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Economic Brief

October 2012, EB12-10

Explaining an Industry Cluster:
The Case of U.S. Car Makers from 1895–1969
By David A. Price and Zhu Wang

The geographic clustering of companies within an industry is often attributed
to several agglomeration economies: intra-industry spillovers (benefits from
proximity to firms in the same industry), inter-industry spillovers (benefits
from proximity to firms in related industries), and spinoffs (firms established
by former employees of a company in the same industry). Analysis of data
on the U.S. auto industry in its first 75 years sheds light on the relative
importance of those forces to the clustering of car makers.
Geographic clustering of industries is common.
For example, the American film industry is concentrated disproportionately in the Los Angeles
area; finance in Manhattan; and computer
technology in Silicon Valley. In some cases,
clustering is readily explained. For example, in
the Fifth District, the concentration of federal
contractors in the Washington, D.C. metropolitan area reflects their desire to be near federal
agency customers. In other cases, particularly
in the manufacturing and energy sectors,
clustering may result in part from proximity to
transportation (such as waterways or railways)
or natural resources.
In addition to essentially exogenous factors
such as these, the emergence of industry clusters is believed to be influenced substantially
by the interplay of several forces that reward
geographic concentration. Economists have
studied these forces, known as economies of
agglomeration, at least since Alfred Marshall’s
Principles of Economics in 1890, in which
Marshall sought to explain what he called the
“localization of industries.”1 The study of agglomeration economies, and their importance

EB12-10 - The Federal Reserve Bank of Richmond

in relation to one another, helps to explain
differences in worker income and productivity in different geographical areas. It may assist
economists in tracing the role of urbanization
and in accounting for the rise of industrial
centers. It also may help national and regional
policymakers understand how to promote—or,
at least, not stifle—the development of industry
clusters that may lead to increased incomes. For
example, to the extent that agglomeration is
positively affected by the mobility of employees to found start-ups that compete with their
former employers, policies that strongly enforce
non-compete agreements may inhibit a region’s
growth and overall industry productivity.
Recent research by one of the authors of this article (Wang), together with Luís Cabral of New York
University and Daniel Xu of Duke University, seeks
to explain the clustering of the U.S. auto industry
in its first 75 years.2 They evaluate the relative
contributions of three agglomeration forces:
Intra-industry spillovers are benefits that a
firm receives from the presence of firms in
the same industry, such as labor pooling

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perhaps because they became dissatisfied with
the prospects of their initial company or because
they believed they could succeed as entrepreneurs. A well-known example of agglomeration from spinoffs is the Silicon Valley computer technology cluster, which arose largely
through spinoffs in the 1960s from Fairchild
Semiconductor—a firm that had itself spun
off from Shockley Semiconductor in 1957.4

(access to a concentrated pool of skilled workers who are drawn to the area by demand for
their skills), sharing of knowledge, and access
to needed inputs and supporting services.
Inter-industry spillovers are benefits that a firm
receives from the presence of firms in related
industries, especially the sharing of knowledge
across industries. The identification of this effect
is most often associated with Jane Jacobs’ 1969
book The Economy of Cities.3
Spinoffs are new companies formed by one or
more high-level, high-skilled employees who
defected from a company in the same industry,

While earlier work has considered the effects
of these forces on various industries, including
the auto industry, the research by Wang, Cabral,
and Xu is unique in quantifying the extent to
which each effect has influenced the industry’s

Figure 1: Clusters of Car Makers in 1910



New York

St. Louis











Sources: Philip H. Smith, Wheels within Wheels: A Short History of American Motor Car Manufacturing, New York: Funk & Wagnalls, 1968; and
Luís Cabral, Zhu Wang, and Daniel Xu, “Competitors, Complementors, and Parents: Explaining Regional Agglomeration in the U.S. Auto Industry”

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geographic concentration. Their research also examines how the importance of the forces in relation
to one another has changed over the industry’s
life cycle.

Figure 2: Percentage of Car Makers in Each Cluster
1895 1900 1905 1910 1915 1920 1925 1930 1935 1940
New York



St. Louis

Sources: Philip H. Smith, Wheels within Wheels: A Short History of American
Motor Car Manufacturing, New York: Funk & Wagnalls, 1968; and Luís Cabral,
Zhu Wang, and Daniel Xu, “Competitors, Complementors, and Parents:
Explaining Regional Agglomeration in the U.S. Auto Industry”

Number of Car Makers in 1910

Figure 3: Geographic Concentration of Car
and Carriage Industries

New York




St. Louis






Carriage and Wagon Industry Employment in 1904
Sources: Census of U.S. Manufacturers, 1904; and Philip H. Smith, Wheels
within Wheels: A Short History of American Motor Car Manufacturing, New
York: Funk & Wagnalls, 1968

Figure 4: Percent of Car Makers that Started
as Spinoffs







Sources: Standard Catalog of American Cars, 1890–1942; and Luís Cabral,
Zhu Wang, and Daniel Xu, “Competitors, Complementors, and Parents:
Explaining Regional Agglomeration in the U.S. Auto Industry”

The Auto Industry’s Evolution
The number of U.S. car makers during the industry’s
early decades swung widely, from a handful in the
late 1890s to more than 200 in 1910 and then back
down to eight survivors in the 1940s. The number
and locations of the industry’s centers of production
also varied over time. In the late 1890s, Chicago and
New York City were the most important clusters. By
1910, other production centers emerged, namely
Indianapolis, Rochester, St. Louis, and Detroit.
(See Figure 1.)5
The industry’s geographic concentration—in terms
of both the number of firms and the firms’ output—
grew over time. (See Figure 2.) By 1905, one-quarter
of all active firms were in the Detroit area, producing
more than half of the industry’s output; 16 percent of
the firms were in New York City; 10 percent in Chicago; 8 percent in Indianapolis; 7 percent in Rochester;
2 percent in St. Louis; and the remaining 32 percent
were scattered in other locations. Fifteen years later,
Detroit had 35 percent of all active firms and more
than 70 percent of output. By 1938, two-thirds of U.S.
car makers were headquartered in Detroit.
The industry’s early production clusters were also
centers of a related industry, carriage and wagon
manufacturing. A center’s activity in the carriage and
wagon industry, as measured by employment, correlates with the number of car makers in that area. (See
Figure 3.) One possible explanation of this relationship is the fact that many leaders in the infant auto
industry, such as William Durant (founder of General
Motors), had been veterans of the carriage and wagon industry. Their experience in the older industry
may have given them engineering, manufacturing,
or marketing know-how that was beneficial to them
as automobile entrepreneurs.
Many of the firms in the study (about 17 percent)
originated as spinoffs. Wang, Cabral, and Xu found
that over the course of the study period (1895 to
1969), there were more than 50 spinoff “families”—
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that is, groups of car makers with spinoff relationships. The largest of these was GM, which yielded
10 first-generation spinoffs and another five secondgeneration spinoffs, or spinoffs of spinoffs. Among
the first-generation spinoffs from GM were Chevrolet (later absorbed into GM), Chrysler, and Lincoln.
The percentage of car makers that were spinoffs
increased from zero in the industry’s first five years
to a high of 60 percent in 1938, declining steadily to
33 percent in the 1950s, and finally stabilizing at 40
percent in the 1960s. (See Figure 4.)
What Explains the Clustering?
Wang, Cabral, and Xu analyze the history of the industry—including its entrepreneurs, spinoff families,
and production centers—using data on every make
of car produced commercially in the United States
from 1895 through 1969. They consider 775 firms, together with data on the relevant regional economies,
including carriage and wagon industry employment.
They incorporate these data into regressions of firm
entry and exit, thereby testing the extent to which
the various agglomeration forces were associated
with greater clustering.6
With regard to intra-industry spillovers, they find no
measurable overall effect on industry clustering; that
is, the presence of other car makers did not appear
to increase firm entry rates or decrease exit rates. At
least in the context of the U.S. auto industry through
1969, this result contrasts with the view that clustering, in and of itself, induces other firms to locate in
an area in pursuit of benefits such as labor pooling.
While positive externalities from clustering may exist, negative effects from the concentration of firms
(such as greater competition for labor and other
inputs) appear to offset the positive externalities.
The researchers did find evidence for important effects from inter-industry spillovers (in this case, from
the carriage and wagon industry). The number and
quality of non-spinoff entrants, even including entrants from outside the carriage and wagon industry,
were significantly affected by the size of the carriage
and wagon industry in the area. While the researchers’ models do not seek to pinpoint the mechanism
by which a strong presence of the carriage and

wagon industry was associated with the development of the infant auto industry in a given area,
the correlation is clearly strong.
The researchers also find that spinoff effects matter.
According to their analysis, spinoffs accounted for
approximately one-third of the industry clustering
during the period, but contributed to agglomeration primarily in later stages of the industry’s life
cycle. The data also yield some indications of when a
spinoff was most likely to take place. The researchers
find that older firms were more likely to give birth
to a spinoff than younger firms. To the extent that
firms’ longevity may have reflected some threshold
of firm quality, this relationship suggests that higherability firms were more likely to give birth to spinoffs.
The likelihood of a spinoff was also associated with
the size of the family; the greater the number of
spinoffs that had already been formed within a family, the higher the probability that another spinoff
would emerge. Again, the size of the family also may
indicate the quality of the family, with high-quality
families generating more spinoffs. The likelihood of
a spinoff from a family was also associated with other
measures of the quality of the family, such as the
number of top automobile producers within
the family.7
These proxies for quality of the family were associated not only with the number of spinoffs, but also
with significantly increased survival rates of the
spinoffs. To investigate this phenomenon further, the
researchers look into the nature of the spinoff family
effect. They consider whether the effect was present
regardless of the spinoff ’s location or only for spinoffs located near their relatives; they find that family
size and quality matter only in the latter case. This
finding suggests that the family effect can be viewed
as a special form of local externality, requiring local
proximity, rather than an effect arising only from the
family relationship itself.
In the setting of the U.S. auto industry, the researchers’
analysis suggests certain refinements of traditional
views of agglomeration. It highlights the importance
of inter-industry spillovers; the significant, but lesser,

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importance of spinoffs; and no measurable overall
contribution by intra-industry spillovers.
Future directions for research on comparative agglomeration effects could include pursuing other
measures of firm performance and family quality,
such as net income, output, employment, or product variety. Further research could extend the
analysis to other, more recent industries. It also could
assess whether spinoff effects have become more
important with the emergence of new forms of financing for entrepreneurship, such as the large and
active venture capital industry.

This article may be photocopied or reprinted in its
entirety. Please credit the authors, source, and the
Federal Reserve Bank of Richmond and include the
italicized statement below.
Views expressed in this article are those of the authors
and not necessarily those of the Federal Reserve Bank
of Richmond or the Federal Reserve System.

David A. Price is senior editor of the Richmond
Fed’s quarterly magazine, Region Focus, and
Zhu Wang is a senior economist in the Bank’s
Research Department.

Alfred Marshall, Principles of Economics, London: Macmillan
and Co., 1890, p. 271.


Luís Cabral, Zhu Wang, and Daniel Xu, “Competitors, Complementors, and Parents: Explaining Regional Agglomeration in
the U.S. Auto Industry,” Manuscript, February 2012.


Jane Jacobs, The Economy of Cities, New York: Random House,


See Steven Klepper, “The Origin and Growth of Industry
Clusters: The Making of Silicon Valley and Detroit,” Journal
of Urban Economics, January 2010, vol. 67, no. 1, pp. 15–32;
also see Christophe Lécuyer, Making Silicon Valley: Innovation
and the Growth of High Tech, 1930–1970, Cambridge: MIT
Press, 2007.


Wang, Cabral, and Xu defined a production center city as a
city with at least five car producers in 1910. They then define
a region within a 100-mile radius of the center city as the
production center named after the city.


On account of the small number of firms from 1943 onward,
and the lack of new entrants from 1943–69, the regressions
cover only the 1895–1942 period.


Wang, Cabral, and Xu defined “top automobile producers” as
those whose sales ranked in the top 15 in the United States in
any one year.

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