United States

Department

of Agriculture

Economic

Research

Service

Electronic

Report

Food Assistance

and Nutrition 

Research Report 

Number 41

January 2005

Interstate Variation in 

WIC Food Package Costs

David E. Davis and Ephraim S. Leibtag

The Role of Food Prices, Caseload Composition, 

and Cost-Containment Practices
www.ers.usda.gov

Want to learn more about WIC food package costs? 

Visit our website at www.ers.usda.gov.

You can also find additional information, both paper and 

electronic, about ERS publications, databases, and 

other products at our website.

Visit Our Website To Learn More!

Just dial 1-800-999-6779. Toll free in the United States 

and Canada.

Ask for Interstate Variation in WIC Food Package Costs: 

The Role of Food Prices, Caseload Composition, and 

Cost-Containment Practices (FANRR-41)

It's Easy To Order Another Copy!

The U.S. Department of Agriculture (USDA) prohibits discrimination in all its programs 

and activities on the basis of race, color, national origin, sex, religion, age, disability, 

political beliefs, sexual orientation, or marital or family status. (Not all prohibited bases 

apply to all programs.) Persons with disabilities who require alternative means for 

communication of program information (Braille, large print, audiotape, etc.) should 

contact USDA's TARGET Center at (202) 720-2600 (voice and TDD).

To file a complaint of discrimination, write USDA, Director, Office of Civil Rights, Room 

326-W, Whitten Building, 14th and Independence Ave., SW, Washington, DC 

20250-9410, or call (202) 720-5964 (voice and TDD). USDA is an equal opportunity 

provider and employer.

National Agricultural Library Cataloging Record:

Davis, David E.

Interstate variation in WIC food package costs : the role of food

prices, caseload composition, and cost-containment practices.

(Food Assistance and Nutrition Research report ; no. 41)

Food relief-United States-Cost control. 2. Food prices-United

States-Regional disparities.

Special Supplemental Nutrition Program for Women, Infants, and

Children (U.S.)-Case studies.

 I. Leibtag, Ephraim. II United States. Dept. of Agriculture. Economic

Research Service. III. Title.

HV696.F6

 
United States

Department

of Agriculture

www.ers.usda.gov

Electronic Report from the Economic Research Service

January 2005

Food Assistance

and Nutrition

Research Report 

Number 41

Interstate Variation in WIC

Food Package Costs

The Role of Food Prices, Caseload

Composition, and Cost-Containment

Practices

David E. Davis and Ephraim S. Leibtag

Abstract

Food prices within States affect average monthly costs of State food benefits

packages provided by the Special Supplemental Nutrition Program for

Women, Infants, and Children (WIC) more than variations in WIC caseload

composition do. In addition, cost-containment practices by State WIC agencies provide different levels of cost savings in different areas, which also

contributes to interstate variation in benefits package costs. This study is one

of the few to examine the degree to which food prices, caseloads, and costcontainment practices influence costs of State WIC food benefits packages.

Because few data exist on the actual food items that WIC participants

purchase, the study used a scanner dataset of supermarket transactions and

other sources to estimate the average monthly cost of WIC food benefits in

several areas.

Keywords: WIC program, cost-containment, food package costs, food

prices, WIC foods, WIC caseloads, Special Supplemental Nutrition Program

for Women, Infants, and Children.

Acknowledgments

This report benefited greatly from conversations with Betsy Frazao, David

Smallwood, and Victor Oliveira of the Economic Research Service.
ii

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

Contents

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1

Research Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3

Method for Simulating Food Package Costs . . . . . . . . . . . . . . . . . . . . . .3

Food Packages and Food Quantities . . . . . . . . . . . . . . . . . . . . . . . . . . . .4

Price Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4

Calculating Average Food Prices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

Defining Representative Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7

Price Differences by Income Category . . . . . . . . . . . . . . . . . . . . . . . . .11

Caseload Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12

Results from Simulating Food Package Costs . . . . . . . . . . . . . . . . . . . .12

Decomposing Price and Participation Effects . . . . . . . . . . . . . . . . . . . .13

Cost-Containment Practices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .17

Milk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18

Peanut Butter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .19

Cheese . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .19

Juice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .20

Breakfast Cereal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .21

Eggs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .21

A Case Study of California and Texas 

Cost-Containment Practices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23

Conclusions and Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .28

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .29

Appendix Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .30
Introduction 

The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) provides Federal grants to States for supplemental foods,

healthcare referrals, and nutrition education for low-income pregnant,

breastfeeding, and nonbreastfeeding postpartum women and for infants and

children at nutritional risk. The WIC program is administered by the Food

and Nutrition Service (FNS) of the U.S. Department of Agriculture (USDA),

which provides grants to the States. These are divided into food grants,

which cover the costs of the supplemental foods, and nutrition services and

administration (NSA) grants. Food grants constitute the majority of the

program’s overall cost, and in fiscal year 2002, grants for supplemental

foods totaled $3.1 billion. 

Average monthly food costs per participant varied considerably across States.

In fiscal year 2002, these costs (net of rebates) for State agencies in the

contiguous United States ranged from a low of $26.70 in Maine to a high of

$41.43 in Connecticut.1 Many factors likely contribute to interstate variation

in food costs. Regional cost differences and other factors create regional price

differences for WIC-approved foods. Infant formula manufacturers offer

rebates for the exclusive right to supply infant formula for WIC programs on a

State-by-State basis; the process by which manufacturers gain this right

creates differences in net infant formula prices across States.2 Seven WIC

food packages, which differ in the mix of food products included and therefore in the average food package costs, are available for the various groups

qualifying for WIC programs. The proportion of participants receiving the

different food packages (WIC caseload composition) varies across States and

likely affects the variation in average monthly food cost. States may tailor the

quantity of foods offered to individuals or categories of participants for nutritional reasons, creating variations in the amount of food prescribed. A further

factor in interstate cost variations may be that States differ in the mix of

brands, container sizes, and types of foods available for WIC participants.

Although required to follow Federal regulations, State agencies have freedom

to restrict the foods that program participants are allowed to purchase. The

agencies may attempt to satisfy food preferences and nutritional needs, or to

restrain food costs, by adjusting the types of approved foods. Because WIC is

not an entitlement program, funding depends on available appropriations.

Lowering the cost of approved foods allows WIC agencies to maximize the

number of applicants they can enroll.

At present, little is known about the degree to which each of these factors

influences interstate variation in average monthly food costs. The associations

between the variables and the costs, if better understood, may have large

policy implications—for instance, for lowering WIC expenditures and serving

more clients. At one extreme, all variation may result from differences in State

policies (e.g., rebates or cost-containment practices). In this case, policies in

low-cost States would provide key insights to high-cost States for reducing

costs. At the other extreme, all variation may result from factors beyond the

control of WIC administrators (e.g., food prices or caseload compositions),

providing little policy guidance for reducing costs. However, because policies

can affect program efficacy, understanding that high costs result from factors

other than State policies can be important; high-cost States may be saved from

1

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

1 FNS calculates State-specific per

participant average monthly food costs

by dividing each State’s total annual

WIC food expenditures by the number

of WIC participants in the State, then

dividing this figure by 12. Hereafter,

we adopt the convention of referring to

average monthly food costs. It should

be understood these costs are per participant. 

2 Typically, WIC State agencies obtain

significant discounts in the form of

rebates from the manufacturers for

each can of infant formula purchased

by WIC participants. In exchange for

the rebates, a manufacturer is given

the exclusive right to provide its products to WIC participants in the State.

The contract is awarded to the manufacturer offering the State WIC agency

the lowest net price, as determined by

the manufacturer’s wholesale price

minus the rebate.
enacting policies intended to reduce costs that instead only affect—and

lower—participant satisfaction. Further, there are implications for State equity.

In reality, factors both within and outside agency control likely affect interstate variation. The goal of this study was to understand the relative importance of some of these factors, including interstate differences in the

effectiveness of cost-containment practices, food prices, and the mix of WIC

participants (caseload compositions).

Few data exist on the actual foods WIC participants purchase and the prices

they pay. Therefore, we simulated the purchase decisions of the participants.

Information on food prices came from scanner data of food purchases in

supermarkets in local market areas. Data on the composition of State caseloads are available from FNS. We used the Federal WIC regulations to identify the maximum quantity of food available in each of the seven food packages for WIC participants. This information allowed us to simulate Statespecific average monthly food costs. By analyzing simulated food package

costs, we were able to identify the relative importance of several factors that

generate interstate variation in costs. Finally, we used the simulated food

packages to conduct experiments for gauging the importance of State-specific cost-containment policies that restrict the food types allowed.

2

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA
Research Approach

We used three pieces of information to simulate State-specific, average

monthly food costs: State food prices, number of WIC participants by

participant category by State, and the maximum quantity of food in WIC

food packages. 

Method for Simulating Food Package Costs

WIC participants can receive one of seven different food packages, each

containing various combinations of WIC foods. We simulated the total

monthly cost of food packages by multiplying the price of the items in the

package by the per participant monthly quantities of the items allowed by

Federal regulations. That is, the monthly cost (Ci, j) of package i in State j,

where Pk,j is the average price of food k in State j, and Qk,i is the quantity of

food k allowed in food package i. The total cost in State j of package i

(STCi,j) is calculated by multiplying the cost of package i by the number of

participants (Ni,j) in State j qualifying to purchase package i, or

The per participant average monthly food cost in State j (ACj

) for all WIC

packages is calculated by summing the STCi,j for all packages, and dividing

the proportion of the caseload qualifying for food package i in State j (hereafter called caseload composition (CCi,j)), we get the following equation for

simulated average monthly food costs in State j:

This simulation method requires three pieces of information, State-specific

average food prices ( Pk,j), State-specific caseload compositions (CCi,j), and

the quantity of foods allowed in each food package (Qk,i). Note also that

average monthly food costs vary across States from two sources in this

calculation: average food prices and the number of participants (and thus the

caseload composition) qualifying for the different food packages.3 Food

quantities are held constant across States and are not a source of interstate

variation in the simulated costs.

3

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

3 We also examined whether there was

significant variation over time in simulated WIC package costs. We have

only 1998 State caseload data and

1997-99 price data, and since food

quantities do not vary over time, time

variation in simulated package costs

comes only from price variation. It

was clear that interstate variation in

costs dominated within-State time

variation, so we chose to focus on

interstate variation in costs by averaging over all 3 years of price data.

* (1) , = ∑ , ,

k

Ci j Pk j Qk i

*C . (2) i, j Ni, j i,j STC =

* * ) (3)

* * )

, , ,

,

, , ,

,

(CC P Q . N

(N P Q

N

STC

AC

i k

i j k j k i

i

i j

i k

i j k j k i

i

i j

i

i,j

j ∑ ∑ ∑

∑ ∑

∑

∑

= = =

by the total number of WIC participants in each State . Letting equal ∑

i i,j N

i,j N

j

⎯

⎯
Food Packages and Food Quantities

Federal regulations (7 CFR ch. 11 subpart D-Participant Benefits) specify

the maximum monthly quantities of each food type for each food package.

States have the option to restrict the types of foods they choose to provide

their participants. We assumed each State provides, and participants then

purchase, the federally mandated maximum amounts of each food.4

Federal regulations permit some flexibility and substitutions among

approved foods. For example, the food package for children ages 1 through

4 allows for a monthly allotment of 24 quarts of milk. However, cheese may

be substituted for fluid milk at the rate of 1 pound per 3 quarts, with a 4-

pound maximum. In our calculations, we assumed a combination of milk

and cheese were purchased.5 Similarly, some packages stipulate that participants may receive either peanut butter or beans. For our calculations, we

assumed these packages contain only peanut butter and no beans. 

We detailed the per participant monthly food quantities for each of the five

food packages simulated (table 1). Federal regulations stipulate two specialized food packages. With proper medical documentation, State agencies may

issue women and children with special dietary needs food package 3. Food

package 7 is an enhanced package for breastfeeding women and includes tuna

and carrots in addition to milk or cheese, eggs, hot or cold cereals, fruit or

vegetable juice, and legumes. We were not able to simulate food packages 3

and 7 because we did not have data on the proportion of a State’s caseload

purchasing these packages. Instead, we assume all children get food package

4 and that all women purchase either package 5 if they are pregnant or breastfeeding or package 6 if they are postpartum and not breastfeeding.

Price Data

To calculate State-specific average food prices, we used a special scanner

dataset of household purchases of food items from the InfoScan Custom

Store Tracking System from Information Resources, Inc. (IRI). These data

record household purchases of food items at supermarkets and include price

information and descriptions of the items.6 The data include purchase transactions for about 43,000 households for 1997, 1998, and 1999, from 24

market areas. Market areas may not be representative of the entire State and

do not cover all States (table 2 and fig. 1).7

Household members scan a card at the supermarket, and their purchase

transactions are recorded at a scanner. IRI then matches household demographic information, recorded at the time households acquire their membership cards, with their purchase transactions. All transactions are recorded,

but IRI sells data according to food categories. 

We had data for household purchase transactions for nine categories of foods

that are eligible for the WIC program according to Federal regulations:

● Fruit and vegetable juice

● Peanut butter

● Infant formula

● Baby cereal

4

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

4 We recognize this as a strong

assumption. It is likely that the quantities of foods purchased by WIC participants vary by State, undoubtedly

playing a role in interstate cost variation. However, State-by-State purchase

data are unavailable.

5 We choose a substitution rate between

cheese and milk to approximate FNSreported cheese expenditures. In FY

2000, FNS reported that cheese expenditures represented 12.7 percent of the

post-rebate food costs. Our method

results in an all-State average expenditure share of 10.9 percent.

6 We were not able to identify WICauthorized vendors in these data. States

impose a number of requirements on

vendors that may result in different

prices for WIC participants. However,

if prices for WIC vendors and non-vendors are highly correlated within a

State, then interstate comparisons, the

focus of this report, would not be greatly affected if we were able to use prices

from WIC vendors. Similarly, we were

not able to examine the impact of WIConly stores. Wic-only stores target WIC

participants and provide only WICapproved foods. They were not included in our data. Some data suggest WIConly stores charge higher prices than

other WIC vendors. And some States

have more WIC vouchers redeemed

through WIC-only stores than other

States. Thus, Wic-only stores may contribute to interstate variation in food

package costs. 

7 For example, there are no data for

purchases made in rural areas, which

may have higher or lower prices than

in urban areas. 
● Eggs

● Milk

● Cheese

● Ready-to-eat breakfast cereal

● Dried beans/peas

Because the IRI is our source for price data, we must restrict our analysis to

the 3 years, 24 cities, and 17 States for which IRI scanned transactions.

Calculating Average Food Prices

Many characteristics of foods purchased in the WIC program are left to

participant choice; while general food types are dictated by Federal guidelines, individual participants have some freedom to choose the flavor, brand,

and package size they prefer. State agencies frequently restrict the choice by

dictating approved types (orange, apple, and grape juice), brands (e.g.,

5

Interstate Variation in WIC Food Package / FANRR-41

Economic Research Service/USDA

Table 1—WIC food packages

Food packages

Food type Federal max. qty allowed Simulated package qty

Package 1: Infants 0 to 3 months

Infant formula 403 oz of liquid concentrate 403 oz of liquid concentrate

Package 2: Infants 4 to 12 months

Infant formula 403 oz of liquid concentrate 403 oz of liquid concentrate

Infant cereal 24 oz 24 oz

Single-strength juice 92 fluid oz 92 fluid oz

Package 3: Women and children with special needs

Not applicable

Package 4: Children 1 through 4 years

Milk 24 qts of fluid milk 20 qts fluid milk

Eggs 30 count 30 count

Cereal 36 oz 36 oz

Peanut butter 18 oz 18 oz

Single-strength juice 276 fluid oz 276 fluid oz

Cheese 4 lbs 1.33 lbs

Package 5: Pregnant and breastfeeding women (basic)

Milk 28 qts of fluid milk 24 qts of fluid milk

Eggs 30 count 30 count

Cereal 36 oz 36 oz

Single-strength juice 276 oz 276 oz

Peanut butter 18 oz 18 oz

Cheese 4 lbs 1.33 lbs

Package 6: Nonbreastfeeding postpartum women

Milk 24 qts of fluid milk 20 qts of fluid milk

Eggs 30 count 30 count

Cereal 36 oz 36 oz

Single-strength juice 184 oz 184 oz

Cheese 4 lbs 1.33 lbs

Package 7: Breastfeeding women (enhanced package)

Not applicable

Source: Federal WIC regulations and ERS simlulations.
private label), and package sizes (e.g., only gallon containers of milk or 46-

ounce cans of juice). While only some of these restrictions may be for cost

containment, with others employed for administrative ease, we refer to all of

them as cost-containment practices. 

Because prices can vary by brand, flavor, and package size, interstate variation in participant preferences and cost-containment practices can be a

source of interstate variation in average monthly food costs. However, we

had limited information on State agency cost-containment practices and

virtually no information on the actual food items, brands, and sizes

purchased by WIC participants.8 We addressed these issues by assuming 

all WIC participants purchase the same types, brands, and sizes of food

6

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

8 Information on State plans is available from State agencies. We did not

pursue this avenue because of the difficulty identifying practices in effect

for the time period covered by our

price data. 

Figure 1

Market areas that were sources of scanner data

•Seattle

•Midland

Denver

• •Grand Junction

•Los Angeles

•San Francisco/

 Oakland

•Memphis

Houston

•

•

•

•

Tampa/ • St. Pete

Atlanta

Rome

Chicago

St. Louis

Kansas City

•

• •

•

Eau ClaireDetroit

Minneapolis/

St. Paul

Cedar Rapids •

• •

•

•

• • Boston

New York

Philadelphia

Pittsfield

Pittsburgh

Source: Information Resources, Inc.

•Visalia

Table 2—Market areas

State Market areas

California San Francisco/Oakland, Los Angeles, Visalia

Colorado Denver, Grand Junction

Florida Tampa/St. Petersburg

Georgia Atlanta, Rome

Illinois Chicago

Iowa Cedar Rapids

Kansas Kansas City

Massachusetts Boston, Pittsfield

Michigan Detroit

Minnesota Minneapolis/St. Paul

Missouri St. Louis

New York New York City

Pennsylvania Pittsburgh, Philadelphia

Tennessee Memphis

Texas Houston, Midland

Washington Seattle/Tacoma

Wisconsin Eau Claire
products. The effect that various cost-containment practices can have on

State food package costs will be discussed.

We calculated average per unit prices (e.g., price per ounce) for food products

from the available scanner dataset of food purchases. However, we wanted to

avoid creating interstate variation in food prices from interstate variation in

food purchases. For example, food prices can vary by package size and

usually decrease on a per unit basis as package size increases. Thus,

consumers in one State may purchase larger packages than consumers in

another State. However, even if prices in both States are the same for identical

products, when prices are averaged over all purchases the average price per

unit will be lower in the State with the larger average purchase size. Similarly,

interstate variation in consumer preferences for flavors, brands, and package

types, along with a host of other factors, can generate interstate variation in

average prices even if prices for identical products are equal. Because we

wished to measure the price difference between two locations for identical

products, we calculated a State-specific average price for a representative

product. To minimize package-size effects, we did not include purchases of

the smallest package sizes of the representative items.9

Defining Representative Products

For this analysis, the absolute price level of the representative item in a

State (market area) is not as important as is its price relative to other States

(market areas). Ideally, whether the price of the representative item in a

market area is above or below the 17-State average should be invariant to

the choice of the representative item for any food category. When this is

true, it suggests that the price of the representative item accurately reflects

the relative price of all items in the entire food category and is therefore a

“good” representative for that category. Of course, this is unlikely to always

be the case, as some food categories are inherently heterogeneous. For

example, juice comes in many different flavors (orange, apple, grape, white

grape, fruit punch, etc.), each with different prices per unit. It is not likely

that the average per unit prices of all these flavors would simultaneously be

above or below average in a particular market area. Nonetheless, choosing

one representative item for each food category is a necessary simplification

to make our analysis tractable.10 Recognizing that the analysis can be

affected by the choice of representative item, however, we present evidence

that a different choice would not dramatically affect the results.

For peanut butter, private label in package sizes greater than 10 ounces is

the representative item (table 3). We used the private label brand because it

is widely available. Peanut butter does have branded products in all the

market areas. However, it does not appear that using an alternative brand

would affect our results. In figure 2, the red bar plots the price of private

label peanut butter divided by the 17-State average price of peanut butter.

The blue bar plots the price of Jiff, a popular brand of peanut butter, divided

by its 17-State average price. A bar greater than 1 indicates a price higher

than average, a bar less than 1 indicates a price lower than average, and a

bar equal to 1 indicates a price equal to the average. In figure 2, the Statespecific average prices of private label brands and the Jiff brand are always

simultaneously above or below average. 

7

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

9 We experimented with a variety of

methods to calculate food prices.

Notably, we calculated weighted average prices using brand shares as

weights. Most analyses, subsequently

reported in the main body of the text,

were not qualitatively affected by using

this method. 

10 Another method for calculating average prices is to calculate a weighted

average price, with each brand and flavor receiving a separate weight, and

with the weights held constant across

States. However, not all brands are

available in every State, and there is

very little information by which to

determine appropriate weights. 
The data include private label brands of ready-to-eat (RTE) cereal. However,

it is not possible to distinguish types of cereals within the private label

brand—for example, to distinguish between private label granola and corn

flakes. There is thus little benefit to restricting the analysis to private label

cereals. Instead, we included all RTE breakfast cereal in boxes 12 ounces or

larger when calculating the average price of cereal. We included all brands

and did not confine the analysis to low-sugar, WIC-approved cereals

because our data did not include information on sugar content. 

RTE cereal is a very heterogeneous product, with many brands and types

whose prices vary on a per unit basis. However, it seems that choosing

another representative item would affect our results only marginally. We plot

the State-specific average price of all boxes 12 ounces or larger, divided by

the 17-State average price (fig. 3). We also plot the State-specific average

price of Cheerios, one of the most popular cereal brands, relative to its 17-

State average.11 Most of the time, the State-specific prices of the two items

are jointly above or below the average (13 of 17 times). 

We included all 1-gallon containers of unflavored milk to calculate the average

price of milk, using an independent price survey to evaluate our choice of

8

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

11 To determine popular brands, we

calculated brand expenditure shares,

which are the total expenditures for a

single brand of an item divided by

total expenditures for all brands of that

item. We calculated brand expenditure

shares for all brands of RTE cereal for

each of the 17 States in the data, and

Cheerios consistently had one of the

largest expenditure shares.

Table 3—Representative foods

Food type Representative item

Peanut butter Private label greater than 10 oz

Ready-to-eat cereal All boxes, 12 oz or larger

Milk Unflavored one-gallon containers of fluid milk

Single-strength juice Private label apple juice greater than 30 oz

Cheese Private label cheddar greater than 8 oz

Infant formula Liquid concentrate (State contract brand)

Baby cereal Boxes of rice or oatmeal

Eggs All brands

Dried beans All brands

Figure 2

Private label and Jiff peanut butter prices 

relative to the 17-State average

Source: Appendix table 1.

Proportion of 17-State average

CA CO FL GA IA IL KS MA MI MN MO NY PA TN TX WA WI

0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

17-State average

Jiff Private label
representative product. USDA’s Agricultural Marketing Service (AMS) regularly monitors milk prices in several market areas around the country. Some of

these markets coincide with markets in our scanner data, and we compare the

AMS average price for gallons of whole milk to the scanner data average (fig.

4).12 AMS prices are frequently similar to the average prices from scanner

data. For 6 of the 11 State price comparisons, prices are less than 5 percent

apart, and for 9 of the 11 less than 15 percent apart. 

Single-strength private label apple juice (i.e., not from concentrate) in

package sizes greater than 30 ounces serves as the representative product for

juice. We chose the private label brand because it is widely available, and

the apple flavor because it is one of the most popular flavors of juice. 

Single-strength juice is another heterogeneous item, with many brands and

flavors and prices that vary on a per unit basis. In our data, the three most

frequently purchased flavors of juice are apple, orange, and grape. Figure 5

9

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

12 AMS market administrators regularly survey retail milk prices for gallon

containers of whole and 2-percent

milk. Market administrators average

the price of the leading milk brand,

based on shelf space, at three locations: the largest and second-largest

retailers and the largest convenience

store in a market. The prices are

recorded at the same stores between

the 1st and 10th of each month.

Figure 3

Ready-to-eat cereal prices relative to 17-State average

Source: Appendix table 2.

Proportion of 17-State average

17-State average

Cheerios All 12-oz boxes

CA CO FL GA IA IL KS MA MI MN MO NY PA TN TX WA WI

0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

Figure 4

Milk prices—Agricultural Marketing Service (AMS) and scanner data

Source: Appendix table 3.

Dollars per/gal.

Average retail - AMS Scanner data

CO FL GA IL KS MA MN MO PA TX WA

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5
plots the average price relative to the 17-State average for the private label

brands for all three of these juice flavors. Although the prices for all flavors

usually move together, in several instances the price of one juice is higher

(or lower) than average, while the price of at least one other flavor is lower

(or higher) than average. 

For cheese, we calculated a price for private label (natural) cheddar in

packages greater than 8 ounces. Cheese is also a heterogeneous product,

with many brands and types, and there was no clear choice for representative product. We chose cheddar because it is popular and the private label

brand because it is widely available. We plot the average price of private

label cheddar cheese, divided by the 17-State average price, and the

average price of private label American cheese, divided by the 17-State

average price of private label American cheese (fig. 6).13 We note again

10

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

13 Cheddar and American cheese are

the two most frequently purchased

cheese types in our data.

Figure 6

Private label cheese price relative to the 17-State average

Source: Appendix table 5.

Proportion of 17-State average

17-State average

American Cheddar

CA CO FL GA IA IL KS MA MI MN MO NY PA TN TX WA WI

0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

Figure 5

Juice prices relative to the 17-State average

Source: Appendix table 4.

Proportion of 17-State average

17-State average

Private label orange Private label apple

CA CO FL GA IA IL KS MA MI MN MO NY PA TN TX WA WI

0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

Private label grape
that the prices of the cheese types are usually in agreement, at above or

below the 17-State average. 

Infant formula is a case where information is available on actual WIC

purchases, as WIC participants are required to buy the State-contract brand.

While we were able to calculate prices for a variety of infant formula types

(e.g., powder or ready-to-drink), an important factor in final WIC food

package costs is the amount of rebate that WIC receives from formula

manufacturers. We were able to calculate average rebates only for liquid

concentrate.14 So we assumed all formula purchases were liquid concentrate, which enabled us to examine the relative roles of interstate price and

rebate differences.15

There are very few purchase transactions for private label baby cereal, so we

included all brands but restricted analysis to boxes of rice or oatmeal. Eggs

are a homogeneous product, and we included all brands of eggs. 

Price Differences by Income Category

Participants in the WIC program are by definition low-income consumers.

We examined whether low-income consumers pay different prices than

those in other income categories. In most instances, they did not pay

significantly lower average prices than consumers in higher income

classes. As an example, we plot milk prices for three income classes of

consumers (fig. 7).16,17 Note that price varies only slightly for the

different classes of households.

Because restricting the sample to low-income consumers dramatically

reduced the sample of purchase transactions, and since we did not detect

large average price differences for low-income or WIC-eligible households,

we chose to average prices over all income classes and retain a much larger

sample of observations.

11

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

16 Households are defined as low

income if the household has one member and income < $15K; two members

and income < $20K; three members,

and income < $25K; four or five members and income < $35K; six or seven

members and income < $45K; eight

members and income < $55K; nine

members and income <$65K. Highincome households are all households

not defined as low-income, and WICeligible households are low-income

households with children under 5

years old.

17 In the scanner dataset, households

report their appropriate income category and size. We used this information

to identify purchases by households in

each of the low-, middle-, and highincome categories defined above.

Figure 7

Milk prices by income

Source: Appendix table 6.

Dollars per/gal.

High income Low income WIC eligible

CA CO FL GA IA IL KS MA MI MN MO NY PA TN TX WA WI

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

14 FNS reports historical rebate data

only for cans of 13-ounce liquid concentrate infant formula.

15 Liquid concentrate infant formula

accounted for 27 percent of all formula

sold in 2000.
Caseload Composition

To simulate State food package costs, we needed data on the number of participants falling into the various WIC categories. The number of WIC participants

qualifying for the various food packages are from the Study of WIC Participant

and Program Characteristics, 2000, a biennial publication of FNS (USDA,

FNS, 2000), a report that includes various measures of WIC program characteristics for 1998. 

Figure 8 shows the composition of caseloads using data for the five WIC

categories. Caseload composition varies across States. Each participant category qualifies for its own WIC food packages, which are differentiated by

the type and/or quantity of food they contain, and so differ in cost. Therefore, differences in caseload composition can also be a source for interstate

variation in average monthly food costs. 

Results from Simulating Food Package Costs

We compared the simulated average monthly food costs from equation 4, along

with the average for all 17 States as well as the average monthly food cost for

1997-99, calculated from food grant and participation data reported by FNS

(fig. 9). FNS average monthly food costs are estimated by dividing total annual

food costs by total annual participation, then dividing this figure by 12.

The simulated average costs reasonably approximate FNS average State

costs (fig. 9). Most often (9 of 17 times), cost differences between simulated

and FNS costs are less than 5 percent, and they are usually (12 of 17 times)

less than 7.5 percent. We expected simulated costs to be higher than FNS

costs because we assumed all participants purchase a full allotment of all

foods and because we do not account for cost-containment practices. Simulated costs were indeed higher for 12 of 17 States; Texas, Colorado, Illinois,

and Tennessee were notable instances where simulated costs are more than

12

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

Figure 8

Caseload composition

Source: Appendix table 7.

Percent

Infant Children Pregnant

CA CO FL GA IA IL KS MA MI MN MO NY PA TN TX WA WI State

avg.

0

20

40

60

80

100

Breastfeeding Postpartum
7.5 percent greater than FNS costs. For these States, our method of

constructing average prices may result in a poor approximation of the prices

WIC participants actually pay. Alternatively, these States may be successfully incorporating cost-containment practices to counteract price effects. In

contrast, Iowa is a case where simulated costs suggest a low average

package cost but where FNS costs are higher than the simulation predicted. 

We did not expect exact replication of State costs because we lacked information on the actual products and quantities that WIC participants purchased and

on purchases in rural or other metropolitan areas within a State, and because

we did not incorporate information on State-specific cost-containment practices. Nonetheless, our simulated average costs correlated with actual costs.

This correlation supports the overall methodology, suggesting that evaluating

sources of cost differences in our simulated packages can offer insights into the

sources of cost differences in actual WIC packages. 

Decomposing Price and Participation Effects

We next sought to quantify the role of price and caseload composition

differences in generating interstate variations in WIC food package costs.

The method was to decompose the difference between State average costs

and a comparison average cost. This difference was then decomposed into

portions attributable to price and caseload differences. For each State, we

decomposed the difference between average monthly food costs in State j

(ACj

) and the 17-State average monthly food cost (AC17) into price and

caseload differences. An algebraic manipulation of the difference in simulated average costs between State j and the 17-State average results in the

following relationship, which we use to decompose the difference in average

monthly package costs:

13

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

Figure 9

Simulated State average cost vs. FNS average cost data

Source: Appendix table 8.

Dollars

Simulated average cost FNS average costs

CA CO FL GA IA IL KS MA MI MN MO NY PA TN TX WA WI Avg

0

5

10

15

20

25

30

35

40

45

* * ( * *( ) (4) , , ,17 , ,17 , ,17

17

P Q CC CC Q CC P P 

AC AC

k i i k j k

k i kj k i i j ii k

j

⎥

⎦

⎤ ⎢

⎣

⎡

⎭

⎬

⎫

⎩

⎨

⎧ + ∑ ∑ − ⎥

⎦

⎤ ⎢

⎣

⎡

⎭

⎬

⎫

⎩

⎨

⎧ ∑ ∑ −

− =
The term in the first set of square brackets is the difference in average cost

between State j and the 17-State average, generated from differences in

caseload composition for the i=5 WIC food package’s participants. The

difference in caseload composition is weighted by State j prices and the

quantities of the k foods in the i food packages.18 Essentially, this portion of

the equation holds food prices and quantities constant between location j

and the 17-State average by counterfactually applying location j prices to

calculate the 17-State average cost. It measures the effect of differences in

caseload composition between j and the 17-State average, while holding

food prices and quantities constant. 

The term in the second set of square brackets is the difference in average

cost between State j and the 17-State average, generated from differences in

the prices of the k foods in State j and the 17-State average, weighted by the

quantity of the k foods, and the 17-State average caseload compositions of

the i groups. This portion of the equation holds caseload compositions and

food quantities constant between location j and the 17-State average, by

counterfactually applying the 17-State average caseload compositions to

location j prices. It measures the effect of differences in prices, while

holding caseload compositions and quantities constant.19

We simulated average costs for each of 17 States and a 17-State average.

The 17-State average was calculated by averaging prices and participation

rates over all 17 States for which we have data. Table 4 gives the results

from decomposing simulated average cost differences between each of 17

States and the 17-State average. Figure 10 summarizes the data in table 4.20

The first row of table 4 shows simulated average costs for 17 States. The

second row shows the simulated 17-State average cost, and the third row

gives the difference between the two. The next two blocks of rows report the

results from using equation 4 to decompose the difference (row three) into

portions attributable to differences in caseload compositions and prices. The

greatest source of variation arises from differences in prices (table 4; fig.

10). While differences in caseload composition can generate differences in

average costs, effects from price differences are, except for Kansas, larger. 

Most of the time the total price effect has the same sign as the individual

food price effects. For example, Texas (Midland, Houston) has a total price

effect of -$2.60, and six of the eight food price differences also have a negative sign, while one has no measurable price effect. In California (Los

Angeles, San Francisco/Oakland, Visalia), the total price effect is $1.83, and

all eight food price differences also have a positive sign. Indeed, for 16 of

the 17 States, the difference between the simulated State average cost and

the 17-State average cost appears to be driven mostly by the price effect.

This difference suggests that some States have lower-than-average prices for

most foods while others have higher-than-average prices. Low-price States

have lower-than-average monthly food package costs, and high-price States

have higher-than-average costs. 

Variation in child caseloads generates many of the largest caseload effects.

Caseload effects contribute more than $1.00 in absolute value to the total

cost difference in 14 cases, nearly half of which are because caseloads of

children are higher or lower than the 17-State average (in Iowa, Illinois,

Minnesota, Tennessee, Texas, and Wisconsin). Notable instances of large

14

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

18 Note that not all i participant categories qualify to purchase all k foods.

In these cases, Qk,i=0.

19 Food quantities do not vary across

States, so they are the same in State j

and the 17-State average.

20 Recall that we approximated State

package costs by using city data. In

table 4 and figure 10, space limitations

require that we head each column, or

data point, with State rather than city

abbreviations.
15

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

Table 4—Decomposing cost differences (dollars)

CA CO FL GA IA IL KS MA MI MN MO NY PA TN TX WA WI

State 34.18 34.74 32.26 30.28 29.69 32.73 32.28 29.10 30.69 31.07 32.38 34.76 30.37 36.27 28.64 34.58 29.66

17-State 31.92 31.92 31.92 31.92 31.92 31.92 31.92 31.92 31.92 31.92 31.92 31.92 31.92 31.92 31.92 31.92 31.92

diff. 2.26 2.81 0.33 -1.64 -2.23 0.81 0.36 -2.83 -1.24 -0.86 0.46 2.83 -1.55 4.35 -3.28 2.66 -2.26

From differences in caseload composition

Infant -0.23 -0.18 0.46 -0.23 -0.43 1.10 -0.25 -0.12 -0.08 -0.16 -0.20 0.47 0.13 1.08 0.25 -0.18 -0.28

Child 0.56 -0.93 -0.87 -0.60 1.67 -1.61 0.64 0.93 0.66 1.45 -0.48 -0.77 0.73 -2.23 -1.21 0.32 1.24

Preg. -0.49 0.60 0.26 1.03 -0.48 0.13 -0.44 -0.28 -0.07 -0.52 -0.05 0.16 -0.84 0.75 -0.24 1.21 -0.46

BF 1.02 1.04 -0.10 -0.36 -0.27 -0.47 -0.13 0.31 -0.54 -0.07 -0.22 0.57 -0.69 -0.57 0.16 0.75 -0.14

PP -0.43 -0.08 -0.33 0.59 0.26 -0.01 0.41 -0.24 0.13 -0.51 1.03 -0.89 0.35 0.61 0.36 -1.48 0.02

Total 0.43 0.45 -0.58 0.43 0.74 -0.85 0.23 0.60 0.10 0.19 0.08 -0.47 -0.32 -0.36 -0.69 0.62 0.37

From differences in prices

Formula 1.38 -0.28 -1.49 -0.72 -0.33 2.37 -0.51 -1.79 -0.03 0.88 -2.35 0.84 -0.89 2.87 -0.71 0.61 0.16

Rebate 1.47 -0.07 -1.75 0.11 0.63 0.94 -0.63 0.45 0.72 0.31 -2.91 0.39 -0.68 -0.78 0.66 0.60 0.53

BCereal 0.02 0.00 -0.06 -0.04 0.04 0.01 0.02 -0.05 0.01 -0.02 0.04 0.06 -0.01 0.05 -0.03 -0.03 -0.01

Cereal 0.32 -0.06 -0.34 -0.10 -0.34 -0.10 -0.28 -0.42 0.44 -0.56 0.23 0.62 0.32 0.55 -0.33 0.41 -0.36

Juice 0.42 1.06 -0.25 -0.81 0.63 0.52 0.52 -0.49 -1.24 -0.84 -0.54 -0.14 -0.31 -0.14 0.31 1.38 -0.08

Milk 0.03 1.44 1.28 -0.01 -1.40 -0.53 -0.07 -0.20 -0.37 0.84 0.38 0.91 -1.16 0.69 -1.00 -0.22 -0.61

Cheese 0.19 -0.01 0.15 -0.18 -0.36 0.05 -0.02 -0.34 0.41 -0.38 -0.07 0.61 0.55 0.28 0.00 -0.23 -0.65

Eggs 0.84 0.03 -0.10 -0.10 -0.54 0.33 -0.22 0.55 0.06 -0.51 -0.14 0.65 -0.42 -0.27 -0.14 0.41 -0.42

PB 0.12 0.12 -0.03 -0.02 -0.03 -0.04 0.06 -0.25 0.11 -0.12 -0.08 0.13 0.01 -0.10 -0.05 0.30 -0.12

Total 1.83 2.37 0.91 -2.07 -2.97 1.66 0.12 -3.43 -1.34 -1.04 0.38 3.30 -1.22 4.71 -2.60 2.04 -2.64

Infant = Infants 0 through 12 months; Child=Children 1 through 4 years; Preg=Pregnant women; BF=Breastfeeding women;

PP=Nonbreastfeeding postpartum women; Formula=Infant formula; Rebate=Infant formula rebate; BCereal=Baby cereal; Cereal=Ready-to-eat

cereal; PB=Peanut butter.

California=San Francisco/Oakland, Los Angeles, Visalia; Colorado=Denver, Grand Junction; Florida=Tampa/St. Petersburg; Georgia=Atlanta,

Rome; Iowa=Cedar Rapids; Illinois=Chicago; Kansas=Kansas City; Massachusetts=Boston, Pittsfield; Michigan=Detroit;

Minnesota=Minneapolis/St. Paul; Missouri=St. Louis; New York=New York City Pennsylvania=Pittsburgh, Philadelphia; Tennessee=Memphis;

Texas=Houston, Midland; Washington=Seattle/Tacoma; Wisconsin=Eau Claire.

Sources: Rebate data: USDA, FNS. WIC Program Infant Formula Rebate Contract Summary (various report dates); all other data:

ERS calculation from WIC cost simulations.

Figure 10

Cost differences from price and caseload effects

Source: Table 4.

Dollars

Total from caseload composition differences Total from price differences

CA CO FL GA IA IL KS MA MI MN MO NY PA TN TX WA WI

-4

-3

-2

-1

0

1

2

3

4

5

6
caseload effects include lower-than-average caseloads of children in

Tennessee and higher-than-average caseloads of children in Iowa. Tennessee

has a child caseload of 46.30 percent (appendix table 7), 5.79 percent below

the 17-Stage average, reducing the cost difference between Tennessee and

the 17-State average by $2.23. In contrast, Iowa has a child caseload of

56.90 percent (appendix table 7), 4.81 percent above the 17-State average,

increasing the cost difference between Iowa and the 17-State average by

$1.67. 

Differences in infant formula rebates sometimes reinforce, and sometimes

counteract, differences in infant formula prices. Because rebates have an

offsetting effect on the formula prices, we need to subtract the difference in

formula rebates from the difference in formula prices. For instance, formula

prices are lower than average in Texas (Houston, Midland), which translates

into a $0.71 lower package cost in Texas than the 17-State average.

However, the average rebate in Texas is also larger than the 17-State

average, and so the difference in rebates contributes another $0.66 to

lowering the package cost in Texas relative to the 17-State average. The

total cost-reducing effect of lower formula prices and higher formula rebates

in Texas is -$1.37 (-$0.71 - $0.66). 

Price effects in Illinois (Chicago), Tennessee (Memphis), and Massachusetts

(Boston, Pittsfield) are largely driven by net formula prices (price difference

minus rebate difference). The net formula price effect in Illinois is $1.43

($2.37 - $0.94), resulting largely from a much-higher-than-average formula

price in the State. The average price of a 13-ounce can of infant formula is

$3.13 in Illinois, vs. the 17-State average of $2.82. The net formula price

effect in Tennessee is $3.65, resulting from a much-higher-than-average

formula price ($3.19). The net formula price effect in Massachusetts is

-$2.23, resulting largely from a lower-than-average formula price of $2.59. 

In 10 of the 17 States, price effects go in the opposite direction of caseload

effects, suggesting that some high-price States are servicing caseloads that

counteract the cost-increasing effect of higher prices (fig. 10). In contrast,

some low-price States are servicing caseloads that counteract the costdecreasing effect of lower prices. 

16

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA
Cost-Containment Practices

State WIC agencies frequently impose restrictions on product types, flavors,

or package sizes in order to reduce food costs, make efficient use of available funds, and accommodate more participants. Analysis to this point has

emphasized that price differences among States for the same food products

can play an important role in generating differences in average monthly

food costs. An analysis of cost-containment practices, including a comparison of the magnitude of the restrictions across States, will suggest the role

of cost-containment practices in creating interstate package cost variation.

Our method for evaluating these practices was similar to our method for

simulating and comparing average monthly food costs. However, now we

wished to estimate the effect of a specific practice. We began by calculating

an unrestricted State average monthly food cost in State j (ACj

U). We then

determined average item prices with minimal restrictions on product brands,

sizes, or types and constructed the equation21

in which is the average price of food k in State j, calculated without

product restrictions, Ni,j is the number of participants, and Qi,k is the quantity of food.

We next calculated average monthly package costs after imposing a single

restriction, expressing the State average monthly food cost as ACR

j

:

where is the average price of food k in State j, calculated with a single

restriction imposed. 

The effect of the restriction is measured as the difference between the unrestricted and the restricted average monthly food costs:

An example may clarify our method. Suppose we wish to measure the effect

of restricting WIC participants to gallon containers of milk. In this case, we

would calculate the unrestricted average monthly food cost by calculating

an average milk price based on the distribution of all brands and package

sizes purchased by consumers in our data. The restricted average monthly

food cost is calculated by restricting the products included in the price

calculation to 1-gallon containers (that is, we do not include purchases of

pints, quarts, or half-gallons). 

17

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

21 We did impose some minor restrictions in an attempt to eliminate product types unlikely to be approved for

WIC participants. For example, we did

not include flavored milk products

even when calculating the unrestricted

milk price, and did not include shredded or “string” cheese when calculating the unrestricted cheese price.

(5)

( * * )

,

, , ,

 N

N Q P

AC

i

i j

i k

U

i j i k j k

U

j ∑

∑ ∑

=

(6)

( * * )

,

, , ,

 N

N Q P

AC

i

i j

i k

R

i j i k j k

R

j ∑

∑ ∑

=

Savings AC AC . (7) R

j

U

j = j −

U Pj,k

R Pj,k
Milk

States frequently impose one or more of three types of restrictions on milk

purchases (Kirlin and Cole, 2001, p. 12; Kirlin, Cole, and Logan, 2003a, p.

34). Some States require participants to buy gallon containers and others

restrict the choice to gallon or half-gallons, while still other States require

the least expensive brand of milk. We therefore restrict milk purchases to

one brand per State (the brand with the lowest average price for the 3 years

for which we have data) and one size (1-gallon). The final savings assumes

that the least expensive brand is the same for all WIC participants and that

all WIC participants have access to the least expensive brand. 

Figure 11 presents the results from these calculations. Cost savings arise from

changes in the average price as container sizes or brands included in the

calculation of the average price change. The magnitude of the cost savings

across States is also affected by the weight placed on the average price, which

varies across States as WIC caseload compositions vary,22 and by the degree

to which purchases are constrained by the restriction. For example, if most

consumers were already purchasing gallon containers before the restriction

was imposed, then the restriction would not result in large cost savings, even

if the per unit price reduction between the average gallon price and the

average price of other containers is large. The same cost-containment practice

has different effects across States (fig. 11). Thus, a restriction can result in

interstate differences in overall average monthly food costs.

The savings from allowing both gallon or half-gallon containers are modest

($0.32 per month, on average, or about 0.9 percent of the unrestricted average

monthly food cost), compared with restricting purchases to only gallon-sized

containers ($1.15 per month, on average, or about 3.08 percent of the unrestricted average monthly food cost).23 Restricting purchases to the least

expensive brand results in the largest reduction in cost—$1.92 per month, on

average, or about 5.13 percent of the unrestricted average monthly food cost.

This last figure must be considered guardedly, because it assumes the least

expensive brand is available to all milk-consuming WIC participants.

18

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

22 Average prices also vary because

the distribution of brands and package

sizes varies across States. We assume

this represents interstate variation in

consumer preferences and that given

the opportunity, WIC participants

would purchase brands and sizes in

accord with the households in our

scanner dataset. 

23 Note that our method assumes that

participants buy combinations of gallon and half-gallon containers in the

same proportions as the consumers in

the scanner dataset. We did not

assume, for example, that given the

opportunity to purchase half-gallons,

WIC participants would purchase only

10 half-gallon containers. Figure 11

Monthly savings from milk-container restrictions

Source: Appendix table 9.

Dollars

Gallon only Gallon or half-gallon only Least expensive brand only

CA CO FL GA IA IL KS MA MI MN MO NY PA TN TX WA WI

0

1

2

3

4

5
Peanut Butter

We examined the effects of three cost-containment practices commonly used to

reduce the cost of peanut butter: restricting purchases to 18-ounce containers

(Kirlin and Cole, 2001, p. 12), restricting purchases to private label brands,24

and substituting beans for peanut butter (allowed by most States in response to

participant preferences). We calculated the change in average monthly food

cost from buying 16 ounces of beans instead of 18 ounces of peanut butter.

Restricting peanut butter purchases to 18-ounce containers results in modest

cost reductions (less than 1-percent savings, on average), with little interstate variation in cost reductions (fig. 12). Average monthly cost reductions

are somewhat larger when purchases are restricted to private label brands

($0.21 per month, on average, or about 0.56 percent of the unrestricted

average monthly food cost). The cost savings from replacing peanut butter

with beans are larger (about 1.6 percent of the unrestricted average monthly

food cost), but the effect is relatively minor compared to, say, some of the

effects of milk restrictions. 

Cheese

We examined the effect of restricting cheese package sizes to 8 ounces or

larger (Kirlin and Cole, 2001, p. 12). Some States require the purchase of the

least expensive brand of cheese available. In our data on cheese transactions,

very-low-priced brands frequently are available, but very small quantities are

transacted at these low prices. Thus, it does not seem reasonable to let these

items approximate the least expensive brand of cheese generally available to

WIC participants (or consumers). Instead of using these sparse data to represent the lowest cost brand, we used the price for private label brands.

Restricting cheese purchases to package sizes of 8 ounces or larger has a

small savings effect on WIC package costs—$0.26 per month, on average,

less than 1 percent of the unrestricted average monthly food cost (fig. 13).

The most significant effect of package-size restrictions is found in Missouri,

where this restriction could save 1.59 percent of the unrestricted average

19

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

24 Kirlin, Cole, and Logan (2003a, p.

23) report that negative participant

reactions to the “least expensive

brand” restriction on peanut butter led

Oklahoma and Texas to drop these

restrictions. Assuming that participants

may have a similar reaction to a private label restriction on peanut butter,

our analysis on this restriction may not

be realistic for some States. However,

we include the analysis because it is

informative to know the potential cost

savings sacrificed when such restrictions are foregone.

Figure 12

Monthly savings from peanut restrictions

Source: Appendix table 10.

Dollars

18-oz size only Private label only Beans only

CA CO FL GA IA IL KS MA MI MN MO NY PA TN TX WA WI

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0
monthly food cost in the State. The private label restriction would also save

about 0.7 percent of the unrestricted WIC package cost, on average. In this

case, the largest savings occurred in Massachusetts (1.99 percent) and New

York (1.8 percent). Again, the variation in savings among States suggests

that purchasing patterns, product assortment and variety, and average food

prices differ significantly across markets. 

Juice

We examined the effects of five restrictions on juice purchases. Four were

based on common cost-containment practices (Kirlin, Cole, and Logan,

2003a, p. 35), while the fifth is included for information. We evaluated the

cost-reducing effect of restricting fluid purchases to 46-ounce cans, to 64-

ounce plastic bottles, and to 128-ounce plastic bottles.25 We also examined

the effect of restricting purchases to private label brands without containersize restrictions, and of frozen concentrate. 

The maximum allotment of fluid single-strength juice is 276 ounces for adults

and children (184 ounces for postpartum, nonbreastfeeding women) and 92

ounces for infants. Although this allotment is not evenly divisible by 64 or 128,

we assume that a full 276-, 184-, or 92-ounce allotment is purchased under

these two restrictions. The maximum allotment of reconstituted frozen concentrate is 288 ounces for adults and 96 ounces for infants. When analyzing the

effect of requiring only frozen concentrate, we calculated the simulated

restricted package, assuming that 276 ounces of adult juice (184 ounces for

postpartum women), or 92 ounces of infant juice, were purchased. 

The different restrictions result in a great deal of heterogeneity in State

savings (fig. 14). In each State we examined, we found the cost reductions

from restricting purchases to 128-ounce plastic bottles to be larger than

from restricting to 64-ounce plastic bottles or 46-ounce cans. On average,

restricting purchases to 128-ounce containers and frozen concentrate

provide approximately the same cost savings. The restriction to 128-ounce

bottles saves about 8.5 percent of the unrestricted average monthly food

costs, and the frozen concentrate saves about 8.4 percent. In many cases the

20

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

25 We are not aware of any State that

restricts juice purchases to 128-oz containers, but include this analysis for

informational purposes.

Figure 13

Monthly savings from cheese restrictions

Source: Appendix table 11.

Dollars

8-oz or larger only Private label only

CA CO FL GA IA IL KS MA MI MN MO NY PA TN TX WA WI

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1.0
cost reductions from restricting to 64-ounce containers are larger than those

from restricting to 46-ounce cans, but on average the 46-ounce can restriction provides the larger cost savings. The 46-ounce can restriction saves

about 4.4 percent on average, while the 64-ounce restriction saves about

3.65 percent on average. Cost savings from the private label restriction are

about 6.2 percent of the unrestricted average monthly food cost. 

The savings from restricting purchases to frozen concentrate are somewhat

overstated because buying frozen concentrate allows 12 more ounces of

adult juice and 4 more ounces of infant juice to be purchased (fig. 14).

These quantity effects are not accounted for in our analysis. 

Breakfast Cereal

We examined the impact of restricting purchases of breakfast cereal to 12-

ounce-or-larger boxes and to only private label brands.26 The cost reductions

from the size restriction are fairly modest, $0.17 per month, on average, or

about 0.4 percent of the unrestricted average monthly food cost (fig. 15).

Restricting purchases to private label brands, however, significantly reduces

the cost—$1.89 per month, on average, or about 5 percent of the unrestricted average monthly food cost. This restriction provides the largest

savings in Massachusetts (6.2 percent), Michigan (6.1 percent), and

Missouri (6.1 percent). 

Eggs

Our scanner dataset did not provide product-type information on eggs that

would allow us to examine many of the product restrictions commonly used.

For example, States frequently restrict egg purchases to a particular size

(medium, large, etc.) or color (white), which our data did not include as

product descriptions. However, the data did include a descriptor of container

size. Since we assumed an allotment of 30 eggs per package, we could

examine the cost implications of restricting purchases to 18- and 12-pack

containers (i.e., to one package of each). On average, this restriction saves

about $0.13, or 0.34 percent of the WIC monthly package cost (fig. 16). A

21

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

26 In our data, we cannot otherwise

distinguish private label breakfast

cereal. That is, we cannot distinguish

between, say, private label bran flakes,

and private label raisin bran. Thus, the

private label average price reflects a

distribution of private label cereals, but

we do not know the content of that

distribution.

Figure 14

Monthly savings from juice restrictions

Source: Appendix table 12.

Dollars

46-oz can 64-oz plastic 128-oz plastic

CA CO FL GA IA IL KS MA MI MN MO NY PA TN TX WA WI

-1

0

1

2

3

4

5

6

Private label Frozen concentrate
notable exception to this small savings is seen in Massachusetts, Pennsylvania, and New York, where savings from egg package-size restrictions

would save 0.84 percent, 1 percent, and 1.43 percent, respectively, of the

unrestricted average cost. 

To summarize, our analysis suggests that different States imposing the same

cost-containment practice can create interstate variations in average monthly

food costs. This will result if:

● the cost-containment practice reduces the average per unit price of the

item restricted by different amounts in different States,

● the cost-containment practice affects participant purchase patterns differently in different States, and

● participant caseloads affected by the cost-containment practice are different in different States.

Furthermore, analysis of simulated food costs suggests interstate variation in

the magnitude of cost savings can be quite large.27

22

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

27 It is important to note that our simulations do not examine the effect of

cost-containment practices on aspects

of program participation. Cost-containment practices may decrease program participation or may cause

under-redemption of food vouchers,

providing even larger cost savings than

are alluded to here. However, these

cost savings come at the expense of

program efficacy because fewer people

are served. 

Figure 15

Monthly savings from ready-to-eat cereal restrictions

Source: Appendix table 13.

Dollars

12-oz or larger only Private label only

CA CO FL GA IA IL KS MA MI MN MO NY PA TN TX WA WI

0

0.5

1.0

1.5

2.0

2.5

3.0

Figure 16

Average monthly savings from restricting egg-container sizes

Source: Appendix table 14.

Dollars

12- and 18-pack containers only

CA CO FL GA IA IL KS MA MI MN MO NY PA TN TX WA WI

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7
A Case Study of California and Texas 

Cost-Containment Practices

We relied on an earlier report, “Assessment of WIC Cost-Containment Practices: Final Report” (Kirlin, Cole, and Logan, 2003a) for information on

individual State cost-containment practices. This study examined in detail

the cost-containment practices of six States, California, Connecticut, North

Carolina, Ohio, Oklahoma, and Texas. Our scanner data contained price

information for Texas and California, which allowed us to model the role of

cost-containment practices in generating interstate cost variation between

these two States. However, remember that the scanner data are for market

areas within the State and are not representative of the entire State.

Table 3-1 in chapter three of the report details the WIC foods in Texas and

California, approved by WIC State agencies in January 2001. Table 5 lists

the approved foods that we were able to identify in the scanner data. We

engaged in three separate exercises to gauge the effect of cost-containment

practices:

(1) First, we used our scanner data to calculate State-level average

prices for foods allowed in Texas and California, using each State’s

own cost-containment practices. For example, we calculated the

average price of milk in California from the purchases of

California’s WIC-approved milk products, that is, of all brands of

gallon containers of white milk and half-gallon containers of

Lactaid. In Texas, we calculated the average price of milk using

purchases of private label, gallon or half-gallon containers of white

milk, and purchases of quart and half-gallon containers of Dairy

Ease and Lactaid.

(2) Next we calculated an average price in a State for the products

allowed under the other State’s cost-containment practices; thus, we

calculated the average price in Texas using foods allowed under

California’s cost-containment practices.

(3) Finally, we calculated the average price in California using products

approved under the Texas cost-containment practices. 

To demonstrate the effect of imposing various restrictions on average item

prices, table 6 reports the average prices calculated from our data, including

the average rebate for 13 ounces of infant formula and the price for 13

ounces of liquid concentrate formula, 16 ounces of baby cereal, 18 ounces

of ready-to-eat cereal, 64 ounces of juice, 128 ounces of milk, one dozen

eggs, 18 ounces of peanut butter, and 16 ounces of cheese. 

In table 6, the column for CA indicates the average price of the products

after we imposed California’s restrictions, and the column for TX shows the

average price of products after we imposed the product restrictions in Texas.

Comparing column CA with column TX reveals that in all cases products in

California have higher average prices than in Texas. 

23

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA
24

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

Table 5—Approved WIC foods in California and Texas

California Texas

Fluid Milk

Brand Any Least expensive (private label)

Package size Gallons only Gallon or half gallon

Flavor White only White only

Type Lactose-reduced/free- Lactaid or Dairy EaseHalf-gallon Lactaid Quart or half gallon

Cheese

Brand Any Any

Type/flavor American, Cheddar, American, Cheddar, Monterey

Monterey Jack, Mozzarella Jack, Mozzarella, Colby, 

Colby-Jack

Package size 12 oz or larger, block or round, 10 oz or larger, block or slices

Deli-sliced

Not allowed Wrapped slices, Wrapped slices, shredded

shredded, string

Eggs

Brand Any Any

Not allowed 6- or 18-packs

Infant Cereal

Brand Gerber Gerber

Type/flavor Rice, oatmeal, barley-mixed Rice, oatmeal, barley-mixed

Package size 8 oz 8 or 16 oz

Not allowed Cereal with fruit Cereal with fruit

Juice

Brand Campbell’s, Dole, Minute Least expensive of private 

Maid, Seneca, Tree Top, label, Seneca, Tree Top, 

Private label Welch’s

Type Apple, grape, orange, Apple, grape, orange, 

pineapple, white grape, pineapple, white grape,

vegetable grapefruit, orange-pineapple,

vegetable

Package size 64-oz plastic 46-oz can

Continued—
The second exercise imposes Texas cost-containment practices on California

products and then recalculates California average product prices. The column

headed “CA with TX practices” reports the effect on average prices from this

experiment. We see that while prices are usually lower in Texas for all products (column CA vs. column TX), imposing Texas practices on California

products does not reduce average California prices to Texas levels. In some

cases, prices rise in California when Texas practices are imposed. 

The final exercise examines what happens if California practices are applied

to Texas products. The final column headed “TX with CA practices” reports

the effect on average prices from this experiment. We see that applying California practices does not increase Texas prices to California levels; in some

cases imposing California restrictions decreases average prices. The key

insight from these analyses is that price differences exist between California

and Texas and that cost-containment practices do not erase the differences.

25

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

Table 5—Approved WIC foods in California and Texas–Continued

California Texas

Peanut Butter

Brand Any Any

Package size 16 or 18 oz 18 oz

RTE Cereal

Package size 12 oz or larger Product-specific

General Mills Cheerios, Wheat Chex, Kix Cheerios, Wheat Chex, 

Country Corn Flakes, Kix, 

Para Su Familia Cinnamon 

Corn Stars, Raisin Bran, Total

Kellogg’s Corn Flakes Corn Flakes, Frosted 

Mini-Wheats

Malt-o-Meal Toasty O’s

Post Bran Flakes Bran Flakes

Grape Nuts

Quaker Crunchy Corn Bran King Vitamin Life

Private label All 13, 13.5, or 15 oz only

Source: Table 3-1 in Kirlin, Cole and Logan, 2003a.

Table 6—Average prices

CA with TX with

Product CA TX practices TX CA practices

Dollars

Liquid concentrate 3.00 3.00 2.73 2.73

Rebate 2.66 2.66 2.55 2.55

16-oz box baby cereal 2.83 2.82 2.62 2.61

18-oz box RTE cereal 3.38 3.55 3.27 2.94

Half-gallon of juice 2.86 2.13 1.87 2.44

Gallon of milk 2.80 2.44 2.32 2.47

Dozen eggs 1.69 1.68 1.10 1.08

18 oz peanut butter 2.37 2.24 1.97 2.02

Pound of cheese 3.58 3.65 3.32 3.06

Source: ERS simulations from IRI scanner data.
Another question is what effect cost-containment practices have on average

package costs. Table 7 presents the results from using equation 3 to simulate

average monthly package costs, using the prices in table 6. We see that a

substantial difference exists between CA and TX prices even under different

scenarios, reinforcing the notion that price differences play a predominant

role in generating interstate average cost differences. The difference is $9.56

when we impose each State’s own restrictions. However, a $7.88 difference

remains even when Texas counterfactually imposes California practices, as

the average cost in Texas rises $1.68. We also see that the average cost in

California falls to $34.15 when California counterfactually imposes Texas

practices, as the monthly average cost in CA decreases $3.75. 

We next followed the procedure detailed in the first section of this report and

decomposed the difference in monthly average food costs between California

and Texas under various cost-containment scenarios (table 8). We did not alter

the contract brand of infant formula among the States, so there is no input for

formula prices or rebates because these factors were not changed. 

Table 8 decomposes the difference in monthly average costs between California and Texas into caseload effects and price effects. The column “With

own cost-containment practices” decomposes cost differences when each

State’s own cost-containment practices are imposed. The column, “With CA

practices” decomposes cost differences after imposing California practices

on both States. The final column, “With TX practices,” decomposes cost

differences after imposing Texas practices on both States. 

In table 8, juice contributes $3.23 to the difference in average monthly food

costs when each State imposes its own cost-containment practices. This

figure drops to $1.40 when California practices are imposed on Texas. The

reduction arises because the price of juice rises in Texas. In contrast, the

effect emanating from juice price differences falls to only $0.82 when Texas

restrictions are imposed on California. This decrease occurs because the

average juice price decreases in California after Texas practices are

imposed. Price effects similarly decrease under alternative cost-containment

scenarios for milk and peanut butter. 

Cereal contributes only $0.16 to the difference in costs between the two

States when we impose each State’s own practices. However, this effect

increases to $0.63 when Texas imposes California restrictions, as the price

of cereal decreases in Texas. Interestingly, imposing Texas practices on

California also increases the price effect from cereal. In this case, the cereal

effect rises from $0.16 to $0.40, as the price of cereal rises in California.

Similarly, price effects from cheese increase when California imposes Texas

26

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

Table 7—State costs with cost-containment practices imposed

With own practices With CA practices With TX practices

Dollars

CA 37.90 37.90 34.15

TX 28.34 30.03 28.34

Difference 9.56 7.88 5.81

Source: ERS calculations from table 5 data and IRI scanner data.
restrictions, as Texas cheese prices decrease. And price effects from cheese

increase when Texas imposes California practices, as California cheese

prices increase.

Only in the case of eggs does it appear that if each State imposed the other’s

cost-containment practice could average prices be reduced. We see that the

price effect from eggs increases from $1.08 under each State’s own costcontainment practices to $1.11 when Texas imposes California’s practices.

The price of eggs decreases in Texas. In contrast, the egg price effect

decreases from $1.08 to $1.06 when California imposes Texas practices, as

the egg price in California also decreases.

27

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

Table 8—Comparing the effect of product restrictions on CA and TX

cost differences

With own costcontainment practices With CA practices With TX practices

Dollars

Participant category

Infant -0.65 -0.65 -0.62

Children 2.14 2.14 1.91

Pregnant -0.25 -0.25 -0.22

Breastfeeding 0.94 0.94 0.84

Postpartum -0.90 -0.90 -0.81

Total from participation 

differences 1.28 1.28 1.09

WIC-approved product

Formula 2.29 2.29 2.29

Rebate -0.89 -0.89 -0.89

Baby cereal 0.06 0.06 0.05

Cereal 0.16 0.63 0.40

Juice 3.23 1.40 0.82

Milk 1.83 1.27 0.49

Eggs 1.08 1.11 1.06

Peanut butter 0.26 0.23 0.17

Cheese 0.26 0.51 0.32

Total from 

price differences 8.28 6.60 4.72

Total explained by 

prices and participation 9.56 7.88 5.81

Texas=Midland, Houston; California=San Francisco, Los Angeles, Visalia.

Source: ERS calculations from table 5 data and IRI scanner data.
Conclusions and Implications

Our method of simulating interstate variation in average monthly WIC food

package costs suggests that interstate price differences play an important

role. Simulated average monthly food costs suggest that States with higherthan-average WIC costs usually have higher-than-average food prices. Similarly, we found that States with lower-than-average WIC costs generally

have lower-than-average food prices. We also found that interstate variation

in the caseload composition of WIC participants usually plays a secondary

role to interstate variation in food prices in creating variation in average

monthly food costs across States. 

Our simulations also suggest that the same cost-containment practice can

generate different cost reductions across States. This results because per unit

price reductions within a product category (for example, between a gallon and

a half-gallon of milk) vary across States. Also, cost-containment practices

generate cost reductions only if they impose constraints on WIC participant

purchasing behavior. For example, if the majority of consumers prefer to buy

milk in gallon containers, then imposing a cost-containment practice

restricting purchases to gallon containers will not generate much cost savings.

Because consumer preferences vary across States, the degree to which costcontainment practices actually constrain participant behavior will also vary, as

will the effectiveness of cost-containment practices to generate cost savings.

Finally, we identified cost-containment practices in two States, California

and Texas, and examined the effects on simulated average monthly costs

from imposing these practices. Again, we found that identical cost-containment practices can have differential effects on average monthly food costs in

different areas. While counterfactually imposing Texas cost-containment

practices on California foods usually reduced the price of most foods, in

some cases average food prices increased. Likewise, imposing California

practices on Texas foods usually increased the price of Texas foods, but in

some cases average prices fell. In neither case did prices change enough to

completely offset average monthly food-cost differences. This implies that

even if States provided identical food packages and had identical WIC caseloads, average monthly food costs would differ across States. It also

suggests that even with equal food grants, accommodating WIC participants

is more difficult in some areas because of higher food prices. 

28

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA
References

Information Resources, Inc. (IRI). InfoScan Custom Store Tracking. IRI,

Chicago, Il.

Kirlin, John A., and N. Cole. Assessment of WIC Cost-Containment

Practices: An Interim Report to Congress. U.S. Dept. of Agriculture

(USDA), Economic Research Service (ERS), Food Assistance &

Nutrition Research Program, E-FAN-01-005, February 2001.

Kirlin, John A., N. Cole, and C. Logan, (a). Assessment of WIC CostContainment Practices: Final Report. U.S. Dept. of Agriculture (USDA),

Economic Research Service (ERS), Food Assistance & Nutrition

Research Program, E-FAN-03-005, February 2003.

Kirlin, John A., N. Cole, and C. Logan, (b). Assessment of WIC CostContainment Practices: Executive Summary. U.S. Dept. of Agriculture

(USDA), Economic Research Service (ERS), Food and Nutrition

Research Report, FANRR-31, May 2003.

Oliveira, Victor, E. Racine, J. Olmsted, and L. M. Ghelfi. The WIC

Program: Background, Trends, and Issues. U.S. Dept. of Agriculture

(USDA), Economic Research Service (ERS), Food Assistance and

Nutrition Research, FANRR-27, October 2002. 

U.S. Dept. of Agriculture (USDA), Food and Nutrition Service (FNS),

Office of Analysis and Evaluation. Study of WIC Participant and

Program Characteristics, 1998, August 2000.

29

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA
30

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

*The appendix tables, except for tables 7 and 8, were complied using ERS calculations

detailed in the report.

Appendix

Tables*
31

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

Appendix table 1—Relative peanut butter prices

State Private label Jiff

Dollars

CA 1.10 1.06

CO 1.08 1.04

FL 0.94 0.97

GA 0.93 0.97

IA 0.91 0.88

IL 0.94 0.89

KS 0.99 0.96

MA 0.94 0.93

MI 1.05 1.05

MN 0.87 0.87

MO 1.11 1.14

NY 1.12 1.17

PA 1.02 1.06

TN 0.88 0.92

TX 0.96 0.98

WA 1.28 1.24

WI 0.87 0.87

Source: ERS calculations.

Appendix table 2—Relative ready-to-eat cereal prices

State All 12-oz boxes Cheerios

Dollars

CA 1.10 1.06

CA 1.06 1.01

CO 0.99 1.08

FL 0.93 1.03

GA 0.98 0.99

IA 0.93 0.91

IL 0.98 1.02

KS 0.94 0.98

MA 0.97 0.87

MI 1.08 1.12

MN 0.89 0.88

MO 1.04 1.03

NY 1.11 1.10

PA 1.06 0.98

TN 1.10 1.10

TX 0.94 0.98

WA 1.07 1.03

WI 0.93 0.89

Source: ERS calculations.
32

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

Appendix table 3—AMS and scanner milk prices1

State Average retail - AMS Scanner data

Dollars

CO 3.22 3.03

FL 3.00 2.99

GA 2.76 2.66

IL 3.03 2.53

KS 2.75 2.65

MA 2.64 2.61

MN 2.99 2.88

MO 2.89 2.76

PA 2.65 2.37

TX 2.68 2.41

WA 3.18 2.61

1AMS milk price data was available only for these markets.

Source: ERS calculations.

Appendix table 4—Private label juice prices relative to 

17-State average

State Grape Apple Orange

Proportion of 17-State average

CA 0.95 1.07 1.34

CO 1.10 1.17 1.22

FL 0.97 0.93 0.78

GA 0.94 0.86 0.79

IA 1.04 1.14 0.83

IL 1.06 1.09 1.06

KS 0.99 1.09 0.89

MA 1.13 1.01 0.90

MI 0.86 0.79 0.93

MN 1.01 0.79 0.88

MO 0.86 0.90 1.00

NY 1.08 0.95 0.99

PA 1.03 0.98 1.00

TN 0.87 0.97 0.85

TX 1.36 0.97 0.82

WA 1.02 1.15 1.78

WI 0.74 1.18 0.92

Source: ERS calculations.
33

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

Appendix table 5—Private label cheese prices relative to 

17- State average

State American Cheddar

Proportion of 17-State average

CA 1.11 1.05

CO 1.15 0.99

FL 0.99 1.04

GA 0.92 0.94

IA 0.67 0.89

IL 1.60 1.01

KS 0.84 0.99

MA 0.91 1.01

MI 1.01 1.11

MN 0.66 0.88

MO 0.81 0.97

NY 1.24 1.17

PA 1.14 1.15

TN 0.94 1.07

TX 0.96 0.99

WA 1.19 0.93

WI 0.84 0.81

Source: ERS calculations.

Appendix table 6—Milk prices by income

State High income Low income WIC-eligible

Dollars

CA 2.70 2.61 2.57

CO 2.43 2.49 2.52

FL 3.00 2.98 3.00

GA 2.69 2.55 2.61

IA 2.30 2.33 2.36

IL 2.54 2.52 2.46

KS 2.64 2.66 2.64

MA 2.61 2.62 2.65

MI 2.57 2.57 2.55

MN 2.88 2.89 2.88

MO 2.76 2.76 2.77

NY 2.90 2.92 2.87

PA 2.37 2.36 2.48

TN 2.85 2.82 2.81

TX 2.40 2.43 2.37

WA 2.62 2.52 2.52

WI 2.51 2.51 2.53

Source: ERS calculations.
34

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

Appendix table 7—Caseload compositions

State Infant Children Pregnant Breastfeeding Postpartum

Percent

CA 23.50 53.50 9.76 7.01 6.14

CO 23.80 49.80 12.28 7.00 7.13

FL 27.90 49.80 11.53 4.37 6.40

GA 23.10 50.40 13.59 3.66 9.22

IA 21.40 56.90 9.61 3.86 8.22

IL 30.20 47.80 11.24 3.43 7.35

KS 23.50 53.80 9.81 4.29 8.60

MA 23.10 54.70 10.17 5.42 6.62

MI 24.40 53.90 10.72 3.23 7.75

MN 24.10 56.20 9.53 4.43 5.73

MO 23.90 50.80 10.78 4.05 10.47

NY 27.70 50.20 11.27 5.90 4.93

PA 25.90 54.10 8.72 2.82 8.46

TN 28.60 46.30 12.73 3.24 9.14

TX 27.50 48.70 10.28 5.02 8.50

WA 23.90 52.90 13.73 6.36 3.09

WI 23.00 55.70 9.65 4.22 7.43

17-State 

avg 25.03 52.09 10.91 4.61 7.36

Source: USDA, FNS.

Appendix table 8—Simulated and FNS average costs

State FNS average costs Simulated average cost

Dollars

CA 33.94 34.18

CO 30.63 34.74

FL 33.62 32.26

GA 29.41 30.28

IA 35.08 29.69

IL 29.26 32.73

KS 29.86 32.28

MA 27.57 29.10

MI 31.64 30.69

MN 29.98 31.07

MO 30.86 32.38

NY 35.58 34.76

PA 32.25 30.37

TN 32.62 36.27

TX 25.81 28.64

WA 33.14 34.58

WI 30.93 29.66

17-State avg. 31.30 31.98*

*Total differs from 17-State average in appendix table 4 due to rounding.

Source: ERS calculations and USDA. FNS.
35

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

Appendix table 9—Average monthly savings from restricting milk containers

State To gallon containers To gallon or half-gallon containers To least expensive

Dollars Percent Dollars Percent Dollars Percent

CA 1.71 4.19 0.45 1.11 3.72 9.07

CO 1.33 3.44 0.04 0.12 2.05 5.30

FL 1.06 2.93 0.36 1.00 1.07 2.96

GA 1.09 3.06 0.15 0.42 1.69 4.73

IA 0.44 1.33 0.13 0.39 0.69 2.10

IL 1.38 3.71 0.64 1.73 3.38 9.12

KS 0.48 1.25 0.22 0.58 1.06 2.76

MA 0.97 2.80 0.23 0.67 1.25 3.60

MI 1.37 3.63 0.52 1.38 1.46 3.87

MN 0.59 1.67 0.11 0.31 0.66 1.88

MO 0.67 1.79 0.15 0.40 1.01 2.70

NY 2.11 4.97 0.50 1.17 3.36 7.91

PA 1.32 3.60 0.64 1.73 2.72 7.41

TN 0.75 1.87 0.18 0.46 2.45 6.12

TX 1.32 4.05 0.38 1.17 2.70 8.26

WA 2.51 5.60 0.55 1.23 2.63 5.88

WI 0.49 1.43 0.18 0.52 0.72 2.07

Source: ERS calculations.

Appendix table 10—Average monthly savings from restricting peanut butter

State To 18-oz size To private label To beans

Dollars Percent Dollars Percent Dollars Percent

CA 0.04 0.11 0.25 0.61 0.71 1.73

CO 0.01 0.03 0.21 0.54 0.64 1.65

FL 0.06 0.17 0.17 0.48 0.59 1.64

GA 0.00 0.01 0.13 0.36 0.49 1.37

IA 0.00 -0.01 0.12 0.35 0.62 1.88

IL 0.03 0.08 0.17 0.46 0.58 1.56

KS 0.01 0.03 0.14 0.36 0.68 1.78

MA 0.03 0.09 0.23 0.67 0.34 0.99

MI 0.01 0.03 0.18 0.49 0.69 1.83

MN 0.01 0.03 0.15 0.44 0.38 1.08

MO 0.04 0.10 0.44 1.17 0.68 1.82

NY 0.04 0.10 0.27 0.63 0.78 1.84

PA 0.05 0.14 0.22 0.61 0.59 1.62

TN -0.01 -0.01 0.13 0.34 0.44 1.11

TX 0.04 0.13 0.22 0.66 0.63 1.92

WA 0.10 0.22 0.33 0.73 0.74 1.65

WI 0.02 0.07 0.16 0.47 0.52 1.50

Source: ERS calculations.
36

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

Appendix table 11—Average monthly savings from restricting cheese

State To 8-oz or larger To private label

Dollars Percent Dollars Percent

CA 0.35 0.85 0.20 0.48

CO 0.33 0.84 0.22 0.57

FL 0.09 0.24 0.25 0.68

GA 0.20 0.56 0.37 1.05

IA 0.38 1.15 0.11 0.32

IL 0.34 0.92 -0.24 -0.64

KS 0.34 0.88 -0.12 -0.31

MA 0.09 0.27 0.69 1.99

MI -0.21 -0.56 0.19 0.50

MN 0.24 0.67 0.29 0.84

MO 0.61 1.59 0.24 0.63

NY 0.36 0.85 0.80 1.88

PA 0.10 0.28 0.34 0.91

TN 0.44 1.08 0.08 0.19

TX 0.22 0.68 0.08 0.24

WA 0.24 0.53 0.50 1.12

WI 0.28 0.81 0.42 1.20

Source: ERS calculations.

Appendix table 12—Average monthly savings from restricting juice

State To 46-oz can To 128-oz plastic To 64-oz plastic To private label To frozen concentrate

Dollars Percent Dollars Percent Dollars Percent Dollars Percent Dollars Percent

CA 2.58 6.30 3.02 7.38 1.37 3.35 2.04 4.98 3.72 9.10

CO 2.82 7.28 3.18 8.20 2.35 6.07 2.32 5.99 4.80 12.39

FL -0.15 -0.42 3.16 8.75 0.86 2.39 2.33 6.47 2.19 6.07

GA 0.81 2.27 3.89 10.90 0.50 1.40 2.54 7.12 2.58 7.23

IA 1.76 5.34 3.36 10.22 1.15 3.48 2.70 8.22 2.90 8.82

IL 0.93 2.51 2.68 7.24 1.36 3.67 1.47 3.97 2.71 7.30

KS 1.40 3.66 2.30 6.00 1.56 4.07 2.26 5.90 3.06 7.97

MA 2.00 5.76 3.52 10.13 1.34 3.85 2.60 7.49 3.85 11.08

MI 1.84 4.90 4.30 11.43 2.12 5.63 3.70 9.83 3.47 9.24

MN 0.74 2.12 2.27 6.49 1.33 3.80 2.17 6.19 3.11 8.88

MO 1.03 2.77 2.88 7.72 1.47 3.94 2.62 7.03 2.35 6.29

NY 2.56 6.02 3.29 7.74 1.91 4.49 3.25 7.64 2.77 6.53

PA 1.54 4.20 3.33 9.07 1.33 3.63 2.70 7.37 2.63 7.16

TN 0.57 1.43 2.36 5.91 1.25 3.14 2.29 5.73 1.92 4.79

TX 1.73 5.29 3.14 9.61 1.02 3.13 2.17 6.64 2.35 7.20

WA 3.48 8.17 4.42 10.37 0.46 1.07 0.22 0.52 5.24 12.29

WI 2.16 6.26 2.62 7.60 1.71 4.96 2.14 6.20 3.69 10.69

Source: ERS calculations.
37

Interstate Variation in WIC Food Package Costs / FANRR-41

Economic Research Service/USDA

Appendix table 13—Average monthly savings from 

restricting breakfast cereal

State To 12-oz size or larger To private label

Dollars Percent Dollars Percent

CA 0.14 0.34 1.93 4.72

CO 0.14 0.36 1.73 4.46

FL 0.22 0.60 2.01 5.56

GA 0.17 0.47 2.07 5.81

IA 0.15 0.46 1.43 4.36

IL 0.21 0.57 1.50 4.04

KS 0.15 0.39 1.73 4.51

MA 0.25 0.73 2.14 6.17

MI 0.18 0.49 2.29 6.08

MN 0.11 0.31 1.70 4.85

MO 0.13 0.34 2.26 6.06

NY 0.25 0.58 2.47 5.81

PA 0.20 0.54 2.09 5.71

TN 0.09 0.23 1.73 4.32

TX 0.13 0.39 1.74 5.31

WA 0.17 0.37 1.71 3.80

WI 0.14 0.41 1.62 4.68

Source: ERS calculations.

Appendix table 14—Average monthly savings from restricting eggs

State To 12- and 18- pack containers

Dollars Percent

CA -0.06 -0.14

CO 0.15 0.40

FL 0.02 0.04

GA 0.12 0.34

IA 0.00 -0.01

IL 0.06 0.17

KS 0.06 0.15

MA 0.29 0.84

MI 0.08 0.21

MN 0.04 0.12

MO 0.13 0.35

NY 0.61 1.43

PA 0.37 1.01

TN 0.02 0.05

TX 0.03 0.08

WA 0.17 0.39

WI 0.08 0.24

Source: ERS calculations.