Food and Nutrition Service

U.S. Department of Agriculture

THE EXTENT OF TRAFFICKING IN

THE FOOD STAMP PROGRAM:

AN UPDATE

Theodore F. Macaluso, Ph.D.

Office of Analysis, Nutrition, and Evaluation

March 2000
i

The Extent of Trafficking in the Food Stamp Program

An Update

EXECUTIVE SUMMARY

Food stamps are intended for food. When individuals sell their benefits for cash it violates the spirit and

intent of the Food Stamp Program as well as the law. This practice, known as trafficking, diverts food

stamps away from their purpose. It reduces intended nutritional benefits and undermines public

perceptions of the integrity and utility of the program. A crucial question, therefore, is the extent to

which trafficking exists.

Several years ago, a method to calculate data-based estimates of the prevalence of trafficking was

developed by USDA. The Extent of Trafficking in the Food Stamp Program* used this method to

analyze over 11,000 completed undercover investigations of trafficking and generate an estimate for

calendar year 1993. This report duplicates the precise methodology of the earlier analysis with more

than 10,000 new investigations to generate an estimate for the 1996 - 1998 calendar year period. We

find that:

The amount of trafficking has decreased. Stores trafficked about $660 million per year for cash

from the government in the 1996 - 1998 period, a 19 percent decline from the $815 million trafficked in

1993.

The rate of trafficking has also decreased. The trafficking rate – which compares dollars trafficked

to benefits issued – declined 8 percent: from almost four cents of every dollar of food stamp benefits

issued to three-and-one-half cents of every dollar issued.

FNS concentrates its enforcement efforts on stores most likely to traffic. In addition, the

expansion of Electronic Benefit Transfer (EBT) – which had grown to half of all issuance during this

period – makes certain forms of trafficking harder to conduct and large-scale trafficking easier to detect.

For these reasons, we find the largest reduction in the trafficking rate among the store

categories most likely to traffic – privately-owned stores, especially small ones that do not

stock a full line of food.

When we repeat our analysis of where store violations occur the overall pattern remains

unchanged:

• Dramatic differences exist among store types: the percent of redemptions that are trafficked

ranged from nearly zero to over fifteen percent across store categories.

 

*

 Theodore F. Macaluso, The Extent of Trafficking in the Food Stamp Program (Alexandria, VA: Food and Nutrition

Service, USDA; 1995).
i

• The stores which redeem the overwhelming majority of food stamp benefits continue to

have very low trafficking rates.

Acknowledgments

The author wishes to express his appreciation to the many individuals who contributed to this report.

Richard Mantovani, Ph.D, Hoke Wilson and Tigran Markaryan at Macro International successfully

compiled and merged the data summarized here, faithfully reproduced the original methodology, made

thoughtful suggestions, and responded promptly to the author’s numerous requests for additional

information and analyses.

Steven Carlson, Director of the Family Programs Staff in the Office of Analysis, Nutrition and

Evaluation (OANE), Food and Nutrition Service, provided guidance and commented thoughtfully on

drafts of the text. Ken Offerman, also of OANE, managed the contractual support for the project,

performed considerable legwork in tracking down data, and also commented thoughtfully on drafts.

Finally, the staff of the Benefit Redemption Division of the Food Stamp Program provided many

comments and corrections and helped to make this a comprehensive – and better – report.
Page 1

The Extent of Trafficking in the Food Stamp Program

An Update

United States Department of Agriculture

Food and Nutrition Service

Office of Analysis, Nutrition and Evaluation

March 2000

INTRODUCTION

Food stamps are intended for food. When individuals sell their benefits for cash it violates the spirit and

intent of the Food Stamp Program as well as the law. This practice, known as trafficking, diverts food

stamps away from their purpose. It reduces intended nutritional benefits and undermines public

perceptions of the integrity and utility of the program. A crucial question, therefore, is the extent to

which trafficking exists.

Several years ago, a method to calculate data-based estimates of the prevalence of trafficking was

developed by USDA. The Extent of Trafficking in the Food Stamp Programi used this method to

analyze over 11,000 completed undercover investigations of trafficking and generate an estimate for

calendar year 1993.ii The report found that:

• About $815 million was trafficked for cash from the government by food stores during 1993. This

amounted to just under four cents of every dollar of food stamp benefits issued.

• Significant differences across types of food retailers existed: supermarkets had very low trafficking

rates, non-supermarkets had substantially higher trafficking rates.

• The food stores which redeemed the overwhelming majority of food stamp benefits had very low

trafficking rates.

This report updates the earlier analysis with more than 10,000 new investigations to generate an

estimate for the 1996 - 1998 calendar year period. We continue to estimate three basic measures of

trafficking:
Page 2

1. the amount of trafficking (i.e., the total sum of dollars trafficked, which depends partly upon the

total sum of benefits issued and partly upon the next measure, the rate of trafficking);

2. the rate of trafficking (the proportion of total benefits issued which were trafficked), and

3. the store violation rate (the proportion of all authorized stores that engage in trafficking).

While all three measures are important for different purposes, the second measure – the rate of

trafficking – is the one that provides an approximation of FNS’ relative success in controlling trafficking.

The trafficking rate is independent of the size of the program (i.e., the total sum of benefits issued) or the

relative market share of different types of retailers (which is not reflected in the store violation rate).

We undertook an update because there have been several significant developments which may affect

each of these measures of trafficking. These developments include the following:

• a 24 percent decline in food stamp caseload: from 10.8 million households per month in 1993 to

8.2 million in 1998. The caseload decline resulted in an 11.3 percent decline in total benefits issued.

This is likely to reduce the total dollar amount of trafficking (since total benefits issued decreased),

but is unlikely – by itself – to change the trafficking rate (i.e., the proportion of benefits issued that

are trafficked).iii

• a 16 percent decline in the number of food retailers authorized to accept food stamps: from

about 210,000 in 1993 to 177,000 in 1998. The decline in participating retailers may change the

store violation rate depending upon whether stores willing to traffic left the program at a faster (or

slower) rate than non-trafficking stores. However the influence of this factor on changes in the rate

of trafficking will depend upon two things: (i) whether trafficking-prone stores that remain on the

program changed their trafficking activity; and (ii) whether food stamp participants choose to shop

at trafficking-prone stores or not.

• a 50 percent change-over from paper food coupons to electronic benefit transfer (EBT). The

Personal Responsibility and Work Opportunities Reconciliation Act of 1996 mandates that all states

convert from paper food stamp coupons to electronic benefit issuance by 2002. By September

1998 slightly more than half of all food stamp benefits were issued and redeemed electronically.

Under EBT certain forms of trafficking are harder to conduct and large-scale trafficking is easier to

detect. Therefore, we would expect its expansion to reduce the rate of trafficking (i.e., the

proportion of benefits issued that are trafficked).iv

The combined effect of these developments is hard to predict. Fortunately, one additional factor that

could affect results – the quality of FNS undercover investigations – appears to have remained stable:

there has been no meaningful change in the quantity or quality of FNS investigations. The total number

of investigations, the number in which any food stamp violation is disclosed (“positives”) and the raw

number in which trafficking is found have each remained relatively constant from 1993 through 1998

(Chart 1).
Page 3

Chart 1

FNS Undercover Investigations: 1991 - 1998

0

1000

2000

3000

4000

5000

6000

9192939495969798

Year

Number

Total

Positive

Trafficking

____________________

APPROACH

This update uses the same methodology as the earlier report to ensure consistent comparisons. The

method focuses on authorized food retailers because all trafficking must eventually flow through a food

retailer authorized to participate in the Food Stamp Program. The reason is obvious, but worth pointing

out explicitly: authorized food retailers are the only ones who can redeem food benefits for cash

from the government.

v

Because authorized food retailers are the only ones who can redeem food benefits for cash from

the government, knowing the prevalence of trafficking among retailers tells us the maximum

amount of dollars diverted from food benefits by trafficking for cash.vi

The Food and Nutrition Service (FNS) maintains a staff of investigators who work undercover to

determine whether authorized food stores sell ineligible items or engage in trafficking. Stores caught

violating are fined or removed from the program and in some instances prosecuted.
Page 4

For the update, we followed the same approach used in the earlier report:vii

• First, we sorted a database of 10,354 completed investigations across five specific dimensions that

categorize store types and store locations. viii

• Second, for each specific category of store and location we compiled national data from calendar

years 1996 through 1998 on the total number of stores and the total food stamp redemptions in that

category.

• Third, we analyzed the investigation outcomes and calculated the weighted trafficking and store

violation rates within each category. ix We weighted the investigation data to accurately represent

the national figures.x We calculated two of our three measures: the trafficking rate, a redemptionbased rate to reflect dollar diversions, and the store violation rate, a store-based rate to identify the

kinds of stores that contain the most violators.

• Finally, we multiplied the redemption-based trafficking rate against the total food stamp redemptions

in each category and summed across all categories to obtain the first of our three measures: the

amount of trafficking, which provides an estimate of dollars diverted from food benefits by

trafficking in the Food Stamp Program.xi

FINDINGS

About $660 million per year was diverted from food benefits by trafficking between 1996 and

1998. This amounts to three-and-one-half cents of every benefit dollar issued (Table 1).

Our methodology yields a cautious estimate that is likely to best represent the maximum dollars diverted

from food benefits per year by direct trafficking in 1996-1998.
Page 5

Table 1 - Trafficking Continues to be Low Among Supermarkets and Large Grocery

Stores But Substantially Higher Among Small Stores and Stores That Do Not Stock a Full

Line of Food.

1993 1996 - 1998

Store

Estimated

Trafficking Store

Estimated

Trafficking

Type of Store

Violation

Rate

Trafficking

Rate

Amount

($000)

Violation

Rate

Trafficking

Rate

Amount

($000)

Supermarkets 4.2 1.7 $282,058 5.3 1.9 $279,163

Large Groceries 6.7 3.7 46,632 9.8 3.2 35,255

Subtotal 5.0 1.9 $328,690 6.7 2.0 $314,418

Small Groceries 12.8 15.7 177,809 14.4 15.8 154,109

Convenience 8.1 9.6 78,090 11.7 10.8 66,809

Specialty 17.6 14.2 117,004 10.7 8.1 55,782

Gas/Grocery 8.7 10.4 27,528 12.8 9.7 21,784

Other Types 10.2 12.4 82,605 16.2 9.4 43,892

Subtotal 10.7 13.0 $483,036 13.0 11.5 $342,376

All Stores 9.4 3.8 $811,726 11.7 3.5 $656,794

Notes: The 1996-1998 data have been annualized – see endnote 7.

Trafficking violation rates are calculated separately for stores and redemptions. The store

violation rate is the percent of investigated stores caught trafficking weighted by the national

distribution of stores. The trafficking rate is the percent of trafficked redemptions in investigated

stores, weighted by the national distribution of redemptions. The apparent anomaly between

the two rates – i.e., the store-based rate was higher in 6 of 7 store types while the redemptionbased rate is lower both overall and in 4 of 7 store types – reflects the fact that the two rates

measure different aspects of trafficking.

____________________
Page 6

TRAFFICKING AND CHANGE IN BENEFITS ISSUED

Compared to 1993, the 1998 figure represents a 19 percent decline in the dollar amount of benefits

trafficked. As expected, we find a similarity among the changes in caseload, total redemptions, and the

amount of trafficking (Chart 2):

However, the decline in caseload and total redemptions is far from a complete explanation of

changes over this period of time: we also find an 8 percent decline in the rate of trafficking,

which is independent of benefits issued. The trafficking rate decreased from 3.8 percent of benefits

issued in 1993 to 3.5 percent of benefits issued in 1998 (Table 1).

Chart 2

Food Stamp Caseload and Dollar Amount of 

Trafficking: 1993 - 1998

0

5

10

15

20

25

Caseload

(x1,000k)

Redemptions 

(in billions)

Trafficking

(x100k)

1993

1998

____________________
Page 7

TRAFFICKING AND CHANGE IN

THE AUTHORIZED RETAILER POPULATION

The 16 percent decline in number of authorized retailers also does not appear to explain the

improvement in the trafficking rate: we actually find an increase in the store violation rate

between 1993 and 1998 (Table 1 and Chart 3).

Chart 3

Authorized Food Stamp Retailers: 

1993 and 1998

0

5

10

15

20

25

# of Stores

(x 10,000)

% of Stores

Trafficking

1993

1998

____________________

TRAFFICKING AND TYPE OF FOOD RETAILER

Part of the explanation for the improvement in the trafficking rate is to be found in two critical

facts:

(1) trafficking continues to vary by type of store;

(2) stores that redeem the most, traffic the least. 

Tables 1 and 2 show that:

• Supermarkets and large grocery stores redeemed 84 percent of all benefit dollars but few of

those dollars are trafficked.

· In comparison to supermarkets and large grocery stores, trafficking rates among small stores

and stores that do not stock a full line of food are 4 to 8 times higher.
Page 8

Table 2 - Distribution and Market Shares of Authorized Food Stamp Retailers.

1993

 Percent of All

1996 - 1998

Percent of All

Type of Store Stores Redemptions Stores Redemptions

Supermarkets 15.3 76.5 14.9 78.3

Large Groceries 6.9 6.0 7.0 5.8

 Subtotal 22.2 82.5 21.9 84.1

Small Groceries 18.8 5.4 20.0 5.2

Convenience 27.7 3.8 26.8 3.3

Specialty 8.7 3.9 9.0 3.7

Gas/Grocery 10.3 1.2 11.9 1.2

Other Types 12.3 3.2 10.4 2.5

 Subtotal 77.8 17.5 78.1 15.9

All Stores 100.0a100.0b100.0c100.0d

Notes:

a Based on a total of 200,568 authorized food retailers redeeming at any point during 1993.

b Based on a total of $21.1 billion.

c Based on 237,824 unique food retailers redeeming at any point during the 1996-1998 period.xii

d Based on total of $56.16 billion over the three years.xiii

____________________
Page 9

Between 1993 and 1998 there was a modest increase in the relative market share of

supermarkets and large grocery stores – the stores least likely to traffic (Chart 4).

Chart 4

Change in Retailer Population and Market 

Share: 1993 - 1998

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

% of

Stores

Market

Share

Large Stores

Small Stores

Notes: Unlike earlier charts, in which each column was a

different year (1993 or 1998), in this chart each column is the

difference between the two periods. The “large store”

category includes both supermarkets and large grocery stores;

“small stores” are everything else. Market share is defined as

the percentage of redemptions accounted for by the given

category of store.

____________________

Food retailers owned by public corporations (i.e., owned by a company whose stock trades

publicly) continue to have lower trafficking rates than privately-owned stores (Table 3). The

public corporation category includes many of the major national supermarket chains, many convenience

store chains, and many grocery marts associated with national gasoline retailers.xiv

• In 375 investigations of public corporations, FNS undercover investigators found trafficking

involved about four percent of publicly-owned stores.

· Among privately-owned food retailers, FNS undercover investigators found trafficking in almost

thirteen percent of stores.
Page 10

Table 3 - Publicly-Owned Food Retailers Display Low Trafficking Rates; Privately-Owned

Retailers, Especially Non-Supermarkets, Are Substantially More Likely to

Engage in Trafficking.

Trafficking

When Store is

Publicly-Owned

Trafficking

When Store is

Privately-Owned

Type of Store

Store

Violation

Rate

Trafficking

Rate

Store

Violation

Rate

Trafficking

Rate

1993 1998 1993 1998 1993 1998 1993 1998

Supermarkets 0.0 4.7 a0.0 3.0 a5.4 5.7 2.6 1.3

Large Groceries 0.0 0.0 0.0 0.0 6.8 9.9 3.8 3.3

Other Types (small groceries,

convenience stores, gas/grocery,

specialty foods, etc.

1.7 4.3 1.8 4.6 12.0 14.0 15.1 12.3

All Stores 1.2 4.4 0.2 3.0 10.7 12.7 5.3 3.7

Notes: aSee endnotexv

Trafficking violation rates are calculated separately for stores and redemptions. The

store violation rate is the percent of investigated stores caught trafficking weighted by

the national distribution of stores. The trafficking rate is the percent of trafficked

redemptions in investigated stores, weighted by the national distribution of redemptions.

____________________
Page 11

The store categories most likely to traffic continue to be small privately-owned stores and

privately-owned stores that do not stock a full-line of food (Table 4):

• Among these stores more than 1 of every 8 benefit dollars redeemed was trafficked.

• While these categories account for about 71 percent of all stores they account for only 14 percent

of all redemptions.

Table 4 - Small Privately-Owned Stores Have the Highest Trafficking Rates But

Redeem Only 14 Percent of All Benefits Issued

Category of Store

Trafficking

Rates

(Redemptions)

Percent of All

Stores

Percent of All Redemptions

1993 1998 1993 1998 1993 1998

Publicly-Owned Stores 0.2 a12.8 12.8 28.0 30.0

Large Private Stores 2.7 1.5 17.2 16.5 56.2 55.8

Private - other stores 15.1 12.3 70.0 70.7 15.8 14.2

 All stores 3.8 3.5 100.0 100.0 100.0 100.0

a See endnote 15.

____________________
Page 12

TRAFFICKING, FNS ENFORCEMENT AND EBT

FNS concentrates its enforcement efforts on stores most likely to traffic. In addition, the expansion of

Electronic Benefit Transfer (EBT) makes certain forms of trafficking harder to conduct and large-scale

trafficking easier to detect. For these reasons, it should not be surprising that we find the largest

reduction in the trafficking rate among the store categories most likely to traffic – privatelyowned stores, especially small ones that do not stock a full line of food (Chart 5).

Chart 5

Reductions In Trafficking Rate: 1993 - 1998

0

2

4

6

8

10

12

14

16

Large

private

stores

Other

private

stores

All

stores

1993

1998

____________________

TRAFFICKING AND STORE LOCATION

The 1993 report examined the prevalence of trafficking by neighborhood and found that trafficking is

more frequent among stores located in the poorest of poor neighborhoods. The 1993 report also found

only a mild relationship between trafficking rates and a store’s location in an urban neighborhood.

These two findings continued to be true in the 1996 - 1998 period.

Stores in the poorest of poor neighborhoods continue to be more likely to engage in trafficking

than stores located elsewhere, although the difference between rich and poor neighborhoods

has decreasedsomewhat (Table 5). Few recipients are likely to sell food stamp benefits for less than

they can buy in food, unless the need for cash is overwhelming. It is no surprise, therefore, to find that

the rate of trafficking (i.e., proportion of benefits trafficked) continues to vary widely by the

economic status of neighborhoods.
Page 13

Table 5 - Trafficking is More Frequent in the Poorest of Poor Neighborhoods.

Percent of Trafficking Rates: Percent of All

Households in Poverty

in Zip Code Where

Store is Located:

Store

Violation

Rate

Trafficking

Rate

Stores

Redemptions

1993 1998 1993 1998 1993 1998 1993 1998

 0 to 10% 4.6 9.5 1.7 2.0 30.3 26.5 27.2 23.2

 11 to 20% 8.7 10.7 4.1 3.1 38.9 40.5 38.9 40.1

 21 to 30% 13.0 13.2 3.8 3.3 20.1 20.5 20.1 21.6

 over 30% 19.2 16.8 7.6 7.1 13.8 12.4 13.8 15.1

All Stores 9.4 11.7 3.8 3.5 100.0 100.0 100.0 100.0

____________________

Although some urban areas are widely perceived as having more crime than rural areas, we

found only a mild relationship between the trafficking rate and urbanicity. The Bureau of the

Census classifies zip codes by the urban/rural percentage of residents in the zip code. The trafficking

rates by urban/rural percentage in the zip code in which a store is located show a modest increase in

highly urban areas (Table 6).

Table 6 - The Trafficking Rate Is Slightly Higher In Highly Urban Areas.

Trafficking Rates:

Stores Located in Zip Codes

Store

Violation

Rate Trafficking Rate

Where Percent Urban is: 1993 1998 1993 1998

 0 to 10% 6.1 12.9 3.5 2.4

 11 to 50% 8.6 11.6 3.1 2.5

 51 to 90% 7.1 10.9 2.8 3.0

 90 to 100% 12.1 11.6 4.4 3.9

____________________
Page 14

While trafficking rates remain low and do not vary sharply by urbanicity, between 1993 and

1998 we find a large increase in the store violation rate in rural and lower-urban areas (Chart

6). Table 5 indicates a similar increase in the store violation rate outside of the poorest areas. The

reason for these changes in store behavior is unknown.xvi

Chart 6

Change in Trafficking Patterns by Urbanicity: 

1993 - 1998

-2

0

2

4

6

8

0 to

10%

11 to

50%

51 to

90%

90 to

100%

Percent Urban

Store Violation Rate

Trafficking Rate

____________________

Stores in low trafficking areas continue to redeem the majority of food stamp benefits.

• Twelve percent of the nation's authorized food retailers are located in high poverty/high trafficking

areas, 88 percent are located in lower poverty/low trafficking areas.

· Eighty-five percent of redemptions flow through stores located in neighborhoods where less than 30

percent of the population is below poverty.
Page 15

CONCLUSION AND

IMPLICATIONS FOR PROGRAM INTEGRITY

The rate of trafficking has decreased over this period. Although the data available are not

sufficient to determine causality, the direction and nature of the decrease are consistent with two facts:

• The stores which redeem the majority of food stamp benefits continue to be stores with the

lowest trafficking rates. Overall, 84 percent of food stamp benefits are redeemed in store

categories with the lowest rates of trafficking.

• Electronic Benefit Transfer accounted for over half of all issuance during the measured

period.

EBT has expanded even more since these data were collected and it now represents over seventy

percent of all food stamp issuance.

Finally, during this period the store violation rate increased in rural and lower-poverty areas. While this

change should be monitored, its significance is muted by the fact that the proportion of benefits

trafficked in such areas (the rate of trafficking) is low.
Page 16

TECHNICAL DISCUSSION

When we look at additional considerations that bear on trafficking, we find two factors which would

tend to increase our estimate and two others that would tend to decrease it. It is important to discuss

each of these additional considerations explicitly.

SOURCES OF UNDERESTIMATION

1. Our procedure underestimates two aspects of the trafficking problem. The first aspect leading to

underestimation is evasion trafficking:

• Among small retailers that are family-owned or where ownership is closely-held, some violators

do not redeem coupons for cash from the government (direct trafficking) but buy food stock for

resale from large stores with trafficked coupons (a form of tax evasion we label "evasion

trafficking"). Evasion trafficking is a gray area, since the practice does not necessarily involve

discounting: a small firm makes an illicit profit at the least risk of detection if it accepts food

stamps at full value for food from legitimate recipients, but uses them (illegally) to buy food at

supermarkets for resale.

• In our estimate we are most concerned about evasion trafficking when it is linked to discounting

(i.e., the firm buys food stamp benefits at a discount). We have no data to estimate the extent

of evasion trafficking by unauthorized food stores or restaurants. However, evasion

trafficking by authorized retailers is partially captured by our estimating procedure,

when the trafficking involves discounting. The data we use to estimate direct trafficking

adequately capture the rate at which all authorized stores engage in discounting. What the data

fail to do is account for redemptions that are unreported by authorized discounting firms that

buy food for resale with the coupons. If unreported redemptions could be measured, then the

evasion trafficking factor would increase the national estimate of dollars diverted from food

benefits by trafficking but would not change the store-based violation rates useful for targeting

future action.

• Engaging in evasion trafficking was relatively easy with food coupons but is substantially more

difficult under EBT.xvii Because the only ones to find evasion trafficking cost-effective

are small privately-owned stores who have not yet switched to EBT, the potential

impact of this factor is limited to a shrinking subset of the privately-owned small-store

component of our estimate.
Page 17

2. The second potential cause of underestimation is network trafficking:

• Some violating stores will traffic with strangers while others restrict their illegal activities to

people they know (which we label "network trafficking"). Investigators can and do catch this

type of trafficking, but it requires a harder investigation.

• As a result, some network trafficking is included in our estimate (because our

investigations include some cases where the network was penetrated and trafficking was

caught). But other instances of network trafficking are not included in our estimate (because

investigators were unable to penetrate the network and make the case). This source of

underestimation applies to all components of our model. If investigators could catch all

instances of network trafficking, the national estimate of trafficking diversions would

increase.

xviii

SOURCES OF OVERESTIMATION

1. However, our procedure also overestimates other aspects of the trafficking problem. A first source

of overestimation is the procedure used to determine legitimate food sales.

• With extremely rare exceptions, stores that engage in trafficking also sell food and we must

allocate some proportion of their total redemptions to legitimate food sales and the balance to

trafficking.xix We purposefully used very low figures to estimate the percentage of

legitimate food sales by violating stores – this procedure serves our goal of assuring

an estimate of the maximum benefits diverted by trafficking. The estimate of trafficking

diversion would be lower to the extent that our method to estimate legitimate food sales was

more precise.

• This consideration is especially relevant to the large-store components of our model

(where most redemptions occur). We reviewed investigator reports in connection with cases

of supermarket trafficking.xx In supermarkets the percentage of total redemptions our

methodology attributes to trafficking (40%) is about four times higher than

experienced FNS field investigators attribute to trafficking (10% or less) when

recommending sanctions or participating in other legal proceedings.

• To be consistent with the 1993 figures, we keep our method the same in this update report

– but it is likely that the percentage of a store’s redemptions we attribute to trafficking

substantially overestimate trafficking, especially in supermarkets. Additional work is

being conducted to determine whether better estimates can be created.
Page 18

2. Another major source of overestimation is that investigations are a non-random sample of stores.

• Our estimating procedure relies on investigations targeted to find fraud: our estimate

would decrease substantially if investigators had randomly selected average stores, rather than

selected suspicious stores on purpose.

• Of our four technical considerations, this is arguably the one with the largest impact on

our estimate and applies to all components of our model.
Page 19

ENDNOTES

 

i Theodore F. Macaluso, The Extent of Trafficking in the Food Stamp Program (Alexandria, VA:

Food and Nutrition Service, USDA; 1995).

ii Both the earlier report and this one intentionally use calendar, rather than fiscal, years for the analysis.

There are two reasons for this. First, it is necessary to combine investigations from several years to

achieve a sufficient number of cases for analysis, so the choice of a fiscal or calendar metric is arbitrary.

Second, the use of calendar year reinforces the fact that we are providing estimates, rather than

administrative data (which typically is presented on a fiscal year basis).

iii There has been speculation that able-bodied adults without dependents (ABAWDS) are more likely

to traffic than other program participants. If this were true, then welfare reform time limits on the

duration of participation by ABAWDS might be expected to reduce the rate of trafficking. However,

the evidence available to USDA indicates that no one category of participant is either more or less

prone to traffic than any other category.

iv EBT also provides new ways to catch any trafficking that does occur. A new system, labeled

ALERT, analyzes EBT transaction data to catch some trafficking stores without the need for in-person

investigations. These cases are still relatively new and are not incorporated here. FNS is working on

developing a new trafficking measure to better reflect the impact of Electronic Benefit Transfer. ALERT

data will be included in the new measure.

v

 While food retailers constitute the overwhelming majority of authorized redeemers of food stamp

benefits, the Food Stamp Program has also authorized a few food wholesalers to accept food stamp

benefits. For simplicity, we refer to all authorized entities as retailers.

vi Trafficked coupons are not always redeemed for cash from the government. Owners of small

authorized or unauthorized stores, restaurants, and the like can pretend to be recipients and illegally use

food stamps to buy food at supermarkets for resale in their stores. We label this "evasion trafficking"

(since it is a form of tax evasion) and discuss its impact on our estimate at the end of this paper.

vii There is one trivial difference: the earlier report involved data on investigations started by January 1,

1991 and completed by March 1994 which were combined with redemption data from 1993 and presented

as a single result for calendar 1993; this update involves data on investigations completed between January
Page 20

 

1996 through December 1998 combined with redemptions from 1996 - 1998, which we annualize and

present as a single result for the 1996-1998 period. Because trafficking was less of a focus of

investigators in the 1980s than it is now, the earlier report involved a cut-off on the start of investigations

to ensure that the investigators’ focus was on trafficking (rather than sale of ineligible items). Such a

restriction is no longer needed.

viii We obtained all investigations included in the FNS Store Investigation and Monitoring System

(SIMS) database for calendar years 1996 through 1998. A small fraction of these investigations were

of stores that could not be matched to zip codes in the redemption file and therefore were not used in

the analysis. Inspection of these dropped investigations indicated (1) that the proportion of trafficking to

non-trafficking outcomes in these investigations was similar to the data used for the analysis and (2) the

cases were distributed across the data in such a way that it is implausible that they would change any

substantive findings. The total number of SIMS investigations and the number used in the analysis

were as follows:

 SIMS Analysis File

1996: 3,709 3,690

1997: 3,624 3,601

1998: 3,095 3,063

Total: 10,428 10,354

The five dimensions we employ consist of three that categorize stores (type of store, ownership, and

amount of food stamp business) and two that categorize the zip code in which each store was located

(degree of urbanization, percent of households in poverty). Specific definitions employed are as follows:

Type of Store.

Store types on the FNS application form were collapsed to the following seven categories (to ensure an

adequate number of cases of each type):

Supermarket any store identifying itself to FNS as a supermarket or grocery with gross sales

over $2,000,000.

Large grocery any store identifying itself to FNS as a supermarket or grocery with gross sales

between $500,000 and $2,000,000.

Small grocery any store identifying itself to FNS as a supermarket or grocery with gross sales

under $500,000.

Convenience any store identifying itself to FNS by this title, regardless of gross sales.

Specialty any store identifying itself to FNS by this title, regardless of gross sales. They

are almost always single product line stores such as meat markets, fish markets,

dairy stores, etc.
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Gas/Grocery any store identifying itself to FNS by this title, regardless of gross sales.

Other Types any store identifying itself to FNS by a title different than any of the preceding,

regardless of gross sales. Examples include produce stands, general stores,

combination grocery/bars, health/natural food stores, milk and/or bread routes.

Ownership.

Ownership types on the FNS application form were collapsed to the following two categories (to

ensure an adequate number of cases of each type).

Public any store identifying itself to FNS as a public corporation (i.e., a retailer whose

stock trades publicly).

Private any store identifying itself to FNS as other than publicly-owned. This includes

private (i.e., closely-held) corporations as well as partnerships, sole

proprietorships, co-ops, etc.

("Franchise" is a separate category on the FNS application, not an ownership type: both public and

private ownership categories include stores that report themselves as franchises.)

Amount of Food Stamp Business.

Stores were categorized into deciles on the basis of food stamp redemptions. The purpose was

statistical, rather than analytical, to ensure that large disparities in redemptions by stores do not distort

results.

Urbanization.

Based on census data for the zip code in which the store is located. Four categories were employed: 0

to 10 percent urban population, 11 to 50 percent, 51 to 90 percent, and over 90 percent.

Poverty.

Based on census data for the zip code in which the store is located. Four categories were employed: 0

to 10 percent of residential population below poverty, 11 to 20 percent, 21 to 30 percent, and over 30

percent.

ix For calculating trafficking rates, the number of investigations in each store category are large enough

to give high confidence in the estimates (ranging from a low of 369 to a high of 3,665 by store type).

x

Statistically, the FNS investigation data base encompasses a sufficient number of cases to be used as a

post-stratified sample of the national "population" of retailers. By categorizing the investigated stores on
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the five dimensions described in note 8 and weighting the stores, by category, to reflect the national

population of retailers, by category, we are able to draw valid conclusions about the national situation.

xi The specific calculation was a two-stage one. The first stage combines the data on the trafficking

rates by type of store and store location with national redemption data to yield an estimate of the gross

redemptions by authorized food stores found trafficking. The second stage accounts for the fact that

some of the gross redemptions are legitimate food sales. To ensure consistency with the earlier

estimate, we continue to use the assumption that legitimate food sales account for 60 percent of the

gross redemptions among supermarkets and large grocery stores caught trafficking and treat 40 percent

of their gross redemptions as trafficked. Among all other types of food stores, we assume that only 10

percent of the gross redemptions are legitimate food sales among stores that do not stock a full line of

food (i.e., small grocery, convenience, specialty food, gas/grocery, and "other" stores) and treat 90

percent of their gross redemptions as trafficked.

xii We processed all stores received from FNS redemption files but used only the ones with a match to

zip code data in the analysis. Stores that had no redemptions were dropped from the analysis (unless

they had been investigated, in which case they were retained). For each specific year the total number of

authorized retailers received and total number in our analysis file are as follows:

Received Analysis File

1996: 205,318; 202,850

1997: 196,408; 193,510

1998: 184,055. 180,857

xiii For each specific year the sum of redemptions (total dollars) was:

Received Analysis File

1996: $21,713,774,005 $21,580,132,008

1997: $18,463,396,131 $18,322,710,580

1998: $16,433,240,311 $16,260,221,191

xiv We categorize stores according to how they categorized themselves in FNS authorization data.

Examples of public corporations are major supermarket chains, like Albertson's and Safeway and gasand-go mini-marts operated by companies like Texaco or Mobil. Many major supermarket chains,

such as the Publix chain in Florida, are private corporations. IGA stores which have the appearance of

a chain but are not public also fall under non-public ownership. Stores that most readers consider

"franchises" may fall under either the public or non-public heading, depending on how they categorized

themselves to FNS. Southland's 7-Eleven chain are classified under public corporations.
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xv In 1993 USDA investigators found no instances of trafficking at publicly-owned supermarkets.

Between 1995 and 1998, however, four cases of trafficking occurred in publicly-owned supermarkets.

Because there are relatively few investigations of supermarkets and because the redemptions flowing

through supermarkets are so large, these four cases have a large apparent impact on trafficking rates.

To be consistent, we report the trafficking rates exactly as computed in the first trafficking report.

However, an examination of the four cases indicates that the procedures used in the earlier report

significantly overstate the amount of redemptions trafficked in supermarkets. Relevant considerations

include the following:

• Only a very small number of supermarket cases detect trafficking in any one year. Combining

the data from the earlier report with this update, we found the following cases of trafficking in

publicly-owned supermarkets: 0 in 1993, 0 in 1994, 1 in 1995, 2 in 1996, 0 in 1997, 1 in 1998.

• Two of the four cases appear to involve the actions of a single clerk. In one of those cases, the

clerk was not even at the cash register when the transaction took place. Two of the four cases,

however, involved a lower-level manager at the store.

• In three of the four cases, redemptions at the supermarket were in a pattern of significant

decline; two of the three were being closed. It is possible that upper management gave

decreased attention to employee actions in such an atypical environment. (This speculation will be

evaluated as additional supermarket trafficking cases emerge over the next several years.)

• The percentage of redemptions attributed to trafficking in these four stores by the

investigators was substantially lower than the percentage we use in our calculations. In the

first report when trafficking was found at a supermarket or large grocery we attributed 40 percent

of the total redemptions in the store to trafficking. In these four instances of trafficking, investigators

estimated that 10 percent or less of total redemptions were trafficked.

• In light of the above, the true rate of redemptions trafficked in supermarkets is likely to be

substantially below the 3 percent figure in Table 3.

xvi The increase in store violation rates outside of high poverty and highly urban areas may have

occurred for several reasons. For example, the results are possible if the decline in authorized retailers

differed by area. Alternatively, the results may reflect the expansion of EBT, either if the EBT switchover forces violators into nearby non-EBT areas (and those areas are less than 90 percent urban and/or

the population in poverty is under 21%) or if rural or higher-income States are implementing EBT at a

slower rate. It is also unclear at this stage whether the increase is occurring among all non-urban stores

or only those located along highways through rural areas. FNS is developing a new trafficking measure

to better reflect the impact of Electronic Benefit Transfer. These – and other – potential explanations

will be analyzed as part of that effort.

xvii The store owner would need to have possession of multiple EBT cards and make multiple trips to
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supermarkets (a small-store owner using more than one card to pay for a large purchase transaction

would involve the supermarket in a violation that is readily detectable through the ALERT system;

supermarkets are unlikely to accept that risk). Not only would the store owner need to have several

cards and use them at several places (or on different days), for the practice to be worth the risk of

getting caught the balances left on the cards would need to be large (which is not usually the case).

xviii

 An additional potential consideration is the quality of the investigation. Even when retailers are

willing to traffic with strangers, investigators with greater experience and adequate time and resources to

establish a case are likely to catch more trafficking than investigators with less experience, time and

resources. We believe the overall quality of investigations in our sample is high for two reasons. First,

FNS investigative procedures provide adequate time and resources to establish a case. Second, in the

earlier report we only used cases from 1991 and later, to ensure that investigators had at least two years

of experience in establishing trafficking cases (or were hired with the understanding that trafficking cases

were highest priority). In this report, most investigators have at least six years of experience in

establishing trafficking cases, which strengthens our confidence in these estimates.

xix On rare occasions phantom stores – i.e., fronts that take coupons but do not have a food business –

are found. This phenomenon is likely to decrease in the future for two reasons: (1) FNS has expanded

its staff resources to visit more stores in person; (2) EBT requires a visit from the EBT vendor to install

terminals and the vendor will not install a terminal if they have questions about the legitimacy of the

business.

xx See endnote 15.