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Economic Brief

November 2014, EB14-11

Does Enforcement of Employee Noncompete
Agreements Impede the Development
of Industry Clusters?
By David A. Price

Employee noncompete agreements are widespread among technical workers
and managers in technology companies. Policies regarding the enforcement
of these agreements vary among states, however. The rise of the technology
industry cluster in Silicon Valley and the car industry cluster in the Detroit
region occurred during periods when California and Michigan courts did not
enforce noncompete agreements. Research has sought to determine the
extent to which enforcement of noncompetes may suppress the formation
of industry clusters by restricting labor mobility and entrepreneurship.
Policymakers have long been interested in
fostering the formation and growth of industry
clusters—what Alfred Marshall in 1890 called
“the concentration of specialized industries in
particular localities.”1 An array of federal, state,
and local programs is aimed at doing so.2 This
interest is perhaps unsurprising since the iconic
example of clustering, California’s Silicon Valley,
has long been synonymous with economic
growth and technological innovation. Located
in an area that was largely agricultural in the
1940s, Silicon Valley now has the second-highest
concentration of high-income households in the
United States.3 There is evidence that industry
clusters in general are associated with higher
employment growth, wage growth, startup
activity, and patenting within the clustered
industry.4 Moreover, local service and retail firms
benefit from the economic activity generated by
the industry’s highly paid employees.
This Economic Brief discusses research suggesting that state policies on postemployment

EB14-11 - Federal Reserve Bank of Richmond

noncompete agreements, commonly known as
“noncompetes,” may affect the development of
industry clusters. These agreements prohibit a
worker whose employment has ended from going to work for a competitor of his or her former
employer, usually within a specified geographic
area and for a period of one to two years. Surveys
indicate that between 50 percent and 90 percent
of technical and managerial employees in technology companies are subject to one.5
Theoretical Effects of Noncompetes
In terms of economic theory, the net effect of
the enforcement of noncompetes is ambiguous.
On the positive side, enforcement may encourage employers to make more investments in the
human capital of their workers, such as training
programs. This is because employers are more
likely to make such investments if they believe
workers are less likely to move to competitors.
In addition, violation of a noncompete is generally easier to detect than the use of a past employer’s intellectual property; to the extent that

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noncompete enforcement protects the intellectual
property of firms more effectively than other methods, such as patent and trade secret protection,
enforcement may encourage firm entry and creation
of intellectual property. (Conversely, it is possible
that strong trade secret protection could partly offset the effect of nonenforcement of noncompetes,
although such protection likely would be a weak
substitute given the greater difficulty of learning
about trade secret violations.)

if they find the restriction “reasonable” as to geographic area and duration.9 In such a case, the employer can obtain an injunction barring its former
employee from working for the competitor and,
if appropriate, obtain an award of damages from
the employee. Within these general rules, there is
variation among enforcing states with regard to such
questions as the determination of reasonableness,
the burden of proof regarding reasonableness, and
the availability of punitive damages.

On the negative side, just as enforcement may encourage greater human capital investment by firms,
it may discourage self-investment in human capital
by workers because enforcement reduces their ability to capture gains from that investment.6 More
importantly, enforcement may directly suppress cluster development through several mechanisms. First,
by restricting the movement of workers, it limits diffusion of knowledge among an area’s firms (known
in the literature as “knowledge spillovers”).7 Second,
it may limit pooling of skilled workers, possibly suppressing wages of those workers and discouraging
their entry into the region. Finally, for the duration
of their noncompetes, enforcement may deter workers from founding spinoffs.

In practice, however, employers rarely need to
bring legal action; research indicates that the fear
of a noncompete being invoked may be enough
to ensure compliance. Based on a survey of 1,029
technology professionals and on interviews with a
separate group of 52 such professionals, Matt Marx
of the Massachusetts Institute of Technology found
that even without actual legal action, many workers
under a noncompete who changed jobs went so far
as to take career detours by switching industries in response to the noncompete; one-quarter of the survey
respondents who were bound by a noncompete and
changed jobs reported taking such a detour, as did
one-third of the interviewees.10

Although the magnitude of the effect of noncompetes on startups and on cluster development is
not known, it is a concern because spinoffs have
been found to perform better than other startups,
on average, in a range of industries, from disk drive
manufacturing to hedge fund management to
fashion design.8 Research on agglomeration in the
Silicon Valley computer and information technology
cluster and the Detroit region’s automotive cluster
indicates that spinoffs—and, by implication, the
noncompete enforcement policies of California and
Michigan at the relevant times—had an important
role in the economic rise of those regions.
Noncompete Policy and Practice
The enforcement of noncompetes is determined by
the laws of each state rather than by federal law. The
courts of nearly all states enforce noncompetes. A
somewhat simplified description of typical state law
in this area is that courts will enforce a noncompete

The reported experiences of Marx’s survey respondents help illuminate the circumstances in which
employees enter into noncompetes. Only 30.5
percent of the respondents who were presented with
noncompetes received them at the time of their job
offers. Some 22.2 percent received them after accepting offers, but before starting work (and thus possibly after giving notice to their current firms). A little
under half (45.3 percent) entered into noncompetes
on or after their first day with their new employers.
One possible interpretation of these results is that
workers do not view noncompetes as burdensome:
having knowledge of the prevalence of noncompetes
in their industries, they nonetheless often accept job
offers without demanding to see the terms of their
noncompetes. Another interpretation is that employers present new hires with noncompetes after
acceptance of job offers to take advantage of various frictions, such as the hirees’ eagerness to join the
firms and their limited ability to bargain after giving
notice to their current employers.

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Three states are outliers in their noncompete policies: California, North Dakota, and Oklahoma have
blanket bans on enforcement of noncompetes.11
Also, Michigan banned enforcement from 1905 until
1985.12 California’s ban has been on its statute books
since it attained statehood in 1872.13 Thus, the growth
periods of both the Silicon Valley and Detroit clusters
took place under unusual legal regimes in which
employers could not use noncompetes to prevent
employees from moving to competitive firms or
starting competitive firms.
Spinoffs in the Development of Silicon Valley
Silicon Valley, a region centered in the northern Santa
Clara Valley near San Francisco, takes its name from
the semiconductor cluster that transformed it into
a major industrial and commercial hub in the 1960s
and 1970s. This cluster was preceded by local manufacturing of vacuum tubes, microwave electronics,
and test equipment, activities that were encouraged
by Stanford University’s electrical engineering department. But Silicon Valley’s turning point occurred
in large measure through serendipity—namely, the
decision of William Shockley, former leader of the Bell
Labs team that had invented the transistor, to locate
his new semiconductor company in a place where he
could live near his mother and his childhood environs
of Palo Alto.14 At the time, in 1955 and 1956, there
were no other semiconductor manufacturers in the
region; the industry was concentrated in New York,
Los Angeles, and Boston.15
Many of Shockley’s technical staff, recruited from
across the country, became displeased with his management. Eight of them, including five with science
Ph.D. degrees, left in 1957 to start a competing semiconductor operation, Fairchild Semiconductor, which
was funded by Fairchild Camera and Instrument. The
Fairchild team patented what would become the preferred form of integrated circuit—the planar integrated circuit—in 1959 and brought the first integrated
circuit product to market in 1961.
Later in the 1960s, waves of Fairchild executives,
engineers, and production managers defected to
various startup competitors in Silicon Valley. Among
these so-called “Fairchildren” was Intel, the company

that would later invent the microprocessor. By 1976,
according to one count, at least 29 Silicon Valley semiconductor startups had one or more founders who
had previously worked for Fairchild.16
The employees joining these competitors commonly
received significant grants of stock options from their
new employers, a practice that Fairchild and other
established companies had extended only to senior
management. Such grants, which typically vest over
a period of three to five years, have become a common means for high-technology firms to recruit and
retain workers. Christophe Lécuyer of Université
Pierre et Marie Curie, a historian of the industry, has
written that the broad distribution of stock options—
a development brought about indirectly by Silicon
Valley’s fluid labor market—was an important innovation in itself; it reduced the division between
managerial and technical employees, gave technical
employees a more entrepreneurial point of view, and
helped Silicon Valley attract top talent from around
the country.17
Silicon Valley had started as a laggard in semiconductors relative to several other regions in 1955, but
two decades later, it represented some 43 percent
of the industry’s output. At that point, the top five
Silicon Valley semiconductor companies were Fairchild and spinoffs of Fairchild (in one case, a spinoff
of a spinoff ).18
The continued success of Silicon Valley’s high-mobility model after 1975 is highlighted by comparison with the computer technology cluster around
Boston’s Route 128. Companies in the Route 128
corridor, as in the rest of Massachusetts, could obtain
enforcement of noncompetes. Unlike in Silicon Valley, computer technology executives there tended
to prefer long-term corporate career paths and to
regard job-hopping as disreputable.19 It is not clear
how much this attitude was fostered by the fact that
noncompetes, or at least the fear of them, rendered
the job-hopping path and the spinoff path more difficult. Still, the economic benefits of the high-mobility model are suggested by the contrasting courses
of development of the two regions, as described by
April Franco and Matthew Mitchell of the University

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of Toronto: “In 1965, Route 128 had approximately
three times more technology employment compared to Silicon Valley. But by 1975, Silicon Valley’s
employment had quintupled, while Route 128 had
only tripled, resulting in 15 percent higher total employment in Silicon Valley. From 1975 to 1990, Silicon
Valley had tripled Route 128’s new job creation.”20
Franco and Mitchell characterize the overtaking of
Route 128 by Silicon Valley as “remarkable” and suggest, on the basis of a model of employee mobility
and spinoff formation, that it can be explained by
the difference in noncompete policy.
Spinoffs in the Development of Detroit
Like Silicon Valley, the Detroit region was not initially
a leader in its industry. At the outset of the U.S. auto
industry in the late 1890s, New York and Chicago
accounted for a larger share of auto manufacturers than Detroit.21 Yet by 1920, Detroit was clearly
dominant, with the highest share of manufacturers
by far and 70 percent of total output. This record
reflects the success of the Detroit cluster in surviving
industry-wide shakeouts that reduced the number
of automakers from its peak of 200 in 1910 to eight
in the 1940s.
The evolution of the Detroit cluster resembles that
of the Silicon Valley cluster in that many of its entrants were spinoffs—with the departing employees unconstrained by noncompetes. For example,
employees of General Motors (GM) spun off 10 auto
manufacturers between 1909 and 1924, including
Chevrolet (later absorbed back into GM), Chrysler,
and Lincoln.22 Four of these spinoffs yielded secondgeneration spinoffs.
According to research by the late Steven Klepper of
Carnegie Mellon University, Michigan’s car industry
had a total of 59 spinoffs, which made up 44 percent
of all entrants. No other state’s car industry had nearly
as many spinoffs; the closest states in terms of share
of entrants, Indiana and Pennsylvania, had 16 spinoffs
and 11 spinoffs, respectively, amounting to 23 percent and 21 percent of their entrants. Klepper found
that in Detroit, as in Silicon Valley, the superior performance of its cluster was the result of superior

performance by its spinoffs, specifically the spinoffs
“that were descended from the leading firms.”23
Research by Zhu Wang of the Richmond Fed, Luís
Cabral of New York University, and Daniel Xu of
Duke University has sought to break down the relative extent to which various factors contributed to
the formation of clusters in the early U.S. car industry.
As detailed in an earlier Economic Brief, “Explaining
an Industry Cluster: The Case of U.S. Car Makers
from 1895–1969” (October 2012), they found that
the presence of other car makers, by itself, did not
appear to increase firm entry rates or decrease exit
rates. They did find evidence that the presence of a
related industry—the older carriage and wagon industry, which was present to varying degrees in most
states with a significant car cluster—seemed to bring
spillovers that were beneficial to the clusters. As one
would expect, access to input materials was also
important. With respect to spinoffs, the researchers
concluded that spinoffs accounted for around onethird of the clustering in the car industry and that
spinoffs were more likely to survive than other firms.24
How General Are the Silicon Valley
and Detroit Experiences?
To what extent can economists and policymakers
extrapolate from the formation of Silicon Valley and
the Detroit region’s auto cluster? As an empirical
matter, the question is fraught with issues of multiple
causation. In recent years, researchers have studied
the effects of noncompete agreements using models
that incorporate national data on states’ enforcement
policies; the findings of this research point in more
than one direction.
With regard to human capital investment by firms,
research has borne out the prediction of economic
theory—that is, enforcement does, in fact, encourage firm-sponsored training and similar investments.
Evan Starr of the University of Michigan found that
a one-standard-deviation increase in the level of
enforceability leads to a 3 percent increase in firmsponsored training for occupations in which noncompete litigation is most prevalent.25 These findings are
consistent with evidence from European countries
indicating that employers tend to fund more general

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training (in other words, training in transferable skills)
if they have less cause to fear that employees will be
poached by competitors.26
Other research implies that enforcement may reduce
human capital self-investment by high-level employees. Mark Garmaise of the University of California,
Los Angeles considered the effects of noncompete
enforcement on the pay and mobility of executives
at large public corporations; he found that the more
stringently a state allows enforcement of noncompetes, the longer executives’ tenures at their companies tend to be, the less their compensation, and the
greater the use of salary compensation over alternatives such as stock options. Garmaise suggested that
these results may have stemmed from executives in
higher-enforcement states investing less in their own
human capital and that their self-investments were
more important than the firms’ investments in them.27
Looking at the effect of noncompetes on the incentives of established firms to innovate, a study
by Raffaele Conti of Bocconi University in Milan
concluded that enforcement, by enabling firms to
capture more securely the fruits of their innovations, may encourage those firms to pursue higherrisk research and development projects.28
With regard to the effects of enforcement on startup entry, research by Sampsa Samila of the National
University of Singapore and Olav Sorenson of Yale
University found that in states where enforcement of
noncompetes is barred or relatively more restricted,
an increase in the local supply of venture capital has
greater positive effects on the number of patents, on
the number of firm starts, and on employment.29
Another such effort, by Starr, Natarajan Balasubramanian of Syracuse University, and Mariko Sakakibara
of the University of California, Los Angeles found
that stricter noncompete enforcement reduces the
number of spinoffs. They also found, however, that
the prospective spinoffs that do overcome the barriers posed by noncompetes tend to have a higher
survival rate and tend to grow faster. They posited
that the entry barriers from noncompetes, such as
litigation and the fear of litigation as well as higher

recruiting costs, create a screen that favors spinoffs
with higher-quality ideas and more resources.30 They
also found that spinoffs in states with enforcement
were more likely to come from small parent firms,
perhaps because those parent firms are less likely
to pursue enforcement litigation.
Finally, MIT’s Marx, Jasjit Singh of INSEAD, and Lee
Fleming of Harvard University analyzed patent
data from 1975 to 2005 and found a “brain drain”
of employees who were inventors (patent holders)
from states that enforce noncompetes to those that
do not enforce them; the brain drain was greatest
among the highest-performing inventors.31 The researchers took advantage of the natural experiment
presented by Michigan’s 1985 policy change—from
nonenforcement to enforcement—to attempt to
tie the causation of the moves to noncompete policy.
To control for the influence of separate factors
specific to changes in the auto industry during the
period, they also conducted their analysis without
auto-related patents and reached similar results.
They also repeated their analysis with four other
states with industrial centers (Illinois, New York, Ohio,
and Pennsylvania), two of them in the Midwest near
Michigan, using their model and found no evidence
of a brain drain in those states during the period following Michigan’s policy change.
The role of spinoffs in the Silicon Valley and Detroit
clusters is an area of continuing study, as are the economic effects of noncompetes more generally. While
the experiences of these clusters are suggestive, the
influence of noncompetes may be sensitive to characteristics of the industry in question and the stage
of the cluster’s development. Further research could
shed light, as well, on the role of labor mobility and
other mechanisms in enabling clusters to reinvent
themselves, as in the case of Silicon Valley’s successful diversification from reliance on semiconductor
production to computer systems and software production and, more recently, Internet services.
David A. Price is a senior editor in the Research
Department at the Federal Reserve Bank
of Richmond.

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Marshall, Alfred, Principles of Economics, London: Macmillan
and Co., 1890.
At the federal level, such programs include Economic Development Agency grants to regional cluster efforts, the Small
Business Administration’s Regional Clusters Initiative, and
the Department of Energy’s Energy Innovation Hubs. See
Chatterji, Aaron, Edward L. Glaeser, and William R. Kerr, “Clusters of Entrepreneurship and Innovation,” National Bureau
of Economic Research Working Paper No. 19013, May 2013,
pp. 23–25. The America COMPETES Reauthorization Act of
2010, Section 603, established a regional innovation program
within the Department of Commerce to make grants and loan
guarantees to “support the development of regional innovation strategies, including regional innovation clusters and
science and research parks.”


See Bee, Charles Adam, “The Geographic Concentration of HighIncome Households: 2007–2011,” U.S. Census Bureau American
Community Survey Brief, February 2013, p. 7.


Delgado, Mercedes, Michael E. Porter, and Scott Stern, “Clusters,
Convergence, and Economic Performance,” National Bureau of
Economic Research Working Paper No. 18250, July 2012.






See Marx, Matt, “The Firm Strikes Back: Non-Compete Agreements and the Mobility of Technical Professionals,” American
Sociological Review, October 2011, vol. 76, no. 5, pp. 695–712;
also see Samila, Sampsa, and Olav Sorenson, “Non-Compete
Covenants: Incentives to Innovate or Impediments to Growth,”
Management Science, March 2011, vol. 57, no. 3, pp 425–438.
See Franco, April M., and Matthew F. Mitchell, “Covenants not
to Compete, Labor Mobility, and Industry Dynamics,” Journal
of Economics & Management Strategy, Fall 2008, vol. 17, no. 3,
pp. 581–606; also see Garmaise, Mark J., “Ties that Truly Bind:
Noncompetition Agreements, Executive Compensation, and
Firm Investment,” Journal of Law, Economics and Organization,
2011, vol. 27, no. 2, pp. 376–425.
On the role of job-hopping in diffusion of innovations in the
information technology industry, see Tambe, Prasanna, and
Lorin M. Hitt, “Job Hopping, Information Technology Spillovers,
and Productivity Growth,” Management Science, February 2014,
vol. 60, no. 2, pp. 338–355.
Regarding the disk drive industry, see Christensen, Clayton M.,
“The Rigid Disk Drive Industry, 1956–90: A History of Commercial and Technological Turbulence,” Business History Review,
Winter 1993, vol. 67, no. 4, pp. 531–588. Regarding the hedge
fund industry, see de Figueiredo Jr., Rui J.P., Philipp MeyerDoyle, and Evan Rawley, “Inherited Agglomeration Effects in
Hedge Fund Spawns,” Strategic Management Journal, July 2013,
vol. 34, no. 7, pp. 843–862. Regarding the fashion industry, see
Wenting, Rik, “Spinoff Dynamics and the Spatial Formation of
the Fashion Design Industry, 1858–2005,” Journal of Economic
Geography, September 2008, vol. 8, no. 5, pp. 593–614.
For recent tables of noncompete enforcement rules across all
50 states, see Kesan, Jay P., and Carol M. Hayes, “The Law and
Policy of Non-Compete Clauses in the United States and Their
Implications,” In Marilyn Pittard et al. (eds.), Business Innovation
and the Law, Cheltenham, U.K.: Edward Elgar Publishing, 2013,
pp. 400–404; and Beck, Russell, “Employee Noncompetes: A

State by State Survey,”, updated August 14, 2013.

Marx (2011)


Kesan and Hayes (2013); Beck (2013)


See Marx, Matt, Jasjit Singh, and Lee Fleming, “Regional Disadvantage? Non-Compete Agreements and Brain Drain,”
Manuscript, July 7, 2011, pp. 5–6.


See Gilson, Ronald J., “The Legal Infrastructure of High Technology Industrial Districts: Silicon Valley, Route 128, and
Covenants not to Compete,” New York University Law Review,
June 1999, vol. 74, no. 3, pp. 575–629. The background to the
adoption of the ban is set out by Gilson at pp. 613–619.


Berlin, Leslie, The Man Behind the Microchip: Robert Noyce and
the Invention of Silicon Valley, Oxford, U.K.: Oxford University
Press, 2005, p. 56.


See Klepper, Steven, “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.


Franco and Mitchell (2008), pp. 582–583


See Lécuyer, Christophe, Making Silicon Valley: Innovation and
the Growth of High Tech, 1930–1970, Cambridge, Mass.: MIT
Press, 2006, pp. 265, 300.


Klepper (2010), p. 20


See Saxenian, AnnaLee, Regional Advantage: Culture and
Competition in Silicon Valley and Route 128, Cambridge, Mass.:
Harvard University Press, 1994, pp. 62–63.


See Franco and Mitchell (2008), p. 582; also see Gilson (1999).


See Cabral, Luís, Zhu Wang, and Daniel Yi Xu, “Competitors,
Complementors, Parents and Places: Explaining Regional
Agglomeration in the U.S. Auto Industry,” Manuscript, August
2014, p. 5.


Cabral, Wang, and Xu (2014), p. 7


Klepper (2010), p. 29


Cabral, Wang, and Xu (2014)


See Starr, Evan, “Training the Enemy? Firm-Sponsored Training and the Enforcement of Covenants Not to Compete,”
Manuscript, April 23, 2014. For evidence that noncompete
enforcement improves the position of physicians working in
institutions, particularly in jobs where patient relationships
are somewhat transferable, see Lavetti, Kurt, Carol Simon, and
William D. White, “Buying Loyalty: Theory and Evidence from
Physicians,” Manuscript, October 10, 2014.


See Muehlemann, Samuel, and Stefan C. Wolter, “Firm-Sponsored Training and Poaching Externalities in Regional Labor
Markets,” Regional Science and Urban Economics, November
2011, vol. 41, no. 6, pp. 560–570; also see Brunello, Giorgio,
and Francesca Gambarotto, “Do Spatial Agglomeration and
Local Labor Market Competition Affect Employer-Provided
Training? Evidence from the UK,” Regional Science and Urban
Economics, January 2007, vol. 37, no. 1, pp. 1–21.


Garmaise (2011)


Conti, Raffaele, “Do Non-Competition Agreements Lead
Firms to Pursue Path-Breaking Inventions?” Presentation at
the DRUID 2011 Conference, Copenhagen Business School,
Denmark, June 15–17, 2011.

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Samila and Sorenson (2011)


Starr, Evan, Natarajan Balasubramanian, and Mariko Sakakibara, “Enforcing Covenants Not to Compete: The Life-Cycle
Impact on New Firms,” Manuscript, June 15, 2014.


Marx, Singh, and Fleming (2011)

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