The United States offers numerous important
governmental support programs, such as the Supplemental Nutrition Assistance
Program (SNAP) (formerly known as Food Stamp Program1), National
School Lunch Program (NSLP), and the Special Supplemental Nutrition Program for
Women, Infants and Children (WIC). The purpose of these programs are to
increase food security, and more importantly the quality and quantity of food
available to individuals. Considering its nutritional perspective, the WIC
includes a specific goods lists, such as milk, eggs and, vegetables. Similarly,
the NSLP stipulates that each meal for children must to include vitamins A, and
C, iron, calcium, protein and less than 10% saturated fat. Hence, both the NSLP
and WIC address not only the quantity of food available but also the quality.
SNAP does not have any such restrictions2.

            The body of literature regarding
investigations of SNAP is broad. Some studies indicate positive results, namely
that SNAP participation reduces food insecurity (FI) (Kabbani and Kmeid, 2005).
Ratcliffe et
al (2011) investigate
the effectiveness of SNAP in reducing FI by using a dummy endogenous variable
model with that instrumental variables (IV estimator) to manage the most
significant issue highlighted in the literature, which is the selection bias
problem. The results show that by using a strong IV model on nationally
representative (Self Invested Personal Pension) SIPP, evidence was obtained
that SNAP reduced the food- related hardship of a household. Furthermore, Mykerezi, and Mills (2010) evaluated
the impact of SNAP on FI using the Panel Survey of Income Dynamics (PSID) 1999 data.
The authors investigated SNAP participants endogenously to estimate treatment
impacts as a binary choice by using state-level errors in over payments or
underpayments of SNAP benefits and a one year FI scale. The results of study
provide strong positive evidence that FI may decrease at least 19% by participating in
SNAP.

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            The decrease of FI is
deemed to increase participants’ health. However, some issues, such as obesity
and diabetes have arisen with program, as it supplies additional food, but the
goods chosen depend on participants’ preferences. In another words, SNAP does not restrict people’s food choices,
unlike the WIC or NSLP as mentioned previously. Minnesota requested permission
from the U.S. Department of Agriculture (USDA) to prohibit the purchase of
candy and soft drinks with SNAP benefits (Guthrie et al, 2007). This proposal
was intended to promote diet quality by limiting the purchase of empty calories
but it was rejected. California, on the other hand has passed a “Healthy
Purchase” pilot program. For every $1 of SNAP spent on fresh produce,
participants refunded a specific portion as a bonus under this program (Guthrie
et al, 2007). Nevertheless, no specific restrictions or limitations exist
regarding the purchasing of junk food such as candy, soft drinks, or fatty
foods.

            Huang et al (1981) conducted one of
the early studies regarding SNAP participants’ food choices. The authors used
Consumer Expenditure Dairy Survey (CEDS) to examine the impact of SNAP on low-income
families’ food patterns. Their results indicate that behavior related to the
amount of food purchased by households may be influenced by SNAP. These
researchers focused only on the low-income group, but the sample for current
study includes, different income groups. While the food classifications in the
study (Huang et al, 1981) refer to food consumed at home,  I included both food consumed at home and  food eaten away from home in this study. Also
different income groups and food choices  are included this study. It may provide more comprehensive
perspective of the evaluation of food choices. Basiotis et al. (1983) evaluated
the nutrition consumption patterns of low-income SNAP receivers. They use the
Engel curve and data from 1977-1978 Nationwide Food Consumption survey. The
authors apply a simultaneous equation system for the estimation of food costs
and diet component availability levels of food at home. The results of the
study show that diet component availability level was relatively constant
across households with different income levels. Because different income levels
are address in the current study, I believe it may provide more comprehensive
knowledge about SNAP participants’ food choices than Huang et al (1981) and
Basiotis et al (1983) did.

            Furthermore, Wilde and Ranney (2000)
evaluated the mean of food spending among SNAP users and found that participants
spend increased amounts within the first three days of receiving benefits. These
spending patterns represent shopping frequency and food intake decisions over
time in light of SNAP benefits. The researchers used a non linear Engel curve
on CEDS data set. The results indicate that the frequency of households’
grocery shopping may be influenced by involvement in the program.

            Guthrie et al, (2007) mention the
significance of SNAP participants choosing food with high nutritional quality
rather than focusing on quantity. Their results suggest that the efficiency of
the program may be affected by economic factors such as, the budget share of
SNAP and food expenditure patterns of participants. Correspondingly, Wiig and
Smith (2009) investigated the relationship between low-income women’s shopping
behavior and participation in SNAP to examine food choices. They applied a
demographic and diet/ health perception questionnaire before measuring
participants’ weight, height, and body mass index (BMI). The results show that
food choices and grocery shopping behavior depend on participants’ economic, environmental
conditions and preferences. Although the study is similar to the current study
because it considers the SNAP users’ food choices, Smith and Wiig restricted
their study only to low-income women.

            Larson and Story (2009) indicate the
importance of the influence of environmental conditions on households’ food
choices, likewise, Wiig and Smith (2009) mentioned before. Their findings show
that a diet-related environment and supplemental nutrition program, such as
SNAP or policy interventions are supported at a population level due to
individual changes. The authors thought possibly ease and sustain if the environment within which choices are made supports
healthful food options.

            Kreider et al
(2012) analyzed the impact of  SNAP on
children’s health outcomes by applying a binary
outcome model and calculating average treatment impact (ATE) for SNAP
recipients on each of the health related outcomes, namely anemia, obesity, and
poor general health. Beatty and Tuttle, (2015)
investigated the effects of large benefit changes in SNAP on the food
expenditure of participants during the economic crisis. The authors used Consumer
Expenditure Quarterly Interview Survey (CEX) data from 2007 to 2010, a period
during which SNAP benefits increased significantly several times. Additionally,
they use difference-in-difference method, a placebo policy dummy, to check the
robustness of the results on expenditure on food eaten away from home collected
CPS. The results show that households change their purchase behavior because of
an increase in in-kind transfer. In another words, SNAP participants
significantly increase spending on food at home due to benefit increases, and SNAP participation may affect
the receivers health.

            In summary, the studies mentioned provide some insights into how food choices may be influenced by
environmental effects, policy intervention and individuals’ income level, which
is increased through involvement in SNAP. Subsequently, people’s general health
may be affected. Therefore, the purpose of this study is to
examine how SNAP participation influences households’ food choices.

1
Consistency of the paper, I use SNAP instead of Food stamp program.

2
SNAP only has restriction about alcoholic beverage, tobacco and non food items,
such as pet foods and household supplies. For more information see:  http://www.fns.usda.gov/snap/eligible-food-items.