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Effect of Proposed Port User Fees
on Export Grain Flow Pattern

The Texas Agricultural Experiment Stationl Neville P. Clarke, Direetor/The Texas A&M University SystemA/Qfioilege Station, Texas

~-

Table of Contents

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

The Port User Charge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

The Nature of Funds Subject to Recovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

The Research Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Methodology and Procedures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Effect of Port User Charge on Grain Trade:

Methodology and Procedures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
User Charge Estimation Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
User Charge Scenarios Based on Ports’

Operations and Maintenance Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
User Charge Scenarios Based on Ports’
New Construction Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

User Charge Scenarios Based on Combined
Operations and Maintenance and

New Construction Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Estimated User Charges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Estimating the Market Effect of Port
User Fees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Effect of Port User Charge on Export Grain A
Flow Patterns: Empirical Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Weight-Based, Port-Specific User Fee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Weight-Based, Uniform User Fee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Ad Valorem-Based, Port-Specific User Fee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Ad Valorem-Based, Uniform User Fee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Altered Flows and Port Elevator Capacity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Appendix I. Technical Discussion
of Methods and Procedures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Procedure to Estimate the Effect of User
Charges on Grain Trade . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Effect of Weight-Based Port User Charges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Effect of Ad Valorem Port User Charges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Elasticity Estimation Procedures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Appendix II. The Grain Transportation Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
General Description of Grain Network
Flow Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
Data Requirements of Grain Network
Flow Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Market-Related Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Transportation-Related Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Validation of Transportation Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Appendix III. Further Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Effect of Proposed Port User Fees
on Export Grain Flow Patterns

Hector Viscencio-Brambila
formerly, Assistant Research Scientist
Department of Agricultural Economics

Texas A&M University

Stephen W. Puller
Professor

Department of Agricultural Economics
Texas A&M University

Preface

Historically, the federal government has funded the maintenance and construction of the
nation's deep-draft ports. However, legislation has been submitted to the U.S. Congress which
would allow the federal government to recover a portion of these costs through imposition of port
user charges. Farm interests are concerned that user charges would increase the price of U.S.
agricultural commodities, reducing export volumes and their income. The purposes of this
research are to evaluate the effect of the proposed deep-draft port user fee on export grain flow
patterns and export levels and provide insight into potential marketing adjustment costs which
may result from diverted flows.

Acknowledgements

The authors express appreciation to the U.S. Department of Agriculture and the U.S. Army
Corps of Engineers for counsel provided during this project. Substantial contributions were made
by Bill Gallimore and Jim MacDonald of Economic Research Service, U.S. Department of
Agriculture. Special appreciation is expressed to Fred Ruppel for improving the exposition of
Appendix I, in particular that portion dealing with the effects of user charges on international
markets. Appreciation is expressed to reviewers Orlo Sorenson, Kansas State University; Mack
Leath, U.S. Department of Agriculture, University of Illinois; and Don Farris and Warren Grant,
Department of Agricultural Economics, Texas A&M University. This research was partially
supported through U.S. Department of Agriculture cooperative agreement number 58-3523-2-
034.

'\\_

a

Effect of Proposed Port User Fees

on Export Grain Flow Patterns

Introduction

The Port User Charge

In the past few years, more than 30 pieces of
proposed legislation have been submitted to the U.S.
Congress that, among other things, would allow the
federal government to recover a portion or all of the
operations and maintenance expenses and the capital
expenditures incurred in keeping the nation's deep-
draft facilities navigable. The legislative efforts pro-
pose a variety of user charge schemes as well as
various cost sharing formulas between federal and
nonfederal jurisdictions as a means to preclude fur-
ther subsidization of commercial deep-draft naviga-
tion. Some legislators have favored weight-based user
fees while others have favored ad valorem-based user
fees. Either type of fee would be applied on a port-
specific or uniform basis. Port-specific fees would be
based on the unique costs at each port whereas a
uniform fee would represent a flat fee to all ports.
Further, there is debate over which expenditures
should be recovered by the user fee. Some legislation
proposes fees which recoupe new construction costs,
others propose recovery of operations and mainte-
nance costs, while some call for recovery of both costs.

Possible imposition of a port user charge has raised
concerns among farm interests, port authorities, and
transport operators. Farmers are concerned that user
charges would increase the prices of U.S. agricultural
commodities—reducing export volumes and, thus,
their income. Port authorities are concerned that such
levies could alter grain flow patterns, ports’ market
areas, and interport competition. If grains flows are
diverted, the viability of railroads and barge firms may
be unfavorably affected on some transportation cor-
ridors. This might render location of the marketing
system infrastructure inappropriate.

The Nature of Funds Subject to Recovery

Several federal programs administered by the Coast
Guard, the U.S. Army Corps of Engineers, and the

Economic Development Administration (U.S. Depart-
ment of Commerce) support commercial navigation
on deep-draft harbors, ports, and channels. Federal
resources are expanded to cover operations and
maintenance costs of the existing port system as well
as construction of new facilities.

For purposes of this study, operations and mainte-
nance costs include those costs incurred by the Army
Corps of Engineers in maintenance of the existing
ports’ navigation facilities. New port construction
costs also are an important expense of the federal
government. Port areas require two types of new
construction. First, there are expenditures for infra-
structure which complement port operation (piers,
etc.). These investments are generally made by the
local jurisdiction. Then, there are new construction
expenditures made by the federal government (Army
Corps of Engineers) which involve the deepening,
widening, or lengthening of channels; it is these
expenditures which are to be recovered with user fees.

The Research Problem

International trade represents a vital economic ac-
tivity for the U.S. farm sector. Grains and soybeans are
the U.S.'s principal agricultural exports, accounting
for over 6O percent of the value of U.S. farm exports in
1983. The value of U.S. grain and soybean exports and
related products, moreover, increased almost sev-
enfold during the 1970-81 period, and accounted for
30 percent of the U. S. farm income (Cramer and Heid).
During the marketing year 1981-82, U.S. farmers
produced 16.8, 47.6, 32.4, and 62.6 percent of the
world's total wheat, corn and other coarse grains, and
soybeans, respectively. In calendar year 1981, the
U.S.'s share of world exports amounted to 40, 58, and
37 percent, respectively, for food grains, feed grains,
and oil crops and meal.

Price competition is a major economic aspect of
grain and soybean world markets. The viability of a
grain exporter, such as the United States, rests on its
ability to remain price competitive. The existence of

1

aggressive grain exporters such as Argentina, Austra-
lia, Thailand, and Brazil makes it difficult to remain a
competitive supplier to the world market (Paggi;
Longmire and Morey). If a user charge is approved,
the increase in transportation costs will increase the
price of U.S. grain and soybean exports to importing
nations and subsequently reduce U.S. sales and farm
prices} Whether or not the user charge would signifi-
cantly impact U.S. grain and soybean exports and
agricultural products is an empirical question and
depends upon the type and size of the fee as well as on
the supply and demand relationships prevailing in the
world markets.

In summary, the levying of a user charge on deep-
draft ports raises the following issues: (1) To what
extent will U.S. exports of grain and soybeans be
affected? (2) How will competition among U.S. ports
change? and (3) Will grain and soybean flow patterns
be significantly altered? This study attempts to answer
these questions for selected commodities (wheat,
corn, sorghum, and soybeans).

Objectives

The purpose of this study is to evaluate the effect of
port user charges on the U.S. export grain economy.
Specific objectives are:

1. Develop a procedure to estimate the size of a user
charge under various scenarios, based on recent
legislation proposed by Congress.

2. Estimate how the proposed user charge affects
foreign demand for U.S. produced wheat, corn,
sorghum, and soybeans.

3. Estimate the impacts of the user charge on U.S. and
export grain flow patterns.

4. Analyze the extent to which the user charge would
change the competitive positions of U.S. ports.

5. Provide insight into potential logistical inefficien-
cies which may result from the diverted grain
flows.

Methodology and Procedures
Based on available legislative initiatives, a proce-

dure to estimate user charges will be developed.

lConceivably the deepening of harbors and channels (new construc-
tion) would facilitate the use of larger carriers and, because of
economies of ship size, rates on routes which link deep water ports
would decline. In which case, the reduced rate may offset or
partially offset the proposed user charge. Although this may occur
for some commodities on selected routes, there was limited evi-
dence that this effect would be widespread for bulk grain carriage.
First, many of the world's grain-receiving ports have less water
than the U.S. ports which are candidates for new construction. In
which case, the destination or foreign port is the constraint to the
use of larger vessels. The important exceptions are several major
ports in western Europe, Taiwan, and Japan. In addition, it has
been observed that evolving ship size is not satisfactorily explained
by the assumption that port constraints determine ship size, i.e.,
there are other factors than port water depth which limit or affect
optimum ship size (Kendall). Kendall shows that ship costs,
terminal costs (port, handling, and storage costs), annual volume
of trade, length of voyage, etc. , interact to determine optimum ship
size.

2

Second, an economic procedure based on an interna-
tional trade model will be required to estimate the
effect of a port user charge on grain prices and

quantities traded in the international and U.S. domes- '

tic markets. Finally, transportation models for each
commodity, modified to account for relevant changes
in ocean shipping rates and in quantities supplied and
demanded in all involved markets, will be used to
estimate the effect of a port user charge on export grain
flow patterns. ‘l

Because no legislation has been enacted to date,
user charge scenarios will be generated based on
major features of the many pieces of proposed legisla-
tion. These include (1) the type of fee, weight- or ad
valorem-based; (2) the fee's form, (port-specific or
uniform); (3) the nature of costs subject to recovery
(operations and maintenance costs and/or capital
expenditures); and (4) the level of cost recovery; i.e.,
the cost-sharing formula between federal and nonfed-
eral jurisdictions.

The interaction of excess supply and demand rela-
tionships determines prices and quantities traded in
the international grain and soybean markets. There
exists a vast amount of economic literature dealing
with econometric models which estimate grain supply
relationships in international spatial equilibrium mod-
els which include both supply and demand relation-
ships as well as grain flow patterns (Grennes, John-
son, and Thursby; Barr; Rausser). To estimate changes
in prices and quantities in all relevant markets, a
simple international trade model involving an export-
ing country (the United States), and an aggregate
importing country (the rest of the world) is developed.
This is shown in Appendix I. In addition, Appendix I
describes the procedure used to evaluate the effect of
weight- and ad valorem-based fees on markets.

Spatial models have been successfully used to ana-
lyze grain and soybean flow patterns regionally, na-
tionally, and internationally (Leath and Blakely;
Makus; Taylor; Fuller and Shanmugham; Barnett,
Binkley, and McCarl). Multiperiod, network flow
models, originally developed by Taylor and later up-
dated by Makus, are employed in an attempt to
quantify the impact of a user charge on export grain
flow patterns. Taylor developed transportation mod-

To test Kendall's notion that ship size on various routes is affected
by other factors than port water depth, data on grain ship size were
collected for routes linking U.S. Gulf and Pacific Northwest ports
with Japan. If water depth was the principal constraint, larger 
carriers would travel the Pacific Northwest to Japan route (Yokoha-
ma port) since both of these ports have deeper water (45-60 feet).
(Lloyds 1984 Ports of the World). Basedon 1984 data, ship size on the
Pacific Northwest route ranged from about 14,000 to 61,000 DWT
with an average of 47,730 DWT (140 observations). On the Gulf
route, ship size ranged from 25,000 to 53,000 DWT with an average
of 48,550 DWT (176 observations). This outcome tends to support
Kendall's work since it shows similar size vessels operating on both
routes, i.e., other factors than port water depth appear to be
affecting ship size on these routes.

Kendall's work implies that a deepened harbor may not substan-
tially increase the size of grain carriers which frequent a port, in

which case, rates may not be lowered. As a result, the user charg 

would not be offset by a lowered ship rate. For these reasons, it was
assumed that any new construction which was financed through
user fees would increase ship rates.

els for various commodities including wheat, corn,
grain sorghum, and soybeans. In addition, separate
odels were developed for hard, soft, and durum

g heats. In this study, the hard wheat model will be
disaggregated into two models to account for dif-
ferences in the geography of production and con-
sumption of hard red winter and spring wheats. The
spatial models used in this study include grain and

‘soybean surplus producing regions, domestic grain
‘ deficit regions, barge loading locations, grain shipping

ports, and foreign demand regions. Four modes of
transportation are specified which include truck, rail,
barge, and ocean shipping vessels. See Appendix II for
an overview of the spatial model used in this study

Effect of Port User Charge on Grain Trade:
Methodologies and Procedures

To evaluate the effect of port user charges on export
grain flow patterns, it is necessary to estimate (1)
increases in ocean shipping rates that result from
imposition of the user charge, and (2) market effects of
the user charge; that is, the changes in prices and
quantities traded in the international and U.S. domes-
tic grain markets. The purpose of this section is to
describe the methodologies and procedures used to
obtain these estimates. The first section details the
user charge estimation procedure. In the second sec-
tion, methodologies and procedures to approximate
the effects of port user fees on grain markets are
developed.

Per-Unit Port-Specific

 
 

  
   

Proposed
Legislation

User Charge i __ User Charge i?

User Charge Estimation Procedure

As stated earlier, various types of user charge
schemes have been proposed. Figure 1 illustrates all
aspects of the proposed user charge and accordingly
identifies features of this user fee which must be taken
into consideration by the estimation procedure. The
port user charge scenarios are based on proposed
legislation and opinions of transportation experts
from the U.S. Department of Agriculture and the U.S.
Army Corps of Engineers.

Table 1 presents the formulae used to estimate user
charges which recoupe operations and maintenance
expenses. A uniform user charge implies a flat rate
applied to all ports regardless of a port's incurred costs
or tonnage. Thus, this type of user fee is obtained
through division of all ports’ operations and mainte-
nance costs by all ports’ tonnage (weight-based) or the
value of all ports’ commerce (ad valorem-based).
Formulae 1 and 3 in Table 1 were used to estimate the
weight-and ad valorem-based uniform user charges.
Port-specific user charge estimates take into account
the costs, tonnage, and value of commerce transiting
each port. This user fee is calculated by dividing the
operations and maintenance costs of each port by the
port's tonnage (weight-based) or the value of all
commerce transiting a port (ad valorem-based). For-
mulae 2 and 4 in Table 1 are used to estimate these
respective charges. Formulae to estimate user fees
which recover new construction costs are obtained by
replacing "operations and maintenance expenses”
which appear in the various formulae in Table 1 with

I‘ Ad Valorem i __J Uniform
User Charge User Charge

-- Corn
Operations and _ 50 Percent __ Sowhum
Maintenance Costs Cost Recovery
li Soybeans
New Hard Red
Construction Costs WW6‘ W719i"
Hard Red
Spring Wheat
Operations and
Maintenance and 100 Percent __J i so“ wheat

New Construction Cost Recovery
Costs

i‘ Durum Wheat

Figure 1. Diagrammatic representation of the various features of the proposed user charges.

Table 1. Formulae Used to Estimate Port User Fees

Number Formula
Weight-Based User Charge (PUUC)
(1) Uniform PUUC =  
All Ports’ Tonnage
(2) Individual Port-Specific PUUC =  
Port Tonnage f, a;

Ad Valorem User Charge (AVUC)

(3) Uniform AVUC = All POFIS’ OM COStS

All Ports’ Value of Volume Serviced

(4) Individual Port-Specific AVUC = port's OM Costs

Port's Value of Volume Serviced

‘OM = operations and maintenance.

"new constructions costs." User fees which include
both costs are estimated by simply aggregating the
two costs (operations and maintenance, new con-
struction).

User Charge Scenarios Based on Ports’
Operations and Maintenance Costs

Data on ports’ operations and maintenance costs
were obtained from the publication entitled, “Deep
Draft Navigation Cost Recovery Analysis,” prepared
by the U.S. Army Corps of Engineers Office and the
Chief of Engineers Directorate of Civil Works Office of
Policy, published in September 1982. Specifically, Table
110.1-D in the publication provides data on operations
and maintenance costs that are subject to cost re-
covery.

Data on the value of products and commodities
moving through individual ports, with an adjustment
for volumes shipped to domestic locations were ob-
tained from Table 501-D of the above document.
Operations and maintenance costs and dollar-value of
port commerce are expressed in 1982 constant dollars.
Tonnage figures correspond to 1981 data. Data on
annual operations and maintenance costs, tonnage,
and value of port commerce are summarized in Table
2. Data are provided for the 16 grain-shipping port
areas. A port area may involve more than one port;
e.g., the New Orleans port area comprises the port of
New Orleans, Baton Rouge, and the Mississippi River
segment connecting these two ports.

User Charge Scenarios Based on Ports’
New Construction Costs

To estimate new construction costs, it is assumed
that ports finance these expenditures through debt

zThere is some disagreement among engineers regarding the opera-
tions and maintenance costs necessary to maintain ports after their
improvement. The U.S. Army Corps of Engineers advised that the
current operations and maintenance costs were good estimates of
these costs. If current costs underestimate the operations and
maintenance costs associated with new construction, the projected
flow levels will be biased downward.

4

capital (bonds). This assumption can be justified on
several grounds. First, since this type of construction
does not represent a voluntary investment project,
there is no a priori reason why the port authority
should consider it as part of their investment port-
folio. Second, historically, ports have financed their
needs for funds mostly through general obligation
bonds and revenue bonds. Third, the decision to issue
bonds is largely influenced by the growth rate of fixed
assets at the port. Long-term assets are often financed
through long-term debt. Fourth, the cost of capital of
externally-raised funds is frequently lower than that of
internal sources (equity or new stock). Two important
reasons accounting for the latter are (1) interest costs
on debt capital are tax deductible while dividends are
not, reducing the cost of debt relative to that of equity
capital; and (2) through bonds, firms are committed to
pay a fixed return to bondholders to maturity of the
issue, which provides protection against interest rate
fluctuations. The yield used in this study represents
an average over the period 1977-83 and is comprised of
annual rates for corporate and general obligation
bonds with maturities of at least 2O years, weighted by
the type of port ownership (Table 3). Due to the fact
that there are numerous port projects subject to cost
recovery, with various government agencies and pri-
vate corporations involved, bonds of mixed quality
were thought to to be most appropiate. Table 4 pre-

sents these yields as well as the weighted average rates

for each year.

It was assumed that an annuity would appropri-
ately reflect the average effect of the callability and the
serial features of the involved bond types. Table 5
provides each port's new construction costs and the
annuities necessary to pay bondholders, under vari-
ous government cost recovery scenarios.

User Charge Scenarios Based
on Combined Operations and Maintenance

and New Construction Costs 

The formulae presented in Table 1 are used to
estimate port charges which incorporate the ag-

Table 2. U.S. Ports’ Annual Operations and Maintenance Costs Subject to Recovery‘

Operations and

‘I Authorized Maintained Maintenance 1981 Value of
' ort State Depth Depth Costs Tonnage Commerce
feet feet $1,000 1,000 ton $1,000

Mobile AL 4O 40 5,303.2 19,541.3 3,119,252.680
New Orleansz LA 40 40 23,037.9 133,421.8 45,466,130.007
Galveston3 TX 40 40 9,093.6 78,189.5 35,570,810.519
‘Iorpus Christi TX 45 45 6,130.9 31 ,525.8 5,719,312.431
I Brownsville TX * * * * 939,397.327
Charleston SC 35 35 5,483.2 8,231.5 8,802,356.191
Baltimore MD 50 42 2,420.9 39,035.7 18,192,283.640
Toledo OH 28 28 3,493.1 22,279.7 1 ,594,432.189
Saginaw Ml 27 27 6,730.2 2,281.7 179,569.765
Chicago IL 28 28 1 ,O20.2 1 3,155.0 1 ,582,631.819
Duluth‘ MN 28 28 2,384.1 39,425.1 2,492,417.947
Seattles WA 34 34 428.2 25,035.1 16,815,769.829
Portland“ OR 48 40 19,063.8 26,712.3 7,483,840.144
San Francisco’ CA 40 40 2,414.7 7,538.3 3,308,574.950
Long Beach“ CA 45 45 144.0 66,9994 44,581,706.615
San Diego CA 35 35 * 2,344.6 7,916,599.482
Subtotal 87,148.0 516,166.8 203,495,085.535

Other Ports 249,357.2 1,157,828.2 198,963,869.310
Total All Ports 336,505.2 1,673,995.0 402,458,954.845

Source: ”Deep-Draft Navigation Costs Recovery Analysis," U.S. Army Corps of Engineers, September 1982; August 1984.

‘All dollar figures in 1982 constant dollars.
Zlncludes New Orleans and Baton Rouge, LA.
3lncludes Galveston and Houston, TX.
‘Includes Duluth, MN and Superior, MI.
Slncludes Seattle and Tacoma, WA.

‘Includes Portland and Astoria, OR and Kalama and Longview, WA.

7lncludes San Francisco, Stockton, and Sacramento, CA.
“Includes Long Beach and Los Angeles, CA.
*Not available.

gregated operations and maintenance and new con-
struction costs. The U.S. Army Corps of Engineers
advised that current operations and maintenance
costs would be reasonable estimates of these costs for
any anticipated new construction activity.

Estimated User Charges

User charge estimates are reported in Table 6 and
correspond to a 100 percent cost recovery level. User
charge estimates for other cost-sharing arrangements
between federal and local jurisdictions can be ob-
tained by multiplying the 100 percent estimate by the

Qppropriate cost-sharing percentage.

In general, the estimated charges are small. For
example, a weight-based, uniform fee designed to
recoupe operations and maintenance costs averages
about $0.006 per bushel ($0.201/ton). A similar type of
fee which recovers new construction is estimated to be
about $0.012 perf bushel ($0.4436/ton), whereas the
combined costs are estimated to be slightly less than
$0.02 per bushel ($0.6446/ton). Although the es-
timated charges are relatively small, there is substan-

; ' l variation among ports. For example, four port
;. reas have estimated weight-based fees which re-

coupe operations and maintenance costs that are less
than $0.0025 per bushel, and seven ports with fees that

are less than $0.005 per bushel. In constrast, the
Saginaw, Michigan port area has an estimated weight-
based fee which is nearly $0.09 per bushel ($2.94/ton).
Similar variation exists among fees designed to re-
coupe new construction costs. Because Congress has
not authorized this new construction, four grain port
areas have no new construction costs. Congress has
thus far not appropriated funds for any port.

Estimating the Market Effect of Port User Fees’

Port user fees would increase ocean shipping rates
that link the United States with foreign buyers. In the
short run, the price of the commodity in the importing
country will rise and the quantity demanded will
decline. U.S. grain producers will find their export
market has decreased. This is due to increased grain
output of the importing regions and the reduced
quantity demanded by these regions. The costs of
production (marginal) will increase with output in the
importing countries and decline in the United States
as output levels decrease.

The extent to which the burden of the ship rate
increase will be shared between the United States and
importing regions depends, among other things, up-
on the importance of the importing region's demand
for the commodity and the elasticities of supply and

5

Table 3. U.S. Port Ownership Categories by Coastal
Region

Type of Ownership

Region State Local Private
percent
North Atlantic 28 24 48
South Atlantic 34 32 34
Gulf 8 44 48
South Pacific 10 61 29
North Pacific 0 48 52
Great Lakes 4 19 77
National Average 12 37 51

Source: National Port Assessment 1980/1990, An Analysis of Fu-
ture U.S. Port Requirements. U.S. Department of Com-
merce, Maritime Administration, Office of Port and Inter-
modal Development. June 1980.

Table 4. Interest Rates for Municipal and Corporate
Bonds

Bond Rates
Weighted
Year Municipals‘ Corporatez Rate
percent
1977 5.68 8.19 6.96
1978 6.03 8.97 7.52
1979 6.52 10.02 8.30
1980 8.59 12.70 10.69
1981 11.33 15.46 13.43
1982 11.66 14.45 13.08
1983 9.51 12.15 10.86
Average 8.47 11.70 10.12

Source: Federal Reserve Bulletin. Board of Governors of the
Federal Reserve System, Washington, D.C. (various is-
sues).

‘Bond Buyer's Series. General obligations only, with 20-year matur-
ity; issued by 20 state and local government units of mixed quality.
Based on figures for Thursday.

2Aaa Utility Bonds. Compilation of the Federal Reserve. Issues
included are long-term (20 years or more). Offered issues on
Friday close-of-business quotations.

demand in the United States and importing regions.
Assuming that the import demand is a significant
portion of total demand, the U.S. export price will
decrease by a greater amount (and the domestic price
in the importing country will increase by a smaller
amount) the less elastic is U.S. demand and supply.
Thus, the United States will bear much of the burden if
its domestic demand and supply are inelastic. A
complete analysis of the various forces becomes too
involved and detailed to present here. See Appendix I
for a procedure to estimate the effect of the various
user charges.

Based on the procedure outlined in Appendix I, the
estimated effects of the various proposed port user
fees on prices and quantities produced and traded are
calculated. Table 7 identifies the estimated percent
change in quantity demanded by foreign buyers of
U.S. grain, the percent change in quantity supplied by

6

Table 5. Estimated Costs of lmprovement and New
Construction of U.S. Deep-Draft Port Areasl

Total Estimated

Port Cost Payment
(million $)
Mobile, AL 447.72 47.97
New Orleans 525.00 56.25
Galveston 595.00 j. 63.75
Corpus Christi 92.02 = 9.86 h.
Brownsville -— —
Charleston 80.10 8.65
Baltimore 400.00 42.86
Toledo -— —
Saginaw — —
Chicago — —
Duluth 10.78 1.15
Seattle 82.24 8.81
Portland 3.16 0.34
San Francisco 276.60 29.64
Long Beach 460.00 49.29
San Diego — —
Total 2,973.22 318.56
Other Ports 3,957.86 424.06
All U.S. Ports 6,931.08 742.62

30-year Annuity 

Source: U.S. Army Corps of Engineers, Washington, D.C.
“All figures in 1982 dollars.

U.S. producers, and percent change in U.S. domestic
consumption. As expected, the supply and foreign
demand for U.S. grain declines while domestic U.S.
consumption increases. In general, the ad valorem-
based fees have the least effect on quantities produced
and traded. Table 8 relates the estimated impact on
domestic and international grain prices that results
from imposing various types of user fees. The analysis
reveals only modest price increases and declines in the
international and U.S. domestic markets, respectively.
Again, the ad valorem-based fee appears to have the
least effect on prices.

Effect of Port User Charge on Export Grain
Flow Patterns: Empirical Results

This section includes discussion of weight-based
and ad valorem-based fees, both of which may be
levied on a port-specific or uniform basis. In addition,
the analysis evaluates the effect of recovering opera-
tions and maintenance expenses as well as new con-
struction expenditures. The analysis assumes 100 per-
cent recovery of costs by local jurisidictions. Altered
flows associated with a 50 percent cost recovery level
as well as individual commodity flows are included in
Appendix III.

Weight-Based, Port-Specific User Fee

A weight-based user charge aimed at recovering
operations and maintenance expenses through use of

a port-specific fee would only modestly affect thr 
aggregate flow of grain and soybeans to Gulf, Atlantitiq.

Great Lakes, and Pacific coast areas (Table 9). The
greatest relative effect is in the Atlantic and Great

Table 6. Ports’ User Charge Estimates for All Types of Costs Subject to Recoveryl

Cost Subject to Recovery2

a OM NC

OMNC

Port Weight-Based Ad Valorem Weight-Based Ad Valorem Weight-Based Ad Valorem

$/ton3 percent $/ton percent $/ton3 percent
Mobile, AL 0.2714 0.17002 2.4548 1.53786 2.7262 1.70788
New Orleans, LA 0.1727 0.05067 0.4216 0.12372 0.5943 0.17439
Galveston, TX 0.1163 0.02556 0.8153 0.17922 0.9316 0.20478
Corpus Christi, TX 0.1945 0.10720 0.3128 0.17240 0.5073 0.27960
Brownsville, TX — — — — — —
Charleston, S.C. 0.6661 0.06229 1.0504 0.09823 1.7165 0.16052
Baltimore, MD 0.0620 0.01331 1.0979 0.22330 1.1599 0.23661
Toledo, OH 0.1568 0.21908 —— — 0.1-568 0.21908
Saginaw, Ml 2.9496 3.74800 — — 2.9496 3.74800
Chicago, IL 0.0766 0.06446 — — 0.0766 0.06446
Duluth, MN 0.0605 0.09565 0.0293 0.04632 0.0898 0.14197
Seattle, WA 0.0171 0.00224 0.3520 0.05240 0.3691 0.05464
Portland, OR 0.7137 0.25473 0.01270 0.00452 0.7264 0.24925
San Francisco, CA 0.3203 0.02711 3.9313 0.89572 4.2516 0.96871
Long Beach, CA 0.0021 0.00032 0.7356 0.11055 0.7377 0.11087
San Diego, CA —
Overall 16-port fee‘ 0.1688 0.04283 0.6172 0.15654 0.7860 0.19937
Uniform fee 0.2010 0.08361 0.4436 0.18452 0.6446 0.26813

‘User charge estimates for a 100 percent cost recovery level.

20M operation and maintenance costs, NC= new construction costs, OMNC=operation and maintenance costs plus new construction
costs.

3Short tons.
‘Weighted port-specific fee for 16 grain-shipping ports.

Table 7. Estimated Market Effects of Port-User Charges: Percent Changes in Quantities

Per-Unit User Charge Ad Valorem User Charge

Port-Specific Uniform Port-Specific Uniform
Commodity OM‘ NC OM , NC OM NC OM NC
Percent Changes in U.S. Foreign Demand (—)
Corn 0.095 0.347 0.113 0.249 0.030 0.109 0.058 0.128
Sorghum 0.118 0.433 0.141 0.311 0.037 0.136 0.073 0.161
Soybeans 0.035 0.128 0.042 0.092 0.023 0.086 0.046 0.101
Wheat 0.036 0.132 0.043 0.095 0.016 0.057 0.031 0.068
Percent Changes in U.S. Supply (—)
Corn 0.012 0.043 0.014 0.031 0.004 0.013 0.007 0.016
Sorghum 0.018 0.066 0.021 0.047 0.005 0.021 0.011 0.023
Soybeans 0.008 0.030 0.010 0.021 0.005 0.020 0.011 0.023
Wheat 0.014 0.050 0.016 0.036 0.006 0.022 0.012 0.026
Percent Changes in U.S. Domestic Demand (+)
Corn 0.024 0.086 0.028 0.062 0.007 0.027 0.014 0.032
“Sorghum 0.036 0.132 0.043 0.09s 0.011 0.042 0.022 0.049
Soybeans 0.011 0.040 0.013 0.029 0.007 0.026 0.014 0.031
Wheat 0.024 0.088 0.029 0.063 0.011 0.038 0.021 0.045

‘OM and NC denote operation and maintenance costs and new construction costs, respectively.

Lakes coastal areas where respective changes in flows
are 3.9 and -2.3 percent of the base solution. In the
Great Lakes area, Lakes Superior and Michigan gain

ain while Huron and Erie lose exports. Lakes Huron

. and Erie ports incur large operations and maintenance

expenses and handle a relatively small volume of
grain; and since weight-based fees are estimated by

dividing costs by tonnage, they have relatively large
user fees. (See Table 1 for procedure to calculate fees.)
Because of the relatively modest operations and
maintenance expenses at Atlantic ports and the associ-
ated small user charge, a portion of the grain originally
routed to Lakes Huron and Erie is rerouted to Atlantic
ports.

Table 8. Estimated Market Effects of Port-User Charges: Percent Changes in Price per Ton

Weight-Based User Charge Ad Valorem User Charge

w

Port-Specific Uniform Port-Specific Uniform
Commodity OM‘ NC OM NC OM NC OM NC
$/ton
International Market (+)
Corn 0.106 0.387 0.126 0.278 0.033 0.122 310.065 0.143 y...
Sorghum 0.063 0.229 0.075 0.165 0.020 0.072 ‘0.039 0.085
Soybeans 0.107 0.393 0.128 0.282 0.072 0.262 0.140 0.309
Wheat 0.056 0.203 0.066 0.146 0.024 0.089 0.047 0.104
U.S. Domestic Market (—)

Corn 0.080 0.293 0.095 0.211 0.025 0.091 0.049 0.108,.
Sorghum 0.123 0.451 0.147 0.324 0.039 0.142 0.076 0.168
Soybeans 0.079 0.288 0.094 0.207 0.053 0.192 0.102 0.226
Wheat 0.131 0.478 0.156 0.343 0.057 0.208 0.111 0.245

‘OM and NC denote operation and maintenance costs and new construction costs, respectively.

Table 9. Effect on U.S. Port Area Grain and Soybean Flows of a Weight-Based User Fee Which ls to Recoupe All
Operations and Maintenance Expenses (OM), New Construction Costs (NC), and the Aggregate of These
Costs (OMNC)1

Port-Specific Fees Uniform Fees

OM NC OMNC OM NC OMNC
Change Change Change Change Change Change
In Percent ln Percent In Percent In Percent ln Percent In Percent
Port Area Volume’ Change3 Volume Change Volume Change Volume Change Volume Change Volume Change
Gulf:
East Gulf - 0.05 - 0.03 -159.59 -83.34 -159.61 -83.35 - 0.1 -0.03 - 0.1 -0.07 - 0.2 -0.10
Mississippi River - 8.20 - 0.39 248.51 11.47 216.80 10.00 9.9 0.45 8.3 0.37 7.0 0.31
North Texas - 0.28 - 0.04 - 14.89 - 2.06 - 15.29 - 2.08 - 0.4 -0.05 - 0.9 -0.12 - 1.5 0.21
South Texas 0.01 0.02 0.88 1.20 0.88 1.23 0.0 0.00 0.0 -0.04 0.1 -0.08
Total - 8.55 - 0.27 74.89 2.38 42.75 1.36 9.5 0.30 7.3 0.23 5.3 0.17
Atlantic:
North Atlantic 22.74 4.19 -107.89 -19.89 - 60.44 -11.14 -10.5 -1.93 -12.6 -2.32 -14.3 -2.63
South Atlantic - 0.01 - 0.02 - 0.03 - 9.07 - 0.03 - 0.07 0.0 -0.01 0.0 -0.04 0.0 -0.07
Total 22.73 3.90 -107.92 -18.52 - 60.47 -10.38 -10.5 -1.81 -12.6 -2.16 -14.3 -2.46
Great Lakes:
Superior-Michigan 10.69 2.66 18.59 4.62 17.19 4.27 - 0.4 -0.10 - 0.4 -0.09 - 0.3 -0.09
Huron-Erie -25.77 -10.21 5.46 2.16 - 11.38 - 4.51 - 0.1 -0.03 - 0.2 -0.06 - 0.2 -0.08
Total -15.08 - 2.30 24.05 3.67 5.81 0.89 - 0.5 -0.07 - 0.5 -0.08 - 0.6 -0.09
Pacific:
Seattle Area 50.17 23.76 - 2.37 - 1.12 49.90 23.76 - 2.2 -1.04 - 2.3 -1.11 - 2.4 -1.15
Portland Area -52.43 -22.14 - 0.18 - 0.08 - 52.66 -22.14 0.0 -0.02 - 0.1 -0.04 - 0.2 -0.09
California 0.00 0.00 0.00 0.00 0.00 0.00 0.0 0.00 0.0 -0.03 0.0 -0.04
Total - 2.26 - 0.48 - 2.56 - 0.54 - 2.76 - 0.58 - 2.2 -0.47 - 2.4 -0.51 - 2.6 -0.55 ‘p
Total Port Exports‘ - 3.16 - 0.06 - 11.53 - 0.24 - 14.67 - 0.30 - 3.7 -0.08 - 8.3 -0.17 -12.1 -0.25 

‘Numbers at the coast level may not add up to totals due to rounding.
zMillion bushels.

3Percent change from baserun volume.
‘Overall reduction in U.S. grain exports resulting from increase in export price due to user charge imposition.

Even though there is only modest redirection of
flows to the various coastal areas, there is substantial
rerouting of grain among ports in coastal areas—in
particular, in the Pacific Northwest (interport flows).
The estimated port-specific user fee in the Seattle area
is about 5 percent of the Portland area fee; consequent-

8

1y, eastern Washington wheat is redirected (50 million
bushels) from the barge-served Portland port area and
routed to Seattle by railroad.
Port-specific user fees that are based on recovery o

new construction costs generate more dramatic
changes in flows than user fees based on operations

~

._ -v

l

Table 10. Effect on U.S. Port Area Grain and Soybean Flows of an Ad Valorem User Fee Which ls to Recoupe All
Operations and Maintenance Expenses (OM), New Construction (NC), and the Aggregate of These Costs

(OMNC)1
Port-Specific Fees Uniform Fees
OM NC OMNC OM NC OMNC
Change Change Change Change Change Change
ln Percent In Percent In Percent In Percent In Percent In Percent
Port Area Volumez Change3 Volume Change Volume Change Volume Change Volume Change Volume Change
Gulf:
East Gulf - 9.67 - 5.05 -45.66 -23.84 -180.34 -94.17 0.0 -0.03 - 0.1 -0.04 - 0.1 -0.06
Mississippi River 19.92 0.91 63.61 2.93 180.74 8.34 10.4 -0.45 9.3 0.42 8.4 0.38
North Texas - 0.56 - 0.08 25.27 3.49 9.41 1.30 - 0.2 -0.05 - 0.5 -0.07 - 0.7 -0.10
South Texas 0.00 0.00 0.00 0.04 0.01 0.05 0.0 0.00 0.0 0.01 0.0 -0.02
Total 9.68 - 0.31 43.21 1.37 9.79 0.311 10.1 0.30 8.7 0.28 7.6 0.24
Atlantic:
North Atlantic 6.43 1.18 -44.56 - 8.21 - 30.29 - 5.58 - 9.7 -1.78 -10.7 -1.99 -11.7 -2.15
South Atlantic 0.00 0.00 - 0.01 - 0.03 0.02 - 0.05 0.0 -0.02 0.0 -0.05 0.0 -0.06
Total 6.43 1.18 -44.57 - 7.65 - 30.31 - 5.20 - 9.7 -1.66 -10.7 -1.86 -11.7 -2.01
Great Lakes:
Superior-Michigan 10.68 2.65 - 0.42 - 0.10 23.16 5.76 - 0.4 -0.10 - 0.4 -0.10 - 0.4 -0.10
Huron-Erie -25.75 -10.20 - 0.08 - 0.03 - 5.53 - 2.19 - 0.1 0.02 - 0.1 -0.04 - 0.1 -0.06
Total -15.06 - 2.30 - 0.50 - 0.07 17.63 2.69 - 0.5 -0.07 - 0.5 -0.08 - 0.5 -0.08
Pacific:
Seattle Area 50.24 23.79 - 2.22 - 1.05 50.08 23.72 - 2.2 -1.02 - 2.3 -1.07 - 2.4 -1.11
Portland Area -52.41 -22.14 - 0.06 - 0.02 - 52.46 -22.16 0.0 -0.01 - 0.1 -0.03 - 0.1 -0.04
California 0.00 0.00 0.00 0.00 0.00 0.00 0.0 0.00 0.0 0.00 0.0 0.00
Total - 2.18 - 0.46 - 2.28 - 0.48 - 2.38 - 0.50 - 2.2 -0.46 - 2.4 -0.49 - 2.5 -0.51
Total Port Exports‘ - 1.13 - 0.02 - 4.14 - 0.08 - 5.27 - 0.11 - 2.2 -0.05 - 4.9 -0.10 - 7.1 -0.15

‘Numbers at the coast level may not add up to totals due to rounding.

2Million bushels.
aPercent change from baserun volume.

‘Overall reduction in U.S. grain exports resulting from increase in export price due to user charge imposition.

and maintenance costs. Since a port's operation and
maintenance expense and capital expenditure on new
deep-draft facilities are not directly related, a different
flow pattern scheme often exists. Port areas in the
Great Lakes are scheduled for less investment on new
deep-draft facilities. As a result, they tend to benefit
from imposition of a port-specific fee based on these
costs. This is particularly true for the Lake Superior-
Michigan area. The Atlantic port area loses grain
volume to Lake and Gulf ports, with the North Atlan-
tic area bearing most of the volume loss. The North
Atlantic ports have been approved for new construc-
tion activity, thus a user fee designed to recover these
costs would direct grain from this area.

Imposition of a port-specific user fee which recovers
new construction costs increases Gulf coast export
volume by about 2 percent, or 75 million bushels. Of
more interest, however, is the altered interport com-
petition within the Gulf coast area. Most Mississippi
River and North Texas (Houston-Galveston area) port
areas increase their volume at the expense of East Gulf
ports. The East Gulf ports have been approved for
new construction and the resulting user fee is proj-
ected to redirect nearly 160 million bushels of corn and

. soybeans from this port area. This grain is redirected

to Mississippi River ports which are projected to
increase export volume by 248 million bushels. A

portion of this increased grain volume is rerouted
from Atlantic coast ports.

User charge scenarios which assume the combined
recovery of operations and maintenance and new
construction expenses yield somewhat different re-
sults than those based on recovery of either cost. In
some coastal areas, altered grain flows resemble those
already discussed, whereas in others, there appears to
be little relationship. This is not surprising since the
aggregated magnitude of the operations and mainte-
nance and new construction expenses may be similar
or quite different than a user charge based on a
particular cost. For instance, the Lakes port area has
virtually no projected expenditures for new construc-
tion, but has comparatively large operations and
maintenance costs; thus, when all costs subject to
recovery are combined, the resulting user charges are
comparable to those of other ports.

Due to its relatively high port user fees, Atlantic
ports lose about 10 percent of their base volume when
fees incorporate full recovery of all costs. In all other
coastal port areas, flows are altered about 1 percent or
less. Changes in interport flows are, in some cases,
substantial and in most cases, similar to those gener-
ated by user fees designed to recover new construc-
tion costs.

Weight-Based, Uniform User Fee

Weight-based user charges which are uniformly
applied to all U.S. ports have a small affect on inter-
coast and interport competition (Table 9). In all cases,
Lake ports suffer minor grain losses to Gulf ports,
regardless of the recovered cost. This outcome con-
firms the belief of some legislators that uniform fees
would leave port competition and port volumes undis-
turbed.

Ad Valorem-Based, Port-Specific User Fee

Table 10 reports alterations in grain flow patterns
that arise from introduction of an ad valorem-based
user charge. Ad valorem-based user fees are generally
different in magnitude than weight-based fees, since
they are based on value of exports transshipped
through a port. Thus, the product mix of a particular
port is an important factor determining the magnitude
of this fee. The effect of an ad valorem-based fee is
made more complex since each grain has a different
value, and as a result, ocean shipping rates are unique
to the commodity being shipped.

Port-specific fees designed to recover port area's
operations and maintenance expenses do not serious-
ly alter flows (Table 10). Atlantic and Gulf coast ports
experience modest increases in grain export volume,
whereas the Lake and Pacific coast port areas suffer
losses. Interport competition is relatively modest in all
coastal areas with the exception of the Pacific North-
west. Seattle and Portland ports are sensitive to ad
valorem-based user fees, even though the changes in
relative ocean freight rates from these port areas to
foreign destinations are comparatively small. In the
Gulf, small quantities of the East Gulf ports’ grain
volume is redirected to the Mississippi River port area,
whereas ports located in the Lake Huron-Erie area
lose export grain while Lakes Superior and Michigan
gain volume.

Port-specific user fees that seek to recoupe new
construction costs would leave flows to various coastal
areas largely unchanged. The exception is the Atlantic
Coast which would lose about 8 percent of its grain
shipments. Interport competition within the Gulf area
is altered at both Mississippi River and North Texas
ports where export volume increases, while sizable
losses are incurred by the East Gulf ports.

Port-specific fees which incorporate the aggregated
operations and maintenance and new construction
fees do not redirect grain from one coastal area to
another; however, grain is redirected among ports in a
particular coastal area (Table 10). In the Gulf area, East
Gulf ports experience a dramatic loss of grain exports,
whereas Mississippi River ports’ volume increases 8
percent or about 180 million bushels. In the Great
Lakes, the Lake Superior-Michigan area has the ad-
vantage over Huron-Erie ports because of the com-
paratively low level of costs subject to recovery; thus,
the former increases its volume by about 6 percent,
while the latter faces a loss of nearly 3 percent. Again,
Seattle's export volume increases with imposition of
the ad valorem-based, port-specific user fee by divert-

10

ing grain exports from Portland. Losses in the Atlantic
Coast are constrained to the North Atlantic area.

Ad Valorem-Based, Uniform User Fee

Ad valorem-based, uniform user fees seem to pro-
vide little change in grain export flow patterns, as was
the case with weight-based, uniform charges (Table
10). In all cost recovery schemes, the Atlantic port area

would be the most affected, though the impact is 

relatively inconsequential.

Altered Flows and Port Elevator Capacity

Five port areas emerged as experiencing increased
volumes under the various user charge scenarios.
These include the Mississippi River, Seattle, Lake
Superior-Michigan, North Texas, and North Atlantic
port areas.

The Mississippi River port area is the most impor-
tant grain outlet in the nation, accounting for up to 40
percent of U.S. agriculture’s grain exports. Depend-
ing on the user fee scenario analyzed, increases in
export volumes range from 19 to 248 million bushels of
grain, which represent percentage increases relative
to the base solution of 0.9 and 11.5 percent, respective-
ly. Historical year-to-year (positive) variation of export
grain volume in this area ranged from 6.2 percent in
1978-79 to 11.4 percent in 1979-80, suggesting that
even an increase of 248 million bushels (11.5 percent)
might be handled by Mississippi River ports. Howev-
er, such an increment would require maximum utiliza-
tion of port elevator capacity. Research by Barnett,
Binkley, and McCarl showed that the Mississippi River
port area operates up to 59 hours per week in peak
volume months. This suggests that the extra volume
generated by the user fees may be handled by in-
creases in hours worked per week. It is estimated that
the Mississippi River's port facilities would need to
operate an additional 12 hours per week to accommo-
date this outflow. In summary, the Mississippi River
port area would probably be able to handle the large
increase in exports brought about by imposition of a
port-specific, weight-based user fee, however, there
may be additional congestion during peak export
periods.

The Seattle area is an important outlet for export-
destined corn and soft, hard, and durum wheats. The
analysis shows Seattle to increase its grain exports
(wheat) by nearly 5O million bushels at the expense of
Portland when user fees are imposed to cover opera-
tions and maintenance costs. Since this yields a total
outflow which approximates some historical levels,
the additional volume should not respresent a threat
to system efficiency.

The analysis shows the Lake Superior-Michigan
port area to increase grain exports about 6.0 percent
above the base volume if a port-specific, ad valorem-
based fee, which is designed to cover operations and
maintenance and new construction costs, were in-

troduced. This maximum increase could be accommo- 

dated by operating facilities an additional 3 hours per
week. Therefore, this modest increase could be ac-

comodated by existing port elevator capacity.

North Texas ports were shown to experience grain
volume increases that range from 1.30 to 4.85 percent
of the base volume. The generated variation in flows is
generally less than the year-to-year variation and
based on estimated port area capacity, the maximum
flow could be accommodated by operating facilities an
additional 2 hours per week.

The North Atlantic port area is an outlet for U.S.
produced soybeans and corn and is a competitor of
Great Lake ports. The analysis shows a port-specific
fee (weight-based), including only operations and
maintenance costs, to redirect grain to this port
area—the maximum increase is estimated to be 23
million bushels or about a 4 percent increase. This
additional volume could be accommodated by operat-
ing port infrastructure an additional 2 hours per week.
Since no port elevators in this area appear to operate
more than 40 hours per week, there would seem to be
few capacity problems (Barnett, Binkley, and McCarl).

The additional annual variation in flows generated
by imposition of port user charges is generally smaller
than the historical year-to-year variation in flows and,
in most cases, the modest increase in flows can be
accommodated with increases in operating hours. The
exception may be the Mississippi River port area,
where infrastructure would need to operate an addi-
tional 12 hours per week if a port-specific user fee
designed to recoupe 100 percent of new construction
costs were introduced

Summary and Conclusions

The purpose of this study is to assess some of the
effects of a proposed deep-draft user fee. User charge
scenarios are generated to include the major features
of legislation presented to Congress in the past several
years. The analysis focuses on weight- and ad
valorem-based charges which may be applied on a
uniform or port-specific basis. In addition, the analysis
examines the effect of recovering the various types of
expenses—these include ports’ operations and
maintenance expenses and new construction costs.

Based on recent legislative proposals, various forms
of the user fee are estimated. Then, with use of a
multiperiod, network flow model, possible changes in
grain flow patterns are analyzed. The model
minimizes grain handling, storage, and transfer costs

Qwhich include truck, rail, barge, and ocean shipping

costs. The model is international in scope and includes
165 U.S. domestic grain surplus regions, 85 domestic
grain deficit regions, 43 river points, and 16 represen-
tative U.S. grain shipping port areas which are linked
to 25 foreign demand regions.

In general, the-analysis shows the most likely port
user fee for grain and soybeans to be small. At most
grain ports, either weight- or ad valorem-based fees
which recover operations and maintenance expenses

@would be less than $0.01 per bushel. If charges de-

signed to recoupe authorized new construction and
maintenance expenses were implemented, charges
would average about $0.02 per bushel. Although the

average fee is relatively small, there is substantial
variation among ports. This is because (1) operations
and maintenance expenses differ among ports; (2)
only selected ports have been authorized for new
construction; and (3) the volume and value of com-
merce transitting the various ports differ.

The least-cost analysis shows grain flow patterns to
be affected most by the form of the user fee (uniform
vs. port-specific) and, to a lesser extent, by the basis
for levying the fee (weight vs. value). Results indicate
that uniform fees, both weight- and ad valorem-
based, alter flows least. In essence, uniform fees leave
flow patterns unchanged. The principal flow pattern
disruptions are limited to port-specific fees. And, in
general, the port-specific, weight-based fee yields
greater flow pattern changes than the ad valorem-
based fee; however, the general effect of either user fee
is similar. Because grain is relatively low-valued, the
share of the ad valorem-based user cost borne by grain
is small as compared to a user fee based on grain
weight.

It is difficult to generalize regarding the effect of user
fees designed to recoupe the various types of costs.
These costs include ports’ operations and mainte-
nance costs, improvement or new construction expen-
ditures, and the aggregate of these costs. The most
dramatic change associated with a user fee designed to
recover operations and maintenance costs is a port-
specific, weight-based user fee which would reroute
about 20 percent of Portland's historic volume to
Seattle. When new construction costs are incor-
porated into this type of user fee, several relatively
dramatic changes in flows occur. In particular, East
Gulf and North Atlantic ports lose 160 (83 percent) and
108 (20 percent) million bushels, respectively, while
Mississippi River ports increase their outflow by 248
million bushels, or about 11 percent. A port-specific,
weight-based user fee which covers the aggregated
operations and maintenance and new construction
costs yields flows that are similar to those generated
by a user fee which is based on new construction. In
general, most of the major changes in flows are limited
to flows within a coastal area (interport) rather than
flows between coastal areas.

In many cases, a port's advantage or disadvantage
that would result from imposition of a user fee is small
and, in the short run, a disadvantaged port's infra-
structure may absorb some of the user fee. Therefore,
the least-cost methodology employed in this study
may tend to overestimate altered flows. It is important
to note that the analyses assumed peak export levels
which approximated those of the 1980-81 period.
Therefore, the magnitude of altered flows is increased
and the pressures on port intermodal capacity possi-
bly overstated. Regardless, an effort was made to
determine whether port area intermodal transfer
capacity was adequate. In most cases, port area inter-
modal transfer capacity was adequate. The exception
may be the Mississippi River port area which may
have inadequate capacity to handle an additional 248
million bushels. This additional volume is projected to
occur through imposition of a port-specific, weight-

11

based fee which recoupes new construction costs.
In summary, the port user fee will not have a major
effect on agriculture since the estimated unit fee is
quite small. The magnitude of the user fee is closely
associated with the amount of the charge to be re-
covered and the volume or value of freight transitting
the port. In most cases, a port's relative cost advantage
or disadvantage that results from imposition of a user
charge is not large. Therefore, in the short run, a port's
cost disadvantage is likely to be partially absorbed by
lowering the rate of return on capital investment, thus
minimizing abrupt disruptions in trade flows.

Literature

A. T. Keamy, Inc. Unpublished study carried out for Inter-
state Commerce Commisssion (contract ICC 78-C-0006)
which involved analysis of 1977 One Percent Waybill

. sample.

Adams, Brian D. and Dale G. Anderson. Implications of the
Staggers Rail Act of 1980 for Level and Variability of Country
Elevator Bid Prices. Paper No. 7825, Journal Series, Nebras-
ka Agricultural Experiment Station, 1985.

Barnett, Doug, James Binkley, and Bruce McCarl. ”Port
Elevator Capacity and National and World Grain Ship-
ments." Western Journal of Agricultural Economics. 9(1984):
77-89.

Barr, T. N. Demand and Price Relationships for the U.S. Wheat
Economy. U.S. Department of Agriculture, Economic Re-
search Service, WS-226, November 1973.

Board of Governors of the Federal Reserve System. Federal
Reserve Bulletin. Washington, D.C., Various issues.

Bredahl, Maury E. and Leonardo Green. "Residual Supplier
Model of Coarse Grain Trade." Americal Journal of Agricul-
tural Economics 65(1983): 785-790.

Bredahl, Maury E. William H. Meyers, and Keith J. Collins.
”The Elasticity of Foreign Demand for U.S. Agricultural
Products: The Importance of the Price Transmission Elas-
ticity" American Journal of Agricultural Economics 61(1979):
58-63.

Cooper, S. Kerry and Donald R. Fraser. The Financial Market-
place. Reading, Massachusetts: Addison-Wesley Pub-
lishing Company, 1982.

Cramer, Gail L. and Walter G. Heid, Jr. Grain Marketing
Economics. New York: John Wiley and Sons, 1983.

Friedlaender, Ann F. The Dilemma of Freight Transport Reg-
ulation. The Brookings Institution, Washington, D.C.,
1969.

Fuller, Stephen and Chiyyarath Shanmugham. "Network
Flow Models: Use in Rural Freight Transportation Analy-
sis and a Comparison with Linear Programming.” South-
ern Journal of Agricultural Economics 10(December, 1978):
183-188.

Fuller, Stephen, Larry Makus, and William Gallimore. ”Ef-
fects of Increasing Panama Canal Toll Rates on U.S. Grain
Exports.” Southern Journal of Agricultural Economics.
16(1984): 9-20.

Fuller, Stephen W., Larry Makus, and Merritt Taylor. "Effect
of Railroad Deregulation on Export-Grain Rates.” North
Central Journal of Agricultural Economics 6 (January, 1983):
51-63.

Grennes, Thomas, Paul R. Johnson, and Mary Thursby. The
Economics of World Grain Trade. New York: Praeger Pub-
lishers Co., 1978.

Hauser, Robert. Unpublished Working Papers, Iowa State
University, 1981.

Hillman, Jimmy. “Policy Issues Relevant to United States

12

Agricultural Trade." Imperfect Markets in Agricultural Trade.
Ed. Alex McCalla and Timothy Josling, pp. 113-142.
Montclair, N .J.: Allanheld, Osmun & Company, 1981.

Interstate Commerce Commission, Bureau of Accounts. 

Carload Cost Scales, 1977. Washington, D.C.: Statemen
No. 1C1-77, November 1979.

Interstate Commerce Commission, Bureau of Accounts.
Uniform Railroad Costing System. Washington, D.C.: De-
cember 17, 1982.

Johnson, Paul R. "The Elasticity of Foreign Demand for USN
Agricultural Products." American Journal of Agricultural
Economics 59(1977): 735-766.

Kendall, P. M. H. "A Theory of Optimum Ship Size." Journal
of Transport Economics and Policy. 2(1972): 128-146.

Klindworth, Keith A., Orlo Sorenson, Michael W. Babcock,
and Ming Chow. Impacts of Rail Deregulation on Marketing of
Kansas Wheat. U.S. Department of Agriculture, Office of
Transportation, September 1985.

Leath, Mack. Unpublished Memorandum on Elevator Cost,
University of Illinois, 1982.

Leath, Mack N. and Leo Blakely. An Interregional Analysis of
the U.S. Grain Marketing Industry, 1966-67. Washington,
D.C.: U.S. Department of Agriculture, Economic Re-
search Service, TB-1444, November 1971.

Leath, Mack N. and Lowell D. I-Iill. Grain Movements,
Transportation Requirements, and Trends in the United States
Grain Marketing System: Patterns During the 1970s. North
Central Regional Research Publication No. 288, Universi-
ty of Illinois at Urbana-Champaign, 1983.

Leath, Mack N ., Lowell D. Hill, and Stephen W. Fuller.
Sorghum Movements in the United States. Illinois Bulletin
No. 765, University of Illinois, January 1981a.

. Soybean Movement in the United States. Illinois Bulle-
tin No. 766, Universtiy of Illinois, January 1981b.

- . Wheat Movements in the United States. Illinois Bulletin
No. 767, University of Illinois, January 1981c.

Lloyds of London Press Inc. Lloyds 1984 Ports of the World.
Essex, United Kingdom.

Longmire, Jim and Art Morey. Strong Dollar Dampens Demand
for U.S. Farm Exports. U.S. Department of Agriculture,
Economic Research Service, Foreign Agricultural Eco-
nomic Report No. 193, December 1983.

McCalla, Alex. "Pricing in the World Feed Grain Market."
Agricultural Economic Research. 19(1967): 93-102.

Makus, Larry and Stephen Fuller. ”Location Shifts in U.S.
Export Grain Demand and Their Effect on the Export
Marketing System." Agribusiness: An International Journal.
(Forthcoming).

Makus, Larry D. "Sensitivity of U.S. Port Market Areas to
Changing World Demands for Grains and Soybeans."
Ph.D. Dissertation, Texas A&M University, December
1983.

Milling and Baking News. 1982 Milling and Grain Directory.

1982. Q,

Paarlberg, Donald. Farm and Food Policies: Issues of the 1980's.
Lincoln, Nebraska: University of Nebraska Press, 1980.

Paggi, Mechel. "A Strong Dollar Hinders Agricultural
Exports." Texas A&M University, Food and Fiber Economics,
ECO, Vol. 12, No. 9, October 1983.

Rand McNally 8: Company. Handy Railroad Atlas of the United
States. Chicago, Illinois, 1978.

Rausser, Gordon C., Ed. New Direction in Econometric Model-
ing and Forecasting in U.S. Agriculture. New York: North-
Holland Publishing Company, 1978.

Ray Daryll E. and James W. Richardson. Detailed Descriptio;  I
of POLYSIM. Oklahoma Agricultural Experiment Station%

Oklahoma State University and U.S. Department of Agri-
culture, 1978.

Taylor, Merrit J. ”A Model to Analyze the Export Grain
Transportation System." Ph.D. Dissertation, Texas A&M
University, May 1982.

~18. Army Corps of Engineers. Deep-Draft Navigation Cost

Recovery Analysis. U.S. Army Corps of Engineers Office,
Chief of Engineers Directorate of Civil Works Office of
Policy, Washington, D.C., 1982.

.Towboat and Barge Operating Costs. Ft. Belvoir, Vir-
ginia, January 1983.

%U.S. Department of Agriculture. Annual Voyage Charter

Rates, 1977-1982, Tape data base, Washington, D.C., Eco-

nomic Research Service, 1983.

.An Assessment of Impacts on Agriculture of the Staggers

Rail Act and Motor Carrier Act of 1980. Washington, D.C.,

Office of Transportation, August 1982a.

.Grain Market News. Agricultural Marketing Service,

Various Issues, 1970-84.

.National Interregional Agricultural Projections. Wash-

ington D.C., Economic Research Service, 1980.

.11 .S . Foreign Agricultural Trade Statistical Report,
Calendar Year 1983. Washington, D. C. , Economic Research
Service, April 1982b.

U.S. Department of Commerce. United States Port Develop-
ment Expenditure Survey. Washington D.C., Maritime Ad-
ministration, Office of Port and Intermodal Development,
January 1980.

.Nati0nal Port Assessment 1980/1990. Washington

D.C., Maritime Administration, Office of Port and Inter-

modal Development, June 1980.

foreign Production, Supply and Distribution of Agricul-

tural Commodities (Tape). National Technical Information

Service, Springfield, Virginia, 1984.

Appendix I. Technical Discussion
of Methods and Procedures

Procedure to Estimate the Effect
of User Charges on Grain Trade

Market effects of both weight- and ad valorem-
based user fees are similar with respect to the direction
of change, but differ in magnitude (Figures 2 and 3).
Major effects include an increase in the price of U.S.
grain to foreign buyers and a subsequent decline in
quantity traded. In the U.S. domestic market, price is
lowered and quantities supplied and demanded de-
crease and increase, respectively. The purpose of this
section is to develop a mathematical procedure which
will allow one to obtain quantitative estimates of these
effects.

 Effect of Weight-Based Port User Charges

In this subsection, algebraic expressions which can
be used to estimate the market effect of weight-based
user charges are derived. Market effects involve
changes in prices and quantities traded both in the
internaitonal market, and the U.S. domestic market.

Changes in Prices and Quantities Traded
in the International Market

Under the assumption of free trade and linear
narket relationships, let

(1a) Q56 = a +b P8, b>o

and
(1b) Qiie=c+d Pe , e20 and d<0

be the supply and demand equations in the exporting
country's (United States) domestic market, and let

(2a) Qiii=g+h Pi , gzO and hsO
and
(2b) Qsi=j +k Pi , k>0

be the demand and supply equations in the ”aggre-
gate” importing country's (Rest-of-the-World or
ROW) domestic market. Qse and Ode are the quantities
supplied and demanded, and Pe is the price in the
exporter’s market, while Qsi, Qdi, and Pi represent
quantities supplied and demanded and price in the
ROW markets, respectively. The letters a, b, c, d, g, h,
j, and k respresent constants.

Using the "excess supply-excess demand" ap-
proach, the following expressions are obtained by
subtracting (lb) from (1a), as well as (2b) from (2a):

(3a) ES=A+B Pe, B20
and
(3b) ED=G+D Pi , D<O and G20

where A=a—c; B=b—d; G=g—j; and D=h—k; and
where ES and ED are the quantites supplied and
demanded in the international market, respectively.

Equilibrium conditions in the international market
require that ES = ED = Q and Pe = Pi = P. Substitut-
ing these requirements into (3a) and (3b) and solving
for P yields,

(4) p: 
B—D

Introducing the weight-based transportation rate, t,
into equation (3a) results in

(5) ES=A—Bt+BPe.
The new equilibrium price P* in the international trade

market is obtained by solving equations (5) and (3b),
under the same equilibrium conditions as above,

G-A-l-Bt

(6) I”: B—D

and the price differential is

(7) P=P*—P=

13

(a) (b) (c)

liwiri.

P P P S.
G?
De ES‘
5e

,,~ X ES ,.*
P P P
P’ P’ X

ED oi
/

i t i t
"up “in "IQ “a Q ° ° Q oSi oSi “m "in Q
Exporting Country International Trade Importing Country

Figure 2. Effect of per-unit increases in transportation costs on international trade.

(n) (b) (c)

P P P ‘i
cs“
De
Se \
ES
P‘!
P P” P
P0 P0 /
[D
"a
/
ode 0.1;! 0:005: o o‘ o o on“; oiil 01h 0
Exporting Country International Trade Importing Country 

Figure 3. Effect of ad valorem increases in transportation costs on international trade.

14

R

‘Ni

‘W! 

R

where,

0s i s1.
B-D

From the equality of ES and ED, it follows that (7) can
also be expressed in elasticity terms as

Ees
(8) P = t,
Ees _ Eef

for small t, where Ees and Eef are the elasticities of
excess supply and excess demand, respectively.
By definition and since Q = ED = ES,

=lQ_l1
 Eef P Q
and
<10) 3 =E.f 

Substituting (8) and (10) yields,

Q _ E Ees t
i — ef __-
Q Ees _ Eef P

Expression (11) allows one to approximate the" per-
centage change in quantity demanded (imports) by
the ROW market due to the inclusion of transportation
rates in the analysis.

(11)

Changes in Prices and Quantities Traded
in the Exporters Domestic Market

Figure 2 shows that price in the exporting country
(the United States) is lowered, quantity supplied
decreased, and quantity demanded increased when a
transportation rate is introduced. The price change
can be obtained from (8). P refers to the increase in
price faced by the importing country. The price de-
crease in the exporting country can be expressed as
follows. The amount of the tax t is composed of two
components, (P*—-P) and (P—P°). By definition, the
negative of this latter term, (P° — P), is equal to P", the
change in price in the exporting country. The former
term is simply P. Hence,

Q2) P°=(P“—P)=(P—t)= [E ESE ]t
__ es- ef

upon substitution of (8) and rearranging. The negative
expression in (12) reflects the price decrease in the
exporting country The percentage change in domestic
quantity demanded by domestic consumers with in-
troduction of a weight-based transportation rate fol-
lows from the definition of the elasticity of domestic
demand:

E9; t
(13) = Ede —.
Qde Ees _ Eef P

Using a similar procedure, the change in quantity
supplied in the exporter’s domestic market, for a
weight-based transportation rate, can be expressed as

follows:
11.. E“ l.
Ees _ Eef P

Effect of Ad Valorem PortUser Charge

 Q58 __

d. '

The purposes of this subsection are the same as in
the case of a weight-based user charge. Again, free
trade and linear market relationships are assumed.

Changes in Prices and Quantities Traded
in the International Market

The starting point of this analysis is given by the
excess supply and demand equations as specified in
the previous section:

(3a) ES = A + BPe

ow ED=G+DR.

Introducing the ad valorem user charge, t, into equa-
tion (3a) yields

ES=A+ B Pe

U3 u+n

since the excess supply curve pivots upward on the
price axis (Figure 3).

Solving (15) and (3b) for the after-user charge
equilibrium price results in

(16) P* =  (1 + t).
Since
G — A

<4) P - Bi?

then

(17) Pi: (B—D)(1+t)

P B—D(LH)'

But since AP = P* — P, then

aw --=--=--r

15

Substituting (17) into (18) yields

AP = (B—-D)(1+t) _1

(19) P B—D (1+t)

which expressed in elasticity terms yields,

AP Eest
(20) =
P Ees _ Eef(1 + t)

which provides an equation to approximate the per-
centage change in world market prices.

From the definition of the elasticity of U.S. export
demand, the percentage change in quantity demand-
ed in the world market is given by

AQ AP
(21) — = Eef—,
Q P a
which, upon substitution of (20) and (21), can be
reduced to
AQ Eest
(22) —— =Eef —————— -
Q Ees _Eef  + t)

Changes in Prices and Quantities Traded
in the Exporters Domestic Market

The change in price given by equation (19) corre-
sponds to a price increase in the importer market
(ROW). To obtain the price decrease in the United
States, however, it is necessary to isolate AP°. In
Figure 4, an enlargement of triangle abc (Figure 3) is
illustrated.Notice that AP° can be expressed trigono-
metrically as a function of AQ and B:

_AQ

23) — .
( tan B

AP°

But tan B is the slope of the excess supply function,
and thus, tan B=Ees Q/P, from the definition of Ees.
Substitution and rearranging yields

AP° _ 1 AQ
P Ees Q '

From the definition of the elasticity of U.S. domestic
supply,

(24)

A Se AP°
<25) Q =ES.—-.
Q88 P

Substituting (22) into (24) and that result into (25)
yields

A se EseEe Ees
(26) Q = ‘ t .

Qse Ees Ees _ Eef(1 + t)

16

Figure 4. Enlargement of the effects of an ad valorem
increase in transportation costs on international trade.

Similarly, for the change in quantity demanded,

 AQde = EedEef [

Eest

de Ees Ees — Eef(1 + t) i

Determination of the effect of port user fees on grain
trade at all levels requires the estimation of U.S. export
demand and U.S. excess supply elasticities. The pro-
cedures used to obtain these elasticities are discussed
in the next subsection.

Elasticity Estimation Procedure

Evaluation of the effect of the user charge on grain
export flow patterns requires the use of the grain
transportation models described in Section III. These
models utilize as input data the changes in foreign
demand by world subregion or country. Although the
mathematical expressions derived above provide an
approximate means to estimate percentage changes in
quantity demanded by the ROW market, they repre-
sent aggregate estimates. Consequently, disag-
gregated estimates by world subregion must be pro-
cured. Moreover, the utilization of such expressions is
contingent upon the availability of elasticities for both
the U.S. grain export (excess) demand and excess
supply functions. A description of the procedures
used to obtain these elasticities follows.

M

7K

The Elasticity 0f U.S. Grain Export Demand

Bredahl, Meyers, and Collins developed a proce-
dure to estimate U.S. export demand elasticities for
corn, sorghum, wheat, soybeans, and cotton. Their
procedure is of interest to this study because the
elasticity estimates are derived by adding the indi-
vidual contributions of seven world subregions or
countries to these elasticities. Essentially, their esti-
mates were a function of the exporting countries’
excess-supply elasticities, excluding the United States,
the importing countries’ excess-demand elasticities,
and the elasticities of price transmission (Epi or Epj).
The latter was defined as the percentage change in the
price of a commodity in the jth exporting country (or
ith importing country) with respect to a percentage
change in the U.S. price. Bredahl, Meyers, and Col-
lins’ analysis was carried out under two basic assump-
tions. First, the United States was treated as a residual
supplier to the world markets; and second, it was
hypothesized that price insulating policies exerted by
both exporter and importer countries to protect their
domestic agricultural sectors have a major influence
on the U.S. export demand elasticity. The treatment of
the United States as a residual supplier implies that (1)
grain exports of other countries are not responsive to
world prices, (2) prices and volumes exported by
competing countries are not simultaneously deter-
mined with those of the United States, and (3) U.S.
exports and production do respond to world prices of
agricultural commodities (Bredahl and Green). The
notion of the United States as a residual supplier has

been sustained by many economists (McCalla; Harri- i

son; Paarlberg; and Hillman). Bredahl and Green
tested these hypotheses and their findings indicate
that the treatment of the United States as a residual
supplier is justified for commodities such as corn and
other coarse grains.

Price-insulating policies which fix domestic prices
are commonplace. The notion is that the magnitude of
the elasticity of price transmission between a given
country and the United States depends upon the
extent of price insulation exerted by that country.
Under a free trade assumption, which implies absence
of trade barriers, the elasticity of price transmission
has a value of 1. In contrast, a highly regulated
international market would induce near zero elas-
ticities of price transmission.

Bredahl, Meyers, and Collins express the elasticity

p of U.S. export demand as follows:

 Eef =  Epi EediQmi—  Epj Eesj 
1 ef ] ef
with
<29) E...= (Edi-Esi) Q“ + E.
and

Q .
Eesj = (Esj _Edj) l + Ej,

mi

(39)

where:

Epi = elasticity of price transmission of ith import-
ing region and is defined as the response of
domestic price in the ith country to a change
in U.S. price.

Epj = similar to Epi but for the jth exporting region,
other than the United States.

Eedi = elasticity of the ith importing region's excess

demand.
Eesj = elasticity of the jth exporting region's excess
supply. .
Edi = ith importing region's elasticity of domestic
demand.
Esi = ith importing region's elasticity of domestic
supply.
Edi = jth exporting region's elasticity of domestic
demand.
Esj = jth exporting region's elasticity of domestic
Supply-
Qmi=ith region's imports of grain from all coun-
tries.

Qxj = jth region's exports of grain to all countries.
Qef=U.S. grain exports.
Qdi, Qdj =quantities of grain demanded in the ith and
jth regions, respectively.

Notice that when Epi (the elasticity of price transmis-
sion associated with importer countries) approaches
zero, Ee; (the U.S. export demand elasticity) becomes
more inelastic. A similar argument holds for Epj (the
elasticity of price transmission of exporter countries).
Bredahl, Meyers, and Collins obtained three sets of
U.S. export elasticities for the commodities mentioned
above, under three different trade assumptions, for
seven world regions. Based on analysis of the most
common price-insulating policies exerted by both ma-
jor exporting and importing world regions, values of
the respective price transmission elasticity were hypo-
thesized for each region. The first case, labeled as the
minimum restricted case, assumed that Epi for the
ROW region, which included mostly third world
countries was zero. The remaining regions, including
ECC-9, Other Western Europe, Eastern Europe, Ia-
pan, Russia, and the People's Republic of China, are
treated separately based on their own policy situation.
The second case, labeled as the maximum restricted
case, assumed ROW’s elasticity of price transmission
as unity; this case was considered by the authors as
probably the more realistic. The third case, referred to
as the free trade case, assumed Epi’s for all seven
regions as unity.

For more current U.S. export demand elasticities for
grain and soybeans, a tape by the National Technical
Information Service (U.S. Department of Commerce)
containing supply and distribution data was used.
Data used in this study covers 1977-78 through 1982-
83. Elasticity estimates are calculated under the max-
imum restricted and the free trade cases. The elas-
ticities of price transmission used here are based on

17

Table 11. U.S. Domestic Supply and Demand Elas-
ticities "

Supply Demand
Commodity Elasticity Elasticity
Corn 0.2 0.40
Sorghum 0.2 0.40
Soybeans 0.2 0.40
Wheat 0.2 0.35

Sources: Paul R. Johnson; Daryll E. Ray and James W. Richardson.

Bredahl, Meyers, and Collins’ policy analysis. Elas-
ticity estimates for U.S. domestic supply and demand
are based on a historical analysis made by Ray and
Richardson and on elasticities used by Johnson (Table
11). The elasticities chosen for this project do not
pertain to any specific author or empirical study,
rather they fall within the range of elasticities pre-
sented by most authors. Domestic supply and de-
mand elasticities for the 25 world regions, specified in
the network flow models, are those assumed by
Johnson; i.e., supply elasticities of all commodities are
assumed 0.2, demand elasticities are assumed -0.2 for
wheat and -0.4 for feed grains and soybeans in each
world region.

Despite the fact that data from a different time
period was used, the reported elasticities (Table 11)
differ only slightly from those of Bredahl, Meyers, and
Collins, whose estimates are provided on the last row.
Table 12 also provides the contribution of each world
region to the total U. S. export demand, by commodity.
These contributions are used to estimate the changes
in foreign demand for 25 world regions specified in the
grain transportation models.

Changes in quantity demanded by individual
foreign regions are obtained through disaggregation
of (11) and (22). In the case of a weight-based user
charge, this is done by substituting (28) into (11) as
follows:

A9: . 521a . .% ..
  EpiEedi Q 2 Ep)Ees] Q :|

mi x' P
Ees _  Epi Eedig +  Epj Eesj "Q*l'
1 C2 1 C2

where Q9; is replaced by Q. Expansion of the summa-
tions in (31) to the nth term yields, in abbreviated
form:

§Q=AQ1+AQz+ +AQn

Q Q Q  Q

where the terms on the right side represent the
percentage changes in quantities demanded by indi-
vidual world subregions.

A similar procedure is used in the case of an ad
valorem user charge (not shown). Because of the large

18

(32)

number of user charge scenarios, estimates for
changes in quantity demanded by foreign region are
not reported.

W

The Elasticity of U.S. Excess Supply

The procedure to estimate the elasticity of U.S.
excess supply is derived as follows:

Let  Q
 ef = Qse _ Qde
differentiation with respect to P yields

dQef = d-Qse _ dQde
dP dP dP

(34)

multiplying by P/Qef and rearranging terms,

P .dQef=dQse. P .Qse.dQde. P ‘Qde

(35)
Pef  I I  QseI Qef  Qde Qef
I l
Ees Ese Ede
which can be expressed as,
Qse Q e
 Ees = Ese _ Ede d
Qef Qef
division of (33) by Qef yields,
 _Q_e_f = Qse _ Qde = 1
Qef Qef Qef
solving (37) for QSe/Qef and upon substitution into (36),
Q e
 Ees = Ese + (Ese _ Ede) d

where Qef is replaced by Q. Estimated excess supply
elasticities for the four commodities are reported in
Table 13.

Appendix II. The Grain
Transportation Models

The purpose of this section is to provide a brief
description of the transportation network flow models
used to assess the potential impact of port user fees on
grain flow patterns. First, a general description of the
grain and soybean network flow models is presented. (I
Second, model data requirements and source of data 
are discussed. Finally, a discussion relating to the
validation of the models is presented.

Table 12. Elasticities of U.S. Grain and Soybean Export Demandsl

Wheat Corn Sorghum Soybeans
Restrictedz Free3 Restricted Free Restricted Free Restricted Free
Trade Trade Trade Trade Trade Trade Trade Trade
Scandinavia 0 0.0667 0 0.0230 0 0.0153 0 0.0159
N.C. Europe 0 0.1484 0 0.0210 0 0.0749 0.1446 0.1446
S.W. Europe 0 0.3016 0 0.1136 0 0.2842 0.1124 0.1124
Islands 0 0.0995 0 0.0029 0 0.0241 0.0221 0.0221
Adriatic 0 0.2090 0 0.0040 0 0.0357 0 0.0044
USSR 0 1.1146 0.0958 0.0958 0 0.2009 0 0.0449
E.B. Europe 0 0.3193 0.0296 0.0296 0 0.3915 0 0.0289
E. Mediterranean 0.0910 0.0910 0.1415 0.1415 0.0676 0.0676 0.0155 0.0155
North Africa 0.0757 0.0757 —“ -— 0.0083 0.0083 0.0006 0.006
Red Sea 0.0134 0.0134 0.3555 0.3555 0.0126 0.0126 . — —
E. Africa 0.0320 0.0320 0.0911 0.0911 0.1766 0.1766 -— —
W. Africa 0.0142 0.0142 0.4713 0.4713 0.0510 0.0510 — —
Persian Gulf 0.1134 0.1134 0.0662 0.0662 0.0095 0.0095 0.0030 0.0030
W. Asia 0.6078 0.6078 — — 0.1069 0.1069 -— --
S.E. Asia 0.0872 0.0872 0.0690 0.0690 0.0673 0.0673 0.0113 0.0113
Taiwan 0.0048 0.0048 0.0532 0.0532 0.0256 0.0256 0.0251 0.0251
Korea 0.0120 0.0120 0.0101 0.0101 0.0341 0.0341 0.0182 0.0182
Japan 0 0.0498 0.3126 0.3126 0.1042 0.1042 0.1019 0.1019
China 0 0.6451 0 0.7214 0 0.6575 0 0.2324
Canada — - — — 0.0714 0.0714 0.0288 0.0288
Mexico 0.0361 0.0361 0.4727 0.4727 0.1386 0.1386 0.0370 0.0370
W.S. America 0.0316 0.0316 0.0620 0.0620 0.0354 0.0354 0.0071 0.0071
E.S. America 0.1167 0.1167 0.3615 0.3615 0.3083 0.3083 0.4183 0.4183
Caribbean 0.0018 0.0018 — — 0.0048 0.0048 0.0009 0.0009
Total“ 1.2377 4.1917 2.5921 3.4780 1.222 2.9063 0.9468 1.2733
Bredahl’ 1.67 5.50 2.36 2.55 1.31 3.13 0.47 1.12

‘Estimated under the assumptions that the domestic supply elasticities were 0.2 everywhere. Domestic demand elasticities assumed —0.2

for wheat, and —0.4 for coarse grains and soybeans everywhere. Period 1976-77 to 1981-82.

zElasticity of price transmission assumed equal to zero for countries exerting insulating trade policies, based on Bredahl, Meyers, and

Collins’ policy analysis.

aElasticities of price transmission assumed unity everywhere.
‘Region not importing from the United States.

slncludes both East and West Mexico.

‘The United States is assumed to be a residual supplier.
7Bredahl, Meyers, and Collins’ estimates for 1972-73 to 1975-76.

General Description of Grain Network Flow Models

Seven separate transportation network flow mod-
els, five of which were originally developed by Taylor
and later updated by Makus, are used in this study to
evaluate the domestic and foreign flow patterns of
U.S. produced wheat, corn, grain sorghum, and soy-
beans. Four classes of wheat are analyzed, namely,
hard red winter, hard red spring, soft, and durum
wheats. Transportation modes include truck, rail,
barge, and ocean vessels. Intertemporal considera-
tions are also included in these models through the
use of quarterly (B-month periods) domestic and
foreign demand ljdata.

The models include surplus domestic production or
supplying regions (SR’s); domestic grain deficit re-
gions (DR’s); 45 river points (RP’s) which act as
intermodal transfer points; 16 ports which are located
on all U.S. coastal areas; and 25 foreign demand
regions (FR’s). With respect to the modes of transpor-
tation, the truck, rail, and barge modes compete

Table 13. U.S. Excess Supply Elasticities

Commodity Elasticity
Corn 1.6155
Sorghum 1.3151 ‘
Soybeans 1 .2934
Wheat 0.5259

directly for domestic grain movements and all mode
combinations are allowed. Ocean ships are the only
means of transportation for overseas U.S. grain ship-
ments. Figure 5 illustrates the general features of the
grain network flow models.

Each of the seven commodity models is solved
separately and the flows through each port area are
aggregated to identify whether flows exceed capacity
or historic volume. In the base model, aggregated
flows were less than or equal to historic flows. Thus,
there was no need to include constraints.

19

 

  
  
  
 
 
 
    

U.S.
Lgglllgillilag Barge Deficit
River '5 P 65a“! 
Locations a‘; 
'43] $51
~\
Q3,‘
,‘\\>0$  619/. t
c“ 0G
1r"
U s Port
- - Ra” Elevators
surplus 7 [m] Ocean Vessel’
Gran] T k o gun
Pmdllfilllfl ruc 7 cfireat Lakes
"Bfllflfls vAtlamic
I165] vPacific
' Model allows for rail and truck shipments to Mexico and Canada
Figure 5. Elements of spatial model.
w?
'\fl\-fl~
\&r-—
it

Figure 6. Model regions.
20

Data Requirements of Grain Network Flow Models

Two types of data inputs are required by the grain
and soybean network flow models: market-related
and transportation-related data. Market data refer to
quantities supplied and demanded in domestic and
foreign markets. Transportation data relate to transfer
costs associated with transporting, storing, and han-
dling grain.

Market-Related Data

Grain supply and demand estimates are required
for domestic producing regions, domestic consuming
regions, and foreign demanding regions. The follow-

. ing sections discuss the data gathering procedures

employed to collect market information pertaining to
the regions.

U.S. Domestic Surplus and Deficit Regions

To determine the basic structure of the network
models, it is necessary to identify the number and size
of supply and demand regions as well as their associ-
ated quantities supplied and demanded. This requires
(1) regional demarcation of surplus and deficit grain
producing regions (domestic and foreign), and (2)
estimation of quantities to be supplied and received by

' the various regions. Demarcation of regions is based

upon existing geographical delineations. The Crop
Reporting District (CRD) is the selected geographical
base unit. For purposes of determining unambiguous
transportation routes and mode rates, the most-cen-
trally located city within a region is chosen as a
representative source or destination location.

The model includes 165 grain and soybean produc-
ing regions (Figure 6). Some regions have grain and/or
soybean surpluses since estimated production
exceeds estimated consumption, whereas other re-
gions have estimated deficits. A surplus region's
supply is available to meet demand from grain deficit
regions or export.

Production estimates are made for each region and
were based on projections elaborated by the Economic
Research Service of the U.S. Department of Agricul-
ture (1980). U.S. Department of Agriculture pro-
jections were procured from the National Interregion-
al Agricultural Projections (NIRAP) model.

Domestic consumption estimates were made for
each region and were comprised of (1) human con-

I sumption, (2) animal consumption, and (3) seed utili-

zation. Human consumption estimates were obtained
from a study made by Hauser at Iowa State University.
Hauser used time series analysis to isolate trends in
human consumption based upon expectations of
population growth and regional milling, processing,
and crushing capacities of grains and soybeans. Ani-
mal consumption figures were obtained from the
NIRAP’s livestock and poultry projections. Seed use
estimates were obtained through total acreage planted
in each state. In some cases, wheat and corn milling
demands and soybean processing demands are iden-
tified with cities rather than regions. The model in-

cludes 85 regions or locations with estimated grain or
soybean deficits.

Foreign Importing Regions

Demarcation of foreign importing regions followed
a similar procedure as that employed in demarcation
of domestic regions. The minimum demarcation unit
was a country. Because of their import volume, size, or
geographical location, some countries were
categorized as world regions themselves; for example,
the United Soviet Socialist Republic, Japan, and
Taiwan. In other cases, due to geographical proximity,
several countries were grouped together; e.g., Scan-
dinavia includes Denmark, Finland, East Germany,
Norway, and Sweden. To establish appropriate ocean
vessel routes and rates, a single port from the foreign
region was chosen as the importing location or port. In
general, the selected port was centrally located within
the importing region.

Estimates of grain and soybean demand (imports)
by foreign region were obtained through trend analy-
sis on historical quantities of U.S. grain exports to
specified countries. U.S. exports to the demarcated
world regions and average shares of U.S. exports to
regions were procured (U.S. Department of Agricul-
ture, Grain Market News). Historical shares were used
to project U. S. exports to each foreign region. The time
series analysis of U.S. exports revealed foreign re-
gions’ imports of U.S. grain were seasonal; thus,
export estimates to each world subregion were di-
vided into quarters to account for this phenomenon.

Transportation-Related Data

An overview of the procedures employed in collect-
ing, analyzing, and estimating mode rates, and stor-
age and handling costs used as inputs in the transpor-
tation network flow models is presented in this sub-
section. Transportation modes discussed include
barge, truck, rail, and ocean vessel.

Barge Rates

The barge mode is extensively used by the grain
marketing system, since it represents the least expen-
sive means of grain transportation. However, its utili-
zation is limited to currently developed and main-
tained waterways such as river channels and port
canals. The network flow models comprise (1) the
Mississippi waterway system which includes the Mis-
sissippi River and its tributaries, (the Illinois, Ohio,
Missouri, and Arkansas rivers) and the Columbia-
Snake waterway system, which includes the Colum-
bia and Snake Rivers (Figure 7).

Barge and towboat costs are based on budget data
from the U.S. Army Corps of Engineers (1983). Cost-
ing procedures take into consideration the unique
physical characteristics of the various segments in
each major waterway system.

Truck Rates

Truck transportation is the most flexible of all inland
transportation modes and grains and soybeans rely

21

o Port Locations
° Barge Locations

Figure 7. LLS. ports and river locations in the grain transportation models.

heavily on trucks at the assembly stage. Due to its
flexibility, truck transportation has a competitive edge
over the barge and rail modes for short hauls, with the
converse holding for longer hauls.

Based on the established demarcation of grain sur-
plus and deficit regions, a computerized algorithm,
developed at Iowa State University, was used by
Taylor and Makus to estimate truck rates. The al-
gorithm estimates truck cost equations, on a state-by-
state basis, through use of regression analysis. Truck
rates are estimated for all possible origin-destination
combinations in which the truck mode may be used.
Truck rates for movements from grain surplus regions
to river points are based on distances between the
surplus region and the nearest barge loading location.

Rail Rates

Railroads play an important role in transporting
grain and soybean for longer distances of haul. Pro-
ducing regions far from major waterway systems
often move their grain and soybean surplus by rail. In
the network models, rail lines link surplus producing
regions to barge loading locations and numerous
demand locations and ports.

There is difficulty in knowing likely railroad pricing

22

behavior in view of the recent deregulation of the
railroad industry Economics has no unified theory of
oligopoly pricing and the recent deregulation experi-
ence has been of insufficient duration to make long-
run inferences regarding railroad pricing strategy.
Several studies, however, have been made in the past
few years and found evidence that railrates have
declined during the post-Staggers era (Klindworth, et
al. ; Adams and Anderson). But the economic environ-
ment since deregulation has been characterized by
declining export sales and large surpluses of transpor-
tation equipment; therefore, the observed competi-
tion between and within tranportation modes may not
be reflective of the long run. A recent study notes that
the rate reductions flowing from these competitive
tendencies may be reversed once economic recovery
takes hold and rail cars and barge surpluses are
reduced or eliminated (U.S. Department of Agricul-
ture, 1982a). Economists agree that in a market charac-
terized by few competitors, interdependence is gener-
ally recognized and, in the long run, there is a tenden-
cy toward tacit ratemaking. Friedlaender states that
”. . .the history of collusive pricing in the railroad
industry is sufficiently long so that collusion would
probably. . . (exist with deregulation)," in which case
interrailroad competition would be limited.



\

'\

For purposes 0f estimating railroad rates, it is as-
sumed that interrailroad competition is limited and
railroads attempt to charge the highest rate that inter-
modal competition will permit in surplus grain pro-
ducing regions. The procedure to estimate rates is
outlined in an article by Fuller, Makus, and Taylor. In
essence, the highest revenue-to-variable cost ratio
permitted by intermodal competition is estimated for
each surplus producing region. These ratios are es-
timated for corn, wheat, soybeans, and sorghum. This
ratio is then multiplied by the estimated variable costs
which link a particular origin-destination combination
for purposes of estimating rates.

The rail-rate estimation procedure requires that
railroads’ variable costs be estimated for each route.
Rail costs are based on the Rail Carload Cost scales
published by the Interstate Commerce Commission
(ICC); while mileages are gathered from several publi-
cations, among them is the Handy Railroad Atlas 0f the
United States published by the Rand McNally Co.

Railroad variable costs are estimated by use of a
computerized algorithm developed at Iowa State Uni-
versity. The algorithm calculates rail rates per bushel
costs for both single-car and multiple-car trains. Rail
rate estimation is based on five ICC regions and takes
into consideration cost parameters associated with
covered hopper car weights, commodity, turnaround
times, required switching, interest rates, size of ship-
ment, route mileage, average mileage between inter-
changes, and mileage between yards. The ICC’s 1981
cost scales and 1982 update cost ratios are used to
estimate variable costs (Interstate Commerce Com-
mission, 1982).

Ocean Shipping Rates

Data on ocean shipping rates were obtained from
the U.S. Department of Agriculture for the 1977-83
period. These data are collected and reported by
Maritime Research Incorporated and include informa-
tion on origin, destination, tonnage, rates, and the
Julian date of charter. Based on this information,
Makus developed estimates for shipping rates from
four coastal areas to the 25 world regions.

Storage and Handling Costs

Though storage facilities are found at all stages of
the grain marketing channel (on farms, country eleva-
tors, subterminals, terminals, and port elevators),
storage was assumed to occur in the supplying re-
gions. Reliable data regarding on-farm storage capaci-
ty were not available. No storage constraints are,
therefore, specified in the models. Cost estimates for
storage follow those estimated by Leath, et al. 1982.

Handling costs rare those associated with loading
and unloading grain. Handling costs are incurred in
the supply regions, at transshipment points, and at
final destinations. Loading and unloading costs are
dependent on the mode of transportation used. Costs
included in the model take into consideration the
combination of modes used in a particular haul. See
Table 14 on estimated handling and storage costs.

Table 14. Summary of Costs by Function and Type of
Facility and Weighted Average Costs for All Facilities,
by Function, 1981-82

Country River Port All
Elevators Elevators Elevators Elevators
cents per bushel
Receiving By:
Truck 4.796 4.213 4.350 4.697
Rail n.a. 6.051 3.931 4.629
Water n.a. 9.354 3.269 3.451
Shipping By:
Truck 5.071 3.821 0.0 4.984
Rail 6.069 4.907 5.955 5.722
Water 2.352 2.337 2.535 2.487
Annual Storage 32.329 30.649 55.266 33.607

‘Information provided in memo by Mac Leath.
2n.a. = not applicable

Validation of Transportation Models

Model validation is the process of gaining informa-
tion on the model's ability to yield realistic grain flow
patterns. Modeling efforts do not seek to exactly
represent reality, since this is virtually impossible for
the majority of situations due to cost, time, and data
availability constraints. As a result, differences be-
tween a given model's outcome and the real-world
situation it attempts to emulate will occur. Conse-
quently, model validation seeks to gain insight with
regard to these differences. The optimization criterion
of the network flow models involves minimization of
total transfer cost associated with grain movements.
In this regard, the models’ solutions may be inter-
preted as the flow patterns that grain ought to follow
in order to achieve this goal.

The quality of the data is of great importance.
Measurement and estimation errors are involved in
collecting, recording, classifying, aggregating,
processing, and reporting data. Mode rates as well as
market data are bound to suffer from these errors. In
addition, inappropriate aggregation of supply and
demand regions may distort flows.

Meaningful comparisons between model-projected
and actual flows are difficult since grain production,
consumption, and foreign demand change from year
to year while the model's values are constants. Fur-
ther, the model is constructed such that the produc-
tion, consumption, and foreign demand estimates
have a predetermined geographical location; whereas,
the actual location of these activities exhibits variation.
Additional divergence between actual and model-
projected flows may exist because of the highly vari-
able ship rate structures (Fuller, Makus, and Galli-
more).

Table 15 includes information on the historical per-
centage of the U.S. aggregated grain and soybean
outflow exiting through U.S. coast areas from 1970 to
1984 and the model-projected flow. Historically, 61.0
to 70.0 percent of U.S. grain and soybean exports have
exited Gulf ports: the model projects 65 percent exiting

23

Table 15. Comparison of Aggregated Historical and
Model-Generated Grain and Soybean Export Flows
through U.S. Coastal Regions‘

Year Gulf Atlantic Great Lakes Pacific
percent
1970 65.0 6.0 15.0 14.0
1971 67.0 6.0 17.0 10.0
1972 66.0 10.0 13.0 11.0
1973 67.0 12.0 10.0 11.0
1974 67.0 13.0 8.0 12.0
1975 65.0 14.0 10.0 11.0
1976 67.0 15.0 8.0 10.0
1977 67.0 14.0 10.0 9.0
1978 63.0 12.0 13.0 12.0
1979 61.0 13.0 11.0 15.0
1980 61.0 11.0 9.0 19.0
1981 64.0 11.0 7.0 18.0
1982 68.0 14.0 6.0 12.0
1983 70.0 9.0 5.0 16.0
1984 67.0 8.0 5.0 20.0
Model 65.0 12.0 13.0 10.0

‘Historical data compiled from U.S. Department of Agriculture,
Grain Market News, various issues 1970-84.

this coastal area. The percentage of total exports
exiting from the Atlantic coast area has varied be-
tween 6.0 and 15.0 percent since 1970, again the
model's projection is within this historical range with
an estimate of 12 percent. The model-projected flows
through Great Lakes and Pacific ports are within the
historical ranges but tend to vary from these ports’
recent export shares. In particular, the model tends to
overestimate recent exports from Great Lakes ports
and underestimate outflow from Pacific ports. Much
of the increase in exports from Pacific ports is attribut-
able to corn which has recently begun moving from
western Corn Belt origins to this port area. Several
factors are responsible. To attract business, the Bur-
lington Northern railroad introduced appealing rates
between the western Corn Belt and Pacific Northwest
ports; ship rates from Pacific ports to Japan, Taiwan,
and Korea have, in some recent time periods, declined
substantially relative to Gulf rates; and the Japanese
importers have become associated with several Pacific
coast export houses. These factors are also responsible
for diminishing export flows from Great Lake ports. It
is difficult to forecast the long run nature of these
factors and their impact; accordingly, the model was
not manipulated to generate the more recent outcome.

In an effort to validate the employed model, Taylor
compared historical grain flow patterns against those
obtained from the models. Spearman’s correlation
coefficients were estimated between model-projected
flows and grain flows from a 1977 survey by Leath, et
al. Sensitivity analysis was later carried out which
showed that the grain network flow models appropri-
ately ”tracked” changes in flows that resulted from
changes in intermodal rates. Even though differences
arose, the model was deemed appropriate to repre-
sent the U.S. grain marketing system in 1977. This
version of the model was used to evaluate the effect of

24

altering Panama Canal tolls and to identify the likely
impact of rail deregulation on export rates (Fuller,
Makus, and Gallimore; Fuller, Makus, and Taylor).
Makus updated Taylor's models to account for
changes in rail and ocean ship rates in order to reflect
1982 conditions. Even though there were some dif-
ferences between the models’ projected flows and
actual grain flows, the model was deemed appropriate

to investigate the sensitivity of U.S. port areas to A

changing patterns in foreign grain demands (Makus
and Fuller). Various versions of the model have been
used to analyze transportation issues and three re-
ferred journal articles have resulted (Fuller, Makus,
and Gallimore; Fuller, Makus, and Taylor; Makus and _
Fuller). These articles provide additional insight into '
the ability of the model to generate historical flow
patterns.

Appendix III. Further Results

Included in this appendix are further results on
grain flow patterns. Table 16 presents grain and soy-
bean flows corresponding to what was labeled as the
baserun solution. The baserun solution consists of the
original model which was calibrated to approximate
the U.S. domestic and international marketing sys-
tem. Grain flow levels in the baserun solution reflect
the grain marketing system prior to 1982. Current
export levels are about 0.6 billion bushels less than the
average for that period.

Tables 17 and 18 report grain flows associated with
port user fees which incorporate a 50 percent cost
recovery level by the federal government. The format
of these tables is identical to that of Tables 9 and 10
which reported grain flows that evaluated port user
fees designed to recoupe 100 percent of all involved
costs. Grain flows associated with port user fees that
recoupe 50 percent of federal expenses proved to be
similar to those which arise from a 100 percent recov-
ery level. However, the magnitudes of altered flow
patterns are for the most part considerably smaller.

Tables 19 through 32 report altered flow patterns at
the individual commodity level. Due to space con-
straints, individual grain and soybean flow patterns
were aggregated by coastal area rather than by port
area. The format of these tables is identical to those

presented above. 

   

7K Table 16. Baserun Solution of Spatial Network Flow Models by Commodity.‘

HRW2 HRS3 Soft Durum
Corn Sorghum Soybeans Wheat Wheat Wheat Wheat Total
million bushels
Gulf:
East Gulf 118.66 0.00 72.84 0.00 0.00 0.00 0.00 191.50
Mississippi River 1,421.78 7.95 475.76 73.42 76.37 94.05 14.61 2,163.93
North Texas 114.30 178.64 5.64 420.41 3.38 0.00 0.94 723.31
South Texas 0.00 71.54 0.00 0.00 0.00 0.00 0.00 71.54
Subtotal 1,654.74 258.13 554.25 493.83 79.75 94.05 15.55 3,150.28
Atlantic:
North Atlantic 413.18 1.20 86.20 0.00 1.24 40.71 0.00 542.54
South Atlantic 0.00 0.00 38.38 0.00 0.00 1.71 0.00 40.10
Subtotal 413.18 1 .20 124.59 0.00 1.24 42.42 0.00 582.64
Greak Lakes:
Superior-Michigan 250.95 1.62 17.92 31.25 51.57 0.00 49.03 402.34
Huron-Erie 136.75 0.00 69.30 0.00 0.00 46.39 0.00 252.45
Subtotal 387.70 1.62 87.22 31.25 51.57 46.39 49.03 654.79
Pacific:
Seattle Area 18.00 0.00 0.00 81.92 83.84 15.98 11.41 211.15
Portland Area 0.00 0.00 0.00 13.61 4.29 218.86 0.00 236.76
California 0.00 0.00 _ 0.00 3.15 7.47 4.36 12.00 26.98
Subtotal 18.00 0.00 0.00 98.68 95.60 239.20 23.41 474.88
Total Port Exports 2,473.62 260.95 766.06 623.76 228.15 422.06 87.98 4,862.59
interior Exports 28.80 0.00 24.32 0.00 0.00 0.00 0.00 53.12
Total Exports 2,502.42 260.95 790.38 623.76 228.15 422.06 87.98 4,915.71

‘Subtotals and totals may not add up due to rounding.
2HRW stands for Hard Red Winter.
3HRS stands for Hard Red Spring.

25

Table 17. Effect on U.S. Port Area Grain and Soybean Flows of a Weight-Based User Fee which  to Recoupe 50 Q

Percent of Operations and Maintenance Expenses (OM), New Construction Costs (NC), and the Aggregate of
These Costs (OMNC)1

Port-Specific Fees

Uniform Fees

OM NC OMNC OM NC OMNC
Change Change Change Change Change Change
In Percent In Percent In Percent In Percent In Percent In Percent
Port Area Volumez Change3 Volume Change Volume Change Volume Change Volume Change Volume Change
Gulf:
East Gulf - 0.02 - 0.01 -30.10 -15.72 -30.12 -15.73 - 0.03 -0.01 - 0.06 -0.03 - 0.10 -0.05
Mississippi River 9.68 0.44 44.81 2.07 60.87 2.81 10.64 0.49 9.81 0.45 9.16 0.42
North Texas - 0.14 0.02 9.99 1.38 11.24 1.55 - 0.21 -0.03 - 0.43 -0.06 - 0.65 -0.09
South Texas 0.00 0.00 0.89 1.24 - 0.03 - 0.04 - 0.01 -0.01 - 0.01 -0.02 - 0.02 -0.03
Total 9.52 0.30 25.59 0.812 41.96 1.33 10.39 0.33 9.30 0.30 8.40 0.27
Atlantic:
North Atlantic - 8.44 - 1.56 -53.28 - 9.82 -52.94 - 9.76 - 9.64 -1.78 -10.70 -1.97 -11.54 -2.13
South Atlantic 0.00 0.00 0.01 - 0.02 - 0.01 - 0.04 0.00 0.00 - 0.01 -0.02 - 0.01 -0.03
Total - 8.44 - 1.45 -53.29 - 9.15 -52.95 - 9.09 - 9.64 -1.65 -10.71 -1.84 -11.55 -1.98
Great Lakes:
Superior-Michigan 10.69 2.66 18.71 4.65 17.32 4.30 - 0.41 -0.10 - 0.40 -0.10 - 0.39 -0.10
Huron-Erie -11.14 - 4.41 5.56 2.20 -11.24 - 4.45 - 0.04 -0.02 - 0.08 -0.03 - 0.12 -0.05
Total - 0.45 - 0.07 24.27 3.71 6.08 0.93 - 0.45 -0.07 - 0.48 -0.07 - 0.51 -0.08
Pacific:
Seattle Area 50.22 23.78 - 2.24 - 1.06 50.05 23.71 - 2.14 -1.01 - 2.21 -1.05 - 2.27 -1.07
Portland Area -52.41 -22.14 - 0.07 - 0.03 -52.47 -22.16 - 0.02 -0.01 - 0.04 -0.02 - 0.07 -0.03
California 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Total - 2.19 - 0.46 - 2.31 - 0.49 - 2.41 - 0.51 - 2.16 -0.45 - 2.25 -0.47 - 2.34 -0.49
Total Port Exports‘ - 1.56 - 0.03 - 5.72 - 0.12 - 7.32 - 0.15 - 1.86 -0.04 - 4.14 -0.09 - 6.00 -0.12

lNumbers at the coast level may not add up to totals due to rounding.

zMillion bushels.

3Percent change from baserun volume.
‘Overall reduction in U.S. grain exports resulting from increase in export price due to user charge imposition.

26

1
 
1
4

T\

Fi Table 18. Effect on U.S. Port Area Grain and Soybean Flows of an Ad Valorem User Fee Which ls to Recoupe 50

Percent of Operations and Maintenance Expenses (OM), New Construction Costs (NC), and the Aggregate of

These Costs (OMNC)1

Port-Specific Fees Uniform Fees
OM NC OMNC OM NC 4 OMNC
Change Change Change Change Change Change
In Percent In Percent In Percent In Percent In Percent In Percent
Port Area Volumez Change3 Volume Change Volume Change Volume Change Volume Change Volume Change
Gulf:
East Gulf - 0.01 - 0.01 -30.05 -15.69 -40.94 -21.38 - 0.02 -0.01 - 0.05 -0.02 - 0.06 -0.03
Mississippi River 10.50 0.48 53.61 2.48 47.21 2.18 10.86 0.50 10.33 0.48 9.93 0.46
North Texas - 0.52 - 0.07 10.70 1.48 10.47 1.45 - 0.12 0.02 - 0.26 -0.04 - 0.36 -0.05
South Texas 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 -0.02
Total 9.97 0.32 34.25 1.09 16.74 0.53 10.72 0.34 10.02 0.32 9.50 0.30
Atlantic:
North Atlantic 6.66 1.23 -33.68 - 6.21 -34.80 - 6.41 - 9.24 -1.70 - 9.78 -1.80 -10.04 -1.85
South Atlantic 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Total 6.66 1.14 -33.68 - 6.21 -34.80 - 5.97 - 9.24 -1.59 - 9.78 -1.67 -10.04 -1.72
Great Lakes:
Superior-Michigan 10.68 2.65 - 0.42 - 0.11 23.16 5.76 - 0.42 -0.11 - 0.43 -0.11 - 0.42 -0.10
Huron-Erie -25.73 -10.19 - 0.04 - 0.02 - 5.49 - 2.18 - 0.03 -0.01 - 0.04 -0.02 - 0.07 -0.03
Total -15.05 - 2.30 - 0.46 - 0.07 17.67 2.70 - 0.45 -0.07 - 0.47 -0.07 - 0.49 -0.07
Pacific:
Seattle Area 50.26 23.80 - 2.14 - 1.01 50.18 23.77 - 2.11 -1.00 - 2.17 -1.03 - 2.21 -1.04
Portland Area -52.41 -22.13 - 0.03 - 0.01 -52.43 -22.14 - 0.01 -0.01 - 0.03 -0.01 - 0.05 -0.02
California 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Total - 2.15 - 0.45 - 2.17 - 0.46 - 2.24 - 0.47 - 2.12 -0.45 - 2.20 -0.46 - 2.26 -0.48

Total Port Exports‘ - 0.56 - 0.01 - 2.07 - 0.04 - 2.64 - 0.05 — 1.09 -0.02 - 2.44 -0.05 - 3.29 -0.07

‘Numbers at the coast level may not add up to totals due to rounding.

zMillion bushels.

3Percent change from baserun volume.

‘Overall reduction in U.S. grain exports resulting from increase in export price due to user charge imposition.

27

Table 19. Effect on U.S. Port Area Corn of a Weight-Based User Fee Which ls to Recoupe Operations and
Maintenance Expenses (OM), New Construction Costs (NC), and the Aggregate of These Costs (OMNC)1

Port-Specific Fees Uniform Fees
OM NC OMNC OM NC OMNC
Change Change Change Change Change Change
In Percent In Percent In Percent In Percent In Percent In Percent

Volumez Change3 Volume Change Volume Change Volume Change Volume Change Volume Change

50 Percent Cost Recovery Level

Gulf - 0.39 -0.02 22.72 1.37 22.37 1.35 -0.47 -0.03 -1.01 -0.06 -1.50 -0.09
Atlantic - 0.70 -0.17 -36.37 - 8.07 -34.07 - 8.25 -0.83 -0.20 -1.81 -0.45 -2.68 -0.65
Great Lakes - 0.00 0.00 6.63 1.71 6.58 1.70 0.00 0.00 -0.01 0.00 -0.01 0.00
Pacific - 0.00 -0.03 - 0.02 - 0.13 - 0.02 - 0.14 -0.01 -0.04 -0.02 -0.09 -0.02 -0.13

Total‘ - 1.00 -0.05 - 4.03 - 0.16 - 5.14 - 0.21 1.31 -0.05 -2.91 -0.12 -4.22 -0.17

100 Percent Cost Recovery Level

Gulf -18.06 -1.09 38.03 2.30 24.87 1.50 0.92 -0.06 -2.07 -0.13 -2.98 -0.18
Atlantic 15.88 3.84 -52.54 -12.72 -41.49 -10.04 -1.68 -0.41 -3.69 -0.89 -5.37 -1.30
Great Lakes - 0.01 -0.00 6.47 1.67 6.39 1.65 -0.01 -0.00 -0.02 -0.00 -0.03 -0.01
Pacific - 0.01 -0.08 - 0.05 - 0.27 - 0.06 - 0.36 -0.01 -0.08 -0.03 -0.17 -0.05 -0.28

Total‘ - 2.20 -0.09 - 8.09 - 0.33 -10.30 - 0.42 2.63 -0.11 -5.81 -0.23 -8.43 -0.34

‘Numbers may not add up to totals due to rounding. 

zMillion bushels.

3Percent change from baserun volume. u i

‘Overall reduction in U.S. corn exports resulting from increase in export price due to user charge imposition.

Table 20. Effect on U.S. Port Area Corn of an Ad Valorem User Fee Which ls to Recoupe Operations and
Maintenance Expenses (OM), New Construction Costs (NC), and the Aggregate of These Costs (OMNC)'

Port-Specific Fees Uniform Fees
OM NC OMNC OM NC OMNC
Change Change Change Change Change Change
In Percent In Percent In Percent In Percent In Percent In Percent

Volumez Change3 Volume Change Volume Change Volume Change Volume Change Volume Change

50 Percent Cost Recovery Level

Gulf -0.14 -0.01 13.60 0.82 13.30 0.80 -0.24 -0.01 -0.53 -0.03 -0.70 -0.04
Atlantic -0.22 -0.05 -14.86 -3.60 -14.90 -3.61 -0.43 -0.10 -0.95 -0.23 -1.19 -0.29
Great Lakes 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 
Pacific 0.00 » 0.00 - 0.01 -0.03 - 0.01 -0.04 0.00 -0.01 -0.01 -0.04 -0.01 -0.05
Total‘ -0.35 -0.01 - 1.27 -0.05 - 1.16 -0.06 -0.67 -0.03 -1.49 -0.06 -1.91 -0.08
100 Percent Cost Recovery Level
Gulf -0.25 -0.01 23.20 1.40 7.15 0.43 -0.48 -0.03 -1.05 -0.06 -1.54 -0.09
Atlantic -0.44 -0.10 -25.71 -6.22 -10.35 -2.50 -0.86 -0.21 -1.92 -0.46 -2.76 -0.67
Great Lakes -0.00 -0.00 - 0.01 -0.00 - 0.01 0.00 0.00 0.00 -0.01 0.00 -0.01 0.00
Pacific -0.00 -0.00 - 0.01 -0.08 - 0.02 -0.09 0.01 -0.04 -0.02 -0.09 -0.02 0.13
Total‘ -0.69 -0.03 - 2.54 -0.10 - 3.23 -0.13 -1.357 -0.05 -3.00 -0.12 -4.34 -0.17

‘Numbers may not add up to totals due to rounding.

\
zMllllOfl bushels. @}
3Percent change from baserun volume. ’

‘Overall reduction in U.S. corn exports resulting from increase in export price due to user charge imposition.

28

P‘ Table 21. Effect on U.S. Port Area Sorghum of a Weight-Based User Fee Which Is to Recoupe Operations and
Maintenance Expenses (OM), New Construction Costs (NC), and the Aggregate of These Costs (OMNC)l

Port-Specific Fees Uniform Fees
OM NC OMNC OM NC a OMNC
Change Change Change Change Change Change
In Percent In Percent In Percent In Percent In Percent In Percent

Volumez Change3 Volume Change Volume Change Volume Change Volume Change Volume Change

50 Percent Cost Recovery Level

Gulf -0.12 -0.04 -0.42 -0.16 -0.54 -0.21 -0.14 -0.05 -0.30 -0.11 -0.44 -0.17
Atlantic 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Great Lakes 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Pacific 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Total‘ -0.12 -0.04 -0.42 -0.16 -0.54 -0.21 -0.14 -0.05 -0.30 -0.11 -0.44 -0.17

100 Percent Cost Recovery Level

Gulf -0.23 -0.09 -0.84 -0.32 -1.06 -0.41 -0.27 -0.10 -0.60 -0.23 -0.87 -0.33
Atlantic 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Great Lakes 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Pacific 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Total“ -0.23 -0.09 -0.84 -0.32 -1.06 -0.41 -0.27 -0.10 -0.60 -0.23 -0.87 -0.33

‘Numbers may not add up to totals due to rounding.

zMillion bushels.

3Percent change from baserun volume.

‘Overall reduction in U.S. sorghum exports resulting from increase in export price due to user charge imposition.

Table 22. Effect on U.S. Port Area Sorghum of an Ad Valorem User Fee Which ls to Recoupe Operations and
Maintenance Expenses (OM), New Construction Costs (NC), and the Aggregate of These Costs (OMNC)1

Port-Specific Fees Uniform Fees
OM NC OMNC OM NC OMNC
Change Change Change Change Change Change
In Percent In Percent In Percent In Percent In Percent In Percent

Volumez Change3 Volume Change Volume Change Volume Change Volume Change Volume Change

50 Percent Cost Recovery Level

Gulf -0.04 -0.02 -0.14 -0.05 -0.17 -0.07 -0.07 -0.03 -0.16 -0.06 -O.23 -0.09
Atlantic 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
‘K Great Lakes 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Pacific 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Total‘ -0.04 -0.02 -0.14 -0.05 -0.17 -0.07 -0.07 -0.03 -0.16 -0.06 -0.23 -0.09
100 Percent Cost Recovery Level

Gulf -0.08 -0.03 -0.26 -0.10 -0.34 -0.13 -0.14 -0.06 -O.31 -0.12 -0.46 -0.18
Atlantic 0.00  0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Great Lakes 0.00 l" 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Pacific 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Total‘ -0.08 -0.03 -0.26 -0.10 -1.34 -0.13 -0.14 -0.06 -0.31 -0.12 -O.46 -0.18

\ ‘Numbers may not add up to totals due to rounding.
“Million bushels.
3Percent change from baserun volume.
‘Overall reduction in U.S. sorghum exports resulting from increase in export price due to user charge imposition.

29

Table 23. Effect on U.S. Port Area Soybeans of a Weight-Based User Fee Which Is to Recoupe-Operations and 
Maintenance Expenses (OM), New Construction Costs (NC), and the Aggregate of These Costs (OMNC)1 ‘

  

OM NC OMNC OM NC
Change Change Change Change Change Change
In Percent In Percent In Percent In Percent In Percent In Percent
Volumez Change?’ Volume Change Volume Change Volume Change Volume Change Volume Change
50 Percent Cost Recovery Level
Gulf - 0.13 - 0.02 1.87 0.34 5.91 1.07 -0.15 -0.03 -0.32 -0.06 -0.45 -0.08
Atlantic - 0.01 - 0.01 - 6.49 - 5.21 -6.50 -5.22 -0.01 -0.01 -0.02 -0.01 -0.03 -0.02
Great Lakes 0.00 0.00 4.16 4.77 -0.02 -0.02 0.00 0.00 -0.01 -0.01 -0.01 -0.01
Pacific 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Total“ - 0.14 - 0.02 - 0.47 - 0.06 -0.61 -0.08 -0.16 -0.02 -0.35 -0.05 -0.50 -0.07
100 Percent Cost Recovery Level
Gulf - 0.25 - 0.04 36.79 6.64 5.35 0.97 -0.29 -0.05 -0.61 -0.11 -0.90 -0.16
Atlantic 14.60 11.72 -41.89 -33.62 -6.54 -5.25 -0.02 -0.01 -0.05 -0.04 -0.07 -0.06
Great Lakes -14.62 -16.76 4.15 4.75 -0.03 -0.03 -0.03 -0.01 -0.02 -0.02 -0.02 -0.02
Pacific 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Total‘ - 0.27 - 0.04 - 0.96 - 0.12 -1.21 -0.16 -0.31 -0.04 -0.68 -0.09 -0.99 -0.13

Port-Specific Fees

Uniform Fees

OMNC 

‘Numbers may not add up to totals due to rounding.

zMillion bushels.
3Percent change from baserun volume.

‘Overall reduction in U.S. soybean exports resulting from increase in export price due to user charge imposition.

Table 24. Effect on U.S. Port Area Soybeans of an Ad Valorem User Fee Which ls to Recoupe Operations and
Maintenance Expenses (OM), New Construction Costs (NC), and the Aggregate of These Costs (OMNC)1

Port-Specific Fees

Uniform Fees

OM NC OMNC OM NC OMNC
Change Change Change Change Change Change
In Percent In Percent In Percent In Percent In Percent In Percent .
Volume’ Change3 Volume Change Volume Change Volume Change Volume Change Volume Change 
50 Percent Cost Recovery Level
Gulf - 0.07 - 0.01 6.16 1.11 1.92 -0.35 -0.16 -0.03 -0.35 -0.06 -0.50 -0.09 *
Atlantic 14.61 11.72 -6.48 -5.20 -6.49 -5.21 -0.01 -0.01 -0.02 -0.02 -0.03 -0.03 _ I
Great Lakes -14.61 a -16.76 -0.01 -0.01 4.16 4.77 0.00 0.00 -0.01 -0.01 -0.01 -0.01 w 
Pacific 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 
Total‘ - 0.08 - 0.01 -0.32 -0.04 -0.40 -0.05 -0.17 0.02 -0.38 -0.05 -0.54 -0.07
100 Percent Cost Recovery Level
Gulf - 0.16 - 0.03 5.89 1.06 1.56 0.28 -0.32 -0.06 -0.67 -0.12 -0.99 -0.18
Atlantic 14.60 11 .72 -6.50 -5.22 -6.52 -5.23 -0.02 -0.01 -0.06 -0.04 -0.08 -0.06
Great Lakes -14.61 -16.76 -0.02 -0.02 4.15 4.76 -0.01 -0.01 -0.02 -0.02 -0.02 -0.03
Pacific 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Total‘ - 0.17 - 0.02 -0.63 -0.08 0.81 -0.10 -0.34 -0.04 -0.75 -0.10 -1.09 -0.14

‘Numbers may not add up to totals due to rounding.

zMillion bushels.
3Percent change from baserun volume.

‘Overall reduction in U.S. soybean exports resulting from increase in export price due to user charge imposition.

30

P‘ Table 25. Effect on U.S. Port Area Hard Red Winter Wheat of a Weight-Based User Fee Which ls to Recoupe
Operations and Maintenance Expenses (OM), New Construction Costs (NC), and the Aggregate of These
Costs (OMNC)1

Port-Specific Fees Uniform Fees
OM NC OMNC OM NC OMNC
Change Change Change Change Change Change
In Percent In Percent In Percent In Percent In Percent In Percent

Volume’ Change3 Volume Change Volume Change Volume Change Volume Change Volume Change

50 Percent Cost Recovery Level

Gulf -0.04 -0.01 -0.37 -0.07 -0.42 -0.09 -0.11 -0.02 -0.25 -0.05 -0.36 -0.07
Atlantic 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Great Lakes 0.00 0.00 -0.01 -0.02 -0.01 -0.02 0.00 0.00 -0.01 -0.02 -0.01 -0.02
Pacific -0.06 -0.06 0.00 0.00 -0.06 -0.06 -0.01 -0.01 -0.02 -0.02 -0.03 -0.03

Total‘ -0.10 -0.02 -0.37 -0.06 -0.49 -0.08 -0.12 -0.02 -0.27 -0.04 -0.40 -0.06

100 Percent Cost Recovery Level

Gulf -0.15 -0.03 -0.75 -0.15 -0.90 -0.18 -0.23 -0.05 -0.50 -0.10 -0.72 -0.15
Atlantic 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Great Lakes -0.01 -0.02 -0.01 0.03 -0.01 -0.04 -0.01 -0.02 -0.01 -0.02 -0.01 -0.03
Pacific -0.06 -0.06 -0.01 0.01 -0.07 -0.07 -0.02 -0.02 -0.05 -0.05 -0.06 -0.07

Total‘ -0.21 -0.03 -0.77 -0.12 -0.98 -0.16 -0.25 -0.04 -0.55 -0.09 -0.80 -0.13

‘Numbers may not add up to totals due to rounding.

zMillion bushels.

3Percent change from baserun volume.

‘Overall reduction in U.S. hard red winter wheat exports resulting from increase in export price due to user charge imposition.

Table 26. Effect on U.S. Port Area Hard Red Winter Wheat of an Ad Valorem User Fee Which ls to Recoupe
Operations and Maintenance Expenses (OM), New Construction Costs (NC), and the Aggregate of These
Costs (OMNC)1

Port-Specific Fees Uniform Fees
OM NC OMNC OM NC OMNC
Change Change Change Change Change Change
In Percent In Percent In Percent In Percent In Percent In Percent

Volumez Changeg’ Volume Change Volume Change Volume Change Volume Change Volume Change

50 Percent Cost Recovery Level

Gulf 0.01 0.00 -0.15 -0.03 -0.16 -0.03 -0.08 -0.02 -0.17 -0.03 -0.26 -0.05
q Atlantic 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Great Lakes 0.00 0.00 0.00 -0.01 -0.01 -0.02 0.00 0.00 -0.01 -0.02 -0.01 -0.02
Pacific -0.06 -0.06 0.00 0.00 -0.06 -0.06 0.00 0.00 -0.01 -0.01 -0.02 -0.02
Total‘ -0.04 -0.01 -0.15 -0.02 -0.21 -0.03 -0.08 -0.01 -0.19 -0.03 -0.28 -0.04
100 Percent Cost Recovery Level

Gulf -0.03  0Q; -0.32 -0.06 -0.35 -0.07 -0.15 -0.03 -0.35 -0.07 -0.51 -0.10
Atlantic 0.00 i 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Great Lakes 0.00 0.00 -0.01 -0.02 -0.01 -0.02 0.00 0.00 -0.01 -0.02 -0.01 -0.02
Pacific -0.06 -0.06 0.00 0.00 -0.06 -0.06 -0.01 -0.01 -0.03 -0.03 -0.05 -0.05
Total‘ -0.09 -0.01 -0.33 -0.05 -0.41 -0.07 -0.17 -0.03 -0.38 -0.06 -0.57 -0.09

\V‘Numbers may not add up to totals due to rounding.
zMillion bushels.
‘Percent change from baserun volume.
‘Overall reduction in U.S. hard red winter wheat exports resulting from increase in export price due to user charge imposition.

31"

Table 27. Effect on U.S. Port Area Hard Red Spring Wheat of a Weight-Based User Fee Which ls to Recoupefil"

  

Operations and Maintenance Expenses (OM), New Construction Costs (NC), and the Aggregate of These
Costs (OMNC)1

Port-Specific Fees Uniform Fees

OM NC OMNC OM NC OMNC

Change Change
In Percent In
Volumez Change3

Change Change
Percent In Percent In
Volume Change Volume Change Volume

Change Change
Percent In Percent In Percent
Change Volume Change Volume Change

Gulf
Atlantic
Great Lakes
Pacific
Total‘

Gulf
Atlantic
Great Lakes
Pacific
Total‘

50 Percent Cost Recovery Level

-0.02 -0.03 -8.40 -10.53 -0.14 -0.18 -0.03 -0.04 -0.08 -0.10 -0.11 -0.14
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00 8.28 16.06 -0.02 -0.03 0.00 0.00 -0.01 -0.02 -0.01 -0.03
-0.01 -0.01 0.03 0.03 -0.02 -0.02 -0.01 -0.01 -0.02 -0.02 -0.03 -0.03
-0.03 -0.01 -0.14 - 0.06 -0.18 -0.08 -0.04 -0.02 -0.10 -0.04 -0.15 -0.07
100 Percent Cost Recovery Level
-0.05 -0.07 -8.49 -10.65 -0.26 -0.33 -0.07 -0.08 -0.15 -0.19 -0.22 -0.27
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
-0.01 -0.01 8.25 16.00 -0.03 -0.06 -0.01 -0.02 -0.02 -0.04 -0.03 -0.05
-0.02 -0.02 -0.05 - 0.05 -0.07 -0.07 -0.02 -0.02 -0.03 -0.03 -0.05 -0.04
-0.07 -0.03 -0.29 - 0.13 -0.36 -0.16 -0.09 -0.04 -0.21 -0.09 -0.30 -0.13

‘Numbers may not add up to totals due to rounding.

“Million bushels.

3Percent change from baserun volume.

‘Overall reduction in U.S. hard red spring wheat exports resulting from increase in export price due to user charge imposition.

Table 28. Effect on U.S. Port Area Hard Red Spring Wheat of an Ad Valorem User Fee Which ls to Recoupe
Operations and Maintenance Expenses (OM), New Construction Costs (NC), and the Aggregate of These
Costs (OMNC)1

OM NC OMNC OM NC OMNC
Change Change Change Change Change Change
In Percent In Percent In Percent ln Percent In Percent In Percent
Volumez Change3 Volume Change Volume Change Volume Change Volume Change Volume Change
50 Percent Cost Recovery Level

Gulf -0.01 -0.01 -0.04 -0.05 -8.36 -10.48 -0.01 -0.02 -0.05 -0.06 -0.08 -0.10 y.
Atlantic 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00  ’
Great Lakes 0.00 ’ 0.00 -0.01 -0.01 8.30 -16.10 0.00 0.00 -0.01 -0.01 -0.01 -0.02 l ‘
Pacific 0.00 0.00 -0.01 -0.01 -0.01 - 0.02 0.01 -0.01 -0.02 -0.02 -0.02 -0.02

Total‘ -0.01 -0.01 -0.06 -0.03 -0.07 - 0.03 0.03 -0.01 -0.07 -0.03 -0.10 -0.04

100 Percent Cost Recovery Level

Gulf -0.02 -0.03 -0.09 -0.11 -8.41 -10.55 -0.05 -0.06 -0.10 -0.13 -0.15 -0.19
Atlantic 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Great Lakes 0.00 0.00 -0.01 -0.02 8.28 16.06 0.01 -0.01 -0.01 -0.02 -0.02 -0.04
Pacific -0.01 -0.01 -0.03 -0.03 -0.03 - 0.03 0.02 -0.02 -0.03 -0.03 -0.04 -0.04

Total‘ -0.03 -0.01 -0.13 -0.06 -0.16 - 0.07 0.07 -0.03 -0.14 -0.06 -0.21 -0.09

Port-Specific Fees Uniform Fees

‘Numbers may not add up to totals due to rounding.
zMillion bushels.
3Percent change from baserun volume.

‘Overall reduction in U.S. hard red spring wheat exports resulting from increase in export price due to user charge imposition.

32

m9JL'$n.-.J_u.fi <

CPFabIe 29. Effect on U.S. Port Area Soft Wheat of a Weight-Based User Fee Which ls to Recoupe Operations and
Maintenance Expenses (OM), New Construction Costs (NC), and the Aggregate of These Costs (OMNC)1

Port-Specific Fees Uniform Fees
OM NC OMNC OM NC OMNC
Change Change Change Change Change Change
In Percent In Percent In Percent In Percent In Percent In Percent

Volumez Change3 Volume Change Volume Change Volume Change Volume Change Volume Change

50 Percent Cost Recovery Level

Gulf 7.72 8.21 7.70 8.18 12.29 13.07 8.79 9.34 8.77 9.32 8.76 9.32
Atlantic -7.73 -18.23 -13.44 -31.67 -12.38 -29.19 -8.80 -20.75 -8.82 -20.79 -8.84 -20.83
Great Lakes -0.01 - 0.01 5.65 12.18 - 0.02 - 0.05 -0.01 - 0.01 -0.01 - 0.03 -0.02 - 0.04
Pacific -0.06 - 0.02 0.20 - 0.08 - 0.24 - 0.10 -0.07 - 0.03 -0.13 - 0.06 -0.19 - 0.08

Total‘ -0.08 - 0.02 - 0.28 - 0.07 - 0.35 - 0.08 -0.09 - 0.02 -0.20 - 0.05 -0.29 - 0.07

100 Percent Cost Recovery Level

Gulf 7.70 8.19 7.66 8.15 12.26 13.04 8.77 9.32 8.75 9.30 8.74 9.29
Atlantic -7.75 -18.26 -13.48 -31.77 -12.44 -29.32 -8.82 -20.78 -8.85 -20.87 -8.88 -20.94
Great Lakes -0.01 - 0.02 5.64 12.16 - 0.04 - 0.10 -0.02 - 0.03 -0.02 - 0.05 -0.04 - 0.08
Pacific -0.10 - 0.04 - 0.38 - 0.16 - 0.49 - 0.20 -0.12 - 0.05 -0.27 - 0.11 -0.40 - 0.17

Total‘ -0.15 - 0.04 - 0.56 - 0.13 - 0.71 - 0.17 -0.18 - 0.04 -0.40 - 0.10 -0.58 - 0.14

‘Numbers may not add up to totals due to rounding.

zMillion bushels.

‘Percent change from baserun volume.

‘Overall reduction in U.S. soft wheat exports resulting from increase in export price due to user charge imposition.

Table 30. Effect on U.S. Port Area Soft Wheat of an Ad Valorem User Fee Which ls to Recoupe Operations and
Maintenance Expenses (OM), New Construction Costs (NC), and the Aggregate of These Costs (OMNC)1

Port-Specific Fees Uniform Fees
OM NC OMNC OM NC OMNC
Change Change Change Change Change Change
In Percent In Percent In Percent In Percent In Percent In Percent

Volumez Change3 Volume Change Volume Change Volume Change Volume Change Volume Change

50 Percent Cost Recovery Level

Gulf 7.72 8.21 12.32 13.10 7.71 8.19 8.79 9.34 8.78 9.33 8.77 9.32
Atlantic -7.73 -18.22 -12.34 -29.08 -13.42 -31.63 -8.80 -20.74 -8.82 -20.78 -8.82 -20.80
Great Lakes 0.00 0.00 - 0.01 - 0.02 5.65 12.18 -0.01 - 0.01 -0.01 - 0.02 -0.01 - 0.03
Pacific -0.02 - 0.01 - 0.09 - 0.04 - 0.10 - 0.04 -0.04 - 0.02 -0.10 - 0.04 -0.14 - 0.06

Total‘ -0.03 - 0.01 - 0.12 - 0.03 - 0.16 - 0.04 -0.05 - 0.01 -0.15 - 0.03 -0.21 - 0.05

100 Percent Cost Recovery Level

Gulf 7.72 8.21 12.30 13.08 7.69 8.18 8.78 9.33 8.76 9.32 8.75 9.30
Atlantic -7.73  -18.22 -12.36 -29.14 -13.44 -31.68 -8.81 -20.77 -8.84 -20.83 -8.86 -20.88
Great Lakes -0.01 - 0.01 - 0.02 - 0.03 5.65 12.18 -0.01 - 0.02 0.02 - 0.04 -0.03 - 0.06
Pacific -0.05 - 0.02 - 0.17 - 0.07 - 0.21 - 0.09 -0.09 - 0.04 -0.19 - 0.08 -0.28 - 0.12

Total‘ -0.06 - 0.02 - 0.24 - 0.06 - 0.31 - 0.07 -0.13 - 0.03 -0.29 - 0.07 -0.41 - 0.10

"\lNumbers may not add up to totals due to rounding.
Million bushels.
‘Percent change from baserun volume.
‘Overall reduction in U.S. soft wheat exports resulting from increase in export price due to user charge imposition.

33

Table 31. Effect on U.S. Port Area Du rum Wheat of a Weight-Based User Fee Which ls to Recoupe Operationfi .1
and Maintenance Expenses (OM), New Construction Costs (NC), and the Aggregate of These Costs (OMNC)1 r

   

Gulf
Atlantic
Great Lakes
Pacific
Total‘

Gulf
Atlantic
Great Lakes
Pacific
Total‘

OM

Change
In

Volume’ Change’

2.50
0.00
-0.44
-2.07
0.00

2.50
0.00
-0.44
-2.07
-0.01

Percent

16.06

0.00
- 0.89
- 8.82
- 0.00

16.06

0.00
- 0.89
- 8.83
- 0.01

Uniform Fees

NC

Port-Specific Fees

NC OMNC OM OMNC

Change Change
In Percent In
Volume

Change
Percent In
Change Volume Change Volume

Change
Percent In
Change Volume

Change
Percent In Percent
Change Volume Change

50 Percent Cost Recovery Level

2.50 16.06 2.50 16.06 2.50 16.06 2.50 16.06 2.50 16.06
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
-0.44 - 0.89 -0.44 - 0.90 -0.44 - 0.89 -0.44 - 0.89 -0.44 - 0.89
-2.07 - 8.83 -2.07 - 8.84 2.06 - 8.82 2.07 - 3.83 2.07 - 8.83
-0.01 - 0.01 -0.02 - 0.02 -0.00 - 0.00 -0.01 - 0.01 -0.01 - 0.01
100 Percent Cost Recovery Level
2.49 16.01 2.49 16.01 2.50 16.06 2.49 16.02 -2.49 16.01
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
-0.45 - 0.91 -0.45 - 0.92 -0.44 - 0.89 -0.44 - 0.90 -0.45 - 0.91
-2.07 - 8.86 -2.07 - 8.86 -2.07 - 8.84 -2.07 - 8.85 -2.07 - 8.86
-0.03 - 0.04 -0.04 - 0.04 -0.01 - 0.01 -0.02 - 0.03 -0.03 - 0.04

‘Numbers may not add up to totals due to rounding.

zMillion bushels.

3Percent change from baserun volume.
‘Overall reduction in U.S. durum wheat exports resulting from increase in export price due to user charge imposition.

Table 32. Effect on U.S. Port Area Durum Wheat of an Ad Valorem User Fee Which ls to Recoupe Operations
and Maintenance Expenses (OM), New Construction Costs (NC), and the Aggregate of These Costs (OMNC)l

OM NC OMNC OM NC OMNC
Change Change Change Change Change Change
In Percent In Percent In Percent In Percent In Percent In Percent
Volume’ Change3 Volume Change Volume Change Volume Change Volume Change Volume Change
50 Percent Cost Recovery Level
Gulf 2.50 16.07 2.50 16.06 2.50 16.06 2.50 16.06 2.50 16.06 2.50 16.06 ,
Atlantic 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 _ 1
Great Lakes -0.44 g - 0.89 -0.44 - 0.89 -0.44 - 0.89 -0.44 - 0.89 -0.44 - 0.89 -0.44 - 0.890
Pacific 2.06 - 8.82 2.06 - 8.82 2.07 - 8.83 -2.06 - 8.82 -2.07 - 8.83 -2.07 - 8.83
Total‘ 0.00 0.00 -0.01 - 0.01 -0.01 - 0.01 0.00 0.00 -0.01 - 0.01 -0.01 - 0.01
100 Percent Cost Recovery Level
Gulf 2.50 16.06 2.50 16.06 2.50 16.06 2.50 16.06 2.50 16.06 2.50 16.02
Atlantic 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Great Lakes -0.44 - 0.89 -0.44 - 0.90 -0.44 - 0.90 -0.44 - 0.90 -0.44 - 0.90 -0.44 - 0.91
Pacific -2.07 - 8.82 -2.07 - 8.83 -2.07 - 8.84 -2.07 - 8.82 -2.07 - 8.84 -2.07 - 8.85
Total‘ -0.00 - 0.01 -0.10 - 0.01 -0.01 - 0.02 -0.01 - 0.01 -0.01 - 0.01 -0.03 - 0.02

Port-Specific Fees Uniform Fees

‘Numbers may not add up to totals due to rounding.

zMillion bushels.

3Percent change from baserun volume.
‘Overall reduction in U.S. durum wheat exports resulting from increase in export price due to user charge imposition.

34

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[Blank Page in Original Bulletin] '

5c zlx I A. l»

‘Knit:

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1M—3-87