Microeconomics of Reight Car Supply and Demand
Douglass Wm. List
Catherine S. Cook
George F. List
3
The second part of the paper describes how a
comparable process is used to estimate a demand
curve from traffic records common on most
freight railroads. Methods for handling such issues as the definition of demand and demand
segmentation are reviewed. The section concludes with examples of actual demand curves .
constructed using the outlined methodology. •
Abstract
To deal effectively with freight car investment
. decisions, knowledge of relevant demand and supply conditions is indispensable. Critics of
microeconomics argue that although important
variables that influence demand and supply can be
isolated by economic theory, they can never be
measured accurately empirically. This paper offers
a methodology for defining and quantifying a
railroad's demand and supply for freight cars in
classic microecono'mic terms, and shows how that
knowledge can be used in the capacity investment
decision process.
The third section of the paper demonstrates how
• the demand and supply curves interact, how the
curves can be adjusted to reflect broader market
realities, and how they can be. used to guide
management.decision-making. Drawing on
specific examples, the authors show how this
approach to investment can lead to 'fundamental
insights different from those often reached by
other evaluation processes.
. . .
The first part of the paper describes how to construct 'a supply curve for freight car capacity. The
relative economics of all sources for freight car
capacity are explored, including existing servicer
able equipment, potential repair program candidates, foreign equipment, leased equipment, and
new cars.
The paper is illustrated throughout with • data
drawn from actual railroad situations.
Management Consultant, Baltimore, Maryland. Formerly Vice-President, Marketing and
Strategic Planning, CSX Equipment,
President, Planning Associates, Cincinnati, Ohio. Formerly Director, Strategic Development,
CSX Equipment.
Assistant Professor, Civil Engineering, Rensselaer Polytechnic Institute, Troy, New York.
1
Introduction
Decisions regarding the addition or deletion of
freight car capacity are fundamental to a railroad
company. Often involving millions of dollars,
these decisions are usually made at the highest
levels of the organization after extensive involvement of many managers and analysts.
Despite the importance of these decisions, many
managers remain frustrated that they are often
made in the context of inadequate information information that fails to portray the key aspects of
such a major capacity decision with adequate richness as to its merits, dimensions, and potential
ramifications.
In the paper which follows, we will show how the
classic economic concepts of supply curves and
demand curves can be used to evaluate and communicate key aspects of car capacity situations.
This approach to evaluating car capacity issues
was initially developed as part of the equipment
planning process of CSX Equipment. A primary
objective was to make more explicit the relationships between marginal costs and marginal
revenues as-they relate to equipment investment.
Its conceptual origins lie in a broad base of published and unpublished thinking on
microeconomics and financial analysis in general,
as well as the application of these concepts to the
specifics of capacity investment, transportation,
and railroad freight cars. Several of the more significant references in these areas are noted at the
conclusion of the paper.
So as to preserve an orderly presentation of the
concepts, we begin by considering a single railroad as a "closed" system. Freight cars do notflow
in and out of the system, and we can create standalone, internal demand and supply curves for this
system without concern for broader markets. We
subsequently explore how the framework can be
adjusted to reflect market realities better, and how
the concepts can be applied in the capacity investment decision-making process.
Definition of Car Type
Quantity demanded and supplied depend on a
number of factors, not the least of which is the
shippers' ability to substitute another car type for
the one in question when market prices change.
Some car types, such as jumbo covered hoppers,
have close substitutes, such as medium cube
covered hoppers and even'open top hoppers fitted
with lids. A change in the price of jumbo covered
hoppers, the prices of the substitutes remaining '
constant, can be expected to cause a certain
amount of substitution. A fall in the price leads
shippers to use more jumbos, and arise in the price •
leads shippers to desire more of the substitutes.
To a great extent, the responsiveness of quantity
demanded and quantity supplied to price depends
on how widely or narrowly the car type is being
defined. There are very few close substitutes for
"box cars", for example, butseveral alternatives to
50 foot, 100 ton box cars with cushion underframes.
In our analysis, we assume for simplicity that there
is no substitution, among car types. That is, the
railroad cannot divert the demand for one car type
to another.
Constructing a Supply Curve for
Freight Car Capacity
We begin our discussion by looking at the supply
curve for freight car capacity. We start with the
supply curve because it is the easier to conceive,
and influences the structure of the demand curve.
Structural guidelines
The supply curve is the relation between the
amount of capacity supplied and theprice. For any
given price we need to ask what amount of
capacity the railroad will choose to supply. First,
we define the appropriate capacity unit, such as
"car-days", "car-months", or "car-years" along the •
x-axis, and "$/car-day" or other cost per unit of
capacity along the y-axis.
Second, we identify the time period relevant to the
investment decision. The pertinent time period will
vary depending on the certainty of forecasted,
demand and the flexibility of the railroad's repair,
purchase, lease and build capabilities. We are
primarily concerned with capacity that can be
brought on-line within that time frame, keeping in
Supply Curve
Car Type A
Dollars «o y
per car
per day
New Cars
<••
'•— Medium Repair
— Light Repair
v :
•y
V
l
0.0
',, , ..v-? ..* -.
l -1 l l l l i
3.0
6.0
9.0
12.0
l
l
15.0
i
^ ,' ,
i l l l
.18.0
21.0
i
24.0
i
1
27.0
1
-% i
s :
l l
30.0
- :
\1
33.0
36.0
39.0
Cumulative Equivalent Cars
(OOOs)
Figure A Freight Car Capacity Supply Curve
mind that we are as interested in potential capacity
as we are in existing capacity. Hence, a one-year
analysis should consider only how many new cars
could reasonably be purchased and installed within
that time frame, not the infinite number of new cars
which could be purchased in the longer term.
To create the supply curve, blocks of capacity are
arrayed from left to right in order of ascending cost,
as shown in Figure A. The process for estimating
the cost of each block of capacity is explored in
more detail below.
Existing serviceable fleet
Determining how much capacity is represented by
a given set of cars requires some thought Ultimately, we need to ensure that the measure of capacity
used in the supply curve is consistent with that used
in the demand curve. We favor the use of a measure
like "available car days" as a unit of capacity since
it is easier to manipulate consistently with data from
the demand side. To measure the "available" car'
days from a set of cars, total car days (number of
cars times total time period) must be reduced for
unavoidable out-of-service time required for normal maintenance and other unavoidable time between loads not captured by the demand analysis.
This is the least costly segment of the fleet to use.
Its cost can be modelled as the basic maintenance
costs to keep these cars in service: brake shoe replacement, wheel replacement, and the like. Such
costs typically run on the order of $25-50 per carper
month.
Existing unserviceable cars
Railroads usually possess an inventory of cars
which require substantial repairs to return to service.
These cars are typically listed as "(heavy) bad-
order" equipment In general, repair to these cars is
a more economical way to add capacity to the
servicea"ble fleet than the acquisition of new cars.
For purposes of the supply curve, we price this
latent capacity as an annuity. First, meaningful
repair categories may need to be defined, based on
extent and cost. For each group of cars with similar
repair needs, we estimate: the cash cost of the
repair, the expected serviceable life of the car
following repair, the periodic cost of keeping the
car in service, and the residual value of the car
when it falls out of service. Standard discounted
cash flow techniques can be used to convert this
stream of cash flows into an equivalent periodic
Discount Rate:
Full
Life Cycle
Basis
15.0%
New Car Cost:
. $35,000
Anticipated Life (years):
Repair Schedule:
Year 8
Year 15
Year 23
30
8,650
10,100
10,100
ves appear to function just as we would expect from
microeconomic theory, with prices on available cars
hovering just below the level that would make it
attractive to invest in additional capacity.
New cars
New car construction is usually at the far right
side of the supply curve. There are two distinctly
different methods for valuing new car construction, with profound implications for capacity investment decisions.
On some railroads, it is typical to look at the cost
of new car capacity on a full life-cycle basis. A
complete economic life cycle of
cash flows is estimated that includes not only new car acquisiService
tion costs and normal operating
Life Cycle
costs, but also a provision for
Basis
majorrepairs several times over
15.0%
the life of the car (say in years
8,15 and 23 for a car that is to
$35,000
last 30 years). This entire stream .
of cash flows is then reduced to
8
a single periodic payment'
0
0
0
An alternative approach is to
treat the new car in precisely the
same manner as an unserviceable
car being repaired- We do not
854
854
Basic Maintenance (per year):
assume
that the car will automat2,000
4,500
Salvage Value:
ically be repaired at the end of its .
initial service cycle. Instead, we
$(37,082) .
Net Present Value (before taxes): $(45,052)..
simply assign a residual value to
$(6,862)
$(8,264)
Equivalent Annual Cost:
the "hulk" which will remain at
the end of the first service cycle.
These two alternative apFigure B Estimating the Cost of New. Car Capacity
proaches to estimating the
equivalent periodic cost of new
payment This periodic payment is the cost as-.
car capacity are shown in Figure B.
signed to this source of capacity in the supply
curve.
Working through these two different approaches
with numbers, one discovers that the first approach
In effect, the "annuity" approach is an estimate of
yields a dramatically lower estimate of periodic cost
the lease rate'we would have to pay to get the
for new equipment than the second approach. In
specified capacity .from an external investor. Minieffect, the automatic repair assumption creates
mum free market lease rates for equipment are set
"cheap" future capacity that subsidizes the cost of
in precisely this manner. Investors contemplating
the first service cycle through the discounted cash
rebuilding cars to place them on the market look at
flow analysis.
these very same cash flows to determine whether
current market rates will support the financing costs
Which approach is correct? That depends largely
of the anticipated rebuilding. Market rates themselon investor behavior. Some freight car owners are
so intent on maximizing asset productivity that
they can be expected to meet downstream repair
needs almost automatically'. These owners can
"take the long view" and effectively plan for an
ongoing cross-subsidy from older cars to newer
ones. Most railroads, however, behave differently.
Cars which fall out of service are accumulated
until there is a clear need to repair them. The
decision to expend funds on major repairs is subject to extensive internal review. In such situations, any assumption of automatic downstream
repairs when acquiring new cars results in a gross
underestimation of the true cost of the additional
capacity. The single cycle approach is also somewhat more realistic if one believes there are
reasonable risks of premature technological obsolescence.
From a purely economic perspective, one would
argue-that new cars should be viewed as having a
single service cycle with a probability distribution
of residual values. The ."worst case" scenario is
that the car will only go one service cycle because
lack of demand or technological obsolescence
precludes repair for a second cycle. Immediate
repair andretum to service is in fact the "best case"
scenario in most.instances.
Observations about the supply curve
Following the principles outlined above, we can
construct a supply curve for freight car capacity as
shown previously in Figure A. If the analysis has
been done correctly,- the total number of cars
owned should be accounted for. Discrepancies
may be due to ambiguous car type .definition and
/or inaccuracies in record keeping.
The general shape of this curve is significant We
have a large region over which capacity is almost
free. 'Capacity then moves up steeply in price,
ending in a region where no additional capacity
can be obtained at any price for the period in
question. This shape to the car capacity supply
curve helps us understand the behavior of the
freight car capacity market. Relatively small
swings in demand can create dramatic changes in
market prices for equipment.
The supply curve we have constructed represents
a fixed period in time. Of greater interest to the
manager and planner is how this supply curve
changes over time.
In the very short run, the railroad can expand
capacity only through basic maintenance. The
supply curve resembles a backwards "L". At the
limit, the amount of supply is perfectly fixed at the
existing serviceable fleet level, regardless of the
prevailing market price.
In the long run, the railroad can respond to higher
prices by performing major repairs and new car
construction. Therefore, the longer the relevant
time period, the greater the effect of a given
change in price on the amount of capacity supplied. Over the very long run, when the railroad
has complete flexibility, in the amount it will supply, the supply curve for freight car capacity will
resemble the classic upward sloping supply curve.
Our medium-run step function supply curve lies
between these two extremes.
Absent investment activity, the supply -curve
"shifts left" over time as serviceable cars become
unserviceable and cars of all types are scrapped
and destroyed. While this "natural attrition" of
supply puts a constant upward pressure on prices,
we have seen in recent years that demand for a
particular car type can contract far faster than the
natural contraction rate for supply. The-more
dynamic the transportation marketplace becomes
in terms of its equipment needs, the more likely
we are to see major discontinuities caused by
market shifts away from existing capacity.
Constructing a Demand Curve for
Freight Car Capacity
Determining the railroad's demand curve is a more
difficult task both conceptually and practically.
However, most railroads today have sufficient
data available to permit a reasonable attempt at
defining their internal demand curve for equipment, and the results of the effort can be enlightening.
On the x-axis we measure the quantity of capacity
required to support a given piece of business. On
the y-axis, we estimate the net contribution that
will be earned by supplying the required capacity.
Both of these dimensions are explored in greater
detail below, but first we need to spend time
deciding how we will actually define "demand".
What demand is out there?
Clearly, the demand curve of interest in investment decisions should be forward-looking, and
some thinking should be devoted to how intelligence gleaned from historical records should be
adjusted for previously unserved demand and future adjustments in shipper requirements.
That said, the remainder of this discussion focuses
on the manipulation of historical traffic data to
develop the demand curve. We should reiterate
that we are looking at the railroad's internal
• demand for cars, not shipper demand for transportation per se. We take as a given that the revenue
received by the railroad for a particular movement
is set through some combination of market and
regulatory forces which are beyond the scope of
this analysis. We further assume that the maximum price the railroad will pay for equipment is
the full contribution before car costs derived from
this revenue.
The analysis presented here requires a data base that
can identify shipper, origin, contribution, any
specific car cost charges against contribution, and
car days required (loaded and empty) to handle the
traffic for individual traffic movements. We further
make the heroic assumption that the assignment of
empty days and empty transportation costs to individual data records is a reasonable representation
of the true incremental empty costs generated by
those movements. (How empty costs should be
assigned to loaded moves is a major topic in itself.)
Aggregating data around shipper/origin
. points
One simple approach to creating a demand curve
would be to take all of the railroad's traffic
records and sort them in descending order of
contribution before car cost per day. While often'
used, this approach is rarely effective. The least
profitable traffic identified by such an approach
tends to be thoroughly polluted with bad data,
extraordinary operational foul-ups, and specific
origin/destination pairs that are loss leaders
necessary to hold other profitable business. This
type of analysis stimulates extensive discussion
of data quality problems and finger pointing over
operational mistakes and pricing levels, but rarely decisive action over capacity investment
We leap over many of these problems by shifting
the focus from the profitability of individual carloads to the profitability of specific origin/shipper
points. The rationale for this shift is as follows:
• The shipper/origin point is the true logical unit of demand for a capacity invest-'
ment decision. The railroad clearly has
the ability to furnish or not furnish a car
to a specific shipper/origin point It has '
virtually no operational control over how
that car is subsequently used by the shipper.
• Operational foul-ups are largely probability-driven phenomena. Their occurrences usually have little or nothing to do
with the specific traffic movements with
which they appear. Aggregating the data
into larger units distributes these costs
back into the overall traffic base as they
should be.
• Data errors exhibit similar characteristics
to operational foul-ups. Costs and/or
revenues have become detached from
their appropriate home. Aggregating
data according to some criteria of "likeness" improves the chances that the right
costs and revenues will fall together in
the analysis.
Contribution per day before car costs
Most railroads have automated costing systems
for assigning to individual carloads an estimate
of the variable costs associated with that movement These costs include train labor, fuel, roadway maintenance, locomotive costs, and
equipment costs.
The appropriate price for the analysis is contribution before car costs, the gross margin left after
subtracting all variable costs except those associated with freight car ownership and maintenance from net revenue. This is the amount of
incremental contribution which the company
will earn if a freight car is provided. This contribution, will be compared to the incremental
cost of obtaining a freight car, as indicated by the
supply curve.
Estimating capacity requirements
Consistency with the supply analysis requires that
contribution before car costs be translated into a
contribution per unit time, usually per month or
per day. This conversion process is not as simple
as it sounds. In the denominator, we must be sure
to include the incremental days needed for supporting empty movements as well as the loaded
movement itself. Wherever possible, car day requirements which are movement driven (e.g. shipper detention) should be captured on the demand
curve in conjunction with the appropriate traffic
involved.
Constructing the curve
Construction of the demand curve begins at the left
with the most profitable traffic and continues right
in descending order of contribution per unit of
capacity.
While we can plot each shipper-origin point individually on this curve, for most purposes such
detail is unnecessary. A simpler approach is to
divide the traffic into larger blocks, say 10% increments, and plot the total capacity and average
contribution of each increment. This simplifica• tion protects the mathematical integrity of the
curve (for example, total contribution is the area
under the curve under either the detailed or
simplified approach) while making it easier to
prepare and analyze.
Observations
Four examples of demand curves are shown in
Figures C through F. These examples vividly illustrate how little an average contribution figure
communicates about the profitability of the underlying traffic. Average contribution figures can
mask the fact that 60% or more of the underlying
traffic will not support the marginal cost of
capacity.
Demand and Supply Interaction
The interaction of demand and supply determines
the railroad's optimal car supply in a competitive
market. Using historical data alone, there is a high
risk that the first attempt to overlay supply and
demand will be both surprising and disappointing.
The two curves cross at or below the size of the
existing fleet! (See Figure G.)
In retrospect, this is not a surprising result at all. If
the only demand reflected in the analysis is what
was actually carried historically, and the supply
curve reflects the current fleet size, the only
feasible points of intersection are to the left of the
current fleet size.
Meaningful results are achieved only if we project
future demand and supply. Demand must be adjusted up or down for anticipated changes in price
and volume. Supply must be adjusted, almost always down, for anticipated losses in capacity over
time, absent additions to the fleet With these
adjustments, the analysis begins to help sharpen
our understanding. (See Figure H.)
What is the anticipated capacity shortfall? What is
the contribution of the traffic at the margin? Is
investment in capacity warranted, or should the
marginal traffic be turned away? What is in the
marginal traffic category? Working from the
demand and supply curves and then- underlying
data, we can intelligently review the options for
bringing future capacity into line with future
demand, and the probable economic consequences
of each option.
Dealing with the Un-simplifying
Aspects of the Real-World Case
The supply and demand curves created above ignore many of the more difficult issues associated
with railroad interactions with one another and the
broader •markets for car supply and transportation
services. We identify below some of the major
complications that arise in adjusting these curves
to address real-world issues.
External sources of car supply capacity
Today there are a dazzling .array of options for
obtaining cars on the secondary market, including
short-term leases, medium-term leases, shareduse agreements, and car-hire leases. The general
approach we have taken with these options is to
attempt to define each one in sufficient detail to
reasonably estimate the level of available capacity
and effective cost of that capacity. Straight term
Demand Curve
Car Type A
Dollars
«° -g,"
per car
perday
*«-fi
• fairly concentrated market
$40 -f
• large variability in contribution
per day
$35 -f
• over half of this market has below
average contribution
$30 -t
$25 -!
$20 ~
'
'
Average Contribution = $17
$15 -f
$10 $5-
*°4—i
-3.0i i 6.0i i 9.0i i 12.0i r 15.0i i 18.01 - 1 21.0i —i—r
0.0
24.0
Cumulative Equivalent Cars
(OOOs)
Figure C
Demand Curve
Car Type B
Dollars
&° f
-
per car
per day
$4o-i
• highly concentrated market with
few shipper/origins
s35 ~\:
• most of this market has above
average contribution
$30 -j
$25 -|
^
/
Average Contribution = $21
$20 -t
$15 $10 -4
i
$5 H
0.0
i
i
3.0
i
i
6.0
i
i
9.0
i
i
12.0
i
i
15.0
n
Cumulative Equivalent Cars
(OOOs)
Figure D
i
18.0
i
i
21.0
n
i
24.0
Demand Curve
Car Type C
Dollars
per car
*so -
•;
\
• demand scattered across a
number of shipper origins
• a few highly profitable customers
,
$35 -
\
while some traffic has profitability
substantially below average
:
,
Average Contribution = $22
•.
••
\
v.
•.
s •••.
:
:
!
s
::
. rrn-.
>
x
• ;
p
•>
• • *""
>.
,.
""
.
:'
::
:
::
:
:
!
i
1
3.0
1
0.0
::
'••
::
%
\
i
6.0
9,0
12.0
15.0
1E.O
21.0-
24.0
Cumulative Equivalent Cars
(OOOs) . .
Figure E
Demand Curve
Car Type D
Dollars
per car
per day
»°'
•
$40-
few shipper/origins
» a small number of profitable
shipper origins distort average
f f
$35-
contribution
%
:
. '
f
$30-
•Average Contribution = $27
j
$25-
'•
"•
•.
;
$20-
'.
f
$15,_
%
£10-
•>•.
-
,
..,
,
,
o ^
Cumulative Equivalent Cars
(OOOs)
Figure F
r. %
.
, ^
i
1
1
1
1
I
1
Demand & Supply Curve
Car Type X
Dollars
per car
per day
Supply
-
Total
Serviceable
Fleet
Demanc
m w.
P__Ir
Heaviest Repair
- Medium Repair
- Light Repair
Basic Maintenance
0.0
3.0
6.0
9.0
12.0
15.0
18.0
21.0
24.0
27.0
30.0
33.0
36.0
39.0
Cumulative Equivalent Cars
(OOOs)
Figure G Demand & Supply Based on Historical Data
Demand & Supply Curve
Car Type X
Dollars *
per car
per day *« •
— Heaviest Repair
— Medium Repair
- Ugh! Repair
0.0
3.0
6.0
9.0
12.0
1S.O
10.0
21.0
24.0
27.0
30.0
Cumulative Equivalent Cars
(OOOs)
Figure H Demand & Supply Based on Forecasted Data
10
33.0
36.0
39.0
Basic Maintenance
leases under which cars function as if they were
owned by the lessee railroad are relatively easy to
incorporate. Reloading foreign equipment is
probably the most difficult, and is discussed in
detail below.
As a practical matter, many railroad data systems
fail to make this linkage. Absent significant data
enhancement, it is necessary to treat off-line time,
as a stand alone demand for capacity. If nothing
else, this treatment does allow the analyst to see
how off-line earnings compare with the marginal
cost of the capacity generating those earnings.
The general objective is to insert these capacity
options on the supply curve at the appropriate
point given by their cost. Hence, one source of
leased equipment may fall between two categories
of repair options. In this case and in the absence of
other factors, the leased cars are a more attractive
capacity option than the second set of cars to be
repaired.
Strategies for Improving
Management Decision Making
Despite these limitations, the demand and supply
curves can provide valuable insight to the asset
manager.
Non-system equipment
A major source of equipment on most railroads is
foreign equipment that can be reloaded before it is
returned to the owner% As a practical matter, this
is a difficult type of capacity to incorporate into
the model.
Using the supply curve
By definition, the supply curve indicates the
amount of capacity that the railroad should be'
willing to supply at any given price. As such, the
data also reflect the relative cost of different options for expanding, or contracting the fleet
Several fundamental questions may then be addressed.
In estimating the volume of available foreign
capacity we need to look at how much effective,
system-car equivalent capacity can be produced, a
number considerably differentfrom the actual number of car days on-line. Adjustments must be made
to refiectdiscretionary car days used to meet on-line
needs and involuntary .time created by inbound
loads. Part of the involuntary time is the unavoidable days required to dispose of the car if it is
not used for discretionary purposes. This source of
capacity may also be more or less efficient in terms
of general levels of utilization and empty transportation costs. Simply put, it is not safe to assume that
a foreign car with a nominal cost of $15 per day has
the same cost per unit output as a system car that
prices out to $15 per day.
For example, has the asset manager chosen the most
economical alternative for changing the fleet size?
In some instances, management may choose other
than the least cost option for intangible or "strategic"
reasons. The supply curve will then indicate how
much management is paying for these "strategic"
benefits.
Second, how does the current marketrate for freight
car capacity (in the form of short and long term lease
rates) compare to the marginal cost of the existing
fleet size? InFigurel, the prevailing marketrate (M)
is higher than the railroad's marginal cost of
capacity (C). Therefore, assuming that external
demand exists that will support rate M, the railroad
shouldrepaircarsup topointB and lease all capacity
not needed internally to the external market
Off-line time
Most railroads see their equipment go off-line in
support of forwarded movements. The investment
required to support this movement needs to be incorporated in our analysis.
A third area of constructive inquiry is how fast the
railroad can respond to any significant increase in
demand. When the supply of potential light repairs
and short term lease options is high, management
can take a "wait and see" approach to projected
demand. However, if short lead time options are
limited, the railroad may need to start placing orders
Ideally, off-line time associated with individual
movements shouldbe tied back to those movements
in the traffic data base. Hence, the demand for
capacity created by a specific movement and the
contribution produced includes the off-line portion
of that movement
11
Enhanced Supply Curve
Car Type B
Dollars
per car
per day
New Cars
Heaviest Repair
Medium Repair
Short-term lease
Light Repair
< |- Basic Maintenance
i
0.0
i r I T i n i r i i i i i t 11 j i I i i
3.0 ' 6.0
9.0
12.0
1S.O 18.0
21.0
A B 27.0
30.0
I I I i i
310
36.0 3S.O
Cumulative Equivalent Cars
(OOOs)
Figure I
and/or performing heavy repairs before they are
actually needed.
than marginal cost. The railroad in Figure J should
therefore expand .capacity to point E using light
repairs and short-term leases, where the contribution of the marginal traffic is greater than or equal
to the cost of the additional capacity.
Using the demand curve
With a few enhancements, the demand curve is a
powerful tool for stimulating management discussion. First, add a vertical line (C-D)' for the
forecasted level of total capacity for the relevant
time period. Barring additions to the fleet, the
railroad must forego part of its projected traffic
base. Second, superimpose horizontal lines representing the cost of various supply options. We now .
have a powerful one-page summary of the
economics surrounding a capacity investment
decision. Replacing the supply curve with the
horizontal lines masks some of the details around
the supply sideissues.butmakes the chartfar more
readable and comprehendible to the layman.
We can also see the relative importance of "car
ownership" and "track ownership" to the railroad's
economics. We will assume that the short term
lease rate Erie represents the' current market, rate
for equipment For most analyses, this line represents the economic cost of the equipment used by
the railroad. The contribution below this line less
the operating costs of car ownership is the net
contribution created by car ownership. The contribution above this line is created by other factors,
primarily by the ownership of the railroad's track
network. We assert that a major problem in the
financial analysis of railroad capacity investments
is the failure to separate, and not double count,
these two pools of contribution.
The downward sloping demand curve presumes
that-the least profitable traffic will be the first to
be turned away. (Again, management may have
"strategic" reasons for sacrificing other than the
least profitable markets.) Basic economics tells us
thatit will be profitable formanagement to expand
capacity whenever marginal revenue is greater
Economic analysis suggests that car ownership is
not required to capture the contribution above the
line, nor is railroad ownership required to capture
the contribution below the line. A freight car investment analysis thatiricludes contribution above
12
Enhanced Demand Curve
Car Type x
.
Dollars
per oar
per day
D
'
*« ~|
... D eman(
$40 -
forecasted
serviceable
fleet
M
$35 -
New Cars
$30 —
X
$25 —
'
$20 —
?%%%%{
J^ Off-line |
] On-line [
..
$15 —
%
$10 —
s
-;
-
„-;
i
v
$5 —
.
$
°
I
0
I
5,000
' „,
1
10,000
'
( (
'(///////A
<
.'
-™
j- . -
Medium Bepate
. n ,' ',',',' '.'.'.'.'
y//MW
'jjjfa
Short-term leases
•
w%%.
I
15,000
Heavy Repairs
1
C
.
HI
E
.
UghJ BeRaV1*
6asfc Maintenance
1
30,000
Cumulative Equivalent Cars
Figure J
the line as a return on' that investment grossly
overestimates the true economic return to the railroad from car ownership (as contrasted with the
options of short term leasing or shipper supplied
equipment). Similarly, an analysis of network
economics thatfails to deduct the full market value
of equipment from contribution figures can substantially overstate the economic earnings of the
network.
References
Allen, W. Bruce.The Demand for Freight
Transportation: A Micro Approach".
Transportation Research. Volume 11, pp. 914,1977.
Borts, G. 'Production Relations in the Railway
Industry". Econometrica, Volume 2.0, pp. 7179,1952.
Braeutigam, R.R., Daughety, AP., and Tumquist,
MA. "The Estimation of a Hybrid CostEunctionforaRailroadFirm".J?evfe>v ofEconomics
and Statistics, Volume 64, pp. 394-404,1982.
Conclusion
Despite the complexities of the freight car market,
the basic microeconomic concepts of demand and
supply can be applied effectively to railroad
freight car capacity investment decisions. The
results of such an analysis are invariably informative, often surprising, and should be considered
essential to making informed investment
decisions.
.Daughety, AP. and Inaba, F.S. "Estimation of
Service Differentiated Transport Demand
Functions". Transportation Research Record,
Volume 688, pp. 23-30,1978.
Daughety, A.F. "Freight Transport Demand
Revisited: A Microeconomic View of Multimodal, Multicharacterisric ServiceUncertainty
and the Demand for Freight Transportation".
13
Transportation Research, Volume 13B, pp.
281-288,1979.
Acknowledgements
The authors would also like to acknowledge the
following individuals whose own work contributed directly or indirectly to the concepts included in this paper: Joel Szabat, Ralph Tang, F.
William Barnett, Lee Broesch, R.M. Hebbeler,
David Levy, and R.A. Sewell.
Daughety, AJP., Tumquist, M.A. and Griesbach,
S.L. "Estimating Origin-Destination Specific
Railroad Marginal Operating Cost Functions".
TransportationResearch, Volume 17A, No. 6,
pp. 451-462,1983.
Daughety, A. F. "Transportation Research on Pricing'and Regulation: Overview and Suggestions
for Future Research". Transportation Research, Volume 19A, No. 5/6, pp. 471-487,
1985.
Felton, John Richard. The Economics of Freight
Car Supply. University of Nebraska Press, Lincoln, Nebraska, 1978.
Harker, Patrick T. "Research Directions in
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Keeler, TJ3. "Railroad Costs, Returns to Scale,
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Martland, Carl D. "Overcoming Fundamental
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Proceedings - Twenty-third Annual Meeting,
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Freight Transportation. Indiana University
Press, Bloomington, Indiana, 1980.
Winston, C. "The Demand for Freight Transporta' tion: Models with Applications". Transportation Research, Volume 17A, pp.419-427,
1983.
Winston, C. "Conceptual Developments in the
Economies of Transportation: An Interpretive
Survey". Journal of Economic Literature,
Volume 23(1), pp. 57-94,1985. .
14