# Transportation Economics/Land Use Forecasting

**Land use forecasting** undertakes to project the distribution and
intensity of trip generating activities in the urban area. In practice,
land use models are demand driven, using as inputs the aggregate
information on growth produced by an aggregate economic forecasting
activity. Land use estimates are inputs to the transportation planning
process.

The discussion of land use forecasting to follow begins with a review of
the Chicago Area Transportation Study (CATS) effort. CATS researchers
did interesting work, but did not produce a transferable forecasting
model, and researchers elsewhere worked to develop models. After
reviewing the CATS work, the discussion will turn to the first model to
be widely known and emulated: the Lowry model developed by Ira S. Lowry
when he was working for the Pittsburgh Regional Economic Study. Second
and third generation Lowry models are now available and widely used, as
well as interesting features incorporated in models that are not widely
used.

Today, the transportation planning activities attached to metropolitan
planning organizations are the loci for the care and feeding of regional
land use models. In the US, interest in and use of models is spotty, for
most agencies are concerned with short run planning and day-to-day
decisions. Interest is higher in Europe and elsewhere.

Even though there isn't much use of full blown land use modeling in the
US today, we need to understand the subject: the concepts and analytic
tools pretty much define how land use-transportation matters are thought
about and handled; there is a good bit of interest in the research
community where there have been important developments; and when the
next upturn in infrastructure development comes along the present models
will form the starting place for work.

## Land Use Analysis at the Chicago Area Transportation Study

In brief, the CATS analysis of the 1950s was "by mind and hand"
distribute growth. The product was maps developed with a rule-based
process. The rules by which land use was allocated were based on
state-of-the art knowledge and concepts, and it hard to fault CATS on
those grounds. The CATS took advantage of Colin Clark's extensive work
on the distribution of population densities around city centers.
Theories of city form were available, sector and concentric circle
concepts, in particular. Urban ecology notions were important at the
University of Chicago and University of Michigan. Sociologists and
demographers at the University of Chicago had begun its series of
neighborhood surveys with an ecological flavor. Douglas Carroll, the
CATS director, had studied with Amos Hawley, an urban ecologist at
Michigan.

!Stylized Urban Density
Gradient{width="350"}

Colin Clark studied the population densities of many cities, and he
found traces similar to those in the figure. Historic data show how the
density line has changed over the years. To project the future, one uses
changes in the parameters as a function of time to project the shape of
density in the future, say in 20 years. The city spreads glacier-like.
The area under the curve is given by population forecasts.

The CATS did extensive land use and activity surveys, taking advantage
of the City work done by the Chicago Planning Commission. Hock's work
forecasting activities said what the land uses-activities were that
would be accommodated under the density curve. Existing land use data
were arrayed in cross section. Land uses were allocated in a manner
consistent with the existing pattern.

The study area was divided into transportation analysis zones: small
zones where there was a lot of activity, larger zones elsewhere. The
original CATS scheme reflected its Illinois State connections. Zones
extended well away from the city. The zones were defined to take
advantage of Census data at the block and minor civil division levels.
They also strove for homogeneous land use and urban ecology attributes.

The first land use forecasts at CATS arrayed developments using "by
hand" techniques, as stated. We do not fault the "by hand" technique --
the then state of computers and data systems forced it. It was a rule
based land use allocation. Growth was the forcing function, as were
inputs from the economic study. Growth said that the population density
envelope would have to shift. The land uses implied by the mix of
activities were allocated from "Where is the land available?" and
"What's the use now?" Considerations. Certain types of activities
allocate easily: steel mills, warehouses, etc.

Conceptually, the allocation rules seem important. There is lot of
spatial autocorrelation in urban land uses; it's driven by historical
path dependence: this sort of thing got started here and seeds more of
the same. This autocorrelation was lost somewhat in the step from "by
hand" to analytic models.

The CATS procedure was not viewed with favor by the emerging Urban
Transportation Planning professional peer group, and in the late 1950s
there was interest in the development of analytic forecasting
procedures. At about the same time, similar interests emerged to meet
urban redevelopment and sewer planning needs, and interest in analytic
urban analysis emerged in political science, economics, and geography.

## Lowry Model

!Flowchart of Lowry
Model{width="600"}

Hard on the heels of the CATS work, several agencies and investigators
began to explore analytic forecasting techniques, and between 1956 and
the early 1960s a number of modeling techniques evolved. Irwin (1965)
provides a review of the status of emerging models. One of the models,
the Lowry model, was widely adopted.

Supported at first by local organizations and later by a Ford Foundation
grant to the RAND Corporation, Ira S. Lowry undertook a three-year study
in the Pittsburgh metropolitan area. (Work at RAND will be discussed
later.) The environment was data rich, and there were good professional
relationships available in the emerging emphasis on location and
regional economies in the Economics Department at the University of
Pittsburgh under the leadership of Edgar M. Hoover. The structure of the
Lowry model is shown on the flow chart.

The flow chart gives the logic of the Lowry model. It is demand driven.
First, the model responds to an increase in basic employment. It then
responds to the consequent impacts on service activities. As Lowry
treated his model and as the flow chart indicates, the model is solved
by iteration. But the structure of the model is such that iteration is
not necessary.

Although the language giving justification for the model specification
is an economic language and Lowry is an economist, the model is not an
economic model. Prices, markets, and the like do not enter.

A review of Lowry's publication will suggest reasons why his approach
has been widely adopted. The publication was the first full elaboration
of a model, data analysis and handling problems, and computations.
Lowry's writing is excellent. He is candid and discusses his reasoning
in a clear fashion. One can imagine an analyst elsewhere reading Lowry
and thinking, "Yes, I can do that."

The diffusion of innovations of the model is interesting. Lowry was not
involved in consulting, and his word of mouth contacts with
transportation professionals were quite limited. His interest was and is
in housing economics. Lowry did little or no "selling." We learn that
people will pay attention to good writing and an idea whose time has
come.

The model makes extensive use of gravity or interaction decaying with
distance functions. Use of "gravity model" ideas was common at the time
Lowry developed his model; indeed, the idea of the gravity model was at
least 100 years old at the time. It was under much refinement at the
time of Lowry's work; persons such as Alan Voorhees, Mort Schneider,
John Hamburg, Roger Creighon, and Walter Hansen made important
contributions. (See Carrothers 1956).

The Lowry Model provided a point of departure for work in a number of
places. Goldner (1971) traces its impact and modifications made. Steven
Putnam at the University of Pennsylvania used it to develop PLUM
(Projective Land Use Model) and I(incremental)PLUM. We estimate that
Lowry derivatives are used in most MPO studies, but most of today's
workers do not recognize the Lowry heritage, the derivatives are one or
two steps away from the mother logic.

## Penn-Jersey Model

!600 px\|Flowchart of Penn-Jersey land use forecasting
model

The P-J (Penn-Jersey, greater Philadelphia area) analysis had little
impact on planning practice. It will now be discussed, even so, because
it illustrates what planners might have done, given available knowledge
building blocks. It is an introduction to some of the work by
researchers who are not practicing planners.

The P-J study scoped widely for concepts and techniques. It scoped well
beyond the CATS and Lowry efforts, especially taking advantage of things
that had come along in the late 1950s. It was well funded and viewed by
the State and the Bureau of Public Roads as a research and a practical
planning effort. Its Director's background was in public administration,
and leading personnel were associated with the urban planning department
at the University of Pennsylvania. The P-J study was planning and policy
oriented.

The P-J study drew on several factors \"in the air\". First, there was a
lot of excitement about economic activity analysis and the applied math
that it used, at first, linear programming. T. J. Koopmans, the
developer of activity analysis, had worked in transportation. There was
pull for transportation (and communications) applications, and the tools
and interested professionals were available.

There was work on flows on networks, through nodes, and activity
location. Orden (1956) had suggested the use of conservation equations
when networks involved intermediate modes; flows from raw material
sources through manufacturing plants to market were treated by Beckmann
and Jacob Marschak (1955) and Goldman (1958) had treated commodity flows
and the management of empty vehicles.

Maximal flow and synthesis problems were also treated (Boldreff 1955,
Gomory and Hu 1962, Ford and Fulkerson 1956, Kalaba and Juncosa 1956,
Pollack 1964). Balinski (1960) considered the problem of fixed cost.
Finally, Cooper (1963) considered the problem of optimal location of
nodes. The problem of investment in link capacity was treated by
Garrison and Marble (1958) and the issue of the relationship between the
length of the planning time-unit and investment decisions was raised by
Quandt (1960) and Pearman (1974).

A second set of building blocks was evolving in location economics,
regional science, and geography. Edgar Dunn (1954) undertook an
extension of the classic von Thünen analysis of the location of rural
land uses. Also, there had been a good bit of work in Europe on the
interrelations of economic activity and transportation, especially
during the railroad deployment era, by German and Scandinavian
economists. That work was synthesized and augmented in the 1930's by
August Lösch, and his The Location of Economic Activities was translated
into English during the late 1940s. Edgar Hoover's work with the same
title was also published in the late 1940s. Dunn's analysis was mainly
graphical; static equilibrium was claimed by counting equations and
unknowns. There was no empirical work (unlike Garrison 1958). For its
time, Dunn's was a rather elegant work.

William Alonso's (1964) work soon followed. It was modeled closely on
Dunn's and also was a University of Pennsylvania product. Although
Alonso's book was not published until 1964, its content was fairly
widely known earlier, having been the subject of papers at professional
meetings and Committee on Urban Economics (CUE) seminars. Alonso's work
became much more widely known than Dunn's, perhaps because it focused on
"new" urban problems. It introduced the notion of bid rent and treated
the question of the amount of land consumed as a function of land rent.

Wingo (1961) was also available. It was different in style and thrust
from Alonso and Dunn's books and touched more on policy and planning
issues. Dunn's important, but little noted, book undertook analysis of
location rent, the rent referred to by Marshall as situation rent. Its
key equation was:

$R = Y\left( {P - c} \right) - Ytd$

where: *R* = rent per unit of land, *P* = market price per unit of
product, *c* = cost of production per unit of product, *d* = distance to
market, and *t* = unit transportation cost.

In addition, there were also demand and supply schedules.

This formulation by Dunn is very useful, for it indicates how land rent
ties to transportation cost. Alonso's urban analysis starting point was
similar to Dunn's, though he gave more attention to market clearing by
actors bidding for space.

The question of exactly how rents tied to transportation was sharpened
by those who took advantage of the duality properties of linear
programming. First, there was a spatial price equilibrium perspective,
as in Henderson (1957, 1958) Next, Stevens (1961) merged rent and
transportation concepts in a simple, interesting paper. In addition,
Stevens showed some optimality characteristics and discussed
decentralized decision-making. This simple paper is worth studying for
its own sake and because the model in the P-J study took the analysis
into the urban area, a considerable step.

Stevens 1961 paper used the linear programming version of the
transportation, assignment, translocation of masses problem of Koopmans,
Hitchcock, and Kantorovich. His analysis provided an explicit link
between transportation and location rent. It was quite transparent, and
it can be extended simply. In response to the initiation of the P-J
study, Herbert and Stevens (1960) developed the core model of the P-J
Study. Note that this paper was published before the 1961 paper. Even
so, the 1961 paper came first in Stevens' thinking.

The Herbert-Stevens model was housing centered, and the overall study
had the view that the purpose of transportation investments and related
policy choices was to make Philadelphia a good place to live. Similar to
the 1961 Stevens paper, the model assumed that individual choices would
lead to overall optimization.

The P-J region was divided into *u* small areas recognizing *n*
household groups and *m* residential bundles. Each residential bundle
was defined on the house of apartment, the amenity level in the
neighborhood (parks, schools, etc.), and the trip set associated with
the site. There is an objective function:

$\max Z = \sum_{k = 1}^u {\sum_{i = 1}^n {\sum_{h = 1}^m {x_{ih}^k \left( {b_{ih}  - c_{ih}^k } \right)} } } \quad x_{ih}^k  \geq 0$

wherein x~ihk~ is the number of households in group *i* selecting
residential bundle *h* in area *k*. The items in brackets are b~ih~ (the
budget allocated by *i* to bundle *h*) and c~ihk~, the purchase cost of
*h* in area *k*. In short, the sum of the differences between what
households are willing to pay and what they have to pay is maximized; a
surplus is maximized. The equation says nothing about who gets the
surplus: it is divided between households and those who supply housing
in some unknown way. There is a constraint equation for each area
limiting the land use for housing to the land supply available.

$\sum_{i = 1}^n {\sum_{h = 1}^m {s_{ih} x_{ih}^k } }  \leq L^k$

where: s~ih~ = land used for bundle *h* L~k~ = land supply in area *k*

And there is a constraint equation for each household group assuring
that all folks can find housing.

$\sum_{k = 1}^u {\sum_{h = 1}^m {x_{ih}^k } }  = N_i$

where: *N~i~* = number of households in group *i*

A policy variable is explicit, the land available in areas. Land can be
made available by changing zoning and land redevelopment. Another policy
variable is explicit when we write the dual of the maximization problem,
namely:

$\min Z' = \sum_{k = 1}^u {r^k L^k  + \sum_{i = 1}^n {v_i \left( { - N_i } \right)} }$

Subject to:

$s_{ih} r^k  - v_i  \geq b_{ih}  - c_{ih}^k$

$r^k  \geq 0$

The variables are *r^k^* (rent in area *k*) and *v~i~* an unrestricted
subsidy variable specific to each household group. Common sense says
that a policy will be better for some than others, and that is reasoning
behind the subsidy variable. The subsidy variable is also a policy
variable because society may choose to subsidize housing budgets for
some groups. The constraint equations may force such policy actions.

It is apparent that the Herbert-Stevens scheme is a very interesting
one. Its also apparent that it is housing centered, and the tie to
transportation planning is weak. That question is answered when we
examine the overall scheme for study, the flow chart of a single
iteration of the model. How the scheme works requires little study. The
chart doesn't say much about transportation. Changes in the
transportation system are displayed on the chart as if they are a policy
matter.

The word "simulate" appears in boxes five, eight, and nine. The P-J
modelers would say, "We are making choices about transportation
improvements by examining the ways improvements work their way through
urban development. The measure of merit is the economic surplus created
in housing."

Academics paid attention to the P-J study. The Committee on Urban
Economics was active at the time. The committee was funded by the Ford
Foundation to assist in the development of the nascent urban economics
field. It often met in Philadelphia for review of the P-J work. Stevens
and Herbert were less involved as the study went along. Harris gave
intellectual leadership, and he published a fair amount about the study
(1961, 1962). However, the P-J influence on planning practice was nil.
The study didn't put transportation up front. There were unsolvable data
problems. Much was promised but never delivered. The Lowry model was
already available.

## Kain Model

!Figure - Causal arrow diagram illustrating Kain's econometric model
for transportation
demand{width="600"}
About 1960, the Ford Foundation made a grant to the RAND Corporation to
support work on urban transportation problems (Lowry's work was
supported in part by that grant). The work was housed in the logistics
division of RAND, where the economists at RAND were housed. The head of
that division was then Charles Zwick, who had worked on transportation
topics previously.

The RAND work ranged from new technology and the cost of tunneling to
urban planning models and analyses with policy implications. Some of the
researchers at RAND were regular employees. Most, however, were imported
for short periods of time. The work was published in several formats:
first in the RAND P series and RM series and then in professional
publications or in book form. Often, a single piece of work is available
in differing forms at different places in the literature.

In spite of the diversity of topics and styles of work, one theme runs
through the RAND work -- the search for economic policy guides. We see
that theme in Kain (1962), which is discussed by de Neufville and
Stafford, and the figure is adapted from their book.

Kain's model dealt with direct and indirect affects. Suppose income
increases. The increase has a direct effect on travel time and indirect
affects through the use of land, auto ownership, and choice of mode.
Work supported at RAND also resulted in Meyer, Kain and Wohl (1964).
These parts of the work at RAND had considerable influence on subsequent
analysis (but not so much on practice as on policy). John Meyer became
President of the National Bureau of Economic Research and worked to
refocus its lines of work. Urban analysis Kain-style formed the core of
a several-year effort and yielded book length publications (see, e.g.,
G. Ingram, et al., The NBER Urban Simulation Model, Columbia Univ.
Press, 1972). After serving in the Air Force, Kain moved to Harvard,
first to redirect the Urban Planning Department. After a time, he
relocated at the Kennedy School, and he, along with José A.
Gómez-Ibáñez, John Meyer, and C. Ingram, lead much work in an
economic-policy analysis style. Martin Wohl moved on from RAND,
eventually, to Carnegie-Mellon University, where he continued his style
of work (e.g. Wohl 1984).

## Policy Oriented Gaming

The notion that the impact of policy on urban development might be
simulated was the theme for a conference at Cornell in the early 1960s;
collegiums were formed, several streams of work emerged. Several persons
developed rather simple (from today's view) simulation games. Land use
development was the outcome of gravitational type forces and the issue
faced was that of conflicts between developers and planners when
planners intervened in growth. CLUG and METROPOLIS are two rather well
known products from this stream of work (they were the SimCity of their
day); there must be twenty or thirty other similar planner vs. developer
in the political context games. There seems to have been little serious
attempt to analyze use of these games for policy formulation and
decision-making, except for work at the firm Environmetrics.

Peter House, one of the Cornell Conference veterans, established
Environmetrics early in the 1960s. It, too, started with relatively
simple gaming ideas. Over about a ten-year period, the comprehensiveness
of gaming devices was gradually improved and, unlike the other gaming
approaches, transportation played a role in their formulation.
Environmetrics' work moved into the Environmental Protection Agency and
was continued for a time at the EPA Washington Environmental Studies
Center.

A model known as River Basin was generalized to GEM (General
Environmental Assessment Model) and then birthed SEAS (Strategic
Environmental Assessment Model) and SOS (Son of SEAS). There was quite a
bit of development as the models were generalized, too much to be
discussed here.

The most interesting thing to be noted is change in the way the use of
the models evolved. Use shifted from a "playing games" stance to an
"evaluate the impact of federal policy" stance. The model (both
equations and data) is viewed as a generalized city or cities. It
responds to the question: What would be the impact of proposed policies
on cities?

An example of generalized question answering is LaBelle and Moses (1983)
La Belle and Moses implement the UTP process on typical cities to assess
the impact of several policies. There is no mystery why this approach
was used. House had moved from the EPA to the DOE, and the study was
prepared for his office.

## University of North Carolina

A group at Chapel Hill, mainly under the leadership of Stuart Chapin,
began its work with simple analysis devices somewhat similar to those
used in games. Results include Chapin (1965), Chapin and H. C. Hightower
(1966) and Chapin and Weiss (1968). That group subsequently focused on
(1) the ways in which individuals make tradeoffs in selecting
residential property, (2) the roles of developers and developer
decisions in the urban development process, and (3) information about
choices obtained from survey research. Lansing and Muller (1964 and
1967) at the Survey Research Center worked in cooperation with the
Chapel Hill Group in developing some of this latter information.

The first work was on simple, probabilistic growth models. It quickly
moved from this style to game-like interviews to investigate preferences
for housing. Persons interviewed would be given "money" and a set of
housing attributes -- sidewalks, garage, numbers of rooms, lot size,
etc. How do they spend their money? This is an early version of the game
The Sims. The work also began to examine developer behavior, as
mentioned. (See: Kaiser 1972).

## Reviews and Surveys

In addition to reviews at CUE meetings and sessions at professional
meetings, there have been a number of organized efforts to review
progress in land use modeling. An early effort was the May 1965 issue of
the Journal of the American Institute of Planners edited by B. Harris.
The next major effort was a Highway Research Board Conference in June,
1967 (HRB 1968) and this was most constructive. This reference contains
a review paper by Lowry, comments by Chapin, Alonso, and others. Of
special interest is Appendix A, which listed several ways that analysis
devices had been adapted for use. Robinson (1972) gives the flavor of
urban redevelopment oriented modeling. And there have been critical
reviews (e.g. Brewer 1973, Lee 1974). Pack (1978) addresses agency
practice; it reviews four models and a number of case studies of
applications. (See also Zettel and Carll 1962 and Pack and Pack 1977).
The discussion above has been limited to models that most affected
practice (Lowry) and theory (P-J, etc.) there are a dozen more that are
noted in reviews. Several of those deal with retail and industry
location. There are several that were oriented to urban redevelopment
projects where transportation was not at issue.

## Discussion

Lowry-derived land use analysis tools reside in the MPOs. The MPOs also
have a considerable data capability including census tapes and programs,
land use information of varied quality, and survey experiences and
survey-based data. Although large model work continues, fine detail
analysis dominates agency and consultant work in the US. One reason is
the requirement for environmental impact statements. Energy, noise, and
air pollution have been of concern, and techniques special to the
analysis of these topics have been developed. Recently, interest has
increased in the uses of developer fees and/or other developer
transportation related actions. Perceived shortages for funds for
highways and transit are one motive for extracting resources or actions
from developers. There's also the long-standing ethic that those who
occasion costs should pay. Finally, there is a small amount of
theoretical or academic work. Small is the operative word. There are few
researchers and the literature is limited.

The discussion to follow will first emphasize the latter,
theory-oriented work. It will then turn to a renewed interest in
planning models in the international arena. Modern behavioral, academic,
or theory-based analysis of transportation and land use date from about
1965. By modern we mean analysis that derives aggregate results from
micro behavior. First models were Herbert-Stevens in character. Similar
to the P-J model, they:

-   Treated land as the constraining resource and land use choices given
    land rent variations as the critical behavior.
-   Imagined roles for policy makers.
-   Emphasized residential land uses and ignored interdependencies in
    land uses.
-   Used closed system, comparative statics ways of thinking.
-   And gave no special attention to transportation.

There have been three major developments subsequently:

1.  Consideration of transportation activities and labor and capital
    inputs in addition to land inputs,
2.  Efforts to use dynamic, open system ways of thinking, and
3.  Inquiry into how micro choice behavior yields macro results.

The Herbert-Stevens model was not a behavioral model in the sense that
it did not try to map from micro to macro behavior. It did assume
rational, maximizing behavior by locators. But that was attached to
macro behavior and policy by assumed some centralized authority that
provided subsidies. Wheaton (1974) and Anderson (1982) modified the
Herbert-Stevens approach in different, but fairly simple, ways to deal
with the artificiality of the Herbert-Stevens formulation.

An alternative to the P-J, Herbert-Stevens tradition was seeded when
Edwin S. Mills, who is known as the father of modern urban economics,
took on the problem of scoping more widely. Beginning with Mills (1972),
Mills has developed a line of work yielding more publications and follow
on work by others, especially his students.

Using a Manhattan geometry, Mills incorporated a transportation
component in his analysis. Homogeneous zones defined by the
transportation system were analyzed as positioned x integer steps away
from the central zone via the Manhattan geometry. Mills treated
congestion by assigning integer measures to levels of service, and he
considered the costs of increasing capacity. To organize flows, Mills
assumed a single export facility in the central node. He allowed
capital-land rent trade offs yielding the tallest buildings in the
central zones.

Stating this in a rather long but not difficult to understand linear
programming format, Mills' system minimizes land, capital, labor, and
congestion costs, subject to a series of constraints on the quantities
affecting the system. One set of these is the exogenously gives vector
of export levels. Mills (1974a,b) permitted exports from non-central
zones, and other modifications shifted the ways congestion is measured
and allowed for more than one mode of transport.

With respect to activities, Mills introduced an input-output type
coefficient for activities; aqrs, denotes land input q per unit of
output r using production technique s. T.J. Kim (1979) has followed the
Mills tradition through the addition of articulating sectors. The work
briefly reviewed above adheres to a closed form, comparative statics
manner of thinking. This note now will turn to dynamics.

The literature gives rather varied statements on what consideration of
dynamics means. Most often, there is the comment that time is considered
in an explicit fashion, and analysis becomes dynamic when results are
run out over time. In that sense, the P-J model was a dynamic model.
Sometimes, dynamics are operationalized by allowing things that were
assumed static to change with time. Capital gets attention. Most of the
models of the type discussed previously assume that capital is
malleable, and one considers dynamics if capital is taken as durable yet
subject to ageing -- e.g., a building once built stays there but gets
older and less effective. On the people side, intra-urban migration is
considered. Sometimes too, there is an information context. Models
assume perfect information and foresight. Let's relax that assumption.

Anas (1978) is an example of a paper that is "dynamic" because it
considers durable capital and limited information about the future.
Residents were mobile; some housing stock was durable (outlying), but
central city housing stock was subject to obsolescence and abandonment.

Persons working in other traditions tend to emphasize feedbacks and
stability (or the lack of stability) when they think "dynamics," and
there is some literature reflecting those modes of thought. The best
known is Forester (1968), which set off an enormous amount of critique
and some follow on thoughtful extensions (e.g., Chen (ed), 1972)

Robert Crosby in the University Research Office of the US DOT was very
much interested in the applications of dynamics to urban analysis, and
when the DOT program was active some work was sponsored (Kahn (ed)
1981). The funding for that work ended, and we doubt if any new work was
seeded.

The analyses discussed use land rent ideas. The direct relation between
transportation and land rent is assumed, e.g., as per Stevens. There is
some work that takes a less simple view of land rent. An interesting
example is Thrall (1987). Thrall introduces a consumption theory of land
rent that includes income effects; utility is broadly considered. Thrall
manages both to simplify analytic treatment making the theory readily
accessible and develop insights about policy and transportation.

## Requiem

Wachs[^1] summarizes Lee\'s (1973) \"Requiem for Large Scale Models.\"
[^2] 

John Landis,[^3] has responded about seven challenges facing large scale
models:

1.  Models - microbehavioral (actors and agents) \... Social
    Benefit/Social Action
2.  Simulation - multiple movies/scenarios
3.  Respond to constraints and investments
4.  Nonlinearity - path dependence in non-artifactual way (structure and
    outcomes, network effects)
5.  spatial vs. real autocorrelation, emergence - new dynamics,
    threshold network effects
6.  preference utility diversity and change over time
7.  Useful beyond calibration periods. Embed innovators and norming
    agents. Strategic and response function.

## References

-   Alonso, William, Location and Land Use, Harvard Univ. Press, 1964.
-   Anas, Alex, Dynamics of Urban Residential Growth, Journal of Urban
    Economics, 5 , pp. 66--87, 1978
-   Anderson, G.S. A Linear Program Model of Housing Equilibrium,
    Journal of Urban Economics. 11, pp. 157--168, 1982
-   Balinski, M. L. Fixed-Cost Transportation Problems Naval Research
    Logistics Quarterly, 8, 41-54, 1960.
-   Beckmann, M and T. Marschak, An Activity Analysis Approach to
    Location Theory, Kyklos, 8, 128-143, 1955,
-   Blunden, W. R. and J. A. Black. The Land-Use/Transportation System,
    Pergamon Press, 1984 (Second Edition).
-   Boldreff, A., Determination of the Maximal Steady State Flow of
    Traffic Through a Railroad Network Operations Research , 3, 443-65,
    1955.
-   Boyce David E., LeBlanc Larry., and Chon K. \"Network Equilibrium
    Models of Urban Location and Travel Choices: A Retrospective
    Survey\" Journal of Regional Science, Vol. 28, No 2, 1988
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[^1]: Wachs, Martin (1994) Keynote Address: Evolution and Objectives of
    the Travel Model Improvement Program in Travel Model Improvement
    Program Conference Proceedings August 14--17, 1994, edited by Shunk,
    Gordon and Bass, Patricia <http://ntl.bts.gov/DOCS/443.html>

[^2]: Lee, Douglass (1974) \"Requiem for Large Scale Models.\" Journal
    of the American Institute of Planners. 39(3) 163\--178

[^3]: from PRSCO conference June 2001
