138%, respectively. The number of seniors in each group rose 119%, 148%, and 252% which also reflects the growing population of seniors.
Earnings nonresponse in household surveys is widespread, yet there is limited evidence on whether and how nonresponse bias affects measured earnings. This paper examines the patterns and consequences of nonresponse using internal Current Population Survey individual records linked to administrative Social Security Administrative data on earnings for calendar years 2005-2010. Our findings confirm the conjecture by Lillard, Smith, and Welch (1986) that nonresponse across the earnings distribution is U-shaped. Left-tail “strugglers” and right-tail “stars” are least likely to report earnings.