FOOD PROCUREMENT BY

USDAs FARM SERVICE AGENCY

Economic Research Service, U.S. Department of Agriculture. Agricultural

Economic Report No. 766.

Abstract

USDAs Farm Service Agency (FSA) purchases food products for distribution

through several of the Departments food assistance programs. This report describes

FSA purchase methods and compares them to procurement strategies used by other

Federal agencies and by private sector firms. It summarizes the principal policy

issues faced by FSA in designing procurement strategies. Finally, it uses a detailed

statistical analysis to compare FSA prices to those realized in the private sector, and

to identify the separate effects of agricultural commodity prices, seasonality, client

location, purchase volumes, product characteristics, and competition on FSA product prices.

Keywords: procurement, auctions, food assistance, competition

This report was prepared by James M. MacDonald [202-694-5391], Charles R.

Handy [202-694-5385], and Gerald E. Plato [202-694-5383]

Washington, DC 20036-5831 September 1998
Contents

Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .iii 

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

An Overview of Federal Food Procurement Programs . . . . . . . . . . . . . . . . . . . . 3 

USDA Domestic Food Procurement: Programs and Expenditures . . . . . . . . . . . 9 

FSA Procurement Auctions: How the Process Works . . . . . . . . . . . . . . . . . . . . 15 

Issues in USDA Procurement Policies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 

Data for Empirical Analyses of FSA Auctions . . . . . . . . . . . . . . . . . . . . . . . . . 27 

Statistical Analysis of Bid Prices for Five FSA Commodities . . . . . . . . . . . . . 33 

Comparing FSA to Commercial Prices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 

Appendix A  Glossary of Acronyms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 

Appendix B  Detailed Regression ResultsAnalyses of Low Bids . . . . . . . 55 

ii
EXECUTIVE SUMMARY

The U.S. Department of Agricultures Farm Service Agency (FSA) purchases food

products for distribution through several of the Departments food assistance programs. FSA purchases food throughout the year, using methods that economists

refer to as auctions. The food products are then delivered to States for distribution to

client agencies, such as school systems and social service organizations, which in

turn distribute the products to needy households.

In the fall of 1996, FSA asked the Departments Economic Research Service (ERS)

to evaluate the agencys procurement system. This report summarizes that work,

based on three sources of information: 1) interviews with participants, including

FSA employees and clients, other government agencies with responsibilities for

food procurement, and private sector food processors and distributors; 2) summary

FSA expenditure and quantity data; and 3) an extensive statistical analysis of data

on individual FSA auctions, focusing on the determinants of FSA bid prices and on

comparisons with commercial prices for the same products.

FSA Obtains Highly 

Competitive Prices

FSAs system aims to elicit low-price bids for the delivery of large volumes of a

limited number of food products. The system works well in reaching those goals:

FSA prices are substantially lower than those paid by private sector buyers for corresponding products. Moreover, processing margins for FSA products are quite low;

FSA stretches USDA budget dollars by purchasing substantial volumes of food

products for any given budget allocation.

Experience at other major Federal procurement agencies, such as the Department of

Defense and the Department of Veterans Affairs, shows that ultimate consumers

want more than low prices. Along with nutrition, they are also interested in timely

delivery and product variety. FSA does not act as a full-line food distributor for its

clients, and hence does not focus on wide variety and rapid delivery. Rather, it provides clients with the opportunity to obtain large volumes of a few items at very

favorable prices, by limiting product variety and by responding more slowly to

orders than full-line distributors. Clients can more effectively spend the rest of their

budgets on a variety of products.

But Clients Cite Four Problems in 

USDA Service Quality

1. Unreliable Delivery. Because of FSAs long lead times for delivery, client agencies must plan meals well in advance. If deliveries arrive late, meal plans are upset,

meal quality can suffer, and client agency costs can rise sharply when they must

replace FSAs orders quickly. Interviewees cited several sources of delivery delays:

lags due to USDA inspection delays (typically at small plants), cancellation of auctions, and vendor noncompliance. 

iii
2. Product Selection. Client agencies feel that surplus removal goals often drive the

selection and distribution of bonus commodities that clients frequently have little

interest in, although this problem relates more to the distribution of bonus commodities through the Agricultural Marketing Service.

3. Product Deterioration. USDA products follow a long distribution chain between

ordering and eating. A client first places an order with USDA, which arranges for

production. A vendor then manufactures the product, and arranges for delivery from

the processing plant to a State warehouse or to another processing site. The product

is then delivered to the clients central facilities, before being distributed to dining

facilities, where further preparation and holding may occur before serving.

Deterioration may occur at any point in the chain.

4. Problem resolution. The client may interact with State government agencies in

ordering and final delivery, and may be unaware that up to five different USDA

agencies may be involved in their order for food, as well as private vendors, truckers, and warehouses.

What Drives FSA Bids? 

Observations and Recommendations

1. Agricultural Commodity Prices. FSA bids are far more sensitive to agricultural

price movements than are wholesale and retail food prices. Because FSA prices are

so sensitive to agricultural prices, they will fall more than wholesale and retail

prices when agricultural prices decline, and they will rise more when agricultural

prices rise. The gap between FSA and corresponding retail and wholesale prices

should therefore be largest during periods of relatively low agricultural prices, and

smallest during periods of high agricultural prices. 

2. Competition. We found that competition matters in FSA auctions, but it matters a

lot only in some circumstances. As an approximate rule of thumb, FSA can do as

much for its clients by attracting a second bidder to a monopoly auction (reducing

prices by 4-7 percent), as by finding four more bidders for an auction that already

has two. Consequently, we recommend that FSA focus its efforts on adding bidders

at those auctions that typically attract only 1 or 2 bidders.

The number of bidders in FSA auctions varies substantially by product and over

time. Where are the most serious competitive problems? The data suggest that seasonality is important for some products: for example, over three-quarters of monopoly auctions in flour occur in the fall, when mills operate near peak capacity.

Monopoly auctions are also more likely among products with limited FSA volume,

because of unusual package sizes or product characteristics.

In those cases, FSA can counteract monopoly by conveying accurate price information to clientsfor example, that FSAs price advantages over commercial flour

providers are weakest in the fall and strongest in other periods, or that FSAs price

advantages are strongest in high-volume products. We recommend that FSA explore

ways to counteract seasonal variations in monopoly by extending the experiment

with rolling contracts, currently in use with cheese, to other products.

iv
Participation in FSA bidding has a distinctive all or nothing character to itbidders typically commit to being active in FSA auctions, in which case they bid

actively each month on auctions for a variety of locations and products. Auction

participation then does not typically decline because bidders reduce the number of

auctions they are active in; rather, firms decide to get out of FSA bidding entirely.

Our present research has not aimed to uncover the reasons why firms decide to enter

or leave FSAs bidding process. But efforts to increase competition should emphasize research into the reasons for entry and exit by those firms, and the research

should generate strategies to attract participation by more firms. 

3. Product Volumes. Monthly FSA purchase volumes have dropped substantially as

a result of changes in USDA commodity support programs. But declining volumes

have not yet had any substantive effects on FSA prices. Purchase volumes have only

small direct effects on prices, and those effects are not always in the same direction.

Moreover, the monthly volumes that matter are total USDA purchases (foreign and

domestic), and not simply domestic purchases. The most important effects on prices

occur in months in which large PL480 purchases are occurringin those months,

coincident large domestic purchases can lead to FSA price increases of 2-4 percent.

The driving factor in these instances are PL480 purchases, which vary quite sharply

from month to month. FSA should initiate strategies to get better prices on domestic

flour and vegetable oil, either by smoothing PL480 purchases, or by timing domestic purchases to avoid peaks in PL480 purchases.

Order volumes (the amount going to a specific destination in a specific order) have

very small effects on prices. Larger orders generally draw more aggressive bidding,

but prices only fall by less than 1 percentcombining orders into multiple truckloads yields very limited savings. Major gains in price likely come as one goes to

truckload volumes from smaller orders, and FSA already acts to combine small

orders into orders of at least truckload sizes.

Service Quality 

Observations and Recommendations

FSAs procurement system is designed to obtain good-quality products at very competitive prices. But at times, FSA may sacrifice service quality in the form of reliable delivery and in the pursuit of advantageous prices:

1. Canceled Auctions. There may be a problem in Kansas City Commodity Offices

(KCCO) calculation of constructed prices, used in deciding whether to cancel an

auction and shift purchases to a later month. In particular, because constructed

prices seem to be less sensitive to underlying agricultural prices than actual bid

prices are, constructed prices may give insufficient weight to agricultural prices.

Now, the threat of cancellation can be useful auction theory suggests that the

threat can lead to more competitive bidding, and the threat of cancellation is only

credible if it is actually used at times. But actual cancellations lead to lags in product deliveries, and can therefore impose substantial costs on clients. We therefore

recommend that FSA review its procedures for calculating constructed prices, with a

particular focus on the weight given to agricultural prices.

2. Penalties. Vendors have traditionally faced weak penalties for failures to meet

FSA delivery dates. Our statistical analysis shows that vendors are very sensitive to

v
economic incentivesthey revise bids quickly to changes in materials costs, transport costs, and capacity utilization. Stronger penalties for noncompliance, in the

form of financial penalties or suspension of later contracts, should lead to improved

vendor compliance.

3. USDA Inspection and Labels. Under existing rules, FSA products undergo onsite

USDA inspection and must carry USDA, rather than commercial, labels. The rules

are related: reliance on USDA labels and packaging shifts some risks of poor product quality to USDA, and consequently creates a need for USDA inspection.

Inspection, along with occasional unusual packaging requirements, can raise vendor

costs by 1-2 percent; USDA inspection and testing can also lead to lags in product

delivery, which clients cite as a persistent problem. Some vendors, especially relatively small plants, cite inspection and packaging requirements as deterrents to participation in FSA auctions, because of the effects on cost and on timely delivery of

products.

The current system results in very competitive prices, and the insistence on USDA

labels may contribute to the competition that leads to those pricessome firms may

not wish to bid aggressively on their own branded products. In some products, in

other words, the net effect of USDA labels and inspection may be lower prices. But

the insistence on USDA labels may, in other products, limit opportunities to obtain

surplus stocks of commercially labeled products and may deter additional bidders

from participating.

FSA currently purchases commercially labeled products in a few commodity categories. In markets with only a few vendors, FSA may be able to obtain more product variety and greater competition by opening auctions to commercially labeled

productsthe clear examples include the current experiments in ready-to-eat cereal

and infant formula. Those two cases illustrate a dilemma for the agency. A principal

argument made for USDA labels is that they limit brand loyalty on the part of consumers and therefore allow for more competitive bidding, but brand loyalty is

important in those two products (especially ready-to-eat cereal). 

FSAs shift to purchase of commercial labels reflects the agencys judgment that the

shift may introduce greater competition into two highly concentrated markets. But

FSA also purchases products for other markets in which brand loyalty is far less

important, because the brands are never seen by ultimate consumers and because the

products are used as ingredients in final servings, not as the serving itself. We recommend that FSA carefully evaluate its current experiments and consider a gradual

expansion of commercial labels (especially including high-quality private label and

wholesalers own-brand products), especially in products with limited existing brand

loyalty and low vendor participation.

The research for this report relied primarily on paper reports, whose data were reentered into an electronic format, because FSA disposes of the electronic records of

auctions after 1 year. Electronic data retention grows cheaper every year, as do

methods for analyzing data. Moreover, because of steady improvements in data

retention and analysis, undergraduate business and economics majors now routinely

learn almost all of the techniques used in this report. KCCO commodity analysts

should in the future be able to easily call up 5 years worth of past auction data (for

example); they should be able to quickly summarize key data patterns, and can easivi
ly be provided with expert summaries of more subtle issues. They should be able to

use that information in making auction decisions and in delivering timely information and advice to client agencies. We recommend that KCCOs future strategy for

information technology include steps to retain electronic auction records and to

develop those records into easily accessible databases. 

vii
The U.S. Department of Agricultures Farm Service

Agency (FSA) purchases food products for distribution

through several of the Departments food assistance

programs. The products are then delivered to client

agencies, such as school systems and social service

organizations, which in turn distribute the products to

needy households. FSA purchases food products

throughout the year, using methods that economists

refer to as auctions. An auction is a bidding mechanism

that encompasses a set of auction rules, which in turn

specify how potential bidders may participate in the

auction; how the winner is determined; and how much,

in the case of procurement auctions, the winner is to be

paid (McAfee and McMillan, 1987; Wolfstetter, 1996).

Auctions are widely used in government procurement

activities, and are also used to distribute oil drilling and

timber harvesting rights on Federal property, and to

finance Federal activities through the sale of Treasury

bills. In the private sector, auctions are used to sell such

products as wine, art, flowers, fish, and tobacco, and to

solicit delivery price offers for products ranging from

office supplies to tires to construction jobs.

In the fall of 1996, FSA asked the Departments

Economic Research Service (ERS) to evaluate the

agencys system for procuring and distributing food

products. This report summarizes that work, and is

based on three sources of information. First, ERS

researchers conducted a series of interviews with participants in the process, including FSA employees and

clients, people at other government agencies with

responsibilities for food procurement, and private sector

food processors and distributors. Second, we acquired

summary expenditure and quantity data from FSA and

from other government agencies. Finally, we developed

a large database, using FSA administrative records, on

the results of separate procurement auctions and performed extensive statistical analyses of those auctions.

We focused particularly on the determinants of bid

prices in FSA auctions and compared those prices to

commercial prices for the same products.

Chapters 2 through 4 describe the environment within

which FSA carries out its procurement activities. We

first provide an overview of the largest Federal food

procurement agencies. In particular, we describe the

differences among USDA, the Department of Defense,

and the Department of Veterans Affairs in procurement

goals and methods, and describe recent major changes

in procurement methods at the latter two Departments.

We then detail, in Chapter 3, USDAs food procurement

programsthe agencies and food assistance programs

involved, the statutory framework that drives USDA

programs, and recent expenditure patterns. Chapter 4

provides a detailed description of the actual steps

involved in purchases administered by FSA.

In the fifth chapter, we build on the material introduced earlier, and describe a set of policy issues that

relate to FSA procurement. That is, a set of specific

rules currently constrains FSA to purchase quite specific products, with customized packaging, and requires an

extensive system of onsite inspection of USDAs food

products. We summarize those rules, identify their

interlinkages, and discuss potential alternatives.

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 1

CHAPTER 1

INTRODUCTION
Moreover, current FSA procedures could be modified in

a variety of ways. We discuss potential modifications

and their possible effects.

Chapters 6 through 8 rely on the large database of FSA

purchase records. We first discuss the construction of

the database in chapter 6, and summarize the key price,

volume, competition, and product measures in the data.

In chapter 7, we report the results of our statistical

analysis of bid prices in FSA purchases. We estimate

the effects of agricultural commodity prices, product

and packaging characteristics, purchase volumes, and

competition on bid prices in five FSA commodity categories over a 5-year period. The results should help

FSA to identify the major factors behind actual and

forecast changes in product prices and to plan for tactical changes in policies aimed at improving performance.

We use the analyses of chapters 6 and 7 to develop

measures of average FSA prices in chapter 8, measured

at particular times and locations. The chapter then compares those average prices to commercial price quotes

for those products, times, and locations. The data provide evidence of the price advantages that FSA can

deliver to its clients, as well as the sources of those

advantages; in short, it summarizes FSAs relative

strengths and weaknesses in food procurement and distribution. A concluding chapter summarizes our major

positive and negative findings, and offers some recommendations for FSA auction strategy. 

2 /ERS-USDA Food Procurement by Farm Service Agency / AER-766
Introduction

Several government agencies administer large-scale

food procurement programs. At the U.S. Department of

Agriculture (USDA), two agenciesthe Farm Service

Agency (FSA) and the Agricultural Marketing Service

(AMS)purchase food products for domestic distribution on behalf of a thirdthe Food and Nutrition

Service (FNS). Those products are distributed through

domestic food assistance programs, such as the

National School Lunch Program (NSLP) or The

Emergency Food Assistance Program, which are

financed by FNS. About three-quarters of the food purchased under domestic food assistance programs is distributed to school districts under the NSLP, while the

rest is distributed through a variety of smaller programs, described more fully in chapter 3. The two

USDA agencies spent $849 million on food purchases

for domestic programs in 1996.

Food procurement forms a small part (less than 2 percent) of total FNS expenditures on domestic food assistance. Most of the total FNS food assistance budget of

$38 billion goes to support direct cash transfers, such as

payments to foodstores for redemption of coupons and

vouchers under the Food Stamp and Women, Infants,

and Children Programs, or cash payments to schools for

subsidized meals under the NSLP. Schools receive

about 20 percent of their USDA support in the form of

commodities, with the rest in cash support.

FSA also purchases and ships food and agricultural

commodities to foreign countries under the Food for

Peace program (PL480) and other international assistance programs. The programs are administered and

financed by the State Departments Agency for

International Development (AID) or another USDA

agency, the Foreign Agricultural Service (FAS), for

which FSA acts as the buying agent. FAS expenditures

for PL480 programs were $1.21 billion in 1996. In

addition, FAS spent another $84 million on food expenditures for the Food for Progress program. Under this

program, U.S. agricultural commodities are provided to

developing countries and emerging democracies that

have commitments to introduce and expand free enterprise in their agricultural economies.

At the U.S. Department of Defense (DoD), the Defense

Personnel Support Center (DPSC) purchases food for

military bases, ships, and other military facilities.

DPSC purchases for all four branches of the military,

acting as the buying agent for the Defense Logistics

Agency (DLA). In addition, DPSC has contracts to act

as purchasing agent for the U.S. Coast Guard, some

prisons, and some school systems. DPSC food purchases amounted to approximately $525 million in 1996,

and the agency also provided $115 million in other contract services.

At the Department of Veterans Affairs (VA), the Office

of Acquisition and Materials Management (OAMM)

purchases food for 173 VA facilities, primarily medical

centers. OAMM food expenditures amounted to $60

million in 1996, along with another $12 million in food

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 3

CHAPTER 2

AN OVERVIEW OF FEDERAL FOOD

PROCUREMENT PROGRAMS
equipment and supplies. The agency also aims to obtain

contracts to act as purchasing agent for other entities;

for example, OAMM handles food purchases for medical facilities in the U.S. Army Medical Command.

Program Goals

Each agency tries to reach several primary and secondary goals through their procurement strategies. For

example, the USDA agencies traditionally have had

dual goalssurplus removal and food assistance.

USDA has historically purchased substantial volumes

of agricultural commodities in order to support prices

for program crops, such as wheat, corn, and dairy

products. The Department has then had to find ways to

dispose of the accumulated surpluses, and one way has

been to distribute them outside of normal commercial

channels through food assistance programs to lowincome households and countries. Surplus removal,

used for Section 32 purchases by AMS, often emphasizes the rapid distribution of large volumes of particular commodities, those that have had large harvests and

falling prices, in order to support producer prices. As a

result, AMS procurement has generally emphasized

agricultural commodities and less processed food products because of their closer link to the farm sector.

Food assistance programs include the distribution of

emergency supplies of staple food items to areas hit by

such natural disasters as floods, hurricanes, and earthquakes, and the regular distribution of food products to

members of low-income households. Assistance goals

include the assurance of nutritionally adequate diets

among client groups, as well as income support for

food assistance recipients. Because most expenditures

have been aimed at staple food products that are often

storable for extended periods, procurement procedures

have emphasized the acquisition of simple, nutritionally

sound foods at competitive prices.

DoD and VA purchasing agencies do not operate under

surplus removal expectations. Because they provide a

substantial share (up to 100 percent, for some) of the

food consumed by their clients, they are under greater

pressure to provide for product variety, and not simply

nutritional adequacy. Moreover, because DoD client

food demands may fluctuate sharply (for example,

when a ship arrives at a base or when a reserve unit is

activated), DPSCDoDs procurement agencymust

respond rapidly to unexpected service demands. As a

result, the agencies procurement strategies emphasize

quick delivery of a wide variety of food products.

Food procurement agencies also aim to realize some

secondary goals that often are imposed by statute. Each

is required to support small businesses by setting aside

a certain percentage of purchases for firms that are designated as small businesses. USDA is required to buy

foods that use products from American farms, and the

Merchant Marine Act requires FSA to arrange for ocean

shipment in American ships. VA medical centers are

expected to purchase a percentage of food in local areas

in order to support local economic development. USDA

agencies often attempt to encourage good dietary and

purchase habits through example, by offering low-fat

versions of food products and by forgoing more expensive commercially branded products.

Procurement Methods

USDA, DoD, and VA use different procurement methods. Most USDA procurement is done through sealedbid auctions for the delivery of a limited variety of food

commodities to central warehouses or further processors. Client agencies then generally take responsibility

for distribution from warehouses, reprocessing some

commodities (such as cheese and flour) into more highly processed foods (such as pizza), delivery to points of

consumption, and local preparation. By contrast, DoD

and VA have recently introduced prime vendor programs, in which a private firm (the prime vendor) is

responsible for ordering products from processors, providing storage for an inventory of products, and delivering a wide variety of food products to all facilities

within a region, with clients then responsible only for

their own ordering and for local preparation.

A Brief Description of 

USDA Procurement Methods

FNS receives the appropriation for USDA programs; it

also allocates funds to the client State and tribal distributing agencies, collects food commodity and product

orders from these agencies, and ensures their compliance with program requirements. State and tribal agencies use FNS program guidelines to determine if individuals are eligible to receive food products and to

deliver products from warehouses to the targeted population. 

Client agencies place orders for food products, working

from product lists (with likely price ranges) provided

4 /ERS-USDA Food Procurement by Farm Service Agency / AER-766
by FNS. USDAs procurement agencies, FSA and AMS,

then aggregate the orders to truckload quantities, and

produce invitations for vendors to enter bids to produce

the orders. An invitation usually includes multiple auctions, where each auction is for the award of an order

for delivery of truckload quantities of a precisely

defined food product to a distribution point within a

defined time period. The time period is usually a 2-

week span, the distribution point is usually a warehouse

in reasonable proximity to the client, and food products

are defined as to type (say, all-purpose flour or bread

flour), package size, and ingredient requirements.

USDA distributes invitations and runs auctions once a

month for some products, while auctions for others are

held weekly (ground beef), seasonally (some fruit products), or annually (infant formula). Vendors (food processing firms) respond by submitting sealed bids;

sealed bids are not known or observed by rivals, as

would occur in the sort of open verbal auctions used at

art auction houses. Vendors typically do not offer bids

on all auctions in an invitation, but frequently enter

bids on more than one. A bidder may place a maximum

on the total quantity that they would be willing to produce from all the bids entered in an auction, and bidders in some auctions may also place minimum quantities, below which they will accept no awards.

USDA aims to award the order to the best bid in an

auction, subject to several constraints. For international

shipments, USDA considers ocean transport charges as

well as the vendors quoted prices for delivery of a

product to a domestic portthat is, the winner is determined by the lowest total cost to USDA. When low

bidders are above their maximum or below their minimum total quantities, agencies will attempt to make

awards in ways that will minimize invitation-wide total

costs to USDA. Finally, some orders are set aside for

small businesses, as long as a qualified small business

enters a bid that is within 5 percent of the lowest bid.

Vendors are expected to arrange for transportation to

warehouse points or, in the case of international shipments, to ports. Commercial freight forwarders arrange

for ocean shipping to international clients, while

domestic clients arrange for transportation from warehouses. USDA requires onsite inspection of all products; inspectors for some products are employed by

AMS, while another USDA agency, GIPSA (the Grain

Inspection, Packers and Stockyards Administration),

provides inspectors for other commodities. Laboratory

testing services supplement the onsite inspectors and

are supplied by AMS and GIPSA.

Prime Vendor Programs

USDAs procurement auctions rely on competition

among processors to obtain precisely defined food

products at favorable prices. Prime vendor programs

also rely on competition, but for a different sort of

award.

Under the DoD program, the country is divided into

regions, and in each region, a single prime vendor supplies military facilities with food products. DoD now

has 50 Prime Vendor contracts in the continental United

States. Contracts are for a single base year, with provisions for three or four 1-year extensions. The prime

vendor is generally not itself a manufacturer; most are

foodservice wholesalers. Prime vendors offer distribution facilities and choices from a wide range of food

items. They obtain products from processors, assemble

loads for clients, and deliver from the prime vendors

warehouses directly to ships, base dining halls, and

other locations. Prime vendors also provide a central

point of contact for problems with deliveries, product

quality, or errors in orders. 

Prime vendors in the VA program perform a similar

function, but the VA divides the country into 16

regions. The geographically larger VA regions are able

to combine hospital purchases into a large enough

aggregate to correspond to the business opportunities

offered to prime vendors in DoD regions.

Prime vendor contracts are awarded after competitive

bidding among potential vendors. The contracts are for

indefinite quantities because base food demands are not

perfectly predictable far in advance. The DoD procurement agency, DPSC, provides bidders with a list of

items wanted, along with estimated quantities and likely minima and maxima; the agency also estimates the

likely dollar volume of sales for each region. In

response to the invitation, and after pre-proposal conferences, bidders submit very large and extensive proposals. DPSC then evaluates the proposals. It considers

a business segment of the proposal, in which it asks for

price quotes on a sample of items, as well as the bidders fee per item. The agency also assembles a technical panel to make site visits and to review the bidders

ordering systems, inventory controls, and delivery technologies. 

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 5
VA technical panels review the size of bidder warehouses, the variety of products and the capability to add

new items, transport options, and purchase and accounting systems. Price quotes are also included for evaluation in the business segment of bidder proposals.

Contract awards are made on the basis of the lowest

priced, technically feasible, proposal. DPSC managers

expect, however, that the basis for awards will shift

somewhat toward best value, which would add considerations of past performance and service quality to the

awards decision.

DPSC purchases some military-unique food items,

including those with special packaging to withstand

shipboard or airborne conditions as well as foods that

are prepared for field consumption. DPSC runs competitions to select a single manufacturer for each militaryunique item, and handles orders and payment to the

manufacturer. Prime vendors then assemble and deliver

military-unique items to bases. 

DoD and VA procurement agencies do not rely on

extensive onsite inspection to provide quality controls

as USDA does. Instead, pressures to maintain quality

and to meet contractual obligations arise from several

sources. First, contracts are renewable, and past performance becomes a factor in competitions for renewed

awards. Second, military facilities are not obliged to

spend all of their food dollars at prime vendors; they

may also purchase from local vendors. Third, mess

halls and other dining facilities are not obliged to

accept deliveries from prime vendors; they may reject

and return unacceptable products. Fourth, the agencies

retain the right to audit the relevant records of prime

vendors during the course of the contract. Finally, most

prime vendor food products are identical to those the

vendor supplies to its other commercial clients. Vendors

have incentives to maintain and assure the quality of

their private-label brands and services; if quality deteriorates, they risk losing not only DoD and VA business,

but commercial sales as well.

Causes of the Shift to 

Prime Vendor Programs

DoD prime vendors supplanted a system of military

depots. Prior to the shift to prime vendors in 1995,

DPSC ordered food products on behalf of military facilities, much as USDAs agencies now order on behalf of

school districts and other clients. Food products were

then delivered to depots operated by the Defense

Logistics Agency (DLA), and from there were distributed to base warehouses. Finally, products were delivered to mess halls, ships, and other dining facilities

from the base warehouses. 

Two problems drove the shift to a prime vendor system.

First, aging military depots and warehouses were in

need of substantial investments in construction and

maintenance. Second, food deliveries required long

lead times, 45 days between order and delivery. Prime

vendors provide substantially improved service to dining facilities; over 99 percent of orders are delivered

within 2 days, if substitution among brands and package sizes is allowed. Vendors operate 7 days a week,

and offer a wide variety of products. The military has

been able to consolidate depots and warehouses, and to

realize substantial savings in the costs of carrying food

inventories, which fell from $230 million prior to initiation of the program to $69 million in late 1996, with a

goal of $15 million after full implementation. 

Of course, the need for warehouse space does not disappear with the introduction of the programprime

vendors now provide services of storage, repackaging,

delivery, and administration that the military used to do

by itself. DPSC managers estimate that vendor fees for

these services amount to 11-12 percent of commodity

sales. DPSC receives additional payments equal to 6

percent of total expenditures for prime vendor commodities and services. DPSC provides translation software to enable the different services to order through a

consistent computer system, advises facility managers

on sound purchasing strategies, handles the flow of

payments from bases and DLA through DPSC to the

vendors, and administers the system of prime vendor

contracts. 

Procurement agencies and clients must make some

adjustments under prime vendor programs. With a

wider range of available products, clients must learn

more about the products that are commercially available, and they need to invest in learning about electronic ordering and tracking systems. Agencies assume

greater responsibility for advising clients and for

reviewing and supervising vendors.

The VAs 1995 shift to a prime vendor program came

slightly before DoDs did. Before then, VA purchased

about 300 different food items distributed through a

depot system. In the view of VA managers, vendor

6 /ERS-USDA Food Procurement by Farm Service Agency / AER-766
prices were relatively high, and delivery times through

the depot system were poor. Food item distribution

costs appear to have been subsidized by pharmaceutical

items in the VA depot system. When pharmaceutical

procurement was pulled out of the depot system, the

food procurement program came under substantial

financial pressure, leading to a search for alternatives.

In the VA case, managers cite lower product prices,

wider variety, more timely delivery, and the elimination

of depot facilities, along with their associated expenses,

as advantages of the new system. Prime vendor fees

average 9-12 percent of food product costs, and the

VAs procurement office, the Office of Acquisition and

Material Management (OAMM), charges a one-halfpercent fee for its services. 

The VA provides some volume guarantees to prime

vendors by committing at least half of a regions purchases to the prime vendor. Clients may also reduce

costs on some items by providing volume commitments

on specific products to the manufacturer/vendor from

which the prime vendor purchases. 

Conclusions

USDAs procurement programs are designed to obtain a

limited variety of precisely defined food products at the

lowest possible cost to USDA for delivery to warehouses. As we shall see in later sections, USDA relies on

tight specifications and direct inspection to ensure product quality. The system is decentralized in that final

delivery, reprocessing, and distribution to dining facilities are the responsibility of the client. The prime vendor programs used by DoD and the VA are designed to

obtain important services, such as variety (and associated inventory) and rapid delivery, in addition to food

commodities. Vendors are expected to compete to offer

packages of service and price. DoD and VA aim to

ensure product quality through reliance on commercial

labels and continued competition among vendors for

contract renewals.

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 7
Introduction

USDA purchases and distributes food commodities

through 13 food assistance programs. Purchase and distribution activities are essentially the same for each program, but spending authorities, target populations, and

program goals differ. The collective goals of the programs are to provide needy people with access to a

more nutritious diet, to improve the eating habits of the

Nations children, and to stabilize farm prices through

the distribution of surplus foods. This chapter summarizes USDAs food procurement programs, identifies

their authorizing legislation, and details the recent history of annual expenditures under these programs.

Programs and Supporting 

Legislation

Table 3-1 lists the 13 programs, identifies their target

populations, links them to their supporting legislation,

and shows the amounts spent on food procurement in

fiscal 1996. The column headed Section of public

law lists numbers that refer to the sections of the original legislation that authorize each programs procurement activity; those numbers are common references

for program administrators. 

The 13 programs spent a total of $849 million on food

procurement in fiscal 1996. The four largest programsthe National School Lunch Program (NSLP),

the Food Distribution Program on Indian Reservations,

the Commodity Supplemental Food Program, and Soup

Kitchens and Food Bankspurchased more than 95

percent of the total, about $811 million. The NSLP

alone accounted for almost 77 percent of the 1996 total,

or $652 million.

The 13 programs are authorized under several different

statutes, which create a variety of funding sources and

funding constraints for USDA. The first three programs

in table 3-1, including the NSLP, are primarily supported by two separate congressional laws and subsequent

amendments to these laws. 

Section 32 refers to that section of the Agricultural

Adjustment Act of 1935. The Section authorizes

USDA to support prices of commodities in surplus by

purchasing them in the marketplace, and also authorizes

USDA to distribute commodities domestically. The legislation authorizes the funding of these activities with

money collected from customs receipts; this funding is

primarily administered by AMS to purchase meat and

livestock, fruit and vegetable commodities, usually

about $400 million annually. 

Funds used under section 32 are designed to support

agricultural markets. As a result, the funds are to be

applied to the purchase of relatively unprocessed food

products that are close to agricultural commodities in

the distribution chain. That is, the funds can be used to

purchase pork but not frozen sausage pizza, and they

can be used to purchase chicken but cannot be applied

to paying for processing the chicken into chicken

nuggets. In addition, section 32 money is intended to be

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 9

CHAPTER 3

USDA DOMESTIC FOOD PROCUREMENT: 

PROGRAMS AND EXPENDITURES
spent on products in surplus, reflecting the surplus

removal goal under which USDA programs operate.

Hence, those products must be designated as being in

abundant supply. Because section 32 money can only

be spent on surplus commodities, the legislation can

lead to substantial year-to-year fluctuations in expenditures and in the mix of commodities purchased.

Section 6 refers to the National School Lunch Act of

1946, and authorizes USDA to purchase food products

for distribution to the Nations school children.

Commodities purchased with Section 6 funds do not

have to be in surplus because there is no requirement

for supporting prices, but the available funds can vary

with annual Congressional appropriations to FNS.

Under current procedures for the NSLP, schools receive

a cash reimbursement of $1.89 for each free meal

served, $1.49 for each reduced-price meal, and $0.18

for each paid meal. In addition to cash, schools are entitled under Section 6 to receive 15 cents worth of commodity foods (those procured by AMS and FSA) for

each meal served as well as Section 32 bonus commodities, as those commodities (and the funds to purchase them) become available. In total, about 17 percent of the dollar value of the food served in school

lunch programs comes from USDA commodity purchase programs.

Free meals are offered to students from families with

incomes that are no more than 130 percent of the

poverty line income (or $20,865 in 1996 for a family of

four), while reduced-price meals are offered to those

from families with incomes between 130 percent and

185 percent of the poverty line. About 25 million children, in 92,000 schools, participate in the NSLP, and

more than half receive a free or reduced-price meal.

Two relatively small programs for the elderly, the

Nutrition Program for the Elderly and Area Agencies on

Aging, are authorized under Section 311 of the Older

Americans Act of 1965. The U.S. Department of

Health and Human Services administers these programs, while USDA purchases food products for them.

Nearly 1 million meals a day are served under these

programs.

10 /ERS-USDA Food Procurement by Farm Service Agency / AER-766

Table 3-1: Domestic food assistance programs for which USDA purchases food products

Program Expenditures Section of Name and target population

acronym (million dollars1) public law

NSLP 652 32 - 6E National School Lunch Program - schools

(76.80)

CACF 5 32 - 6E Child and Adult Care Feeding Program - child care centers and

(0.61) special need adult care centers

SFSP 1 32 - 6E Summer Food Service Program - summer meal service for 

(0.14) needy children during the day 

NPE 4 311 Nutrition Program for the Elderly - congregate feeding sites for 

(0.51) elderly people (State option)

AAA 1 311 Area Agencies on Aging - congregate feeding sites for elderly 

(0.18) people (State option)

FDPIR 74 4A Food Distribution Program on Indian Reservations - food packages for 

(8.71) needy Indian families

CSFP 48 17 Commodity Supplemental Food Program - food package for pregnant or 

(5.61) postpartum women and children up to age 6

TEFAP 16 104 The Emergency Food Assistance Program - food for homeless or needy 

(1.93) people/households

SKFB 37 110 Soup Kitchens and Food Banks - food for meal service at soup kitchens 

(4.34) and food bank networks

CI 9 416 Charitable Institutions - nonprofit institutions

(1.01)

SC <1 416 Summer Camps - nonprofit summer camps for children

(0.01)

FBDP <1 32C Food Bank Demonstration Projects - food banks in high-need areas

(0.01)

DF 1 32C Disaster Feeding - food provided to or used to prepare meals for disaster 

(0.16) victims

1Numbers in parentheses show percent of total food spending accounted for by the program.
Sections 4A and 17 refer to those sections in the

Agriculture and Consumer Protection Act of 1973.

This law authorizes the Food Distribution Program on

Indian Reservations and the Commodity Supplemental

Food Program. Each distributes food packages; about

115,000 people participate in the first, and about

400,000 in the second. These programs received the

second and third largest amounts spent for commodity

and product in fiscal 1996, over $120 million. 

Two programs were authorized through the Hunger

Prevention Act of 1988. Section 104 authorizes USDA

to distribute surplus commodities to needy individuals

or households, while Section 110 authorizes USDA to

purchase and distribute commodities and food products

to soup kitchens and food banks. 

Section 416 of the Agricultural Adjustment Act of 1949

authorizes the Commodity Credit Corporation (CCC) to

make available CCC-owned commodities for distribution. FSA administers the CCCa public corporation

that supports the prices of commodities through nonrecourse commodity loans and manages commodities

acquired by the agency. The commodities provided

under Section 416 may be in private stocks or in public

stocks that were acquired through forfeiture of nonrecourse commodity loans. Commodities donated under

this legislation are known as bonus commodities, and

may be used in any of these programs. 

Section 32C also refers to Section 32 in the Agricultural

Adjustment Act of 1935. Section 32C funds are funds

set aside by the Secretary for use in extreme surplus or

to provide for disaster relief. These funds also come

from customs receipts, and may also be used in any of

the other programs in table 3-1. They are the primary

source for the Food Demonstration Projects and

Disaster Feeding Programs. Section 32C funds are

used primarily for purchasing and distributing AMS

commodities. 

Program Expenditures

FSA and AMS purchase different products. AMS is

responsible for purchasing Group A commodities,

which include poultry, red meat, fish, eggs, and fresh

and processed fruits and vegetables. FSA purchases

Group B commodities, which include dairy products

(primarily cheese but also including butter and evaporated milk), grain-based products (such as wheat flour,

corn products, pasta and ready-to-eat cereal), peanut

products, honey, vegetable oil, rice, and infant formula.

Most Group B products are derived from agricultural

products that are or have been subject to agricultural

support programs also administered by FSA. 

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 11

Million dollars

Total

Group A

Group B

1979 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

2,200

Figure 1

USDA food purchases for domestic feeding programs, 

1979-96
Figure 3-1 displays annual USDA expenditures, in current dollars, for domestic food procurement for a period

starting in 1979 and ending in 1996. The data display a

distinct pattern, with total expenditures rising steadily

from $785 million in 1979 to a peak of $2.16 billion in

1984. After remaining just above $2 billion through

1987, annual expenditures began a steady decline, to

$849 million in 1996.

The sharp post-1987 decline is driven by declines in

Group B expenditures. Group A commodities show a

modest upward trend, starting at around $437 million in

1979 and reaching a peak of $736 million in 1993,

before declining to around $629 million in 1996. But

Group B commodities purchased by FSA show a far

more dramatic cycle. Expenditures on those commodities rose from $348 million in 1979 to a peak of $1,692

million in 1984 (a 386-percent expansion in 5 years).

Expenditures remained between $1.4 billion and $1.7

billion between 1983 and 1987, before beginning a

steady and precipitous decline to $220 million in 1996.

The sharp expansion in the early 1980s, and the subsequent contraction, reflected developments in agricultural commodity markets and USDA support programs.

Falling world commodity prices, when set against relatively high USDA support prices, led to large USDA

purchases through the CCC and an enormous increase

in commodities available for the programs. Because the

expanded purchases largely went to programs other

than school lunches, the importance of the NSLP in

USDA purchases also varied through time, as figure 3-2

shows. In 1979, NSLP purchases accounted for 73 percent of total USDA purchases and 78.7 percent of FSA

(Group B) purchases. At the peak expenditure year, in

1984, the NSLP share fell to 38 percent of total USDA

purchases and just 26 percent of FSA purchases; by

1996, school lunch purchases were back to 78 percent

of the total and 60 percent of FSA purchases.

12 /ERS-USDA Food Procurement by Farm Service Agency / AER-766

National School Lunch Programs account for a growing share 

of USDA food purchases

1979 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

2,200

Million dollars

Total domestic

School Lunch Program

Figure 3-2

Table 3-2: FSA purchases by commodity group, 

1993-95

Expenditures 1995 NSLP

Commodity 1993 1994 1995 share of

expenditures

 Million dollars Percent

Dairy 287.0 240.6 202.5 63.4 

Flour 20.4 16.2 15.3 90.8 

Peanut products 65.1 54.0 21.1 40.2 

Pasta 9.5 11.5 11.5 28.7 

Vegetable oil 34.8 43.2 21.2 95.1 

Rice 11.4 16.6 12.3 18.4 

Corn 9.5 17.0 1.2 44.5 

RTE cereal1 6.3 4.3 4.7 0.0 

Processed cereal 4.4 5.0 3.1 12.6 

Honey 0.5 1.1 3.6 0.0 

Total 448.8 409.5 296.5 59.6 

1RTE cereal is ready-to-eat cereal.
At present, FSA purchases of Group B commodities are

increasingly concentrated on one major program, and

are also concentrated on a major commodity group.

Table 3-2 shows that dairy purchases now account for

over 68 percent of FSA purchases, and for nearly twothirds of the agencys NSLP purchases. In turn, cheese

accounts for the major share of dairy purchases. 

U.S. agricultural policy, as set in 1996 farm legislation,

has moved away from a reliance on price supports for

program commodities. If that policy continues, then

procurement of bonus commodities under Section 416

legislation will become a less important driver of

USDA procurement. In turn, annual entitlement appropriations will become more important, and the NSLP

will continue to be the primary recipient of USDA

foods.

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 13
Introduction

To understand the issues involved in structuring FSA

auctions, one needs to understand how the existing

process works. This chapter describes the steps

involved in administering an FSA auction, using as an

example an auction held by FSAs Kansas City

Commodity Office (KCCO) in late March 1996 for

products to be delivered to distributing agencies during

May 1996. That auction is representative of most FSA

auctions, but, at the close of the chapter, we discuss

recent auction changes for some commodities. 

Table 4-1 summarizes the auction; column 2 defines the

key steps in the auction, while column 3 lists the associated dates. Column 4 lists the time remaining, at each

step, until the beginning of the delivery month (May 1,

in this case). Auctions for other months frequently have

slightly different days of the month for the procurement

activities, but essentially the same time remaining, after

accounting for weekends and holidays, until the beginning of the delivery month. In a typical auction, KCCO

aims to schedule dates for each step by working backward from the beginning of the delivery month. For

example, KCCO aims to receive bids and select and

inform auction winners during a period that is typically

5 to 6 weeks prior to the opening of the delivery month.

Actual deliveries can be scheduled for two periodsthe

first or second half of the delivery month.

KCCO aims to prepare final invitations about 8 weeks

(55 days) before the beginning of a delivery month. A

final invitation is FSAs notice of intent to purchase

products, and is sent to vendors and the trade; it is a list

of the tendered contracts for purchasing products. The

55-day span reflects auction experience: a shorter span

would result in more failures to complete the remaining

steps on time and could increase the cost of completing

these activities.

FSA excludes product orders that do not arrive by the

deadline. Excluded orders may sometimes be included

in a special supplemental invitation and auction, with

delivery in the same month as the current auction.

Otherwise, late orders are held for the next months

auction.

A supplemental auction includes all the steps in other

auctions, but with the time until the beginning of the

delivery month compressed for steps 4 through 11.

Generally, deliveries for a supplemental auction are in

the latter half of the delivery month to ease the scheduling problems caused by missing the 55-day deadline.

The current or regular auction has deliveries in both the

first and second halves of the delivery month.

The FSA Auction Process

Information and Client Planning

USDAs Food and Nutrition Service (FNS) provides

client agencies with a list of products that can be

obtained from FSA and AMS auctions along with their

expected prices, based on experience and forecast inflaFood Procurement by Farm Service Agency / AER-766 USDA-ERS / 15

CHAPTER 4

FSA PROCUREMENT AUCTIONS: 

HOW THE PROCESS WORKS
tion. Client agencies include school systems as well as

public and private social service agencies. Each client

agency is also provided with a budget for domestic

commodity distribution based upon the characteristics

of the agencys target population, FNS entitlement

rules, and the congressional appropriation for the current fiscal year. 

Client agencies use the information to develop purchase

plans, which form the basis for commodity and product

orders to KCCO and AMS. The distributing agencies

coordinate their plans for procurement through USDA

auctions with plans for purchases with other funds. For

example, school lunch providers will have access to

entitlements earmarked for the purchase of FSA and

AMS products, but they will also receive direct cash

entitlements from FNS, revenues from the sale of

lunches, and sometimes additional cash support from

States and localities. In considering which FSA commodities to purchase with their food entitlements,

clients will consider private sector prices and service

quality, as well as menu needs, and aim to concentrate

their FSA purchases on those products for which FSA

offers the greatest competitive advantage. 

Developing an Invitation Worklist

Schools and other distributing agencies work with FNS

regional offices to develop orders for USDA products,

called delivery orders. Delivery orders for FSA products are then sent by the regional offices to KCCO

(steps 1 and 2 in table 4-1). An order specifies the

product desired, order size, package size, and how the

product is to be shipped. Order sizes are in truckload

units. A truckload unit may be split into two parts, with

each part having its own final delivery destination,

which is typically a warehouse designated by a coordinating State agency. Since FSA holds auctions monthly,

with delivery 60-90 days after an order is placed,

clients schedule their FSA purchases with that time

frame in mind.

The orders are entered on worklists by KCCO, and

arranged by commodity category and product.

Worklists for each product are then distributed to

KCCO personnel for preparation of the final invitation. 

Developing and Distributing 

Final Invitations

KCCO takes about 1 week to prepare final invitations

(step 4), while making several decisions that can influence bid prices. Orders will sometimes be combined

into a larger unit if several clients order the same product for delivery to the same location, on the grounds

that larger orders may attract lower bid prices. The

client agency also specifies a delivery window, either

the first or second half of the delivery month, in order

to give processors opportunities to spread production

loads by having contracts for each delivery period. By

spreading production, processors may lower costs and

bids, and more processors may bid. But combining

orders for the same destination may reduce opportunities for spreading production loads; therefore, judgments must be made about how to combine orders.

16 /ERS-USDA Food Procurement by Farm Service Agency / AER-766

Table 4-1: A work schedule for the March 1996 KCCO auction

Step Activity Date Days until (since) 

May 1 

1 Clients submit product orders to FNS regional offices Ongoing Ongoing

2 FNS delivers orders to KCCO March 5 57

3 KCCO completes invitation worklist March 6 56

4 KCCO completes final invitation March 7-1 51-55

5 Final invitation is distributed March 12-14 48-50

6 Vendors prepare and submit bids March 18 44

7 KCCO evaluates bids and selects winning bids March 25 37

8 KCCO informs each winning bidder of awarded contracts March 26 36

9 Awarded contracts are publicized via FSA Internet site March 27 35

10 Notices to Deliver are sent to vendors March 28-29 33-34

11 Vendors produce, package, and ship products April 1 - May... 30 - ...

12 Clients receive orders May 1- May 15 0-(14)

May 16 - May 31 (15)-(30)

Notes: KCCO is Kansas City Commodity Office, FSA is Farm Service Agency, and FNS is Food and Nutrition 

Service, all with the U.S. Department of Agriculture. 
Some orders are selected as small-business set asides.

Set-aside contracts give qualified small businesses a 5

percent bidding advantage; that is, the award will be

made to a small firm if its bid is no more than 5 percent

greater than the best bid. 

A final invitation for a particular commodity group,

such as flour, will often cover many specific orders.

That is, it will separately list each delivery of a specific

product, distinguished by package size and precise

characteristics. For each product order, it will list a city

or town to which the product is to be delivered (sometimes, two will be listed for a split load). The invitation

will specify the quantity being sought for each product

and destination, and it will identify any specific transportation or distinctive packaging requirements.

KCCO solicits bids by sending the final invitation for

each commodity category to the appropriate vendors

(step 5). The agency also publicizes the final invitation

to the trade and to the public for each product through

mailings and through electronic postings on the Internet. After receiving the solicitation, vendors have about

1 week to prepare their bids and return them to KCCO.

Bid Preparation and Selection

In preparing bids (step 6), vendors account for expected

competition as well as product costs. Costs include the

expected costs of processing, including labor, energy,

and packaging materials, and also must reflect expected

prices for the agricultural commodities that will be

processed into FSA products. Bidders are generally

fairly certain of future agricultural prices because bidding occurs only 1 to 6 weeks before processing and

because many FSA products are based on agricultural

commodities that have deep futures markets.

Bid prices are FOB destination at the warehouse and

processor locations are specified by distributing agencies. Vendors pay transportation costs to receiving locations and, therefore, account for likely transportation

costs when preparing bids. Bids also reflect distinctive

USDA requirements, such as USDA labels, unusual

packaging or product standards, and inspections.

Finally, bidders consider likely capacity utilization

when preparing bids. Those who expect to have excess

capacity at the time of processing are likely to bid

aggressively (low). Since they will need to pay capital

and other fixed costs whether they win the bid or not,

they will seek to win the bid as long as the revenues

from winning exceed only the additional variable costs

associated with filling an order. By contrast, firms that

expect to be producing near full capacity will bid higher; for a winning bid to be worthwhile, it will have to

return more to the firm than the production that it supplants. In short, firms will be more likely to add

capacity charges to the bid when they are already

producing near full capacity.

A vendor can specify a total quantity restriction; that is,

the vendor can be awarded contracts only up to the

restriction quantity, even if the vendor is the low bidder

on other contracts. In addition, a vendor may submit a

minimum quantity restriction that specifies the lowest

quantity of product the vendor is willing to supply. The

minimum restriction means that the vendor chooses not

to be awarded any contracts if the total quantity won is

less than the specified minimum. 

Bids submitted by a vendor can vary among contracts,

even among contracts for the same product to the same

destination. However, a vendor can bid only one price

for an entire contract. Frequently, bidders submit

revised bids just before they are opened to reflect the

latest market information. 

Bid Evaluation and Selection 

of Winners

KCCO opens all the bids at the same time (step 7). No

revised bids are accepted after the envelopes are

opened. The bids are evaluated and winners are selected on the day the envelopes are opened so that vendors

can be notified the next day. Bids are binding contracts;

selection of a winner obligates the winner to fulfill the

contract even before being notified. 

The bid evaluation is complicated because of the minimum and maximum quantity restrictions and the 5-percent bidding advantage given to small businesses. A

search procedure implemented on the KCCO computer,

known as linear programming, is used to select the

combination of contract winners that yields the lowest

total procurement costs while satisfying the restrictions.

Winning bids that are greater than a maximum purchase

(constructed) price are reviewed. Constructed prices are

based on prior experience and expectations of inflation,

and are developed by KCCO commodity analysts prior

to bid evaluation. KCCO may decide to accept the bid,

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 17
or they may approach the winning bidder and attempt

to get the bid reduced, or they may reject the bid and

cancel the contract. Orders in canceled contracts may

be reintroduced in the next auction round, and those

orders are delivered late to clients, or KCCO may issue

a supplemental invitation to purchase the orders for the

same delivery period.

Announcement of Awards

Winning vendors are notified quickly, the day after

selection, since those who have not already purchased

materials (step 8) may consequently be placed in speculative positions. The price risks from these speculative

positions increase in direct proportion to the elapsed

time between bid submission and notification of contract awards. Winning bidders then have about 5-7

weeks to fulfill contracts with delivery in the first half

of the delivery month, and about 7-9 weeks for contracts with delivery in the second half. 

KCCO provides public notice of the auction results 2

days after bid openings and evaluations (step 9). The

results revealed include the price and winning bidder on

each contract. Releasing this information helps ensure

the public that the auction is competitive and provides

vendors that did not win with information about how

much they must lower their bids to win at the next auction. It is important to release the information quickly

because some losing bidders may have purchased materials in anticipation of winning contracts, and quick

release allows for easier reallocation of materials.

Finally, quick public release via electronic means saves

resources for FSA and KCCO; agency personnel no

longer have to respond directly to frequent requests for

information.

Notices to Deliver

KCCO produces a document for each contract, called

the Notice to Deliver, and sends it to the winning bidder (step 10). The notice includes the product description (for example, rice, milled U.S. No. 2 medium), as

well as the contract number, invitation number, delivery

order number, commodity code, contract size, package

size, and shipment mode. Notices also list the name,

address, and telephone number of the vendor, the distributing agency, and the designated agency person

responsible for receiving the product (the consignee).

The notice to deliver provides the vendor with all the

information necessary for fulfilling the contract. 

Production and Shipping

The vendor produces the product and ships it to the

consignee (step 11). Contracts call for USDA inspectors

to be on site at the plant during production runs for

USDA commodities. Vendors must, therefore, arrange

for inspection by personnel from AMS (peanut and

dairy products and salad dressing) or GIPSA (all other

items), and must generally time production runs for

their presence. For remote or small plants, this can

sometimes lead to delays. Inspectors monitor production processes and may perform some onsite tests. They

certify product type, quality (through lab tests), and

weight, and also certify that packaging meets contract

standards for information, strength, and sanitary

requirements. Most USDA products must be shipped

with USDA labels, instead of the processors normal

brands or private labels.

Contracts also require that product samples be sent to

USDA-approved labs for testing. Required tests vary

with the product. For example, USDA aims for certain

nutritional goals in cheese purchases, and also prefers a

product that will melt properly when cooked, while

stretching across a pizza or hamburger. Precise lab tests

for cheese include tests of fat, moisture, salt, and acid

content. Inspection procedures can also sometimes lead

to delays, and products are sometimes shipped pending

receipt of test results, at the vendors risk.

Delays are not always due to USDA inspection and

testing requirements. Sometimes processors will deliberately delay production because an unexpected, more

lucrative, order came in. USDA can impose fines for

late delivery, and can also suspend contracts for vendors that are chronically late. If USDA does not use the

tools at its disposal, vendors can have strong incentives

for late delivery, especially when vendors are producing

near full capacity.

Distribution

The vendor informs the distributing agency by fax that

the product order is being shipped (step 12). This notification must be given on the date the product is

shipped. The trucker or a rail employee calls the consignee, at least 24 hours prior to delivery, to schedule

delivery. FSA products are often shipped to a manufacturing plant for further processing. For example, school

districts often use FSA entitlements to purchase flour

and cheese, which are then shipped to nearby proces18 /ERS-USDA Food Procurement by Farm Service Agency / AER-766
sors who make them into frozen pizza or other more

highly processed foods.

Title to the product is transferred from vendor to distributing agency at the receiving location when the consignee signs for the product. At this stage, USDAs

responsibility for product quality ends. The consignee is

then responsible for any further processing, as well as

product transportation to client facilities and handling at

dining facilities.

Recent Variants on the FSA

Auction Process

FSA has altered the typical process in recent auctions

for several commodities. The alterations affect the timing of the auction process, the use of USDA labels, and

the reliance on USDA inspection.

Commercially labeled items in five product categoriesinfant formula, evaporated milk, instant nonfat

dry milk, ready-to-eat cereal, and rice cerealare being

purchased under a 5-year pilot program. The products

are purchased not for the school lunch program but for

two smaller programsthe Commodity Supplemental

Food Program (CSFP) and the Food Distribution

Program on Indian Reservations (FDPIR).

By purchasing commercially labeled products, vendors

may supply USDA programs out of existing inventory,

thus altering the production process outlined in step 11.

Moreover, with commercial labels, FSA now relies on

vendor certification of quality, since the vendors brand

is on the package. As a result, USDA inspection (also in

step 11) is forgone.

The process outlined in table 4-1 uses a series of

monthly auctions to procure products to be delivered to

clients 5-9 weeks after the selection of winning bids. In

infant formula, KCCO has lengthened the contract to a

full year, while at the same time allowing commercial

labels on formula. Invitations now specify an indefinite

quantity to be delivered throughout the year, instead of

specifying precise quantities to be delivered to specific

locations each month. Contracts can be less precise in

infant formula because bids show no geographic variation. Because of the longer contract duration, the volume at bid is considerably larger, and KCCO hopes that

larger volume will induce more competitive bidding

among the small number of manufacturers. Similarly,

KCCO has lengthened contract durations for ready-toeat cereal purchases as part of the experiment in purchasing commercially labeled products.

KCCO has altered the bidding process in another way

for cheese purchases. It now issues rolling invitations,

covering several months, for deliveries of cheese. For

example, KCCO will issue an invitation in July to bid

on deliveries of cheese in specified 2-week windows

from September through December. The August invitation will then include any new school orders for

October through January deliveries. In essence, the new

cheese process adds certain elements of flexibility:

firms can now place bids further in the future than they

did under the prior system, and they can achieve more

certainty, in that they can commit to USDA production

for a quarter of a year at a time instead of a month.

Rolling contracts also provide KCCO with the opportunity to reject winning bids that are above constructed

prices, and still deliver products on time.

Under the cheese experiment, KCCO enters orders as

they come in. Clients now have some reason to enter

early orders, since KCCO will act upon them. In addition, KCCO can use rolling contracts to encourage

client agencies to shift the temporal pattern of their

orders, away from peak and toward off-peak periods, to

take advantage of seasonal price fluctuations. 

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 19
Introduction

FSA sets precise requirements for the commodities that

it buys for food assistance programs. Those requirements include product specifications (such as nutritional guidelines), packaging and labeling standards, and

rules for product testing and onsite product inspection

to ensure compliance with specifications. From those

processors who are willing to offer products that meet

FSA requirements, the agency then chooses vendors by

using a bidding process, as outlined in chapter 4, that is

designed to use competition to purchase products at the

lowest feasible prices.

When FSA chooses a specific bidding process, it makes

several other choices. It specifies the timing of the

process: FSA decides when invitations to bid will be

announced, when they will be closed, how quickly the

award will be made upon closure, and how quickly the

product must be delivered upon award. In defining the

award and the bidding process, FSA also specifies any

transportation requirements, plans solicitation of potential bidders, formulates procedures for aiding small

businesses, sets damages for noncompliance with award

requirements, and sets policies for cancellation of an

invitation if bids appear to be noncompetitive.

Most awards are for precisely defined quantities (say,

42,800 pounds) of a precisely defined product (all-purpose bleached wheat flour in 50-pound bags) to be

delivered to a precise location (a warehouse in Omaha,

Nebraska) during a set time (between November 1 and

November 15). But in principle, the award could also

be for the delivery of an indefinite quantity (with, for

example, a minimum of 1 million pounds and a maximum of 25 million) throughout a year. In other words,

FSA can also choose the duration and quantity of the

award at bid.

FSA acts on behalf of other clients, such as State distributing agencies. When it designs the bidding process,

FSA must also specify the timing that clients must follow to place orders. That is, client agencies must deliver food orders to FSA 55 days prior to the delivery

month in order to be included in an invitation order to

receive delivery in a specified time window. FSAs policy choices for order, auction, and delivery timing ultimately drive one dimension of service qualitytemporal responsiveness to client orders.

These are all policy choices. FSA could choose other

product requirements or other auction designs; alternative choices could affect processor costs, product

prices, product quality, and FSA service quality. Actual

choices often can involve a tradeoff of a gain in one

dimension of performance against a loss in another

(McAfee and McMillan, 1987; Laffont and Tirole,

1993; Wolfstetter, 1996). Key FSA decisions revolve

around four interlinked areas: product packaging and

labeling requirements, inspection requirements, the timing of order, bid, and delivery stages, and the design of

procurement auctions. We discuss the issues surrounding these areas in this chapter, and begin by showing

why we say these issues are interlinked. 

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 21

CHAPTER 5

ISSUES IN USDA PROCUREMENT POLICIES
Labels Require Inspection: 

The Need for Quality Certification

in USDA Procurement

FSA food procurement procedures are not unique, but

they do differ in important ways from those used by

commercial buyers, as well as some other government

agencies. For example, some private firms (such as

national fast food chains, retail supermarket firms, or

wholesalers arranging for private-label products) will

select a small set of qualified suppliers through an

intense search. Once selected, a qualified supplier will

receive a large volume of orders from the firm, at relatively profitable prices. Because the status of qualified

supplier is so important to a suppliers profits, the supplier will have strong incentives to maintain agreed levels of quality and therefore to retain qualified supplier

status. Firms using that procurement strategy, which is

quite similar to prime vendor programs, trade off higher

product prices to gain greater supplier efforts to maintain product quality and to provide timely service.

FSA uses auctions to procure food commodities, and

the auctions are designed to get favorable prices for

FSA clients by relying on price competition among bidders. That is, FSA does not form long-term relations

with suppliers. Moreover, FSA generally does not purchase products with commercial labels (that is, common supermarket brands). Instead, USDA requires that

all USDA products be packaged according to specific

USDA directions and carry USDA labels. While the

procedure can generate strong price competition among

bidders, resulting in lower FSA costs, it also provides

bidders with incentives to reduce their own costs by

delivering low-quality products. Since the products do

not carry commercial labels, quality problems will not

damage the reputations of vendors commercially

labeled products; instead, USDA and its client agencies

bear the risks of poor product quality. 

FSA aims to control those risks by setting precise product specifications, by requiring the presence of USDA

inspectors on site during production of USDA products,

and by performing laboratory tests of product samples,

to ensure that delivered products adhere to contract

specifications. In short, FSAs inspection requirements

follow from the use of USDA labeling requirements

and a competitive bidding process. 

Critics note four potential problems with current USDA

product requirements. They may increase costs, both to

processors and to USDA, compared with commercial

practices that realize the same quality goals. They may

erode one dimension of service qualitythe timeliness

with which commodities are delivered to the warehouses designated by States, and ultimately to client agencies. They may limit competition for USDA awards,

and thereby raise bidder prices, if some processors

decide not to participate because of the requirements.

Finally, they may limit the range of products available

to school lunch programs and other USDA clients.

Some consumers associate the USDA label with low

product quality, but in fact, FSA typically sets relatively

high product specifications (for example, apples must

be grade A, and rice must be U.S. No. 1). Actual quality problems rarely stem from poor product specifications or from lax inspection standards. Problems occasionally arise from poor vendor compliance with product specifications, and from inspector failures to immediately detect noncompliance. More often, quality problems can arise in the distribution channel. FSAs

responsibility for product quality ends when commodities are delivered to warehouses; from there, responsibility for products falls to States and school districts.

After being held in warehouses, products may be

shipped to schools (using a variety of different forms of

transportation) or they may be shipped to other plants

for further processing before being shipped to school

districts. At a district, products may be held in inventory and then prepared into meals at schools, or they may

be prepared at a districts central kitchens before meals

are transported to schools. Once meals are at a school

cafeteria line, they may be on a serving line for a significant period of time before consumption. Product

quality can deteriorate at each stage. Because of the

time lags at each stage of delivery, unacceptable quality

in a package of cheese or a can of peanut butter may

not be detected until opened at a cafeteria. By then,

several weeks or even months may have passed from

the date the product was shipped from the manufacturer. In many cases, this sort of lag makes it difficult to

assign accountability for quality problems.

USDA Inspection Requirements

The Agency maintains a distinctive and relatively

demanding set of inspection requirements. Contracts

call for USDA inspectors to be on site at the plant during production runs for USDA commodities. Vendors

must arrange for inspection by personnel from the Food

and Drug Administration (FDA) for infant formula,

22 /ERS-USDA Food Procurement by Farm Service Agency / AER-766
AMS (peanut and dairy products and salad dressing), or

GIPSA (all other items), and must generally time production runs for their presence. Inspectors monitor production processes, assemble product samples for lab

tests, and may perform some onsite tests. They certify

product type, quality, and weight, and also certify that

packaging meets contract standards for strength, information, and sanitary requirements. 

Contracts also require that product samples be sent to

USDA labs, or USDA-approved labs, for testing. Required tests vary with the product. For example, USDA

aims for certain nutritional goals in cheese purchases,

and also prefers a product that will melt properly when

cooked, while stretching across a pizza or hamburger.

Precise lab tests for cheese include tests of fat, moisture, salt, and acid content. Vendors pay fees for inspection and lab tests, fees that are ultimately recovered in

product prices at auctions. Because USDAs tests are

unique (some would not be done except for USDA

requirements), they can increase bid prices by amounts

ranging from 0.5 percent to 2.0 percent.

Inspection also can impose indirect costs on the programs. Some vendors, typically small plants in more

remote locations, complain of problems in getting

inspectors to come to the plant on a timely basis to

inspect the USDA production run. Other vendors complain of lags in performing tests at USDA labs and

reporting results back in a timely fashion. Some complain that specific required tests are not reliable or not

useful. Such indirect costs show up as delays in delivery of products to State warehouses, and as reductions

in the number of firms participating in FSA auctions.

Inspection is closely tied to USDA labeling; USDA

labels place risks on the Department for product quality

failures. A shift to more commercial labeling would

also likely imply a shift to vendor certification of quality, with an attendant shift of responsibility to the vendor. That would not imply a cessation of USDA quality

control activities, but rather a shift toward more random

inspection of products, with a schedule of penalties and

increased probabilities of inspection for noncompliant

plants. 

Commercial Labeling 

of USDA Products

Reliance on USDA labels creates several kinds of costs

to the system. USDA packages and labels are not free,

and there is some direct cost associated with them. But

for regular participants in USDA programs, these do

not necessarily increase final product costs compared

with the use of commercial packaging and labeling.

However, several types of indirect costs may be relevant. First, specific USDA packaging requirements can

sometimes raise product costs if production lines are

not designed for USDA packages. Second, firms that do

not typically sell large volumes to USDA may have to

place special orders for USDA packaging and labels,

and that may either slow their delivery times or limit

their participation in FSA bidding. Third, reliance on

commodities that are USDA labeled prevents the

Department from accessing excess inventories of commercially branded product that from time to time

become available at low prices. Most important,

reliance on USDA brands means that USDA bears the

onus for poor quality control. Hence USDA labeling

creates the need for reliance on government inspection

for quality control, and that reliance does impose significant costs. 

Our empirical research (described more fully in chapter

7) shows that FSA attracts only a few bidders for lowvolume products. That is, more firms bid in auctions for

flour in 10-pound packages (the most common type and

the most common FSA flour purchase) than in auctions

for flour in 50- or 100-pound packages, and more bid in

auctions for bleached than for unbleached flour. Fewer

bid in pasta auctions for rotini than for spaghetti, and

fewer firms bid in auctions for low-fat peanut butter

than for other kinds. Now, there may simply be fewer

firms producing relatively unusual items, but the indirect costs of USDA requirements (the need to arrange

for USDA labels and packaging, and to time runs for

the presence of inspectors) may be more onerous for

distinctive products, and may therefore limit the number of potential bidders. In turn, few bidders mean

higher bid prices (also shown in chapter 7), thus limiting FSAs price advantage over other forms of procurement. If FSAs advantage is smallest in unusual and

low-volume products, then FSA will be unable to offer

a wide variety of products economically.

Proponents of restrictions on commercial labels

advance three reasons for relying exclusively on USDA

packaging and labeling. First, they assert that commercial labels can induce brand loyalty on the part of

USDA clients. If clients insist on particular brands, then

FSA buying power will be eroded as commodity volumes are split among brands, and FSA and its clients

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 23
will ultimately pay more for food. Second, most States

now route USDA shipments through commercial warehouses before distribution to schools. Some argue that

commercial warehouses with ties to particular brands

will offer poor service on rival brands, or will refuse to

carry them. Third, they argue that firms will be unwilling to offer their branded products at substantial discounts compared with normal commercial prices, and

hence reliance on commercial brands will result in

higher prices to FSA.

The third objection becomes irrelevant if processors are

given the option of providing either commercial or

USDA brands. The second objection should apply only

in States in which a commercial warehouse has market

power and the State has limited warehousing and distribution alternatives. With alternatives, States can simply

cancel contracts for poor performers and shift to warehousers who are willing to earn money by distributing

the States products. Warehousing is not generally

thought of as a market activity where firms can maintain monopoly power; hence, all States should be able

to develop alternatives to poor performers. As a result,

the important issues for commercial labeling come

down to brand loyalty.

Brand loyalty is an important issue. Research by ERS

shows that leading branded food products in supermarkets often sell at prices that are substantially higher

than corresponding nonbranded products, by over 30

percent, on average, for a sample of 30 staple products,

such as rice, spaghetti, peanut butter, and flourall

products purchased by FSA (Kaufman et al., 1997).

Given the price advantages held by strong brands,

many firms will want to sell branded products to

schools in hopes of developing brand loyalties that will

persist as school children grow into adults. 

USDA officials (as well as producers of nonbranded

products) may react in a different way to the same data.

They argue that USDA purchase policies should

demonstrate wise shopping practices to schoolchildren

by ignoring product differences based solely on image

and aggressively seeking high-quality products at low

prices. Bans on commercial labels would be the primary demonstration of that strategy, but not the only

demonstration. USDA could alternatively pursue the

purchase of private-label products generally produced

for wholesalers and retailers, but under USDA specifications. 

It is important to recognize that brand loyalty can mean

different things for different FSA products, and it is

possible that decisionmakers can improve program performance by a more discriminating use of commercial

labels. For most FSA products, clients are not ultimate

consumers, such as schoolchildren in school lunch programs, but rather school lunch administrators and cooks

who prepare foods using USDA commodities. FSAs

ultimate consumers see the package for only a few

products. Moreover, only some products carry the distinctive flavoring or advertising images that create

brand loyalty. In short, only some products carry the

risk that use of commercially labeled product may

induce later brand loyalty on the part of schoolchildren.

For example, several interviewees remarked that

schoolchildren appeared to have strong taste preferences in some types of chicken products (nuggets, fingers): they wanted products to taste like those offered

by leading fast food chains. Schoolchildren also clearly

form strong preferences for different brands of readyto-eat cereal. But many products do not carry strong

brand attachmentsfor example, ground beef, pasta,

flour, and many cheese products. FSA may need to

identify those commodities where labeling and brand

loyalty concerns are strongest, and discriminate

between those and other commodities.

Issues of Timing and FSA

Service Reliability

We can think of quality in two dimensions. The first is

product quality, which concerns the taste, nutritional

adequacy, and deterioration of the products that FSA

purchases on behalf of school districts and other clients.

The second is FSA service quality, which concerns the

speed with which the agency can respond to client

requests for food products, the reliability of FSA deliveries (that is, the extent to which deliveries arrive when

they are supposed to arrive), and the variety of FSA

product offerings.

In considering FSA service quality, recall the timing of

order and delivery from the point of view of clients in

school districts. In the spring (March and April), State

coordinators release information to school districts for

the following school year. Included in the information

is the likely size of district entitlements as well as the

range of allocation among cash, AMS (Group A) commodities, and FSA (Group B) commodities. Also

included is a listing of likely FSA and AMS commodi24 /ERS-USDA Food Procurement by Farm Service Agency / AER-766
ties, and projected prices for those commodities. Many

coordinators also offer advice on the most effective

ways to spend entitlement dollars, and work with districts to identify cooperative purchasing arrangements

through private vendors. Armed with this information,

along with additional information on other revenue

flows, prices for non-USDA food products, and meal

requirements, school district administrators begin to

plan food purchases and to place monthly orders with

FSA, AMS, and private vendors for deliveries to support meals beginning in September.

By the time administrators place orders, school district

plans have become relatively inflexible. Districts have

typically designed menus by that time, and have placed

orders for non-USDA commodities on the assumption

that they will be receiving known combinations of

USDA commodities at known dates. Failure to receive

timely deliveries means that districts will often have to

replace the USDA commodity with the same product

purchased under unfavorable conditions from a private

vendor. Late deliveries, therefore, impose substantial

costs on school districts, and are a primary source of

school district complaints about FSA service reliability.

Deliveries can be late because a vendor failed to meet

the contractual delivery date in the award. They can

also be late because FSA canceled an auction because

bids were too high. Typically, FSA will issue a supplemental invitation and attempt to purchase the product

for the same delivery period at a lower price. If this is

not successful, KCCO will place the order and award

up for bid again in the following month, so that cancellation then works out to late delivery. In FSAs view,

cancellation is an important tool because it provides a

means to induce bidders to bid more aggressively (that

is, a low bidder is not guaranteed an award), it serves as

a tool to police possible collusion among bidders, and it

allows FSA to shift purchases in response to unexpected increases in prices. 

From the point of view of school districts, cancellations

impose significant immediate costs on them in return

for uncertain and hard-to-document future gains in

prices. Moreover, to the extent that the gains arise from

reduced collusion and more aggressive bidding, they

are shared by all districts, while the costs are borne by

those whose auctions were canceled. Because of the

costs imposed, FSA needs to do more to identify the

size of any benefits in order to justify this strategy.

Vendor failures can occur for several reasons. At peak

production periods, vendors may win an award, and

then receive an unexpected order from a higher paying

client. The vendor may then choose to ignore the

agreed delivery date and accept an FSA fine for late

delivery. During fall harvest periods, transportation

may at times be difficult to arrange, and during the winter, deliveries may be held up because of bad weather.

Deliveries can also be late because vendors had difficulty arranging for inspectors, or because AMS labs

were slow in performing tests.

Adjustments in 

the Bidding Process

Commodity volumes, competition, and seasonality all

seem to affect bid prices. KCCO purchase strategies

might be able to affect bid prices by influencing these

factors.

KCCO argues that competition, measured by the number of bidders for an award, is an important determinant

of prices. That view is supported by the economic theory of auctions, by a considerable amount of empirical

research on procurement through auctions, and by our

own analyses of auctions carried out by KCCO (chapter

7). KCCO also believes that the number of bidders is in

turn influenced by the size of the contractthat is, the

volume being purchased. Chapter 3 shows that KCCO

volumes have fallen sharply in recent years. But ERS

research suggests that monthly volumes have only

small effects on bidder numbers and bid prices. We

believe that product characteristics and expected capacity utilization in the industry have more important

impacts on bidder numbers. Moreover, our analyses

show that bidder numbers have large effects on prices

only when the number of bidders is very small. In

other words, losing a competitor has a much more

important effect on price when there are only two competitors to begin with than when there are four or five.

KCCO does face tight oligopolies: for example, readyto-eat cereals and infant formula are each produced by

a very small number of firms. Moreover, government

procurement is subject to collusive bid-rigging among

participants, as well as more tacit (and legal) attempts

by vendors to refrain from strong price competition

(Brannman, 1996). This is more likely to occur when

the same few bidders respond to the monthly invitations

to bid. Some of the commodities that USDA purchases

have strong seasonal demand patterns. For example,

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 25
retail sales of flour surge in the late fall, so flour mills

operate near their production capacities in early and

mid-fall, preparing to meet the seasonal increase in

retail purchases. Mills will bid higher prices when they

operate near capacity than when they have substantial

excess capacity. Consequently, flour bids show a seasonal pattern of increases during the peak fall season

and offpeak declines. KCCO thus realizes better prices

and more competition for invitations during offpeak

seasons. 

KCCO has altered the bidding process for several commodities in hopes of reducing bid prices. For example,

the contract duration for infant formula has been

lengthened to a full year, from 3 months, at the same

time that commercial labels for formula have been allowed. A longer duration contract increases the volume

at stake in a bid; KCCO hopes that longer duration,

higher volume contracts will induce more competitive

bidding among the small number of formula vendors.

Similarly, KCCO has lengthened contract durations for

ready-to-eat cereal purchases as part of an experiment

in purchasing commercially labeled products.

KCCO has altered the bidding process in another way

for cheese purchases. It now issues rolling invitations,

covering several months, for deliveries of cheese. For

example, the office will offer an invitation in July to

bid on deliveries of cheese in specified 2-week windows from September through December. The August

invitation will then include any new school orders for

October through January deliveries. In essence, the new

cheese process adds certain elements of flexibility:

firms can now place bids further in the future than they

did under the prior system, and they can achieve more

certainty in that they can commit to USDA production

for a quarter of a year at a time instead of a month.

Under the cheese experiment, KCCO enters school

cheese orders as they come in. Schools now have some

reason to enter early orders, since KCCO will act upon

them. These rolling contracts may also allow KCCO to

improve timeliness in product delivery, by providing

the office with the flexibility to reject contracts and

reopen auctions while still meeting desired delivery

dates. For other commodities, KCCO would like to

encourage schools to shift the temporal pattern of their

orders away from peak and toward offpeak periods to

take advantage of seasonal price fluctuations. To

expand this experiment, FSA and its clients may need

changes in spending authority to shift expenditures

from one fiscal year to another. 

Longer contract durations, in which firms place bids on

deliveries further in the future, will introduce some new

risks into USDA procurement. When bidding on a

short-duration contract (for example, bidding in

October for the November delivery of flour), firms may

be quite confident that input price risks are low; that is,

vendors bid with firm knowledge of the likely level of

wheat prices when placing bids to deliver flour. They

may also be quite confident that capacity risks are low;

that is, vendors bid with firm knowledge that plant

capacity will be lightly utilized (in which case they will

bid low) or heavily utilized (leading to a higher bid).

With contracts of longer duration (bidding in October

for March delivery), firms will have less certainty about

input prices and capacity utilization well into the future.

Because of greater uncertainty, longer contract durations could lead to higher prices for USDA commodities, even if the greater volumes in longer duration contracts attracted more bidders. USDA could reduce the

risks from input price uncertainty, and could therefore

induce lower bids, by allowing bids to be indexed to a

measure of input prices.

26 /ERS-USDA Food Procurement by Farm Service Agency / AER-766
Introduction

FSA amasses data while administering auctions, data

that can be used to investigate the factors driving bids

and to compare FSA bids with private sector prices for

comparable items, as a step in evaluating auction strategy. To perform that evaluation, FSA provided ERS with

auction records for five commodity categoriesall-purpose flour, bakery flour, pasta products, vegetable oil,

and peanut butterfor the 5 years covering January

1992 through December 1996. 

This initial analysis focused on just five commodity

categories because that seemed like a manageable number for a new project. The records were not kept in

electronic format, but in paper archives, and included

separate records for approximately 2,000 to 6,000 auctions for each commodity category. Coding the records

into electronic format was a major task, and limited our

original commodity coverage. 

The five chosen were important FSA commodities that

were closely linked to related agricultural commodities

(wheat, peanuts, and soybean and cottonseed oils) with

reliable data on prices. The major omitted category,

cheese, is a large category undergoing substantial

changes in agricultural commodity pricing. ERS will

investigate cheese auctions in later analyses. 

Data Sources and Definitions

of Variables

Auction Records

Much of the data are derived from records (PPCR30

forms) generated by FSA during the bidding process.

Each record refers to an auction of a specific commodity on a specific date for delivery to a warehouse within

a State (or to a plant for further processing) during a

specified 2-week time window, generally 5-8 weeks

after the auction (see table 4-1).

Each record specifies the commodity up for bid, with a

precise description of package size and distinguishing

product characteristics. It specifies the quantity up for

bid (usually between one and five truckloads, but specified in pounds), as well as the place and the State to

which the product is to be delivered. Separate bidder

codes identify each bidder, the bidders price, whether a

bidder is a qualified small business, and the constructed price developed by FSA prior to the auction. The

file also identifies the date of the auction and the month

and 2-week time window (first or second half of a

month) for delivery.

Most of our discussion in this report emphasizes the

lowest bid in FSA auctions, which also is usually, but

not always, the winning bid (see chapters 2 and 4 for an

overview of the process and the determination of winning bids). Some analyses investigate a dataset consistFood Procurement by Farm Service Agency / AER-766 USDA-ERS / 27

CHAPTER 6

DATA FOR EMPIRICAL ANALYSES

OF FSA AUCTIONS
ing of all bids in a commodity category, although we

can say that the general factors driving low bids also

drive other bids. In the sections that follow, we discuss

the explanatory variables that we think account for fluctuations in bids.

Specific Agricultural Price Measures

We expected that FSA bids would be closely linked to

price movements in related underlying agricultural

commodities. Moreover, key agricultural prices showed

a strong pattern during the period: wheat and oilseed

prices rose sharply from 1992 through 1995, before

abating somewhat in late 1996. To analyze that linkage, we obtained monthly USDA price data for key

commodities. We generally developed price series for

three variables: the average cash price in the month of

delivery, the change in the average cash price between

the delivery month and the following month, and the

change in the average cash price between the delivery

month and the prior month. By using these measures,

we can distinguish the effects of longrun shifts in price

from shortrun shocks. That distinction turns out to be

useful (chapter 7) because it appears that month-tomonth price fluctuations have little or no effect on FSA

prices, while longer run shifts have large effects.

All-purpose flour uses a variety of different wheats. In

our statistical analysis, we found that one wheat price

series fit the data best, and that other price series added

no additional explanatory power to our models.

Consequently, we relied on the series for No. 2 Soft

Red Winter Wheat (St. Louis). For bakery flour, we

found that a different series fit the data best, so we

relied on prices for No. 1 Hard Red Winter Wheat,

Ordinary Protein (Kansas City). Pasta uses durum

wheat, so we relied on the price series for No. 1 Hard

Amber Durum (Minneapolis). All three monthly wheat

price series are reported in the 1997 Wheat Yearbook

(ERS/USDA).

In contrast to flour and pasta, we found that two agricultural price series were important in explaining FSA

vegetable oil bids. Soybean oil is the primary ingredient, but cottonseed oil is also important and statistically

relevant. We consequently used wholesale prices for

Crude Soybean Oil (Decatur) and the Crude Cottonseed

Oil (Mississippi Valley points), as reported in the Oil

Crops Yearbook (ERS/USDA). 

Peanut butter presented more of a challenge. Peanut

butter is purchased throughout the year, so we have

FSA monthly prices for the product, but peanuts are

marketed only in part of the year, so peanut prices are

generally available for the period from August through

January. We tried several approaches to handle months

outside of the marketing year. First, we dispensed with

monthly peanut price data and used average annual

(marketing year) prices for each month, but found that

they fit the data poorly. We then used monthly data, and

assigned the price for January (the last observed price)

to the remaining months before a new marketing year.

Finally, the best specification used that second

approach, but allowed the regression coefficient on the

January price to vary by month during the rest of the

year. In other words, the third approach added interaction terms between the assigned monthly price and the

month. Monthly peanut prices were also taken from the

Oil Crops Yearbook.

Specific Measures of Purchase Scale

Chapter 3 showed that FSA commodity purchases

declined sharply during the 1992-96 period. We wanted

to assess the effect of that decline, if any, on prices. To

do that, we used the PPCR30 records and calculated

monthly sums of FSA purchases; we refer to that measure as the monthly FSA volume in a commodity category.

FSA volumes are not the only volume effect worthy

of study. FSA also purchases quantities of commodities

for delivery overseas, and these vary widely from

month to month. We wanted to know whether FSA foreign purchase volumes affect domestic purchase prices.

We obtained data on monthly commodity volume in

international (PL480) auctions for flour and vegetable

oil products, and designated these as PL480 volume.

We matched PL480 volumes to the delivery months of

FSA domestic auctions, but our analysis is limited by

an important problem of timing. Our domestic volumes

measure the amount to be delivered in any month, but

the PL480 variable measures the amount that is contracted for in any monthand contracting occurs some

time before delivery. As a result, the two volume measures may not match up appropriately.

The amount of a product to be delivered to any specific

domestic location in any particular auction also varies

in the data; generally, from one to five truckloads are

up for bid for delivery to a particular location in a particular time window. We wanted to know whether these

28 /ERS-USDA Food Procurement by Farm Service Agency / AER-766
variations in auction quantity (designated in our tables

as truckloads in order) have any effect on prices, and

so we retained this variable directly from the PPCR30

records. Finally, inspection of the data reveals that there

are large and persistent product flows to some locations, but other locations receive only small and sporadic deliveries. We suspected that remote locations that

rarely received deliveries might be bid at higher prices.

To investigate that possibility, we calculated the total

number of auctions for a location in the 1992-96 period

from the PPCR30 records, and designated that variable

as total orders at location.

Measures of Product Characteristics

Each of the five commodity categories contains a variety of specific products distinguished by package size

and by product characteristics. These factors can have

important effects on costs and prices, and need to be

controlled for in analyses. All of our measures were

taken directly from the PPCR30 forms. 

We dropped some very rare commodity types and package sizes from the analysis. In addition, we dropped

some auctions with incomplete or inaccurate data, and

those with delivery destinations outside the 48 contiguous United States.

Table 6-1 lists the package sizes and

product characteristics for the products retained for each commodity category, as well as the share of each in

the commodity category auctions that

were retained for the analysis.

Numbers in parentheses are the total

number of auctions retained for analysis in each commodity category.

Measures of Competition

We used the PPCR30 forms to determine the number of bidders in each

auction. Because we thought it likely

that the effect of an additional competitor on price would depend on the

number of existing bidders, we did

not simply use the number of bidders

as an explanatory variable

(MacDonald, 1987). Instead, we

defined a series of categorical variables, each of which takes a value of

zero or one. If an auction had a single

bidder, a variable defined as one bidder would take

on a value of one, while other bidder variables would

be zero. If an auction had two bidders, the variable

two bidders would be set equal to one, and others set

to zero; similar variables were specified for each level

of competition. Tables 6-3 through 6-7 (discussed

below) summarize bidder numbers across the different

commodity groups and over time.

Seasonal and Locational Effects

FSA prices clearly vary with the location to which a

product is delivered. For example, to deliver bakery

flour to Vermont, either wheat or flour will have to be

shipped there, incurring greater transport costs than if

an order of flour were to be delivered to a client in

Kansas. To account for location, we entered separate

State effects. When State effects are entered, the coefficients on other variables show how prices vary from the

State-specific means as other variables vary from their

State-specific means; the State coefficients then show

how mean prices vary from State to State.

Similarly, FSA prices and orders show clear seasonal

variations. Because our analyses control for underlying

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 29

Table 6-1--Product characteristics and their share of commodity 

category auctions

Commodity & Auction Commodity & Auction

characteristic1 share characteristic share

Percent Percent

All-purpose flour (5,727) Bakery flour (1,712)

5-lb. bag 34.47 50-lb. bag 9.58

10-lb. bag 46.20 100-lb. bag 13.64

50-lb. bag 19.20 Bulk 76.78

100-lb. bag 0.13 Unbleached 33.85

Unbleached 1.83 Bleached 66.15

Bleached 98.17 Hearth 13.30

Pasta (4,781) Shortening & vegetable oil (7,153)

Spaghetti, 2-lb. box 12.38 Shortening, 3-lb. can 24.60

Spaghetti, 20-lb. carton 25.37 Shortening, 50-lb. cube 3.86

Macaroni, 1-lb. box 17.71 Shortening, 1-gal. can 11.17

Macaroni, 20-lb. carton 24.05 Vegetable oil, 48 oz. bottle 1.54

Rotini, 20-lb. carton 20.49 Vegetable oil, Bulk 7.95

Vegetable oil, 1-gal. bottle 50.88

Peanut butter (5,243)

Smooth, 2-lb. can 66.53

Smooth, # 10 can 33.28 

Reduced fat, smooth, # 10 0.19

1Numbers in parentheses are the total number of auctions analyzed in each 

commodity category.
30 /ERS-USDA Food Procurement by Farm Service Agency / AER-766

Table 6-2--Monthly variation in FSA auctions,

by commodity category 

Monthly share of auctions,

by commodity category

All

Delivery purpose Bakery Vegetable Peanut

month flour flour Pasta oil butter

Percent

January 7.75 17.32 11.92 11.46 11.12 

February 15.19 15.32 9.13 9.65 9.46 

March 10.84 12.11 7.34 5.11 8.18 

April 7.62 13.05 5.69 5.11 7.74 

May 6.46 8.87 5.96 3.12 7.84 

June 8.01 8.02 5.56 4.49 7.13 

July 8.89 1.41 9.12 6.77 8.70 

August 13.02 1.80 11.61 13.92 10.65 

September 9.16 8.26 14.26 13.34 10.19 

October 3.17 4.96 6.53 9.01 4.88 

November 4.13 4.41 6.44 11.01 7.15 

December 5.76 4.47 6.44 7.01 6.96 

Table 6-3: All-purpose flour auctions, 

volume and bidders

1992 1993 1994 1995 1996

Tons 

Volume 85,772 35,273 21,600 27,130 17,950

Number

Auctions 2,518 1,087 742 809 561

Percent of annual volume

Number of 

bidders 

1 1.3 15.6 1.4 13.2 3.7 

2 9.8 20.9 28.7 25.6 14.9 

3 15.3 33.6 33.4 26.3 25.3 

4 20.6 13.6 21.7 22.5 33.8 

5 24.7 8.1 5.9 11.0 20.0 

6 16.7 5.1 8.9 1.4 1.7 

7 or more 11.4 3.1 0.0 0.1 0.6 

Table 6-4: Bakery flour auctions, volume and bidders

1992 1993 1994 1995 1996

Tons

Volume 35,434 12,735 11,814 9,420 5,286

Number

Auctions 722 342 264 231 141

Percent of annual volume 

Number of 

bidders 

1 27.8 13.8 62.9 12.6 19.6

2 33.7 45.3 27.1 35.6 23.9

3 31.8 16.3 4.1 30.3 40.7

4 5.5 4.6 5.9 12.2 14.0

5 0.9 0.0 0.0 9.3 1.7

6 0.4 0.0 0.0 0.0 0.0

Table 6-5: Pasta auctions, volume and bidders

1992 1993 1994 1995 1996 

Tons

Volume 21,360 20,908 15,288 18,252 13,741

Number

Auctions 1,076 1,047 784 893 688 

Percent of annual volume

Number of 

bidders 

1 25.4 33.1 12.7 4.2 19.9 

2 35.1 26.0 28.5 26.3 39.3 

3 25.8 24.2 36.0 32.7 29.2 

4 9.2 12.4 15.6 18.3 8.4 

5 4.3 3.1 6.0 11.8 2.8 

6 or more 0.2 1.1 1.2 6.7 0.6 

Table 6-6: Vegetable oil auctions, volume and bidders

1992 1993 1994 1995 1996

Tons

Volume 44,385 43,550 40,182 23,618 20,071

Number

Auctions 1,821 1,727 1,650 1,022 857

Percent of annual volume

Number of 

bidders

1 10.3 18.6 12.8 2.2 4.2 

2 52.1 43.9 39.5 53.4 74.2 

3 23.4 26.5 38.9 31.9 17.3 

4 12.6 7.6 6.3 9.6 3.3 

5 1.5 3.1 2.3 2.7 1.0 

6 0.1 0.3 0.1 0.2 0.0 

Table 6-7: Peanut butter auctions, volume and bidders

1992 1993 1994 1995 1996 

Tons

Volume 38,200 29,917 22,621 14,121 8,877 

Number

Auctions 1,711 1,348 1,046 637 427 

Percent of annual volume

Number of 

bidders 

2 0.4 0.2 0.2 1.6 1.7 

3 9.0 6.4 0.0 0.3 0.6 

4 32.1 29.1 7.4 3.4 16.2 

5 52.7 48.9 23.5 30.4 47.1 

6 5.6 15.5 47.8 47.1 34.5 

7 0.2 0.0 21.0 17.0 0.0 
commodity prices, seasonal variation in FSA prices

reflects variations in marketing margins through the

year. To control for the phenomenon, we enter separate

variables for each month in our analysis. Table 6-2

shows how orders vary by month for each commodity

category. With 12 months, an average month ought to

handle about 8.3 percent of a categorys auctions. 

Some Basic Data Patterns

Volume and Competition

Tables 6-3 through 6-7 provide summary information

on commodity volumes and bidder numbers for each

commodity by year. Consider, for example, all-purpose

flour, in table 6-3.

Awards totaling 85,772 tons (just under 4,000 truckloads) were put up for auction in 1992 in 2,518 auctions. In that year, 1.3 percent of that volume (or about

1,115 tons) was offered in auctions that attracted only a

single bidder, while another 9.8 percent was offered in

auctions that attracted two bidders. In that year, it was

far more typical for all-purpose flour auctions to attract

four (20.6 percent of volume) or five (24.7 percent of

volume) bidders. 

Volumes dropped by nearly 80 percent over the next 4

years, as CCC stocks fell. There was also a clear shift

in bidder numbers; most auctions in 1993-95 attracted

three or fewer bidders, in contrast to the generally

greater participation in 1992 auctions. But bidder numbers rose again at the end of the period, in 1996, as

more auctions attracted four and five bidders.

The other four commodity groups show similar trends

in purchase volumes. Bakery flour and peanut butter

each showed 1992-96 declines of more than 75 percent

in volume and number of auctions, while vegetable oil

fell by more than half and pasta by more than a third.

Typical bidder numbers vary across commodity groups

and over time. Bakery flour and vegetable oil auctions

typically attract relatively few bidders. Until 1994,

more than half of all bakery flour auctions attracted

only one or two bidders, while that same pattern held in

all years for vegetable oil. By contrast, more than half

of all pasta auctions attracted at least three bidders after

1992, and peanut butter auctions rarely attracted fewer

than four bidders.

Price Trends

Table 6-8 displays broad trends in average FSA prices

across the five commodity groups during the 1992-96

period. Prices are not comparable across commodities

because they are quoted in different units (dollars per

hundredweight, cents per gallon), but they show some

interesting temporal patterns. The three wheat-based

commodities show sharp increases over time, about

18-25 percent between 1992 and 1996. Low bids in

vegetable oil auctions rose by about one-third between

1992 and 1994, before dropping off somewhat in the

next 2 years, while peanut butter bids fell (15 percent)

between 1992 and 1995 before rising in 1996.

The trends in low bids could reflect the effects of

changes in competition, the geographic distribution of

auctions, or the mix of products and package sizes purchased, but those factors really have only very minor

effects on the broad trends. The major factor driving

broad temporal movements in FSA prices is underlying

agricultural commodity prices: wheat prices rose

sharply through the period, soybean and cottonseed oil

prices rose and then fell somewhat, and peanut prices

generally fell.

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 31

Table 6-8: Price trends in FSA auctions

Commodity 1992 1993 1994 1995 1996

group

Mean low bids in FSA auctions 

(dollars)

All-purpose flour 13.08 12.27 13.35 15.08 16.60

Bakery flour 12.27 12.50 14.02 14.81 16.81

Pasta 27.46 26.27 29.77 30.36 32.24

Vegetable oil 32.27 36.64 42.59 42.21 39.50

Peanut butter 83.07 78.07 74.62 70.93 78.82

Mean ratio of low bid to 

FSA constructed price

All-purpose flour .812 .803 .815 .833 .859

Bakery flour .859 .861 .867 .881 .897

Pasta .892 .891 .902 .898 .913

Vegetable oil .760 .783 .823 .808 .762

Peanut butter .895 .886 .881 .876 .888

Mean ratio of low bid to 

second lowest bid

All-purpose flour .963 .947 .935 .939 .955

Bakery flour .947 .945 .929 .936 .946

Pasta .937 .942 .953 .947 .956

Vegetable oil .974 .978 .972 .977 .975

Peanut butter .985 .981 .982 .976 .978
FSA develops a constructed price for comparison

purposes for each auction. The constructed price is used

as a forecast tool to develop expectations about likely

bid ranges, and it can also be used as a decision tool in

that FSA may cancel auctions in which the low bid

exceeds the constructed price. The middle panel in table

6-8 shows annual average ratios of low bids to constructed prices. Two factors stand out. First, the ratios

clearly vary systematically, and by quite a bit, across

commodity categories. Pasta ratios are always the highest, around 0.90, while vegetable oil ratios are generally

the lowest, around 0.80. Second, the ratios seem to

move up, sometimes sharply, as commodity prices rise.

That pattern raises the question of whether FSA properly accounts for the effects of changes in agricultural

prices when calculating constructed prices; there is

some evidence in this pattern that the agency underestimates the sensitivity of bid prices to agricultural prices.

Finally, the bottom panel reports average ratios of low

bids to the second lowest bid in FSA auctions (clearly,

this ratio can only be calculated when there are at least

two bidders). That ratio shows no particular time pattern, suggesting that all bids rise in unison as agricultural prices rise. They also show some distinctive difference across commodity groups. Peanut butter low

bidders beat the number two bidder by only about 2

percent, for example, while, on average, low bidders in

pasta are 5-7 percent below the second lowest bidder. 

32 /ERS-USDA Food Procurement by Farm Service Agency / AER-766
Introduction

The statistical analysis aimed to answer the following

questions:

◆ How do variations in related agricultural commodity

prices affect FSA bids?

◆ Are FSA bid prices affected by declining FSA auction volumes?

◆ Do PL480 (international) shipments affect FSA

domestic bids?

◆ Do FSA bid prices vary with requested package

sizes? By how much?

◆ Do other product characteristics affect bid prices? By

how much?

◆ Do bid prices show important seasonal variations?

◆ How important are transport costs?

◆ Do changes in the number of bidders affect FSA bid

prices? By how much?

◆ What factors drive changes in bidder numbers?

The first question, the relationship of agricultural commodity prices to FSA bid prices, relates to FSAs ability

to predict likely bid prices and to agency decisions to

cancel auctions when prices are unacceptably high. For

most commodities, changes in related agricultural commodities are the most important factor driving temporal

changes in FSA bid prices, and many agricultural commodity prices fluctuate sharply through time. The

analysis aims to identify typical responses of FSA bids

to changes in commodity prices; with that information,

FSA should be better able to identify those cases in

which bid prices are unusually high.

The other questions relate to issues that FSA has some

influence over. There have been fairly large changes

over time in FSA monthly purchase volumes for both

domestic and foreign (PL480) programs. In principle,

if monthly volumes had a large effect on prices, FSA

could consider altering purchase strategies in an attempt

to reach volumes associated with the lowest prices. If

the data were to show strong seasonal effects, FSA

could move to shift the temporal pattern of purchases to

low-priced months. Either decision would impose storage and transactions costs on clients, such as school

lunch programs; the information from the analyses

could help clients decide whether the price gains from

volume shifting were large enough to offset any added

costs.

Similarly, clients purchase a variety of specific products

(for example, pasta can be spaghetti, macaroni, or rotini) in a variety of package sizes. Statistical information

on the price effects of these choices can guide clients in

making better decisions. 

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 33

CHAPTER 7

STATISTICAL ANALYSIS OF BID PRICES

FOR FIVE FSA COMMODITIES
Over time, the typical number of bidders in FSA auctions has generally declined; moreover, during any

given year, there are often large variations in the number of bidders participating in different auctions. Our

analysis attempts to identify the effect of the number of

bidders on prices, and to identify the factors affecting

variations in the number of bidders. Information on the

issues can help FSA to better identify those commodities, locations, and periods in which actions to increase

competition would be most effective. 

Methods

ERS investigated the above issues with regression

analyses of FSA bid prices. Most regressions focused

on the low bids in FSA auctions, although some analyzed all bids. The regression analyses aim to estimate

the effect of variations in particular variables (for

example, the number of bidders) on FSA bid prices,

while controlling for other variables. For example, suppose that, on average, low bids in FSA auctions were

higher in those auctions in which only a single bidder

participated. That pattern could appear because of a

lack of competition, but it could also appear if singlebidder auctions were more likely in auctions for delivery to high-cost, remote locations, or if single-bidder

auctions were more likely during periods of high agricultural commodity prices. In regression analyses, we

try to control for those other factors so we can more

precisely identify the reasons for observed statistical

relations. In other words, our analyses are designed to

ask whether prices are higher in single-bidder auctions

for given levels of agricultural prices and transport

costs.

Regression analyses can be flexible in the sense that we

can use them to see whether effects are linear or nonlinear. For example, it is reasonable to think that adding

an extra bidder in a market with a single bidder might

have a bigger effect on prices than adding another bidder in a market that already has six bidders; in short,

the effect of adding a bidder varies with the number of

bidders. Our analyses are designed to assess alternative

specifications of how one variable might affect another.

No analysis is perfect. We will not be able to control

for all possible factors that affect bid prices, and we

will not be able to test among all possible (or even likely) ways in which the variables affect price. But we can

provide a substantial amount of useful information.

This chapter summarizes the key findings. Data sources

and variable definitions were summarized in chapter 6.

Summary of Results from the 

Regression Analysis

We summarize the key findings below. Our discussion

is organized around groupings of key related variables,

and we attempt to emphasize the size of our reported

effects and their implications in our discussions. Exact

regression results, which contain a large number of separate coefficients and associated statistical tests, are

reported in appendix B. 

Linkages Between FSA Prices and 

Agricultural Commodity Prices

FSA purchases basic products that are closely linked to

agricultural commodities. Some agricultural commodities display wide price swings through time, and these

swings can have strong impacts on FSA product prices.

Our statistical analysis allows us to identify the effects

of agricultural commodity price changes on FSA bid

prices. For this analysis, and those that follow, we

regressed low bids in FSA auctions on the average

delivery month spot price of the agricultural product, as

well as the change in the agricultural price for 1 month

back and 1 month forward. Other controls included

product characteristics, the number of bidders, measures of auction volume, fixed monthly effects, and

fixed State effects. Table 7-1 shows the results.

We list the related agricultural commodity for each of

our five FSA products. The list is not exhaustive; for

example, all-purpose flour uses wheats other than No. 2

soft white, but that price series gave the best fit to our

data. In vegetable oil, two price series, for cottonseed

oil and for soybean oil, gave the best statistical fit to

the data when they were both used.

We represent the effect of agricultural price changes in

two ways. First, we show the estimated effect on FSA

prices of 10-percent increases in agricultural prices. The

two flour products (bakery and all-purpose) show the

strongest responses, 7.0 percent and 7.9 percent. By

contrast, pasta prices are noticeably less responsive to

wheat price changes, with a 3.4-percent increase in

pasta prices following a 10-percent increase in durum

wheat prices. Pasta requires more processing than flour,

with the result that durum wheat is a smaller part of

total pasta costs; hence wheat price changes have weaker effects on pasta prices than on flour prices.

34 /ERS-USDA Food Procurement by Farm Service Agency / AER-766
The evaluation performed above asked how FSA product prices changed in response to uniform 10-percent

increases in agricultural commodity prices. But some

agricultural commodity prices fluctuate widely, while

others do not. The final column looks at agricultural

price effects in another way. It shows the estimated

change in FSA product prices in response to a typical

large change in an agricultural commoditys price. 

Here, typical is defined as a two-standard-deviation

change in price. If prices are normally distributed, then

roughly 95 percent of observed prices will fall within

two standard deviations of the mean price (that is, from

two standard deviations above the mean to two standard

deviations below). The calculated standard deviation

will be quite small if prices in the sample show little

variation, and it will be large in samples in which prices

vary widely. In our analysis, typical large price

changes have very little effect on peanut butter prices

because peanut prices varied very little in 1992-96. By

contrast, flour prices can easily vary by 20 percent in

response to typical wheat price changes because wheat

prices show some substantial variation and because

flour prices are quite sensitive to wheat price changes.

The price effects in these models should be thought of

as longrun effects; for example, they show how flour

prices change in response to a 10-percent increase in

wheat prices over those observed 1 year earlier. The

models also show that FSA bid prices do not respond

nearly as strongly to shortrun month-to-month fluctuations in agricultural commodity prices. In general, if

agricultural commodity prices were to rise by 10 percent in a month, the resulting FSA bid prices could be

expected to rise by about one-fifth as much as the numbers shown in table 7-1 (bakery flour bid prices would

rise by 1.4 percent instead of 7 percent). 

The longrun effects for wheat-based products are larger

than one would expect to see for normal commercial

distribution. As a first approximation, if an agricultural

commodity price rose by 10 percent, we would normally expect manufacturer product prices to rise by an

amount directly proportional to the share of the commodity in manufacturer costs. For example, U.S.

Census Bureau data show that wheat accounts for 59

percent of flour mill costs; we would, therefore, expect

flour prices to increase by 5.9 percent, following a 10-

percent increase in wheat prices. But table 7-1 shows

that FSA flour prices were more sensitive to wheat

prices, with all-purpose flour rising by 7.9 percent and

bakery flour by 7.0 percent. Following the same reasoning, Census data suggest that pasta prices should rise by

1.9 percent (wheat accounts for 19 percent of pasta

costs), but FSA pasta prices rose by 3.4 percent in

response to a 10-percent increase in wheat prices.

Similarly, FSA peanut butter prices rise by 5.5 percent

for each 10-percent increase in peanut prices, whereas

Census data suggest that commercial prices would rise

by about 3.5 percent. Only in vegetable oil were FSA

prices in line with expectations: Census data suggest

that vegetable oil prices should rise by 4.7 percent in

response to a 10-percent increase in underlying agricultural commodity prices, while FSA prices rose by 4.0

percent.

The results imply that some FSA prices may be more

sensitive to changes in agricultural commodity prices

than commercial products are, an issue explored further

in chapter 8, where we compare trends in FSA prices to

trends in average manufacturer and retailer prices for

similar products. This sensitivity is not undesirable,

since it can come about if FSA is getting highly competitive prices for the products that it buys. In that case,

agricultural commodity costs could be larger shares of

FSA product costs than of commercial product costs. 

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 35

Table 7-1: Projected effect of changes in agricultural commodity prices on FSA product prices

Effect on FSA price of Effect on FSA price of

FSA commodity Related agricultural commodity 10 percent increase typical increase in 

agricultural price agricultural price

Percent

All-purpose flour No. 2 soft white winter 7.9 21 

Bakery flour No. 1 hard red winter wheat 7.0 19 

Pasta Durum wheat 3.4 16 

Vegetable oil Cottonseed & soybean oil 4.0 16 

Peanut butter Peanuts 5.3 5 

Notes: The measures are derived from regressions of low bids on agricultural commodity prices, volume, product characteristics,

measures of competition, seasonality terms, and fixed State effects. The typical increase in an agricultural price is a two-standard-deviation change in price.
Effects of Geographic Location 

on FSA Bid Prices

The FSA data clearly show that bid prices vary with the

location to which the product is to be delivered. We

identified the locational pattern of prices by entering

separate variables representing each State into our

regression analysis. The resulting estimates show how

average bid prices vary across States, given product and

packaging characteristics, seasonality controls, auction

volumes, agricultural commodity prices, and levels of

competition. Table 7-2 provides a summary of the

results, by listing, for each of the five FSA products,

the lowest price State, the highest price State, and the

estimated price gap between the two.

Locational effects largely reflect transportation costs.

The lowest price States are the States where production

of the FSA product and the related agricultural commodity are concentratedKansas for flour and wheat,

Minnesota for pasta and durum wheat, Georgia for

peanuts and peanut butter, and Iowa for soybeans and

salad oil. Very little transportation is required to deliver

bakery flour to Kansas or peanut butter to Georgia.

State effects increase as one moves away from production centers and incurs transport costs for the agricultural commodity, for the FSA product, or both. For flour,

pasta, and peanut butter, prices are highest in New

England and in the Middle Atlantic States.

Transportation costs are important parts of the final cost

of the product for some locations and some commodities. For example, table 7-2 shows that prices for delivery of all-purpose flour to Maine are 31.1 percent higher, on average, than prices for delivery to Kansas.

Other New England States face prices only slightly

lower than Maine, and Middle Atlantic States (New

Jersey, for example) see prices that are a little over 20

percent higher than Kansas prices. For distant locations

like Maine, transport costs will account for over 20 percent of the delivered price of flour, while transport

costs will account for less than 5 percent in Plains and

Western Corn Belt States.

Transport costs are also less important for more highly

processed products, like pasta and peanut butter. Prices

rise for each product as one moves away from production centers, but prices for delivery of pasta to New

England are only 12.7 percent higher than Minnesota

prices because transport costs are a smaller share of the

total for this product that has a higher value per hundredweight than flour. 

Seasonality Effects

Each FSA product displays persistent seasonal movements in bid prices. These movements are analyzed in a

model that already controls for agricultural commodity

prices, so the seasonal effects capture movements in

margins (the gap between product prices and agricultural commodity prices). The model includes separate

variables for each month, and the results should be

interpreted as showing differences in average prices

across months, once one controls for agricultural commodity prices, product and packaging characteristics,

measures of competition, and location and volume

effects. Table 7-3 presents summary data on the monthly averages.

Flour and pasta products show persistent and fairly

strong monthly effects. In each case, monthly peaks

occur for products to be delivered in September, with

36 /ERS-USDA Food Procurement by Farm Service Agency / AER-766

Table 7-2: Effects of geographic location on FSA

commodity prices

FSA commodity Low-price High-price Price

State State gap 

Percent 

of low

All-purpose flour Kansas Maine 31.1 

Bakery flour Kansas West Virginia 35.4 

Pasta Minnesota New Hampshire 12.7 

Vegetable oil Iowa Nevada 9.4 

Peanut butter Georgia Rhode Island 7.5 

Notes. The results are derived from the fixed State effects in

the low bids regression, and measure the difference between

the highest and lowest State effect.

Table 7-3: Effects of seasonality on FSA commodity

margins

FSA commodity Low month High month Price

gap

Percent 

of low 

All-purpose flour August September 6.2 

Bakery flour July September 14.7 

Pasta June September 8.7 

Vegetable oil September February 7.6 

Peanut butter May December 3.9

Notes: The measures are derived from the fixed monthly

effects in low bids regressions, and report the difference

between the high and low months.
monthly troughs occurring just 1 to 3 months earlier.

For both pasta and all-purpose flour, schools purchase

disproportionate amounts for delivery in September

14 percent of pasta auctions and 9 percent of all-purpose flour auctions are for September delivery. This is

particularly interesting because data presented in chapter 8 suggest that FSA prices are closest to commercial

flour prices in Septemberthat is by far the least favorable month for FSA to buy flour. The results indicate

that schools contemplating peak-period purchases could

save 6-9 percent on the purchase price, and possibly

more compared with commercial prices, by shifting

purchases to an earlier month. To decide if that strategy makes sense, buyers would have to weigh the purchase price savings against storage costs and risks of

product deterioration.

The seasonal movements most likely reflect changes in

capacity utilization at mills. For example, retail demand

for flour increases sharply in the fall, leading to

increases in capacity utilization at flour mills. Mills

operating at full capacity are less likely to bid on

USDA purchases, and when they do bid, they are likely

to bid high. By contrast, mills operating with excess

capacity are likely to bid more aggressively for USDA

production because winning a bid will not lead to the

displacement of other production.

How FSA Bids Vary with Product

Characteristics

The five FSA commodities analyzed in this section can

be purchased in a variety of different package sizes and

in several specific product types. Bid prices vary systematically with these product types, and table 7-4 summarizes the average effects on bid prices.

In the statistical analysis, one specific product is chosen

as the base size and product type, and prices for other

sizes and product types are expressed as percentage

deviations from the base price. We used a common

product as the base in each FSA commodity category

5-pound bags of unbleached all-purpose flour,

unbleached bakery flour delivered in bulk, spaghetti in

1-pound boxes, vegetable oil in 1-gallon bottles, and

smooth peanut butter in 12-ounce cans.

The results are in line with what one might expect. The

price per hundredweight falls as products are shipped in

larger package sizes, although the magnitude of the

package size effect varies across commodity categories. In all-purpose flour,

for example, prices fall by a little over

5 percent as one moves from 5-pound

to 100-pound bags. Prices fall more in

moving from 50- and 100-pound bags

in bakery flour to bulk shipment (13

and 10 percent, respectively).

Package size effects in vegetable oil

are quite large; prices rise by 34 percent as one moves to a 48-ounce container from a 128-ounce (1-gallon)

container, and falls by 22 percent if

one moves to bulk delivery from the

128-ounce container.

Product characteristics also matter.

Macaroni and rotini cost about 10 percent more than spaghetti, while

reduced-fat peanut butter, introduced

in small samples near the end of the

period, carries a price premium of

nearly 40 percent over regular peanut

butter.

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 37

Table 7-4: Effect of product characteristics on FSA prices

FSA commodity & base Alternate

product characteristics product characteristics Price effect

Percent of base

All-purpose flour 10-lb. bag -1.8

Base: 5-lb. bag, unbleached 50-lb. bag -4.6

100-lb. bag -5.6

Bleached, 5-lb. bag +1.9

Bakery flour 50-lb. bag +13.0

Base: unbleached, bulk 100-lb. bag +9.8

Bleached, bulk -1.4

Hearth, bulk, unbleached +8.2

Pasta Spaghetti, 2-lb. box +4.0

Base: Spaghetti, 20-lb. box Macaroni, 1-lb. box +9.7

Macaroni, 20-lb. carton +1.3

Rotini, 20-lb. carton +8.1

Vegetable oil Shtng/hydrog veg oil, 3-lb. can +19.8

Base: veg oil, 1-gal. bottle Shtng/hydrog veg oil, 50-lb. can -2.0

Shtng/hydrog veg oil, 1-gal. +4.9

Veg oil, 48-oz. container +34.2

Veg oil, bulk -22.3

Peanut butter Smooth, # 10 can -1.2

Base: Smooth, 2-lb. can Smooth, reduced fat, # 10 can +38.5
Purchase Volumes and FSA Prices

Monthly volumes of FSA commodity purchases

declined sharply during the 1992-96 period. We wanted

to assess the effect of that decline, if any, on prices. But

that is not the only volume effect worthy of study in

the dataset. FSA also purchases quantities of commodities for delivery overseas, and these monthly PL480

commodity volumes vary widely from month to month.

We wanted to know if FSA foreign purchase volumes

affected domestic purchase prices. In addition, the

amount of product to be delivered to any specific

domestic location in any particular auction also varies

in the data; generally, one to five truckloads are up for

bid for delivery to a particular location in a particular

time window. We wanted to know if these variations in

auction quantity had any effect on prices. Finally,

inspection of the data reveals that there are large and

persistent flows of product to some locations, but other

locations receive only small and sporadic deliveries. We

wanted to know if the total number of auctions for a

location in the 1992-96 period had an effect on prices.

That is, we suspected that remote locations that rarely

received deliveries might be bid at higher prices. Table

7-5 summarizes the results of the statistical analysis of

the effect of volume.

In general, auction quantities had small negative effects

on price: moving from small (single-truckload) quantities to two- and three-truckload quantities would reduce

bid prices by 0.5 percent to 1 percent in bakery flour,

pasta, and vegetable oil, but had no discernible effects

in all-purpose flour and peanut butter. Technically, that

the coefficients on auction quantity in the all-purpose

flour and peanut butter regressions were not significantly different from zero, and, with very large sample

sizes, this means that the estimated coefficients were

also very small. The other three regressions had statistically significant, negative coefficients, and the reported

effects are the change in price attendant upon a twostandard-deviation change in quantity (see our earlier

discussion of agricultural commodity price effects for

why we use two-standard-deviation changes, and what

they are).

Location volumes also mattered in that locations that

regularly received deliveries generated bid prices that

were between 0.5 percent and 1.5 percent lower than

locations that rarely received deliveries. The effect,

while small, appeared for four of the five FSA commodities; all-purpose flour was again an exception.

Three commodities are also shipped overseas as part of

FSAs PL480 purchasesall-purpose and bread flour

(we used all PL480 purchases of wheat flour), as well

as vegetable oil. Mean monthly domestic purchases

were close to mean monthly PL480 purchases, and the

estimated coefficients of domestic and PL480 purchases

were almost identical in each regression; that is, what

appears to matter for prices is the total monthly volume

38 /ERS-USDA Food Procurement by Farm Service Agency / AER-766

Table 7-5: Effects of purchase volumes on FSA prices

Volume measures 

FSA commodity Auction quantity Total auctions Monthly FSA commodity Monthly PL480 commodity

at location volume volume

All-purpose flour No effect No effect U-shaped, small U-shaped, zero 

(1.5 percent) negative effect at mean 

effect at mean 

Bakery flour Small (0.5 percent) Small (1.5 percent) U-shaped, modest U-shaped, modest 

negative effect negative effect (2.5 percent) & (3.5 percent) and

negative at mean negative at mean 

Pasta Small (0.5 percent) Small (0.5 percent) Large (6 percent) n.a.

negative effect negative effect negative effect 

Vegetable oil Small (1 percent) Small (1 percent) U-shaped, zero at U-shaped, zero at

negative effect negative effect means, negative at means, negative at 

small volumes small volumes 

Peanut butter No effect Small (1 percent) Large (7 percent) n.a.

negative effect positive effect 

Note: n.a. means not applicable.
of USDA purchases, and not whether those purchases

are foreign or domestic. In one sense though, PL480

purchases are more important: the standard deviation of

PL480 volume is triple that of domestic volumes. That

is, there is a lot more month-to-month variation in

PL480 purchases, primarily because there are many

months with low PL480 purchases.

The estimated effects of monthly purchase volume

appear to be complicated, but the complicated effect is

statistically quite significant, and the same pattern

shows up in all three FSA commodities (therefore, there

is good reason to believe that the complicated pattern is

true and not some statistical artifact). The complicated

effect is that the pattern is U-shaped. That is, at low

volumes of USDA purchases, increasing the volume of

purchases will lead to lower bid prices. At high volumes (for example, when USDA is already purchasing

large volumes through PL480), increases in domestic

purchase volumes will lead to higher prices. The effects

are not particularly large (in the range of 1-4 percent,

depending on volumes). At sample means, the effects of

changes in volume are close to zero.

Our analysis is limited by one important problem of

timing. Our domestic volumes measure the amount to

be delivered in any month. But the PL480 variable

measures the amount that is contracted for in any

month, and contracting occurs some time before delivery. As a result, the two volume measures may not

match up appropriately. We experimented with different

ways of handling the problem, but the estimation

results were unchanged.

Two commodities, pasta and peanut butter, do not have

corresponding PL480 purchase volume. In each, monthly volume has large effects, but of opposite sign.

Typical increases in pasta volumes are associated with

6-percent declines in pasta prices, while

typical increases in peanut butter volume

are associated with 7-percent increases in

peanut butter prices. We suspected that

these results might have been spurious,

picking up trends in the data that were

otherwise unaccounted for, but the estimated volume effects did not change

when we took steps to account for time

trends.

Effect of Competition on Bid Prices

The number of bidders varies across FSA auctions.

Some commodities, like peanut butter, almost always

have at least three firms bidding, and usually get four,

five, or six. In bakery flour, pasta, and vegetable oil,

auctions more typically attract only one or two bidders

(chapter 6). Competition varies sharply over time, as

well, in all five commodity groups. For example, in

1994, only 1 in 10 bakery flour auctions had more than

2 bidders, while half of the 1995 bakery flour auctions

attracted more than 2 bidders (chapter 6).

Competition, as measured by the number of bidders,

can affect the value of an auctions low bid in two

ways. First, there could be a direct effect on bidder

decisions: they may decide to offer lower bid prices in

auctions with more bidders participating so as to

improve their chances of winning. Second, there could

be an indirect, or selection, effect on the low bid,

even if individual bidders do not change their bidding

strategies in the face of more competition. With more

bidders, there is a greater likelihood that someone with

low costs (due perhaps to excess capacity) will participate, generating a lower low-bid price.

We can assess each of these effects with the FSA data

that we have at hand. That is, we can see if the number

of bidders affects the value of the low bid in FSA auctions by analyzing a dataset consisting of the low bids

in each auction. Second, we can see whether competition has a direct effect on bidder strategies by using a

dataset consisting of all bids, and testing to see whether

bidders changed their bids in response to changes in the

number of competitors.

Competition has important effects on FSA commodity

prices (table 7-6). First, consider the analysis of low

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 39

Table 7-6: Effects of competition on FSA prices

Low bids All bids 

FSA Range of Single-bidder Range of Single-bidder

commodity price effect effect price effect effect

Percent

All-purpose flour 11.4 7.2 4.0 3.6

Bakery flour 8.0 5.6 9.1 6.1

Pasta 10.9 3.9 0 (not sig.) 0 (not sig.)

Vegetable oil 8.6 5.3 11.2 7.9

Peanut butter 4.6 n.a. 6.9 n.a.

Note: not sig. means not significantly different from zero in statistical tests.

n.a. means not applicable.
bids. In the first row, the range of price effect for allpurpose flour is reported to be 11.4 percent. The statistic means that, on average, low bids in all-purpose flour

auctions with a single bidder are 11.4 percent higher

than low bids in all-purpose flour auctions with the

maximum number of bidders specified in the model,

which in all-purpose flour is seven. The estimated single-bidder effect in all-purpose flour is 7.2 percent;

that is, low bids rose by 7.2 percent as the number of

bidders falls from two bidders to one. Combined, those

two statistics suggest that some competition matters a

lot: most of the effect of reducing the number of bidders (7.2 of 11.4 percent) occurs as we move between

two bidders and one, while the effect of moving from

seven to two is much smaller (4.2 percent). 

Results in the other four FSA commodity groups are

similar. As the number of bidders goes from two to one,

low bids rose by 5.6 percent and 5.3 percent in bakery

flour and vegetable oil, respectively. As the number of

bidders goes from five (the maximum in each) to two,

low bids rose modestly, by 2.4 percent and 3.3 percent

respectively. Peanut butter had no single-bidder auctions: there, low bids rose (by 4.6 percent) as the number of bidders fell from six to two. Pasta shows some

distinction in that prices rose more sharply (by 7 percent) as the number of bidders fell to two from five.

Pasta low bids increased again, by 3.9 percent, as the

number of bidders fell from two to one.

The results thus far suggest that changes in bidder numbers matter, but that such changes generally matter

most where there are a small number of bidders. That

is, the number of bidders affects auction prices most

when there are only two or three bidders to begin with;

when there are four or five bidders, auction prices are

affected less by the number of bidders. 

The results reported so far are based on an analysis of

the low bids in each auction. We can try to gain additional information with an analysis of all bids in FSA

auctions (sample sizes in the all-bids analyses are three

to four times larger than in the low-bids analysis).

Consider the all-purpose flour results first. When there

is a single bidder, that bidder typically bids a price 3.6

percent higher than the bidder would bid in a situation

that was identical except for the presence of two bidders. In other words, bidders do appear to change their

strategies in response to changes in the number of bidders, but the effect is small; selection appears to dominate changes in bidder behavior.

The results in pasta provide stronger support for selection. There, the number of bids has no significant effect

on bidder behavior (a bidder does not change a bid as

the number of bidders changes). But low bids are substantially lower when there are many bidders. Taken

together, the two results suggest that selection effects

account entirely for the effects of competition on low

bids in pasta. 

Results differ in the other three FSA commodities. In

bakery flour, vegetable oil, and peanut butter, bidders

reduce their bids as the number of bidders rises, and the

effects are larger than in the low bids dataset. Selection

does not appear to be a driving force here, and the

direct effects of competition matter most.

The effects of competition appear to be quite robust

because of the regression specification that we use. In

early models with few other controls, bid prices

appeared to be higher where there were few bidders.

We were concerned that the observed effects might be

spurious. Specifically, we were concerned that remote

locations that were more costly to serve might attract

few bidders and might also generate high bid prices

because they were costly to serve. But the final model

reported here has an extensive set of controls, including

the State that the product is to be delivered to, the flow

of product to specific locations, and the characteristics

of the items being auctioned. Holding all those constant, the results still show the number of bidders to

have strong effects on bid prices.

Tables 6-3 through 6-7 show that competition appears

to vary sharply over time, while table 7-6 shows that

competition strongly affects bid prices. What factors

drive the extent of competition? We have not been able

to perform a complete analysis, but several factors

stand out. Product volumes only modestly affect the

number of bidders. As changes in national policy

reduced CCC stocks, tables 6-3 through 6-7 show that

FSA product volumes fell dramatically for each commodity between 1992 and 1996, by amounts ranging

from 36 percent of 1992 pasta volume to 85 percent for

bakery flour. Bidder numbers showed no such steady

decline, but rather a mixed pattern of increases and

decreases.

In interviews, some vendors stressed the importance of

capacity utilization in manufacturing plants. They

argued that, during periods of low utilization, vendors

are more likely to bid on USDA products, and are more

40 /ERS-USDA Food Procurement by Farm Service Agency / AER-766
likely to bid aggressively. They asserted that this was

because USDA auction procedures generated competitive prices and, therefore, relatively low margins for

vendors; they would, therefore, only aim to win auctions when USDA production was unlikely to replace

other, high-margin, business. The data offer some support for this hypothesis. For example, in flour mills,

capacity utilization peaks in the late summer and fall

(August through November, for delivery to FSA clients

in September through December). Those 4 months

account for a roughly proportional share (34.7 percent)

of all FSA all-purpose flour auctions but a hugely disproportionate share (84.8 percent) of the auctions that

attract only a single bidder. In short, competition has a

clear seasonal pattern, and the risks of attracting a single bidder rise sharply in the fall.

The data also show annual fluctuations in competition

that do not necessarily follow patterns of capacity utilization. Our inspection of bidding records shows considerable persistence in patterns of bidding. That is,

once a firm enters bidding, it tends to stay in, offering

bids every month from at least some plants on at least

some auctions. Similarly, once a firm drops out of bidding for USDA products, it tends to stay out, rarely

coming back in. Very few firms come in and out of bidding status. Those patterns appear to suggest that FSA

marketing of their auction programs may have had

some effects on firms decisions to participate. Further,

each commodity had sharp reductions in bidder numbers in one year during the study period (all-purpose

flour in 1993, bakery flour in 1994, pasta in 1993, vegetable oil in 1993, and peanut butter in 1992). None of

the reductions held: average bidder numbers increased

sharply in the year after the reduction for each commodity. That pattern may reflect simple market entry

(declines in bidder numbers drove up prices and profits,

thereby attracting more bidders), or it may reflect positive actions taken by FSA to attract more players. FSA

needs to review their actions here in order to identify

effective strategies. 

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 41
Introduction

We perform two types of price comparisons in this

chapter. First, we compare price levels by matching the

prices that FSA receives in auctions for several commodities with prices quoted by manufacturers to private

sector clients for closely related commodities. Second,

we compare price trends by matching changes in FSA

prices over the 1992-96 period to well-known indexes

of food price inflation for related commodities.

Comparisons of FSA Price 

Levels with Comparable 

Private Sector Prices

Method of Comparing Prices

One of our major goals was to compare the prices realized in FSA auctions with those that could be obtained

through private sector purchasing. To do that, we

solicited the cooperation of a major foodservice wholesaler. Foodservice firms take deliveries to their own

warehouses from food manufacturers, and provide food

products and support services to restaurant and fast

food chains, schools, commercial kitchens, hospitals,

and other large providers. Such firms operate as prime

vendors in the VA and DoD food procurement systems.

Foodservice warehouses are the appropriate point of

price comparison for FSA because the firms order large

volumes of products from manufacturers, take delivery

in truckload lots, and are located at the same level of

the distribution chain as the State and commercial

warehouses that receive FSA commodities.

The cooperating firm provided us with data on 1996

manufacturer prices for delivery to the firms warehouses. We asked the firm to provide price data for their

highest quality private-label product because we felt

that was most comparable with USDA products. In

some cases, we received branded product prices rather

than private-label, and we note those cases in our discussion. We strove to compare identical package sizes

and product characteristics, but at times, had to compare closely related (rather than identical) products; we

define product characteristics, and any adjustments that

we made, in the discussion below.

Some FSA product prices can vary sharply by geographic region. Consequently, we asked for prices for

delivery to several different States served by the foodservice firmCalifornia, Texas, Illinois, and

Massachusetts. Because FSA prices show some seasonal variability, we also asked for two time periods

April and September 1996. 

The cooperating foodservice firm was able to provide

us only with September data for peanut butter and

pasta, and only on a nationwide price quote. We therefore compared those prices to nationwide average FSA

prices for September 1996. In addition, FSA data show

few 1996 auctions for delivery to two of the cooperators States, Illinois and Massachusetts, so we used

mean FSA prices for points in Illinois, Indiana, and

Wisconsin for comparison with foodservice prices in

the firms Illinois district. We also used mean FSA

prices for delivery throughout New England for comparison to the Massachusetts District. FSA prices vary

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 43

CHAPTER 8

COMPARING FSA TO COMMERCIAL PRICES
little (1-2 percent) within each region, and FSA mean

prices, therefore, are not driven by any unusual price

quotes from remote locations. 

Results of Price Comparisons

Table 8-1 reports the results of our price comparisons.

In general, FSA prices were substantially below those

reported by the private sector firm, with a gap of about

30 percent being most common. We discuss each commodity in turn; we discuss flour last, since it presents a

more complicated pattern.

Liquid Shortening and Vegetable Oil. We obtained private-sector prices for truckload delivery in cases containing six 1-gallon containers, and compared them

with FSA auction prices for identical package sizes. We

had only limited FSA California data (for September

delivery of vegetable oil), but could perform price comparisons for both months for all other locations. Our

results show substantial price advantages for FSA, larger in the fall than in the spring. On average, FSA shortening prices were 31.5 percent below private sector

prices in September and 26.5 percent lower in April.

Vegetable oil prices averaged 34.9 percent lower in

September (excluding those for California, which

would expand the gap more) and were 28.8 percent

lower, on average, in April. 

Pasta. We compared prices for truckload delivery of

20-lb. cartons of three productsspaghetti, elbow macaroni, and rotini. We used nationwide average prices for

FSA data, for September 1996, and the results were

quite consistent across the three products (table 8-1):

FSA prices were consistently 37-38 percent lower than

private sector prices. Our cooperator did not specify

whether the price quotes were for a branded or privatelabel product, but branding should not be an important

price factor in this (20-pound) package size.

Peanut Butter. The cooperator provided price quotes

for delivery of truckload quantities of a branded smooth

peanut butter in cases of 12 24-ounce containers. FSA

prices are quoted for delivery of truckload quantities of

smooth peanut butter in cases of 24 32-ounce containers. Our data show that FSA prices were, on average,

17.6 percent below those of the private sector product

in September 1996. Because the private sector containers are slightly smaller, they should carry a higher price

for the added convenience, but we did no direct adjustment because we had no basis for one. Based on our

experience with other price comparisons, we would

estimate that the container difference accounts for about

2 percent of the 17.6 percent gap. Another point of difference in this comparison was that we had to match a

USDA-labeled product with a branded product, and

many purchasers might prefer to pay a price gap of this

size in exchange for the greater perceived quality assurance associated with the branded product.

All-Purpose and Bakery Flour. The flour results show

a strong temporal shift consistent with other ERS

research on flour pricing. The cooperator provided us

with data for the delivery of all-purpose flour in truckload quantities of cases containing eight 5-pound bags,

and for delivery of truckload quantities of bread flour in

50-pound bags. The quoted prices were for a branded

product, and branded products carry a modest price premium at small package sizes (5-pound bags) in flour.

Prices for three locations (California, Texas, and

Illinois) and 2 months (April and September) were

cited. FSA runs some auctions for delivery of all-purpose flour in 5-pound bags, but 10-pound bags were far

more common in 1996, so we also used FSA 10-pound

auctions and adjusted those prices up by 2 percent, the

package size premium estimated in our price regressions. FSA purchases bread flour in 50-pound bags, the

same size as the cooperator.

FSA all-purpose flour prices were substantially below

private sector prices in April: by 31.5 percent for Texas

delivery, 31.1 percent for Illinois, and 7.8 percent for

California (the cooperators California prices were estimated and are considerably less reliable). But in

September, FSA prices were only 14.3 percent below

private sector prices in Texas and California and 17.4

percent lower in the upper Midwest. 

Bread flour is a far thinner FSA market; there were no

FSA auctions for the relevant months in Texas and

California. In Illinois, FSA prices were 21.7 percent

below corresponding private sector prices in April, but

in September, were quite close to private sector quotes

(3.5 percent lower), consistent with the all-purpose

flour results. Finally, FSA prices rose sharply in

October and November 1996 to levels above the

September private sector prices (we do not have access

to the cooperators later prices).

Why are September prices so much closer? In brief, the

data show that FSA prices rise during the fall, while

private sector prices decline. Three factors drive the

44 /ERS-USDA Food Procurement by Farm Service Agency / AER-766
seasonal increase in FSA prices. First, wheat prices (the

primary material cost) show some seasonal variation,

and typically rise slightly in the fall. Second, flour

demand rises quite sharply during the fall. FSA bidders

bid more aggressively when they expect to have excess

production capacity, and they have little excess capacity

at that time; as a result, they include capacity charges in

their fall bids. Finally, and also because of capacity limits, fewer firms bid in fall FSA auctions, leading to

higher bids. In short, FSA prices rise because costs rise

and also because FSA auctions become less competitive

in the fall.

In contrast to FSA price patterns, retail prices for flour

typically drop sharply in the fall, by as much as 20 percent, just as demand is increasing sharply. Other ERS

research has identified patterns of falling prices in the

face of seasonal demand surges for most retail food

products with strong seasonal demand swings, and the

pattern appears to be quite strong for flour. Prices in

retail markets move closer to costs in the fall apparently

because seasonal demand surges lead to greater competition among flour manufacturers for retail markets.

This results in prices that fall quite sharply relative to

FSA prices.

Some Caveats 

Table 8-1 shows that FSA prices fall substantially

below corresponding private sector prices in most

cases. We should keep three cautions in mind.

First, representatives from the cooperating foodservice

firm feel that their quoted prices are not the minimum

that a client could receive from manufacturers. In particular, clients wishing to make significant volume

commitments can sometimes obtain lower manufacturer

prices, and manufacturers sometimes offer lower prices

to certain classes of buyers, including government

agencies. We did not seek out those sorts of prices

because they are substantially more difficult to obtain,

being quoted on a case-by-case basis. In addition, we

compared cooperator prices with average FSA prices in

a given month, not to the lowest obtainable FSA prices,

and we compared with FSA auctions that did not entail

long-lasting volume commitments (such as are currently done in FSA infant formula auctions). Therefore, we

decided that the cooperator prices that we did have represented an appropriate basis for comparison.

The second caution is that we compared prices for commodity categories in which FSA currently does a significant amount of purchasing, and which therefore have

passed a type of market test. That is, clients who

choose to purchase these products through FSA presumably do so because they find that FSA can obtain

these products at substantial discounts compared with

what the clients can do for themselves. Our comparisons, therefore, have focused on those products where

FSAs buying advantages may be the greatest, and one

should be cautious about extending these results to

products that are not currently purchased by FSA.

Finally, we remind readers that FSA and prime vendor

systems are designed to do different things. FSAs food

procurement strategies are designed to obtain large

quantities of a few basic food products, and to obtain

them at the lowest possible manufacturers prices, subject to USDA product specifications. Foodservice firms

are in the business of delivering a wide variety of food

products to clients on a timely basis; in other words,

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 45

Table 8-1: Comparing FSA prices with comparable 

private sector prices

FSA price

Product and divided by private sector price

location April 1996 September 1996

Liquid shortening:

Texas 0.734 0.683

IL/IN/WI 0.733 0.685

New England 0.737 0.685

Vegetable oil:

California n.r. 0.585

Texas 0.712 0.683

IL/IN/WI 0.764 0.718

New England 0.670 0.552

All-purpose flour: 

California 0.932 0.867

Texas 0.685 0.867

IL/IN/WI 0.689 0.826 

Bread flour:

IL/IN/WI 0.793 0.965

Pastanationwide: 

Spaghetti n.r. 0.629

Macaroni n.r. 0.621

Rotini n.r. 0.622

Peanut butter:

Nationwide n.r. 0.824

Note: n.r. means that no cooperator price was reported for

that month.
they target several goals other than price. Depending on

their goals, clients may rationally decide to purchase

through a foodservice wholesaler, even if an FSA auction strategy can obtain lower manufacturer prices,

because of the additional services provided by the foodservice wholesaler.

Comparing Price Trends in 

FSA Commodities

In the previous section, we compared price levels of

products purchased under FSA and private sector procurement strategies. ERS was also asked to investigate

trends in FSA prices to see if those trends matched

price trends for private sector purchases of the products

that FSA buys. This is a much more difficult and uncertain task because we do not have access to comparable

prices for specifically defined products going back in

time. To perform that comparison, we obtained

Producer Price Index (PPI) data from the Bureau of

Labor Statistics (BLS). The PPI aims to measure

changes in net prices received by manufacturers for

precisely defined products. BLS produces PPI indexes

that closely match four FSA commoditiesall-purpose

flour, bakers flour, pasta, and vegetable oil. BLS does

not produce a PPI for peanut butter, but does produce

one for peanuts.

FSA buys a variety of different specific package types

and product types within the broad commodity categories, and obtains bid prices for delivery to particular

locations across the country. Systematic changes in

locations, product characteristics, and container sizes

could affect average FSA prices over time, even if there

were no changes in bid prices for delivery of precisely

defined products to precisely defined locations. To

control for the possible effects of location, product

type, and container size, we ran regressions with those

variables in them: separate year effects then captured

FSA price trends. Results are summarized in table 8-2.

Price increases for FSA products were close to 1992-96

PPI changes for two products, bakery flour and vegetable oil, but substantially exceeded PPI growth in

pasta and peanut butter. In each of the latter two cases,

FSA prices rose about 4.5 percent per year faster than

the corresponding PPI. In the fifth category, all-purpose

flour, FSA prices rose modestly faster than the PPI.

We performed a second comparison using A.C. Nielsen

data on average supermarket prices. The Nielsen data

are derived from electronic scanners at supermarkets,

and measure changes in what consumers pay at retail

for items, rather than what manufacturers receive. The

scanner data provide measures of the average price per

ounce for all-purpose flour or all peanut butter sold in

U.S. supermarkets; since the data cover the period

1989-96, they overlap with the FSA data. The supermarket product definitions match up well with FSA definitions (for example, peanut butter is captured), and

may represent an important source of price comparison

for FSA clients, such as school lunch purchase agents.

FSA prices grew sharply faster than supermarket prices

in all four comparison categories. The differences are

again quite striking for pasta, where supermarket prices

rose very slightly in line with the PPI, and also in allpurpose flour and in peanut butter, where the supermarket measure captures a more appropriate price comparison than the PPI does.

We made one further decomposition of the retail price

data, by looking separately at price trends for privatelabel products. Those are products that are made by

processors at the direction of a supermarket chain or a

wholesaler that supplies supermarkets, and that carry

the chain or wholesaler label. In that sense, they are

similar to FSA products, which are also made by

processors to USDA specifications and for a USDA

label. Private-label price trends are below trends for

FSA products (table 8-2), but are relatively close,

except for pasta.

46 /ERS-USDA Food Procurement by Farm Service Agency / AER-766

Table 8-2: Comparing price trends in FSA auctions 

with related price indexes

Producer Average Private- FSA

Commodity price supermarket label prices

index prices prices (low bids)

Percent increase in prices, 1992-96

All-purpose flour 24.6 17.9 22.2 32.6 

Bakery flour 26.2   22.3 

Pasta 7.8 8.1 9.9 25.3 

Vegetable oil 20.4 11.7 15.0 18.2 

Peanut butter -14.4 -7.7 3.1 4.4 

Notes: FSA price trends are derived from the coefficients on

year terms in regression analyses of low bids that also included product characteristics, fixed monthly effects (for seasonality), and fixed State effects. The Producer Price Indexes

measure 1992-96 changes in annual averages for the most

closely related products, while average and private-label

supermarket prices reflect December 1992 to December

1996 changes in the weighted average price per ounce of

closely related supermarket categories. The measures are

based on supermarket scanner data, and the weights are

sales weights assigned to each item in a category.
There is one strong explanation for more rapidly rising

FSA prices. Agricultural commodity prices generally

rose sharply during 1992-96. For example, prices for

durum wheat, the major pasta ingredient, were 75 percent higher in the spring of 1996 than in 1992. Prices

fell by the fall of 1996, but were still 40 percent higher

than they had been 4 years before. By mid- to late

1996, prices for the hard and soft wheats used in flour

averaged 30 percent above their levels 4 years earlier,

in 1992. 

Millers pay the same prices for wheat, whether they are

producing for FSA purchases or for private sector purchases. Could agricultural price increases nevertheless

have stronger effects on FSA prices? Yes, if wheat

accounts for a greater share of the costs of manufacturing FSA products. If FSA prices are lower (and they

appear to be) and if FSA products use the same

amounts of wheat as private sector products (also true),

then wheat costs will be a larger share of the total costs

of producing FSA products than others. Increases in

wheat prices ought to lead to greater percentage

increases in FSA product prices than in average manufacturer or retail prices for the corresponding products.

Retail prices also include the costs of providing retail

services, which means that ingredient costs will have a

still smaller percentage impact on retail prices than on

FSA prices. By the same reasoning, FSA prices ought

to fall more sharply when wheat prices are falling than

average manufacturer and retail prices. In short, FSA

prices should be noticeably more sensitive to input

costs, both temporally in response to fluctuations in

agricultural prices and spatially in response to differences in transport costs. The data in table 8-2 are consistent with that interpretation; we could have more

confidence in it if we could also compare FSA price

trends with manufacturer and retail price indexes during

periods of agricultural price declines.

Conclusion

FSA appears to be able to obtain substantial price savings on the five commodities that we investigated, with

30-40 percent gains being common. We caution, however, that the comparison is at present based on a limited sample of commodities and on comparison to prices

quoted by manufacturers to one large foodservice

wholesaler.

Because FSA prices appear to be more sensitive than

private sector prices to geographic location and to

movements in underlying agricultural commodity

prices, the FSA price advantage will also vary temporally and geographically. FSA prices will be lowest, relative to comparable private sector prices, near production centers and during periods of low agricultural commodity prices. Moreover, FSAs advantage is likely to

be greater on common package sizes and product types,

where the agency can induce greater competition in

auctions. 

Recent price trends suggest that FSA prices for pasta

and peanut butter products have risen sharply compared

with average manufacturer prices. In the case of pasta,

FSA prices still appear to be far below private sector

prices; however, FSA peanut butter prices are moving

closer to private sector levels. When combined with

perceived quality problems, many clients may not view

FSA peanut butter as an attractive purchase.

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 47
USDAs Farm Service Agency operates a system

designed to elicit low bids for the delivery of large volumes of a limited number of food products. The system

largely reaches those goals. The evidence in chapter 8

shows that FSA prices are substantially below those

obtained by private sector buyers; chapter 7 supports

those findings by showing that agricultural commodity

purchase costs represent high shares of the prices for

FSA food product purchases, suggesting that processing

margins are quite low. By implication, FSA stretches

USDA budget dollars by purchasing substantial volumes of food products for any given budget allocation.

As the experience of DoD and the VA show, low prices

are only one of the things that ultimate consumers want

from their food distribution system. Along with nutritional needs, they are also interested in timely delivery

and product variety. FSA does not act as a full-line food

distributor for its clients, and hence, does not focus on

wide variety and rapid delivery. Rather, it fills a niche

by providing the opportunity for clients to obtain large

volumes of a few items at very favorable prices, and it

fills that niche by limiting product variety and by

responding more slowly to orders than a full-line distributor would. By saving clients money on USDA

products, FSA can allow them to more effectively

spend the rest of their budgets on a variety of products. 

Nevertheless, FSAs actions can affect clients realization of their several goals. Because of FSAs long lead

times for delivery, client agencies must plan meals well

in advance. When FSA deliveries arrive later than

expected, meal plans are upset, meal quality can suffer,

and client agency costs can rise sharply when they must

replace FSAs orders quickly. Moreover, USDAs product offerings, sometimes devised with a view toward

surplus removal, do not always match client needs or

expectations from USDAs niche service. As a result,

even though FSAs strengths lie in the provision of

large volumes of a relatively few low-priced items, reliable delivery and product variety still matter to clients,

and the agency must be concerned with meeting client

expectations of FSA in those areas. 

The Role of Agricultural Prices

FSA bids are quite sensitive to movements in agricultural pricesfar more sensitive to agricultural price

movements than are general wholesale and retail food

prices. There is an important implication of that finding: because agricultural prices tend to fluctuate widely,

FSAs prices will fluctuate more widely over time than

corresponding wholesale and retail prices. FSA prices

will fall more than wholesale and retail prices when

agricultural prices decline, and they will rise more

rapidly than wholesale and retail prices when agricultural prices rise sharply. The gap between FSA and corresponding retail and wholesale prices, therefore,

should be largest during periods of relatively low agricultural prices and smallest during periods of high agricultural prices. Because our data also suggest that FSA

prices may be more sensitive to transport costs, the gap

between FSA and corresponding retail and wholesale

prices should also be highest in those regions that are

close to agricultural production regions.

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 49

CHAPTER 9

CONCLUSIONS
Chapter 6 shows that bids for FSA products rose along

with agricultural prices in the later part of our study

period, and that bids rose relative to FSAs constructed

prices. That pattern suggests a possible problem in

KCCOs calculation of constructed prices: in particular,

because constructed prices seem less sensitive to underlying agricultural prices than bid prices are, constructed

prices may not give enough weight to agricultural

prices. The issue is important because KCCO uses its

constructed prices to decide whether to cancel an auction, and shift orders to later auctions. While, the threat

of cancellation can be useful (auction theory suggests

that the threat can lead to more competitive bidding,

and the threat of cancellation is credible only if it is

used at times), but actual cancellations lead to lags in

product deliveries, thereby imposing substantial costs

on clients. FSA needs to guard against cancellation of

auctions when constructed prices are unreliable guides.

We therefore recommend that FSA review its procedures for calculating constructed prices, with a particular focus on the weight given to agricultural prices.

Competition 

Competition matters, but it matters a lot only in some

circumstances. Our statistical analysis of bidding shows

that more bidders are consistently associated with lower

prices on FSA products, but the effect of more bidders

becomes rather small once an auction has two and three

bidders. Most of the gains for FSA from competition

come from adding a bidder in auctions where there

would otherwise be only one bidder. As an approximate

rule of thumb, FSA can do as much for its clients by

finding a second bidder for a monopoly auction (reducing prices by 4-7 percent) as by finding four more bidders for an auction that already has two. Consequently,

FSA should be most concerned about competition in

those auctions that consistently attract a very small

number of bidders. We recommend that FSA focus its

efforts to add bidders for auctions that typically attract

only one or two bidders.

Chapter 6 shows that the number of bidders in FSA

auctions varies substantially by product and over time.

Where are the most serious competitive problems?

Seasonality is important for some products: for example, over three-quarters of monopoly auctions in flour

occur in the fall, when mills operate near peak capacity.

Monopoly auctions are also more likely among products with limited FSA volumeunusual package sizes

and product characteristics.

In those cases, FSA can counteract monopoly by conveying accurate price information to clientsfor example, that FSAs price advantages over commercial flour

providers are weakest in the fall and strongest in other

periods, or that FSAs price advantages are strongest in

high-volume products. We recommend that FSA explore ways to counteract seasonal variations in monopoly by extending the experiment with rolling contracts,

currently in use with cheese, to other products. At present, funding authorizations can constrain FSAs ability

to use rolling auctions because money appropriated in

one fiscal year must usually be spent in that year.

Participation in FSA bidding has a distinctive all or

nothing character to it; bidders typically commit to

being active in FSA auctions, in which case they bid

actively each month on auctions for a variety of locations and products. Auction participation then does not

typically decline because bidders reduce the number of

auctions they are active in; rather, firms decide to get

out of FSA bidding entirely. Our present research has

not tried to uncover the reasons that firms decide to

enter or leave FSAs bidding process, but the data we

have developed do allow us to identify the firms that

have entered and left the process during the period.

Efforts to increase competition should inquire into the

reasons for entry and exit by those firms, and the

research should generate strategies to attract participation by more firms. 

Effects of Purchase Volumes

Monthly FSA purchase volumes have dropped substantially as a result of changes in USDA commodity support programs. But declining volumes have not as yet

had any substantive effects on FSA bids. Purchase volumes have only small direct effects on prices, and those

effects are not always in the same direction. Moreover,

changes in purchase volumes for individual products

appear to have had little effect on competition (typically, bidder numbers fell and then rose during the period,

while volumes fell consistently and sharply).

Monthly volumes have small effects on bids, and the

direction of the effect varies with volume; increases in

volume are first associated with declining prices, but

then drive prices up slightly in very high-volume

months. The data also show that markets respond to

total USDA purchases (foreign and domestic), and not

simply to domestic buys. The most important effects on

prices occur in months in which there are large PL480

50 /ERS-USDA Food Procurement by Farm Service Agency / AER-766
purchases; in those months, coincident large domestic

purchases can lead to FSA price increases of 2-4 percent. The driving factor in these instances are PL480

purchases, which vary sharply from month to month.

We recommend that FSA initiate strategies to get better

prices on domestic flour and vegetable oil, either by

smoothing PL480 purchases or by timing domestic purchases to avoid peaks in PL480 purchases.

Order volumes (the amount going to a specific destination in a specific order) have very small effects on

prices. Larger orders generally draw more aggressive

bidding, but prices only fall by less than 1 percent;

combining orders into multiple truckloads yields very

limited savings. Major gains in price likely come as

one goes to truckload volumes from smaller orders, and

FSA already acts to combine small orders into orders of

at least truckload sizes.

We also recommend that FSA advise client agencies

that they can generally save 1-2 percent on purchase

prices if they are willing to accept delivery to major

destination points within a State, rather than to locations that are rarely used for FSA deliveries. 

Commercial Labels and 

USDA Inspection

The reliance on USDA labels and packaging shifts

some risks of poor product quality away from the vendor and toward USDA, and consequently creates a need

for USDA inspection. USDA inspection, along with

occasional unusual packaging requirements, can raise

vendor costs by 1-2 percent; USDA inspection and testing can also occasionally lead to lags in product delivery, which clients cite as a persistent problem. Some

vendors, especially relatively small plants, cite inspection and packaging requirements as deterrents to participation in FSA auctions because of the effects on cost

and on timely delivery of products.

The current system results in very competitive prices,

and the insistence on USDA labels may contribute to

the competition that leads to those prices; some firms

may not wish to bid aggressively on their own branded

products. In some products, in other words, the net

effect of USDA labels and inspection may be lower

prices. But insistence on USDA labels may, in other

products, limit opportunities to obtain surplus stocks of

commercially labeled products and may deter additional

bidders from participating.

FSA currently purchases commercially labeled products

in a few commodity categories. In highly oligopolistic

markets with only a few vendors, FSA may be able to

obtain more product variety and greater competition by

opening auctions to commercially labeled products. The

clear examples include the current experiments in

ready-to-eat cereal and infant formula. Those two cases

illustrate a dilemma for the agency. A principal argument for USDA labels is that they limit brand loyalty

on the part of consumers and, therefore, allow for more

competitive bidding, but brand loyalty is important in

those two products (especially ready-to-eat cereal).

FSAs shift to purchase of commercial labels reflects

the agencys judgment that the shift may introduce

greater competition into two highly concentrated markets. But FSA also purchases products for other markets in which brand loyalty is far less important

because the brands are never seen by ultimate consumers and because the products are used as ingredients

in final servings, not as the serving itself. We recommend that FSA carefully evaluate its current experiments and consider a gradual expansion of commercial

labels (especially including high-quality private-label

and wholesalers own-brand products), especially in

products with limited existing brand loyalty and low

vendor participation.

Service Quality

Client agencies cited four common complaints. The

primary complaint, referred to earlier, related to unreliable delivery of products. This complaint has three

major components: lags due to USDA inspection

delays (typically at small plants), cancellation of auctions, and vendor noncompliance. FSA can improve

reliability by reviewing procedures for cancellation and

inspection (including labeling requirements), and by

instituting a more effective system of contractual penalties for noncompliance. 

A second common complaint referred to product selection: client agencies feel that surplus removal goals

drive the selection and distribution of bonus commodities that clients frequently have little interest in. Third,

complaints sometimes referred to deterioration of some

products. Finally, and related to the first three, clients

cited barriers to problem resolution. 

USDA products follow a long distribution chain

between ordering food and serving a meal: a client

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 51
places an order with USDA, which then arranges for

production. A vendor manufactures the product, and

arranges for delivery from the processing plant to a

State warehouse or to another processing site. The

product is then delivered to the clients central facilities

before being distributed to dining facilities, where further preparation and holding may occur before serving.

The client may interact with State government agencies

in ordering and final delivery, and may be unaware that

up to five different USDA agencies may be involved in

their order for food.

FNS is developing a hotline system in an attempt to

respond better to immediate client problems with

agency deliveries. Larger issues, relating to program

goals and design, are likely to arise in response to

ongoing changes to Federal farm and food assistance

policies. 

Retention and Use of 

FSA Auction Data

FSA disposes of the electronic records of auctions after

1 year. The research for this report relied primarily on

paper reports, the data from which were re-entered into

an electronic format. Electronic data retention grows

easier and cheaper every year, and so do methods for

analyzing data. Moreover, because of steady improvements in the electronic retention and analysis of data,

undergraduate business and economics majors now routinely learn almost all the techniques that were used in

this analysis, and high school students are being introduced to techniques of graphing and summarizing statistical data. In short, KCCO commodity analysts

should, in the future, be able to easily call up 5 years

worth of past auction data (for example); they should

be able quickly to summarize key data patterns, and can

easily be provided with expert summaries of more subtle issues. They should be able to use that information

in making auction decisions and in delivering timely

information and advice to client agencies. We recommend that KCCOs future strategy for information technology include steps to retain electronic auction records

and to develop those records into easily accessible databases. 

52 /ERS-USDA Food Procurement by Farm Service Agency / AER-766
Brannman, Lance, Potential Competition and Possible

Collusion in Forest Service Timber Auctions.

Economic Inquiry 34 (October, 1996): 730-745.

Durham, Catherine A., and Emerson M. Babb, The

Impact of the Number of Bidders and Costs on School

Milk Prices. Unpublished Manuscript. Purdue

University. January 1997.

Kaufman, Philip R., James M. MacDonald, Steven M.

Lutz, and David M. Smallwood, Do the Poor Pay More

for Food? Item Selection and Price Difference Affect

Low Income Household Food Costs. Economic

Research Service, U.S. Department of Agriculture,

Agricultural Economic Report No. 759. November

1997.

Kuhlman, John M., and Stanley R. Johnson, The

Number of Competitors and Bid Prices. Southern

Economics Journal 51 (January 1985): 924-926.

Laffont, Jean-Jacques, and Jean Tirole, A Theory of

Incentives in Procurement and Regulation (Cambridge:

The MIT Press, 1993).

MacDonald, James M., Competition and Rail Rates

for the Shipment of Corn, Soybeans, and Wheat. The

RAND Journal of Economics 18 (Spring, 1987): 151-

163.

McAfee, R. Preston, and John McMillan, Auctions

and Bidding. Journal of Economic Literature 25 (June

1987): 699-738.

Meyer, Donald J., Competition and Bidding Behavior:

Some Evidence From The Rice Market. Economic

Inquiry 26 (January, 1988): 123-132.

Porter, Robert H., and J. Douglas Zona, Ohio School

Milk Markets: An Analysis of Bidding. National

Bureau of Economic Research Working Paper No.

6037. May 1997.

U.S. General Accounting Office, Best Practices

Methodology: A New Approach for Improving 

Government Operations. GAO/NSIAD-95-154. May

1995.

Wolfstetter, Elmar, Auctions: An Introduction.

Journal of Economic Surveys 10 (December, 1996):

367-420.

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 53

REFERENCES
AID  Agency for International Development, State

Department 

AMS  Agricultural Marketing Service, USDA

BLS  Bureau of Labor Statistics, Department of

Labor

CCC  Commodity Credit Corporation, FNS/USDA

CSFP  Commodity Supplemental Food Program,

FNS/USDA

DLA  Defense Logistics Agency, DoD 

DoD  Department of Defense 

DPSC  Defense Personnel Support Center,

DLA/DoD

ERS  Economic Research Service, USDA

FAS  Foreign Agricultural Service, USDA

FNS  Food and Nutrition Service, USDA

FDIR  Food Distribution Program on Indian

Reservations, FNS/USDA

FSA  Farm Service Agency, USDA

GIPSA  Grain Inspection, Packers and Stockyards

Administration, USDA

KCCO  Kansas City Commodity Office, FSA/USDA

NSLP  National School Lunch Program, FNS/USDA

OAMM  Office of Acquisition and Materials

Management, VA

TEFAP  The Emergency Food Assistance Program,

FNS/USDA

USDA  United States Department of Agriculture 

VA  Department of Veterans Affairs 

Food Procurement by Farm Service Agency / AER-766 USDA-ERS / 55

APPENDIX A

GLOSSARY OF ACRONYMS
Food Procurement by Farm Service agency / AER-766 USDA-ERS / 57

Table B-1: Regression analysis of low bids in USDA allpurpose flour auctions

Variable Coefficient t-statistic 

Wheat price variables

Cash price, bid month 0.7874 96.34 

Month ahead change .1637 9.78 

Month behind change -.7697 38.65 

Product characteristics

10 lb. bag (Base is 5) -.0180 6.02 

50 lb. bag -.0469 14.26 

100 lb. bag -.0581 3.72 

Bleached .0190 2.67 

Auction characteristics

Truckloads in order .0006 0.57 

Monthly volume, FSA flour -.6445 14.93 

Monthly volume, PL480 -.3412 14.77 

(FSA volume)2 .0094 6.82 

(PL480)2 .0003 4.10 

FSA volume*PL480 .0212 14.40 

Total orders at location .0001 0.09 

One bidder (base is three) .0815 20.76 

Two bidders .0123 4.38 

Four bidders -.0163 6.14 

Five bidders -.0248 7.94 

Six bidders -.0178 4.54 

Seven or more bidders -.0266 5.49 

Bid month

February (January is base) - .0179 4.14 

March .0456 10.19 

April .0254 4.92 

May .0390 7.68 

June .0907 13.73 

July .0184 3.94 

August -.0011 0.25 

September .0589 12.97 

October .0372 6.22 

November .0542 10.99 

December .0235 5.08 

Summary statistics 

Number of observations 5,726 

R2 .80 

Dependent variable mean 2.6183 

Root mean square error .0636 

Notes: Dependent variable is natural logarithm of winning bid

price. Wheat prices, the number of orders at a location, and

monthly volume are also expressed in natural logarithms, and

truckloads variable takes on values from 1 to 5. All other variables are dichotomous, taking values of zero or one. Model

also includes 48 separate State effects. Data consists of

shipments to contiguous 48 States.

Table B-2: Regression analysis of low bids in USDA

bakery flour auctions

Variable Coefficient t-statistic 

Wheat price variables

Cash price, bid month .7019 47.90 

Month ahead change .1862 5.15 

Month behind change -.7622 21.81 

Product characteristics 

50-lb. bag (base is bulk) .1204 14.54 

100-lb. bag .0970 18.20 

Bleached -.0117 2.71 

Hrth .0763 14.44 

Auction characteristics

Quantity in order -.0049 1.43 

Monthly volume of FSA flour .1619 3.01 

Monthly volume, PL480 flour .0574 2.92 

(FSA flour volume)2 -.0046 2.66 

(PL480 flour volume)2 -.0011 6.91 

FSA volume*PL480 volume -.0025 1.78 

Total orders at location -.0084 3.68 

Transport mode not truck .0118 2.17 

One bidder (base is three) .0789 14.87 

Two bidders .0221 4.83 

Four bidders -.0083 1.12 

Five bidders -.0039 0.36

Bid month

February (January is base) -.0030 1.12 

March -.0023 0.30 

April -.0215 2.79 

May -.0447 5.32 

June -.0155 1.70 

July -.0619 4.29 

August -.0141 0.92 

September .0662 7.81 

October -.0371 3.68 

November -.0220 1.90 

December -.0199 2.00 

Summary statistics

Number of observations 1,711 

R2 .82 

Dependent variable mean 2.599 

Root mean square error .0643 

Notes: Dependent variable is natural logarithm of winning bid

price. Wheat prices, the number of orders at a location, and

monthly volume are also expressed in natural logarithms, and

truckloads variable takes on values from 1 to 5. All other variables are dichotomous, taking values of zero or one. Model

also includes 48 separate State effects.

APPENDIX B 

DETAILED REGRESSION RESULTSANALYSIS OF BID PRICES
58 /ERS-USDA Food Procurement by Farm Service Agency / AER-766

Table B-3: Regression analysis of low bids in USDA pasta

auctions

Variable Coefficient t-statistic

Wheat price variables

Durum cash price, bid month .3351 55.63 

Month ahead change .0071 0.40 

Month behind change -.3099 16.59

Product characteristics 

Spaghetti 2 lb. (base is 20 lb. spaghetti) .0393 9.90 

Macaroni, 20 lb. .0136 4.88 

Macaroni, 1 lb. .0925 26.90 

Rotini, 20 lb. .0780 23.75 

Auction characteristics

Truckloads in order -.0098 2.31 

Monthly volume, FSA pasta -.0681 17.90 

Total orders at location -.0024 2.09 

Small business bidder .0178 7.23 

One bidder (base is 3) .0620 19.70 

Two bidders .0237 9.08 

Four bidders -.0168 5.05 

Five or more bidders -.0419 5.55 

Bid month

February (January is base) .0107 2.08 

March -.0192 3.56 

April -.0079 1.38 

May -.0027 0.46 

June -.0305 5.14 

July .0248 4.60 

August .0219 3.98 

September .0532 9.60 

October -.0150 2.67 

November .0306 5.41 

December -.0119 2.16 

Summary statistics

Number of observations 4,487 

R2 .764 

Dependent variable mean 3.3333 

Root mean square error 0.0649 

Notes: Dependent variable is natural logarithm of winning bid

price. Wheat prices, the number of orders at a location, and

monthly volume are also expressed in natural logarithms, and

truckloads variable takes on values from 1 to 5. All other variables are dichotomous, taking values of zero or one. Model

also includes 48 separate State effects.

Table B-4: Regression analysis of low bids in USDA

vegetable oil auctions

Variable Coefficient t-statistic

Agricultural price variables

Soybean oil cash price, bid month .4869 73.98 

Month ahead change .1313 14.58 

Month behind change -.1848 21.90 

Cottonseed oil cash price, bid month .3673 64.30 

Month ahead change .1810 17.13 

Month behind change -.2305 20.50 

Product characteristics

Vegetable oil, 48 oz. (1 gal. is base) .2967 65.64

Vegetable oil, bulk -.2479 104.02 

Shortening, 3 lb. .1818 123.27 

Shortening, 50 lb. -.0214 6.80 

Shortening, 1 gal .0474 25.98 

Auction characteristics

Truckloads in order -.0048 3.18 

Total orders at location -.0002 0.28 

Monthly volume, FSA -.1569 3.27 

volume squared .0113 8.71 

Monthly volume, PL480 -.2617 5.32 

volume squared .0125 10.53 

PL480 volume * FSA volume -.0103 4.91 

Small business winner -.0131 8.47 

One bidder (base is 3) .0554 25.76 

Two bidders .0085 6.32 

Four bidders -.0132 5.80 

Five or more bidders -.0226 5.77 

Month 

February (January is base) .0014 0.41 

March -.0460 13.50 

April -.0102 2.88 

May -.0364 9.07 

June -.0366 10.40 

July -.0426 12.70 

August -.0447 13.13 

September -.0664 20.36 

October -.0593 18.53 

November -.0435 14.12 

December -.0264 8.05 

Summary statistics

Number of observations 7,152 

R2 .940 

Dependent variable mean -.9808 

Root mean square error .0423 

Notes: Dependent variable is natural logarithm of winning bid

price. Oil prices, the number of orders at a location, and volumes are in natural logarithms, and truckloads variable takes

on values from 1 to 5. All other variables are dichotomous.

Model also includes 48 separate State effects.
Food Procurement by Farm Service agency / AER-766 USDA-ERS / 59

Table B-5: Regression analysis of low bids in USDA

peanut butter auctions

Variable Coefficient t-statistic 

Peanut price variables

Peanut cash price, bid month 0.5350 28.29 

February adjustment -0.6321 7.72 

March adjustment -0.4562 5.24 

April adjustment -0.6337 6.87 

May adjustment -1.0036 10.86 

June adjustment -1.5615 16.02 

July adjustment -2.1790 24.03 

Product characteristics

No. 10 can (base is 2 lb.) -0.0136 7.98 

Reduced fat, No. 10 can 0.3384 16.78 

Auction characteristics

Truckloads in order -0.0004 0.18 

Monthly volume, FSA peanut butter 0.0490 27.54 

Total orders at location -0.0032 3.72 

Small business winner -0.0095 5.31 

Two bidders (base is 4) -0.0254 1.53 

Three bidders 0.0107 2.53 

Five bidders -0.0101 4.47 

Six or more bidders -0.0404 15.35 

Month

February (January is base) -0.7679 7.64 

March -0.5517 5.18 

April -0.7720 6.85 

May -1.2288 10.87 

June -1.906 15.96 

July -2.6660 23.94 

August -0.0172 4.40 

September -0.0078 1.96 

October 0.0294 6.39 

November 0.0447 10.42 

December 0.0560 12.60 

Summary statistics

Number of observations 5,242 

R2 .544 

Dependent variable mean -0.2446 

Root mean square error 0.0532 

Notes: Dependent variable is natural logarithm of winning bid

price. Peanut prices, the number of orders at a location, and

volumes are in natural logarithms, and truckloads variable

takes on values from 1 to 5. All other variables are dichotomous. Model also includes 48 separate State effects.

Because peanut prices only are available for marketing year

months, model includes last quoted monthly price of marketing year for off-season prices, and then allows the coefficient

on that price to vary with the off-season month (the adjustor

variables).
60 /ERS-USDA Food Procurement by Farm Service Agency / AER-766