Jacobs’ Externalities: Where We Have Been and Where We Might Go in Studying How
Urbanization Externalities Affect Innovation

Innovation is key to firms’ sustainable competitive advantage. When deciding where tolocate the firms’ innovation activities, managers must consider the locational factors that affectfirms’ innovation performance. Understanding what the most important factors are and how theycome into play is important. Existing literature on agglomeration and clusters emphasizes one
important factor: externalities. Externalities originate from the co-location of firms and relevant
institutions. Organizations are like leaking containers whose resources constantly spill over totheir immediate environment. The spillovers can be information, knowledge, talent, customers,
etc. As a result, co-located firms spontaneously create common goods shared by all neighbors.
The existence of externalities means when deciding where to locate their firms, managers must
pay attention to their neighbors.
Depending on the nature of externalities, researchers have differentiated two kinds ofexternalities (Gleaser et al., 1992). One is the Marshall-Arrow-Romer externalities, or the MAR
externalities. The MAR externalities root its theoretical foundation in the works of Alfred
Marshall (1890), Kenneth Arrow (1962), and Paul Romer (1986). In his seminal book Principles
of Economics (Book IV, Chapter X), Marshall’s (1890) listed four forces that drive
agglomeration: 1. Access to natural resources and transportation; 2. Labor pooling; 3.
Knowledge spillover; 4. Share of middle suppliers. Aside from access to resources andtransportation, all three other forces are externalities endogenously generated by lo-located firms.
Marshall’s externalities are complemented later by Arrow (1962) and Romer (1986), both ofwhom emphasize the role of knowledge in fostering endogenous growth. Arrow (1962) points
1out that because most learning happen in the process of doing, new technologies often emerge
from accumulated knowledge base. Similarly, Romer (1986) assumes knowledge has increasing
returns (because of spillover) and proposes an endogenous long-run growth model. Because of
its power in explaining agglomeration phenomena, the MAR externalities are further studied bymany other researchers such as Porter (1990), Krugman (1991a, b) and Saxenian (1994).
The other kind of externalities is Jacobs’ externalities. In contrast to the MAR
externalities which are generated by firms in the same industry, Jacobs’ externalities refer toexternalities generated by firms in different industries. Jane Jacobs believes knowledge spillovers
across industries are the most important source of innovation, and that economic diversity is a
key to urban prosperity (Jacobs, 1969). The rationale is diversity enables the cross-fertilization ofideas. In addition, diversity offers local labor force a broader mix of skills to working with newtechnologies.
An intriguing question to management scholars is whether Jacobs’ externalities havepractical implications to managers. Most researchers studying Jacobs’ externalities share a
primary interest in urban prosperity and growth issues (Beaudry & Schiffauerova, 2009; Fujita,
Krugman, & Venables, 1999; Fujita & Thisse, 2002) and the investigations often stay at theindustry level. Much fewer researches have been done to investigate the micro foundations ofJacobs’ externalities, i.e. how the forces function at the firm level. However, if we can observe
Jacobs’ externalities at the urban economies level, we should be able to observe them at the firmlevel as well and see how they affect certain activities of firms. Yet we know very little about
what is going on when zooming in to look at how individual firms are affected.
Despite of the relatively sparse knowledge we have on the micro foundations of Jacobs’
externalities, some pioneering studies have cast some light on the topic. Among them is a study2

by Duranton and Puga (2001). By observing the relocation of French manufacturing and businessservices firms, Duranton and Puga (2001) find a significant amount of firms in innovative
industries have relocated from diversified metro areas to more specialized metro areas over time.
They interpret the phenomenon as firms exploiting different agglomeration externalities atdifferent stages of the products’ life-cycle. In the firms’ product innovation stage, firms benefit
more from locating in diverse metro areas as diversity offers richer opportunities to experimentand lower searching costs. As production becomes standardized, however, firms have the
incentive to relocate to smaller, more specialized metro areas to reduce inefficiency and lower
production costs. Van der Panne and van Beers (2006) find contradictory evidence in their studyof firms in the Netherlands. They find that firms in Jacobian regions are more successful thanfirms in Marshallian regions in commercialization, while firms in Marshallian regions are more
successful than firms in Jacobian regions in product development.
From the pioneering studies on the micro foundations of Jacobs’ externalities we can see
Jacobs’ externalities seem to benefit certain firm activities more than others. But what activities
benefit more is far from clear. Moreover, preliminary findings are observatory in nature. The
mechanisms through which Jacobs’ externalities function are not fully examined. Generally
speaking, existing literature that covers Jacobs’ externalities lacks attention to “how.” Many
researches focus on isolating and comparing the effects of MAR externalities and Jacobs’
externalities, while the underlying processes through which the forces function remain largely
unexplored (Desrochers and Leppala 2011; Beaudry and Schiffauerova, 2009). The problem is,without thoroughly understanding how the forces function, the indicators we choose may risk tobe irrelevant and the conclusions we draw risk to be biased.

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The purpose of this paper is to examine where we have been in studying Jacobs’
externalities and discuss where we may go further down the path, and whether there is a need toadjust our direction. The following two sections provide a brief review on existing literature on
Jacobs’ externalities and discuss some major challenges. The next section specifies importantunanswered questions for future researches to consider.

Prior Literature
As there are different dimensions in firm performance, existing studies on Jacobs’
externalities use a variety of indicators to measure performance. For the purpose of this study,
the following review focuses on studies that concern innovation performance primarily. Thisfocus on innovation is consistent with the theoretical origin of Jacobs’ externalities, as Jacobs
believes the primary benefit of diversity is it fosters innovation (Jacobs, 1969).
Table 1: Empirical Studies on Jacobs’ Externalities and Innovation
Study

Industry

Time
Fra
me

Henderson(1986)

Multiple U.S. 1970
and Brazilian
industries

Industri
es

ProductivityGleaser
et al.
(1992)The largest
six industries
within agiven MSA
in the U.S.

Industries

Employment
growth1

19561987

Level of Innovatio
Analysi nsMeasures1

Indicatorsof Jacobs’
Externalit
ies
Urban
population,
total
employment

Geograp
hic UnitofAnalysis
MSAs,
urban
areas

Summary of
Relevant
Findings

Employme
nt in otherindustries

MSA

Diversity andcompetition
encourage
employment
growthFind no support
for urbanization
economies

This study does not investigate innovation directly but focuses on employment growth. Here I treat employment
growth as part of the result of innovation.

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Audresch&Feldman(1996)

Miscellaneous U.S.
manufacturin
g industries

1982

IndustriesDocumentedcommerci
alinnovationnone

statesIndustries forwhichknowledge
spillovers are
particularly
important havea highertendency toclusterHarrison, U.S.
Kelly, & manufacturin
Gantg(1996)

1987

Firms

Likelihoo
d to adopt
newtechnologyMetro area
size andcentrality

counties

Baptista UK& Swann manufacturin(1998)g

19751982

Firms

Employme
nt in otherindustries

U.K.
standard
regions

Baptista(2000)

CNC
machinetools andmicroprocess
ors

1981

Firms

none

U.K.
standard
regions

Regional
learning effectis mediated bystock of earlier
adopters

Duranton&Puga(2001)

Frenchmanufacturin
g andbusiness
services

19931996

Firms

Directinnovation
countsbased on apredefined
innovation
database(SPRU)
Time toadopt anew
technolog
y recorded
by UK
CSO
technolog
y adoption
surveyRelocation
fromdiversified
tospecialize
d areasFirms locatednear large
metro areas
have thehighestlikelihood toadopt newtechnologies
Strongemployment inother sectors
does not appear
to be significant
in affecting
innovation

Inverse ofaHerfindahl
index(employment
diversity)

Franceemployment areas

Firms learning
about theproduction
process benefit
from locating inlarge, diverse
metro areas;
however, forstandardized
production, firms
benefit morefrom locating insmaller,
specialized metro
areas

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Beaudry&
Breschi(2003)

UK andItalianmanufacturin
g industries

19901998

Firms

Numberof patents

Employme
nt in otherindustries

UK
countiesandItalianprovinces

Preliminary
results seem toindicate strong
presence offirms in otherrelatedindustries leadto morepatentingHenderson(2003)

U.S. hightech andmachineryindustry

19721992

Firms

ProductivityNumber ofplants inotherindustries

MSAs

Count of otherown industry
plants increases
the productivityof high-tech but
not machineryindustries. Find
little effect ofdiversity on
productivity

van derPanne
and vanBeers(2006)

Miscellaneous Dutchindustries

20002002

Firms

Innovation The
countscompleme
nt of theGini
coefficient

Postalareas

Desrochers &Leppala(2011)

NA

NA

IndividualinventorsInnovation Qualitative
countsNA

Firms in
Jacobianregions are
more successful
than firms in
Marshallian
regions incommercializati
on, while firmsin Marshallian
regions are
more successful
than firms in
Jacobianregions in
product
development
Qualitative
survey of
Canadianinventors

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Challenges
Industry or Activity. Recent studies on agglomeration show economic activities
agglomerate not by sector but by function (Duranton and Puga, 2005). Yet because in reality data
often comes in packages organized by industries, many studies on Jacobs’ externalities have usedindustries as the channel of observation and have not dug deeper to explore how the externalities
affect specific firm activities. Audresch and Feldman (1996) find that innovative activities tend
to cluster spatially, even after controlling for the agglomeration of production. Duranton andPuga (2001), van der Panne and van Beers (2006) find different activities of firms in the same
industry benefit differently from different agglomeration externalities. That means whenchoosing the channel to observe the effects of Jacobs’ externalities, it should make a difference
between choosing an industry and choosing a set of activities. Few research by far has addressed
this issue well.
Industry scope. One tricky conceptual problem in studying Jacobs’ externalities is how todefine “diverse.” Essentially, diversity depends on the standard researchers use to groupindustries or activities. Two industries can be identified as the same or similar using one
standard, or they can be identified as different using another standard. The conceptual trickperhaps explains most of the ramifications in findings using two, three, and four-digit SIC codes(Ellison and Gleaser, 1997). In addition, defining relevant industries is challenging (Rosenthal
and Strange, 2004). Standard industry classification may not be accurate. Ellison and Gleaser(1997) try to address the issue by analyzing product components. But most studies have nottaken similar measures but instead adopted restrictive treatments of industrial scope (Rosenthal
and Strange, 2004). Failing to adopt a flexible industrial scope may be a major limitation forstudies on Jacobs’ externalities, as the theory essentially deals with the cross-fertilization of ideas
7and products across industries. A side effect of failing to consider industrial distance is usingcoarse measurements for diversity. Many studies use employment in other sectors or Gini index
to proximate diversity. The measurements are too coarse to draw insightful conclusions.
Geographic scale. As Marshall (1890) and Krugman (1991b) argue, knowledge
spillovers are confined to certain geographic boundaries. Jaffe et al. (1993) find knowledge
spillovers tend to fade out over distance in their observation on patent citations. Rosenthal and
Strange (2003) find proxies for knowledge spillovers (the number of new products) positively
affect agglomeration at the zip code scale, but not significant at the county or state scale.
Rosenthal and Strange (2003) find agglomeration affect employment much more within the 1mile radius distance than the 5-mile radius distance, and there is virtually no effect at the 15-mileradius distance at all. Although those studies do not target Jacobs’ externalities and innovation
directly, the findings seem to indicate that certain externalities function at finer scales. Given thefact that existing researches investigating Jacobs’ externalities have mostly focused on the MSA
or county scale, it would be of interest to zoom in and conduct the investigation at finer scales.

Unanswered Questions
Jacobs’ externalities and the evolution of firms. Because many studies are confined toindustry boundaries, how externalities affect the evolution of industries and firms is virtually
unknown. However, we should take into consideration that firms are constantly evolving withthe environment, as Nelson and Winter (1982) point out firms are constantly searching for new
routines. Some routine innovations are local, while others are distant. Distant routine innovations
could mean the firm has ventured into some new businesses. It is therefore biased to view the8nature of a firm’s businesses as static. The evolutionary point of view is supported by evidences
documented in Chandler’s (1962) seminal book. For research on Jacobs’ externalities, theevolution of firms is theoretically interesting, as the theory emphasizes knowledge spillovers
across industries and how the spillovers foster the development of new industries. Consistent
with Jacobs’ theory, Marshall (1890), Brezis et al. (1993) and Porter (1990) point out that highly
specialized regions face higher risks of technological locked in. For future studies on Jacobs’
externalities, it would be of great interest to investigate how diversity affects the evolutionary
path of firms and fosters the development of new industries.
Jacobs’ externalities and entrepreneurship and radical innovation. Similar to thearguments above, how diversity affects entrepreneurship opportunities is another question ofinterest. If diversity is indeed as predicted a source of creativity, the spaces between industries
should be the cradle for new opportunities. Whether diversity nurtures more new opportunities
and how entrepreneurs exploit the opportunities are questions of interest to researchers interested
in geography and entrepreneurship. Following Joseph Schumpeter (1934), researchers
differentiate two kinds of innovation: progressive innovation and radical innovation (Brezis,
Krugman & Tsiddon, 1993; Anderson & Tushman, 1990). According to Jacobs’ prediction, firms
in diversified regions should have a better chance to generate radical innovation. Whether radical
innovations are more likely to happen in diversified regions and what specific conditions are
required to channel the process are little explored.
Demand-side externalities. To date, the majority of studies have investigated the supplyside externalities only. The rationale is that supply-side externalities are most pertinent toproduction. However, with businesses increasingly integrate user participatory design in theirproduction process, proximity to customers might be important to innovation (Feldman, 1994;9van der Panne and van Beers, 2006). It is therefore important to reconsider the role of demandside externalities in affecting innovation.

References
Arrow, K. J. 1962. The economic implications of learning by doing. Review of Economic
Studies, 29: 155–173.
Anderson, P., Tushman, M. 1990. Technological discontinuities and dominant designs: A
cyclical model of technological change. Administrative Science Quarterly, 35(4): 604-633.
Audretsch, D. B., Feldman, M. P. 1996. R&D spillovers and the geography of innovation andproduction. American Economic Review, 86(3): 630-640.
Baptista, R., Swann, P. 1998. Do firms in clusters innovate more? Research Policy, 27: 525–540.
Baptista, R. 2000. Do innovations diffuse faster within geographical clusters? International
Journal of Industrial Organization, 18(3): 515–535.
Beaudry, C., Breschi, S. 2003. Are firms in clusters really more innovative? Economics
of Innovation and New Technology, 12: 325–342.
Beaudry, C., Schiffauerova, A. 2009. Who’s right, Marshall or Jacobs? The localization versus
urbanization debate. Research Policy, 38: 318–337.
Brezis, E., Krugman, P., Tsiddon, D. 1993. Leapfrogging in international competition: a theoryof cycles in national technological leadership. The American Economic Review, 83(5): 12111219.
Chandler, A.D. 1962. Strategy and structure: Chapters in the history of the industrial
enterprise. Cambridge: M.I.T. Press
Desrochers, P., Leppala, S. 2011. Opening up the “Jacobs Spillovers” black box: local diversity,
creativity and the processes underlying new combinations. Journal of Economic Geography,
11(5): 843–863
Duranton, G., Puga, D. 2001. “Nursery cities: urban diversity, process innovation, and the lifecycle of products”. American Economic Review, 91(5): 1454-1477.
Duranton, G., Puga, D. 2005. From sectorial to functional urban specialization. Journal of Urban
Economics, 57(2): 343–370.
.
10

Ellison, G., Glaeser, E. 1997. Geographic concentration in U.S. manufacturing industries: adartboard approach". Journal of Political Economy, 105: 889-927.
Glaeser, E. L., Kallal, H. D., Scheinkman, J. A., Shleifer, A. 1992. Growth in cities. The Journalof Political Economy, 100: 1126–1152.
Harrison, B., Kelley, M. R., Gant, J. 1996. Specialization versus diversity in local economies: theimplications for innovative private-sector behavior. Cityscape, 2(2): 61–93.
Henderson, J. V. 1986. Efficiency of resource usage and city size. Journal of Urban
Economics, 19: 47-70.
Henderson, J.V. 2003. Marshall's scale economies. Journal of Urban Economics, 53: 1-28.
Jaffe, A. B., Trajtenberg, M., Henderson, R. 1993. Geographic localization of knowledge
spillovers as evidenced by patent citations. Quarterly Journal of Economics 108, 577–598.
Jacobs, J., 1969. The Economies of Cities. New York: Random House.
Krugman, Paul, 1991a. Geography and Trade. Cambridge, Mass.: MIT Press.
Krugman, Paul, 1991b. Increasing returns and economic geography. Journal of Political
Economy 99, 483-492.
Marshall, A. 1890. Principles of Economics, 8th edn. London: MacMillan. Available online at:
http://www.econlib.org/library/Marshall/marP.html
Winter, S. G., Nelson, R. R. 1982. An Evolutionary Theory of Economic Change. Cambridge,
Mass.: Harvard University Press
Porter, M., 1990. The Competitive Advantage of Nations. London: Macmillan.
Breschi, S., Lissoni, F. 2001. Knowledge spillovers and local innovation systems: a criticalsurvey. Industrial and Corporate Change, 10: 975–1005.
Romer, P. M. 1986. Increasing returns and long-run growth. Journal of Political Economy, 94:
1002–1037.
Rosenthal, S., Strange, W., 2003. Geography, industrial organization, and agglomeration.
The Review of Economics and Statistics 85, 377–393.
Rosenthal, S. S., Strange, W. C. 2004. Evidence on the nature and sources of agglomeration
economies. In J. V. Henderson, J.-F. Thisse (eds) Handbook of Regional and Urban
Economics, Vol. 4, pp. 2119–2171. Amsterdam: Elsevier.

11

Saxenian, A., 1994. Regional Advantage: Culture and Competition in Silicon Valley and Route128. Cambridge, Mass.: Harvard University Press.
Schumpeter, J.A. 1934. The Theory of Economic Development: An Inquiry into Profits, Capital,
Credit, Interest, and the Business Cycle. Transaction publishers.
Van der Panne, G., van Beers, G. 2006. On the Marshall–Jacobs controversy: it takes two totango. Corp Change, 15(5): 877-890.

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