EVIDENCE-BASED
ECONOMIC
DEVELOPMENT
POLICY
MARYANN FELDMAN AND NICHOLA LOWE
Investing in economic capabilities that enhance firms’ ability to innovate and
compete on the world stage has become an important national and local policy
focus. This type of investment occurs in specific communities and jurisdic-
tion, often providing the foundation for regional economic development. Le
ability to extend economic prosperity depends on decision-makers’ under-
standing of how and whether such investments contribute to innovative
regional economies. Armed with this knowledge, decision-makers can evaluate
obstacles to innovation more effectively, and in the process they can tweak,
adjust, and—when necessary—redirect scarce policy resources in ways that
extend the benefits of innovation more widely.
For this to occur, cependant, it is important
that federal, state, and local policymakers
use accurate and timely data to shape
public investment decisions and policy
priorities, monitor progress, and suggest
pivots and improvements. While strate-
gies of entrepreneurship and innovation
are widely adopted with the assumption
that they will benefit society, there are
many instances in which public and pri-
vate investments in innovative activities
have failed to achieve their goal of pro-
moting regional development and broad-
ly shared prosperity. The failure of these
investments may be attributed in no small
part to competing and unreconciled
visions of economic development; unreal-
istic expectations about the foresight of
government agencies; and a dearth of
timely information on the status of local
économies, particularly updates on local
firms that provide jobs and increase pro-
ductivité. Analysts lack the timely micro-
level data they need to diagnose their
regions’ economic challenges and oppor-
tunities accurately, and policymakers lack
tested principles to compare across, et
act upon, suggested remedies. In the
absence of useful data and other key
information, policymakers are often left
to adopt programs and policies that they
believe have worked well in other places.
Cependant, policymakers tend to copy pol-
icy actions from regions that have very
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different characteristics and circum-
stances from where they are working,
thereby hoping for good results without
understanding what their own economic
and business communities need. Until
analysts have access to more accurate
data and information, policymakers will
continue to make decisions based on
anecdotes, intuition, and hope, plutôt
than on empirically sound evidence.
Our objective is to advance the use of data
in making decisions about economic
development investment and planning
projects to support innovation and entre-
preneurship. This requires rethinking the
way we approach the analysis of innova-
tive regional economies. Despite signifi-
cant public resources devoted to promot-
ing innovation and entrepreneurship,
there is little agreement about how to
measure and advance outcomes to
achieve the larger objectives of economic
development. This paper starts by defin-
ing economic development, en particulier dans
relation to entrepreneurship and innova-
tion, and then considers how government
can intervene to support new and innova-
tive firms and activities. We argue that
public policy should focus on building
individual and regional capacities that are
beyond the market’s ability to provide.
We also advocate for government as a
builder of capacities that enable econom-
ic agents—in this case entrepreneurial
founders and firms—to realize their
innovative potential.
DEFINING ECONOMIC
DEVELOPMENT
While this paper focuses on policy that
supports entrepreneurship and innova-
tion, it is useful to contextualize that
effort within a larger conceptualization of
economic development. Material pros-
perity and high quality of life are univer-
sal goals for democratically elected gov-
ernments
(Feldman, Hadjimichael,
Kemeny, & Lanahan, 2016). Cependant, le
way to achieve these goals most effective-
ly is the subject of considerable debate.
Policy agendas are dominated at times by
macroeconomic considerations that favor
austerity, yet there is widespread recogni-
tion that the
long-term growth of
advanced economies relies on active
intervention in support of innovation,
entrepreneurship, production, et travailler-
force development—decidedly microeco-
nomic concerns. Malheureusement, bien que
these topics have gained currency, ils
remain only one element in a chaotic and
divisive debate on the role of government
in the economy, and in particular in sup-
porting economic growth. To provide
greater background, this section draws on
prior work from Feldman et al. (2016),
Feldman & Storper (2016), and Lowe &
Wolf-Powers (2017).
The policy debate is particularly confused
because it lacks a clear, shared under-
standing of what we mean when we talk
about economic development. Policy dis-
ABOUT THE AUTHORS
Maryann Feldman is the S. K. Heninger Distinguished Chair in Public Policy at the
University of North Carolina, Chapel Hill.
Nichola Lowe is an Associate Professor in City and Regional Planning at the University of
North Carolina, Chapel Hill.
© 2017 Maryann Feldman and Nichola Lowe
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Maryann Feldman and Nichola Lowe
cussions on economic development fre-
quently conflate economic growth with
développement économique, as if the two con-
cepts are interchangeable. In designing
evidence-based policy, it is first important
to examine the difference between the
two concepts, and to differentiate the
objectives of economic development poli-
cy. Economic growth is the more straight-
forward concept, and it is easier to calcu-
late and compare across
locations.
Economic growth is traditionally meas-
ured by aggregate changes in rather well-
defined, quantifiable concepts, such as
gross national product.
Economic
growth is also the primary concern of the
branch of economics known as macro-
économie.
Economic development is a more difficult
concept to pin down. Most scholars asso-
ciate economic development with some
form of qualitative
socioeconomic
changement, although debate remains over
what form that change should take
(Fitzgerald & Green-Leigh, 2001; Malizia
& Feser, 1998). We broadly define eco-
nomic development as a transformative
process that contributes to qualitative
improvement of a range of economic
actors and organizations within a regional
economy. Economic development is not
just producing more of the same thing,
such as more jobs, more patents, plus
entrepreneurial firms. Plutôt, économique
development results in improved quality
of life (Feldman et al. 2016) et, où
economic benefits extend across society,
benefits those with more limited econom-
ic resources and power (Feldman et al.
2016; Lowe & Wolf-Powers, 2017).
But economic development is also a col-
lection of interventions that help increase
the capacity of a regional economy to sup-
port qualitative, transformative, et
ce
inclusionary
regard, economic development is neither
faceless nor predetermined but enacted; il
is shaped and reshaped by actors who
intervene to build the capacity to promote
improvements. Dans
a higher standard of life. In this paper, nous
are particularly interested in interven-
tions that enhance regional capacity to
support innovation through entrepre-
neurship. With that in mind, we draw on
work by Feldman et al. (2016) that con-
ceptualizes four overlapping and mutual-
ly reinforcing dimensions of regional
capacity. Each contributes to the overall
innovative capacity of the region and is a
potential target for interventions that
support entrepreneurial development:
(cid:2)(cid:1)Community capacity: The existing and
well-established physical (c'est à dire., location),
sociale, educational, and environmental
assets of a region or community
(cid:2)(cid:1)Firm and industry capacity: The assets
relevant to forming firms and develop-
ing industry, including facilities and
equipment, organizational know-how,
and supply-chain connections
(cid:2)(cid:1) Entrepreneurial capacity: The poten-
tial for generating new small business-
es, including a risk-taking culture, net-
travaux, and access to financial capital
and a skilled workforce
(cid:2)(cid:1) Innovative infrastructure capacity:
Regional capacity to support new prod-
ucts, processes, and organizations in
terms of facilities, support services, et
willingness to encourage creativity; ce
capacity relies on multiple, reinforcing
organizations
Other categories are certainly possible,
especially when other targets for econom-
ic development are involved, but these
four represent broad yet interconnected
constructs that governments could sup-
port, track, and align in their efforts to
promote regional innovation and entre-
preneurial capacity. An initial assessment
of these capacities also provides a
resource for diagnosing the prospects for
future innovation and entrepreneurship.
It can indicate where capacity is strong or
increasing, and highlight where addition-
al investigation and intervention might be
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Evidence-Based Economic Development Policy
needed to understand and overcome
roadblocks, information gaps, or underly-
ing tensions.
Capacity-building in a jurisdiction is
beyond the mandate of any private firm,
industry association, or other economic
institution. Ainsi, capacity can be
thought of as a key public good that is also
the basis for economic development poli-
cy. Capacity-building requires an active
public sector, but it also necessarily
involves a range of additional collective
actors or organizations. À cet égard, nous
do not limit our focus to policymakers or
professional planners, as we also recog-
nize the involvement of other economic
and institutional actors within a regional
setting (Lowe & Feldman, in press). Their
contribution to expanding micro-capaci-
ties for themselves and others can also
enhance region-wide capacity to support
creativity, resilience, and advancements
in product and process innovation. Ils
help create a relationship between the
new microeconomics of economic devel-
opment and desirable economy-wide
macro outcomes (Feldman & Storper,
2016).
What, alors, is the role of government in
economic development? Among institu-
tion, the public sector is arguably the
best-equipped actor in the economy, avec
the necessary long-term perspective, un
sufficient command of resources to make
large-scale investments in infrastructure
and education, and the ability to effective-
ly coordinate economic systems in sup-
port of innovation. De plus, govern-
ment—as the agent for its citizens—has a
mandate to ensure that the benefits
resulting from these investments are
widely and fairly distributed. At a funda-
mental level, the government’s role in
economic development is to strike a bal-
ance between realizing potential and
maintaining incentives for creative and
collective action; to provide scaffolding
for economic transactions without over-
regulating; and to make investments that
advance the public interest and encourage
the full participation of private individu-
als and organizations, meanwhile avoid-
ing corporatism, cronyism, and the pro-
motion of entrenched special interests.
Private-sector objectives are more easily
defined as maximizing profits and organi-
zational survival, although we increasing-
ly find examples where environmental or
social impact have been added to the mix.
Cependant, there is less consensus in gov-
ernment, and articulating a set of broad
policy objectives is more difficult due to
competing logic and interests. In the
absence of a consensus vision, it is too
easy for government to give in to short-
term demands or to privilege one objec-
tive at the expense of others. An articulat-
ed vision for government not only
requires reconciling diverse perspectives
and temporal horizons, but sometimes
also making difficult decisions that might
initially appear unprofitable for business-
es. This is also true within the policy
realm of innovation and entrepreneur-
ship, which in certain regional economies
has been enacted in ways that undermine
concurrent objectives to promote inclu-
sion and equity (voir, par exemple., Lowe & Loup-
Pouvoirs, 2017). This suggests that eco-
nomic development policy is not simply a
case of favoring certain objectives, mais
that it also requires building regional
capacity to integrate and align multiple
economic and social objectives, y compris
identifying and working through the
underlying frictions or tensions that
might hinder policy progress (Ashei,
Boschma, & Cooke, 2011; Lowe & Loup-
Pouvoirs, 2017; Pike, Rodríguez-Pose, &
Tomaney, 2007).
Ainsi, to construct our definition further,
economic development requires policy-
making through institutional integration,
and where that integration helps promote
consensus in support of openness and
access, tolerance for risk, appreciation of
diversity, and confidence in the realiza-
tion of mutual gain for citizens and for
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Maryann Feldman and Nichola Lowe
the private sectors (Feldman et al., 2016).
Institutional integration provides the
foundation for building basic capabilities
for sustainable economic development. Il
helps sustain the increasing prosperity
and quality of life that will be realized
through innovation, lower transaction
frais, and by applying innovative capabil-
ities to the responsible production and
diffusion of goods and services. Yet insti-
tutions are the result of interactions with
entrepreneurs over time and are socially
constructed, making them difficult to
étude (see Lowe & Feldman, in press).
Cependant, due to the availability of digital
data sources, the time is ripe for detailed
research on the interactions of institu-
tions and their role in entrepreneurism
and economic development (Feldman &
Lowe, 2015).
RECLAIMING POLICY
As indicated above, organismes gouvernementaux
provide essential support and guidance
for regional innovation, yet in that capac-
ity they often struggle with significant
gaps in knowledge. This policy paradox
once led mainstream economists to rec-
ommend that governments take a back-
seat to private investors and entrepre-
neurial firms in developing novel and
innovative technologies, the core assump-
tion being that market signals are superi-
or to government indicators in determin-
ing when, si, and where to invest.
In recent years, a compelling counterar-
gument has emerged that challenges this
perspective and recognizes the deeper
social and environmental benefits of
industrial policy, especially the role gov-
ernment agencies play in nurturing tech-
nologies long before they are viable for
private-sector investment (Block, 2008;
Lazonick & Mazzucato, 2013; Mazzucato,
2014; Rodrik, 2014; Schrank & Whitford,
2009). In this capacity, government does
not simply step into the fray once private
investors have evaluated and denied sup-
port for a nascent, potentially important
technologie. Motivated by long-term poli-
cy concerns and societal needs rather
than by more immediate profitability,
government agencies combine organiza-
tional capacity and technical expertise to
exercise control over a new technology
(Mazzucato, 2014). In other words, gov-
ernment is not simply responding to an
obvious market failure; it is also acting as
a forward-thinking catalytic force to sup-
port mission-oriented
innovation
(Mazzucato, 2015).
This revisionist stance—which has gained
strong academic and policy support in the
wake of the Great Recession and ultimate-
ly helped reignite an earlier policy debate
(Audretsch & Fritsch, 2002)—has led U.S.
researchers to document the pioneering
role of federal government funding for
essential platform technologies, y compris
the Internet, GPS, high-performance
lithium batteries, biotechnologie, le
Human Genome Project, and numerous
clean-technology applications (Block &
Keller, 2011; Fuchs, 2011; Rodrik, 2014).
Early government leadership in these
technology areas certainly has helped
spur profitable and competitive indus-
tries, along with phenomenal entrepre-
neurial success stories (par exemple., Apple,
Google, and Tesla), but more broadly it
has created opportunities to draw in and
guide private investment and encourage
the formation of public-private partner-
ships to help solve challenging social,
environmental, and medical problems.
Toujours, with this supportive turn toward
industrial policy comes growing recogni-
tion that public-sector agencies need
more accurate, opportun, and precise infor-
mation, not simply to track and publicize
the progress and potential of technologies
over time but to tweak, adjust, et, quand
necessary, redirect public resources and
support (Rodrik, 2014). Somewhat ironi-
cally, data gaps of this kind are rarely
solved with existing public datasets, dans
large part because of lengthy time lags,
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Evidence-Based Economic Development Policy
confidentiality requirements, and restric-
tive access (Feldman & Lowe, 2015).
Evaluations by academic researchers and
consulting firms are also limited, as they
tend to focus on the impact of one gov-
ernment-funded program in isolation
from others. This risks obscuring the role
earlier institutional support played in
helping to nurture and produce a success-
ful technology, which suggests the need
for alternative approaches to data analysis
and collection. This includes real-time
sources that can help government agen-
cies make better informed, more expedi-
ent decisions in support of technology
processes and mission-oriented objec-
tives.
We believe this challenge is particularly
pronounced among state and local gov-
ernments, which have been surprisingly
absent from current research on U.S.
industrial policy. While federal agencies
tend to support technology development
through investments in basic and applied
recherche, state and local government pro-
grams position themselves further down-
stream, where they help promote the
commercialization of technology by
actively engaging with entrepreneurial
firms and founders. As recent scholarship
on new industrial policy has noted, feder-
al agencies that support technology and
innovation often benefit from high-level
elected officials’ willingness to run inter-
ference when ideological challenges are
mounted by vocal critics of industrial pol-
icy (Block, 2008). Their involvement
helps build longevity and momentum in
federal policy, which in turn creates
breathing room to experiment with and
adapt policy. Cependant, these protective
buffers tend to remain at the federal level,
which suggests that state and local eco-
nomic development agencies might be
especially vulnerable to shifting political
perspectives and preferences, and to the
resulting cuts or challenges to local gov-
ernment funding and institutional sup-
port.
Reinforcing this view, many state and
local economic development practition-
ers face added pressure to prioritize
strategies that generate immediate politi-
cal payoffs for local politicians, y compris
those associated with high-profile ribbon-
cutting events and those that promise
more immediate gains in employment—
events that are less likely to involve small
entrepreneurial firms in the early stages of
technology development and commer-
cialization (Lowe & Feldman, 2015). Ce
often makes it harder for local practition-
ers to sustain support of innovation and
technologie, especially as such public
investments can take years, if not decades,
to pay off.
Timely, more immediate data sources are
therefore needed to help state and local
development agencies justify ongoing
support for entrepreneurship and tech-
nology development, and to know when
and whether to double-down their efforts
when a promising firm or technology is
not achieving its full potential. In the next
section, we discuss a specific type of data
needed to motivate and monitor the
development of innovative and entrepre-
neurial capacities over time.
ARTICULATING THE NEED
FOR DATA
New policy imperatives focus on innova-
tion, entrepreneurship, and emerging
technological industries—concerns that
were not important when legacy econom-
ic data systems—such as those collected
by government statistical agencies—were
designed. Innovation is not always visible
through new products, but it can be
observed through improvements to pro-
duction or design processes (Clark, 2013;
Doussard & Schrock, 2015; Feldman &
Ronzio, 2001; Pisano & Shih, 2012).
Entrepreneurship and the formation and
growth of new firms are important
sources of employment growth, but it is
difficult to capture changes in their prod-
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Maryann Feldman and Nichola Lowe
uct focus, as technology has become fluid
and defies
classification
industriel
schemes. Economic activity does not con-
form to the boundaries of political juris-
dictions or administrative data, mais
instead expands organically with trans-
portation links, available space, et
opportunité, making it particularly con-
founding to effective policymaking. Le
dynamic geography of innovative places
defies the way we typically collect data to
provide the evidence required for effec-
tive policy design and implementation, ou
to monitor investments and progress.
Investment analysts on Wall Street and
decision-makers in the private sector rely
heavily on data to inform their decisions.
Seeking the highest rate of return on their
money and leaving nothing to chance,
and up-to-the-minute
sophisticated
information tracks the movement of
stocks, which is summarized in charts and
synthesized into oft-quoted indices, comme
the Dow Industrial Average. All these
data inform investment decisions.
Contrast this situation to the information
typically used when making public invest-
ment decisions, specifically investments
in economic development that affect the
wealth of local economies. Economic
development practitioners have limited
access to the timely information that can
help them make the best investment deci-
sions. Our efforts to build and maintain
regional economic advantage often
involve some combination of bottom-up
efforts by regional public and private
actors and top-down resources invested
by the federal and state governments.
These efforts are far more scattershot
than would be the case if the actors
involved were able to access significantly
improved data and information.
In this time of economic volatility and
vulnerability to global competition, many
existing data products are not sufficient
for generating intelligent public and pri-
vate economic investment decisions.
Typical data products aggregate the num-
ber of businesses, jobs, and workers into
summary tables for jurisdictions that are
defined for other purposes, but firms do
not follow the contours of either political
jurisdictions or statistical regions; ils
instead locate along transportation links
where space is available and near other
interesting firms. Legacy federal econom-
ic data do not meet users’ regional data
needs because the traditional mission of
federal economic statistics agencies has
been to support federal macroeconomic
policy and guide the distribution of feder-
al funds to political jurisdictions with par-
ticular economic characteristics, such as
high unemployment.
Innovative sources of economic data,
cependant, offer analysts new ways of
understanding regional economic activi-
ty. A regional economy is the collection of
economic transactions among firms and
social relationships among people, lequel
are best understood with microdata.
Microdata at the level of firms and indi-
viduals can be used not only to track the
actions of individual institutions, entre-
preneurs, investors, and workers over
time and geographic space, but also to
provide information about the relation-
ships among these actors and the out-
comes of their relationships. While feder-
al agencies restrict access to administra-
tive data, there is a variety of digital data
sources that provide a wealth of timely
et
information.
Par conséquent, data sources like LinkedIn
and Wanted Analytics have far greater
capacity to provide immediate insights
into how regional economies work than
more traditional data products (voir
Feldman et al., 2012). These contempo-
rary and digital sources in turn facilitate
better
informed private and public
actions to create jobs, revenu, and profits.
disaggregated
Le plus important, the communities most
relevant for regional analysis do not fit
neatly within predetermined boundaries.
Areas such as Silicon Valley, Route 128,
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Evidence-Based Economic Development Policy
de
réussi
and the NC Research Triangle—the
archetypes
régional
economies—have complex, organically
evolved geographic shapes. These region-
al economies are built on the location of
prominent institutions and firms, sont
influenced by existing transportation
routes and land-use patterns, and expand
idiosyncratic and
out of seemingly
serendipitous events. Their spatial pat-
terns do not acknowledge political juris-
dictions or census geography, but instead
follow a logic that motivates firms to
locate near others with similar products,
marchés, and employees who have the
requisite workforce skills.
Regional economies not only blithely
ignore town and county boundaries, ils
disregard state boundaries as well.
En outre, the geographic clustering of
innovative, creative firms in small places
such as multitenant buildings, neighbor-
hoods, or adjacent industrial parks is
often invisible when data are available
only for larger, rigidly defined political
units, such as counties. Data that suggest
a cluster at the county level may indeed
mask several geographically and often
technologically distinct clusters grounded
in distinct social relationships, lequel
operate based on unique needs, produc-
tion logics, and positions in the value
chain. The use of aggregate data often
overlooks promising early-stage activity
and micro-geographies.
Locating market actors across real eco-
nomic space requires access to data that
facilitate flexible, user-determined analy-
sis of salient characteristics. Such data
may be drawn easily from standard
records, scraped from the Web, pulled
from voluminous documents through
text analysis, found on an open-data plat-
formulaire, purchased from a third party, et
integrated with other digital datasets.
There is more data available than ever
before, and it is now possible for
researchers to link and analyze microdata
to explore economic relationships within
unique, self-defined economic bound-
aries.
Successful efforts to build new companies
often result in an infusion of venture cap-
ital, a merger or acquisition, or some
other change in ownership that induces
relocation. As a result, successful eco-
nomic development may have a negative
impact on local employment in the near
term. Alternately stated, success in grow-
ing one particular company may, by cer-
tain metrics, appear to be a “failure” for
the region. En réalité, cependant, the locality
has benefited from the example of what
an entrepreneurial company can accom-
plish. This could persuade others to start
companies or invest in early stage activity;
additional company founders may stay in
the region and become serial entrepre-
neurs; and key employees will have
learned skills that will benefit their next
employer. The economic development
effort that was mistakenly judged to be a
failure in terms of local employment may
thus increase the region’s capacity in
future rounds of development.
As firms struggle to survive, they often
modify their products or services, mais
there is no time or incentive for them to
update their
industrial classification
codes or North American Industry
Classification System, the mechanism
used most often to understand industrial
activité. The innovative firms driving
regional economies are in fact fluid and
difficult to classify. The catalytic nature of
economic development can be under-
stood by demonstrating that projects that
translate research results into practical
applications can create not only new
firms but entire new industries. These
new industries create platforms that have
the potential to transform regional
économies, thus putting them on higher
growth trajectories, changing the types of
jobs offered and the skills required, pay-
ing higher wages, and providing better
products at lower prices for customers.
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Maryann Feldman and Nichola Lowe
Both patents and product announce-
ments provide information on the eco-
nomic future of firms. Patent documents
provide an idea of where a company is
headed with its inventive activity, alors que
new product announcements help to
explain where in the market a firm is plac-
ing its bets. Understanding forward-mov-
ing industrial activity requires classifica-
tion schema that are fluid and malleable,
and perhaps based on algorithmic text-
mining programming to define relational
attributes. Static classification schemes
will never provide an understanding of
the emerging technologies that have the
greatest promise for building new indus-
tries and setting regions on a new growth
trajectory. The time lag inherent in the
collection of traditional data sources
means that an analysis is consistently ret-
rospective and lagging behind the current
reality we are trying to analyze. These
limitations reflect the technologies of a
time before we had Internet access to cur-
rent administrative data and the comput-
ing power to manipulate them at our fin-
gertips.
Traditional datasets and industrial classi-
fications do not describe the relationships
between organizations and across space;
cependant, innovative data sources allow
the identification of networks and social
relationships among firms, between firms
and institutions, and between their con-
nections both inside and outside the
region. This enables analysts to determine
points of leverage for economic expan-
sion. These relationships are particularly
relevant for institutions such as universi-
liens, trade associations, business services,
and other quasi-governmental entities
that are important to innovative activity
and provide the foundation for regional
economic vitality.
Longstanding forms of economic data
also impede analysts’ ability to view mar-
ket actors’ behavior over time. Analysis of
regional innovation systems, par exemple,
has been limited to looking at a series of
disconnected snapshots, which can easily
lead to inappropriate or incomplete con-
clusions that ignore the complexity of
these endogenously and historically path-
dependent systems. Although case study
narratives provide insights, they lack both
analytical power and generalizability.
Cependant, using advanced IT, chercheurs
can now construct longitudinal microda-
ta that enable them to follow the dynam-
ics of emerging and mature industries,
understand the theoretically important
links between firms and institutions, et
measure the employment outcomes of
different approaches to education.
sources—based on
Innovative data
advanced IT, new statistical methods, et
nontraditional research topics—offer the
opportunity to fill this knowledge gap.
Realizing this opportunity will require
research organizations, federal decision-
makers, philanthropic
foundations,
entrepreneurs and private investors, et
economic and workforce development
agencies to do the following:
(cid:2)(cid:1) Support, demand, and create a market
for these innovative data sources
(cid:2)(cid:1)Continually redefine the state of the art
(cid:2)(cid:1) Bring to bear the degree of creativity,
risk-taking, and entrepreneurship
being asked of regional economic
actors
A plethora of innovative regional data
sources and tools are emerging from fed-
eral statistical and mission agencies, com-
mercial firms, universities, and nonprofit
research organizations. These data
sources have the potential to greatly
increase governments’ and advocacy
organizations’ ability to understand and
respond to issues and opportunities in a
timely manner. These data also provide
the resources needed to understand the
nature of regional economies, y compris
the factors that influence competitiveness.
De plus, tracking regional economies in
real time makes it possible to design
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Evidence-Based Economic Development Policy
national and regional policies and pro-
grams to promote economic develop-
ment, growth, and prosperity.
Information is one of the most essential
and cost-effective policy tools at govern-
ment’s disposal. Both policymakers and
market participants require current, accu-
rate, detailed economic statistics to moni-
tor, assess, and respond to competitive-
ness issues and opportunities. Addressing
these needs is a relatively low-cost
endeavor that increases the function of
markets and highlights both opportuni-
ties and potential problems. The availabil-
ity of economic data and the tools to ana-
lyze them has never been greater, yet fed-
eral economic policy and data collection
have remained tied to traditional busi-
ness-cycle management tools, with a
focus on data useful for fiscal and mone-
tary policy. As a result, the need for
coherent, evidence-based regional policy
is an important unaddressed need.
THE PROBLEMS OF
ATTRIBUTION AND WHY
BUILDING CAPACITY IS THE
THING THAT MATTERS
The highest scientific standard is to dis-
cern causality: if A, then B. Isolating the
effect of a treatment is the gold standard
in science and policy. Par exemple, quelques
quasi-experiments examine the impact
subsidized medical insurance has on
health outcomes, while others explore the
effects of individual choices, such as the
effect attending college has on lifetime
earnings. At the firm level, it is impossible
to attribute an outcome—for example, un
increase in sales of exported goods—to
one specific program. There are no pure
treatment effects for economic develop-
ment activity in general. This section
identifies some of the measurement prob-
lems inherent in evaluating economic
development programs
in order to
cement the need for an alternative, plus
expansive approach.
Case studies of the development of
regional economies reveal a complex
process in which public investment is
only one of many important elements.
Optimizing the performance of any one
component of such a complex system will
not necessarily optimize or even improve
the performance of the system overall, comme
the returns to economic development are
affected by multiple individual decisions
and the influence of multiple actors.
Regional development is also affected by
macroeconomic policy changes that,
while exogenous, certainly affect out-
comes in ways that are not entirely pre-
dictable. Cependant, regional economies
have interrelated sequences and processes
that make it difficult to link economic
development investments to outcomes
with any degree of precision.
De plus, the amount of funding provid-
ed for economic development, alors que
important to recipients, is miniscule rela-
tive to the size of a regional economy.
Attributing good outcomes to specific
programs, investments, or events is prob-
ably more about good luck, publicity, et
hype than true causality demonstrated by
sound economic analysis. Communities
that apply for economic development
funding appear to be better organized
than the average, et la communauté
organizations that lead funded projects
usually are connected to professional net-
works and aware of funding opportuni-
liens. This heightened awareness, com-
bined with a higher level of social capital,
certainly differentiates projects
que
receive funding from those that do not
even apply for support.
Economic development engages a wide
range of activities, from building infra-
structure to developing businesses. Ce
variety is warranted because the projects
serve heterogeneous communities and
technologies. Evaluating outcomes is eas-
iest when comparing similar programs or
inputs; it would in fact be facilitated if
projects offered identical services, mais
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Maryann Feldman and Nichola Lowe
that would not advance the mission of
local economic development officials.
Edwin Mansfield (1991) noted that the
lag between an academic
temporal
research discovery and new product
innovation is seven years. Many other
economists have tried various approaches
to estimating the temporal lag between
investment in R&D and the realization of
benefits. The consensus is that the time
lag between investment in research and
realized commercial advances is lengthy,
uncertain, and varies
significantly
between fields. En fait, un 2001 National
Academy of Sciences report observed that
“history . . . shows us how often basic
research in science and engineering leads
to outcomes that were unexpected or took
many years or even decades to emerge.”
Perhaps the best way to invest in local
economic development is simply to make
steady progress on a variety of measures
of increased capacity. Monitoring real-
time data on a region provides an ability
to spot trends and direct attention to cor-
recting deficits and remediating prob-
lems.
BUILDING AN EVIDENCE
BASE: THE EXAMPLE OF
THE RESEARCH TRIANGLE
Seven years ago, we began developing a
database that provides a 50-year perspec-
tive on technology-intensive entrepre-
neurial activity in North Carolina’s
Research Triangle (Feldman & Lowe,
2015). Funding from the National Science
Fondation, the Kauffman Foundation,
and the University of North Carolina has
supported the development of this data-
base, which provides a unique resource
for studying the temporal dynamics of a
regional economy using a firm-centric
analytical framework while also consider-
ing the institutional richness of the
regional support system. Our method-
ological approach has been to study the
development of a regional entrepreneur-
ial economy over time while providing a
comprehensive analysis of its constituent
organizations and institutions. Our study
region is defined as the spatial configura-
tion of firms in the 13-county Research
Triangle region. In addition to the entre-
preneurial firms we study, this region
contains large multinational and multi-
jurisdictional firms that were recruited to
join the Research Triangle Park as early as
1962. Over time, mergers, acquisitions,
and other startup activity have resulted in
thousands of technology-intensive entre-
preneurial firms populating the area adja-
cent to the Research Triangle Park. Notre
database draws from more than 30 dis-
tinct sources to capture the entrepreneur-
ial development of this region, et
includes details on company founders,
annual firm employment, and engage-
ment with the entrepreneurial ecosystem.
The result of this multifaceted data-col-
lection approach is a unique platform that
provides a data resource that is useful to
state and local policymakers, entrepre-
neurial support agencies, and local busi-
ness media.
One final lesson we learned during this
project was the fact that some entrepre-
neurs have selective recall when inter-
viewed about their participation in early
support programs. While many studies of
entrepreneurial economies depend on
interviews with founders, a comparison of
our interview results with our database
records demonstrates that interviewees
tend to under-report their company’s
engagement with institutions. Individuals
simply do not remember the institutions
they worked with in the early days of their
firm, or the people who worked with
those institutions have moved on. Ce
finding highlights the value of using a
mixed-methods approach.
“Circling
le
The Feldman-Lowe
Triangle” database includes more than
5,000 technology-oriented firms in the
13-county Research Triangle region (voir
Feldman & Lowe, 2015, for detailed infor-
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Evidence-Based Economic Development Policy
mation on database construction, data
sources, and content validation). We cap-
ture detailed information on the dates
firms were founded, the company histo-
ries, products and product development,
and firm location. For entrepreneurial
ventures in particular, the database con-
tains detailed information on key mile-
stones, including initial public offerings;
patent applications and grants; new prod-
uct announcements; infusions of venture
capital; funding from the Small Business
Innovation Research and Small Business
Technology Transfer programs and other
federal grants; liquidity events such as
mergers, acquisitions, and bankruptcies;
et, finally, annual employment and sales
revenue, the latter drawn from the
National Establishment Times Series
dataset (for a discussion on the use of this
as a database for entrepreneurial studies,
see Donegan, 2016). Rather than relying
on any one dataset, we triangulate differ-
ent sources to test consistency and accu-
racy in the descriptions of the stages of
firm development and sequence of events.
Our database offers a standard by which
other data sources can be evaluated and
new tools vetted to automate data collec-
tion, so that this analysis method can be
used to study other regions.
pour
We have partnered with local organiza-
tions to provide detailed information on a
wide array of institutional supports pro-
vided by state and local economic devel-
opment agencies, including the North
Carolina Biotechnology Center and the
Council
Entrepreneurial
Développement. We also integrated detailed
information on a variety of institutional
supports, such as participation in incuba-
tors, accelerators, and business plan com-
petitions; entrepreneurial coaching pro-
grams and grants; and low-cost loans pro-
vided by state and local economic devel-
opment agencies. Rather than taking any
one source at face value, we collect multi-
ple sources and make comparisons to
triangulation
ensure accuracy. Ce
between different sources enables us to
validate information, reconcile discrepan-
cies, and provide a clear understanding of
firm progress and the sources of bias in
certain cases.
In addition to firm-level data, we have
collected career histories and educational
background information on entrepre-
neurial company founders, some of
whom were academics who leveraged
technologies identified through research
conducted at one of the region’s three R1
universities. Social media sources, surtout-
cially LinkedIn, have proven useful for
compiling detailed career timelines and
educational profiles. In the process of
data collection, we have amassed archival
materials from quasi-public, private, et
nonprofit organizations located in the
region. These documents range from
organizational directories and annual
reports to meeting minutes for commit-
tees tasked with designing technology
support policies and programs. We treat
these data sources as equally valuable to
the study of regional innovation, as a
resource for contextualizing statistical
patterns and econometric relationships,
and for supporting our mixed-method
research design. Our research team also
has conducted in-depth interviews and
structured focus groups or salons with
more than one hundred local life science
entrepreneurs or key representatives from
regional support organizations.
Our methodological contribution con-
trasts with cross-sectional studies that
make comparisons between places and
often draw conclusions that gloss over
differences in industry composition and
specialization, a point made by Kenney
and Von Berg (1999), including stages of
development in an industry life cycle
(Eisingerich,
Falck, Heblich, &
Kretschmer, 2008), and structural or
institutional differences or changes that
might cause inflection points or reverse
trends (Murmann, 2003). Many studies
examine one industry across multiple
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Maryann Feldman and Nichola Lowe
regions to draw conclusions about the
region, but Kenney and Von Berg (1999)
provide a cautionary note about this
approche, as there is great heterogeneity
across industries. Our approach is to con-
struct a detailed temporal investigation of
a regional economy.
POLICY FOLLOWS
The future of the nation’s prosperity is
substantially determined by activities at
le niveau local. Some economists are skep-
tical of place-based economic develop-
ment strategies, arguing that there is a
tradeoff between local gains and national
welfare. Their contention is that resources
are simply being redistributed from one
local economy to another, to the detri-
ment of overall national welfare. UN 2009
World Bank report advocates for a spa-
tially blind (or people-based) approche
rather than a place-based one as the most
effective way to generate efficiency, guar-
antee equal opportunities, and improve
the lives of individuals where they live
et travailler. The report asserts that encour-
aging mobility enables people to live in
places where they likely will be more eco-
nomically productive, which in turn
increases individual incomes, productivi-
ty, and aggregate growth and leads to a
more even geographical distribution of
wealth. D'autre part, proponents of
place-based approaches to economic
development argue that it is necessary to
fully understand the local and regional
context in order to create development
policies that will succeed in a particular
area (Barca, McCann, & Rodriguez-Pose,
2012). The place-based approach asserts
that one-size-fits-all policies fail to con-
sider regional contexts. But at this point,
neither theoretical nor empirical econom-
ics can address the question of how to
promote economic prosperity most effec-
tivement.
Policymakers cannot afford to wait. Comme
Kline and Moretti (2013) conclude,
“Second best may, in practice, be very
attractive relative to the status quo” (p.
34). En gardant cela à l'esprit, we conclude with
some brief reflections on the policy impli-
cations of our research. From a regional
policymaking perspective, there is clearly
value in capturing a more complete pic-
ture of entrepreneurial experience within
a regional economy. Why is this? Pour
starters, economic development as a pro-
fessional practice often supports transfor-
mative economic and institutional change
on multiple fronts (Feldman & Lowe,
2011; Feldman & Storper, 2016). Ce
involves a mix of concurrent interven-
tions designed to support and benefit a
wide range of economic actors and estab-
lishments (Lowe & Wolf-Powers, 2017;
Markusen & Schrock, 2006). New firm
formation and entrepreneurial survival is
of course one key objective for regional
economic development. But even within
the entrepreneurial support community
(as opposed to other supports that target
well-established or large corporations),
other goals are often in play, including job
creation, improved job quality, job access,
increased educational attainment, inno-
vation, environmental sustainability, ou
increased
revenue.
government
Policymakers and practitioners of eco-
nomic development rarely optimize on
one front, as they need to satisfy multiple
constituencies (Kupers & Colander,
2014). Even in cases where individual
practitioners (or development agencies)
specialize in one area—say, promoting
education to support entrepreneurship or
new venture financing, technology trans-
fer, business management, or network-
ing—they typically participate within a
larger regional network that is pushing
for progress on multiple economic fronts.
Obviously, only a limited set of develop-
ment goals will be attainable at the indi-
vidual firm level, but this nevertheless
suggests that, in aggregate terms, a diverse
regional entrepreneurial community can
contribute to multiple intersecting eco-
nomic development objectives. Et, par
46
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Evidence-Based Economic Development Policy
default, the full array of entrepreneurial
firms in the region should be well under-
stood by—and within sight of—regional
practitioners.
Recognizing this, some regions have
intentionally adopted what scholars have
described as a portfolio approach to eco-
nomic development policy (Markusen &
Schrock, 2006; Rodrik, 2014). In this pol-
icy environment, the goal is not simply to
have parallel yet independent policy
tracks. It is also important to identify and
seek out opportunities for integrating
entrepreneurial supports in ways that bal-
ance and combine multiple developmen-
tal objectives. This policy logic is also out-
lined in the call for “smart specialization”
in Europe, which strongly emphasizes
supporting entrepreneurship through
combined goals of innovation, equity, et
environnement. It also reflects recommen-
dations from researchers of state and local
policy in the United States to embrace
economic development planning as more
than competing public investment choic-
es (Kupers & Colander, 2014). Plutôt, il
should include an integrating policy plat-
form for both layering and combining
multiple objectives (Lowe & Feldman
2015).
A portfolio policy approach also means
managing a range of projects and busi-
ness investments in support of innovation
(Rodrik, 2014). This is especially relevant
for interventions in support of entrepre-
neurship, which involve inherent risk, pas
just for the firm and its founder/s but for
the host region. In evolving economic or
technological environments, certain
kinds of entrepreneurial opportunities
and ventures could disappear altogether.
But that risk is not just economic; it can
also emerge in a political form—some-
thing we are currently witnessing in
North Carolina under conservative lead-
ership. With shifting political environ-
ments and priorities, certain pathways for
entrepreneurship may be foreclosed,
which suggests that gains can be made by
simultaneously pursuing a wide array of
entrepreneurial and organizational types.
A related final point: privileging one form
of entrepreneurship or the portal that
helps to create it can blind us to the way
entrepreneurship, as one of many eco-
nomic activities, intersects with other
aspects of regional economic life. As one
exemple, large corporate anchors that
spawn entrepreneurial firms might be
influenced by non-entrepreneurial poli-
cies that support large firms, y compris
efforts to recruit them to a region
(Feldman & Lowe, 2016; Lowe & Feldman
2015). This means seemingly unrelated
decisions about which firms to recruit (ou
pas) can later have an effect on regional
entrepreneurial development by influenc-
ing which types of apprenticeship exist in
a region. Some large firms are extremely
nurturing of entrepreneurial opportuni-
liens, helping their employees gain access
to technology, finance, and networks to
support a new venture (Mayer, 2011). Dans
our study region, Glaxo Smith Kline is but
un. But this is not always the case, lequel
suggests that entrepreneurship practi-
tioners might do well to influence
upstream decision-making around indus-
trial recruitment—assuming this is not
just a competing use of economic devel-
opment funding but a potential resource
for shaping entrepreneurial opportunity
and success. But these interconnections
also have implications in terms of labor
market disruption, especially when large
firms shed workers as a result of downsiz-
ing,
relocating.
Practitioners of entrepreneurial develop-
ment must be well positioned to respond
to this kind of event, ready to offer sup-
port in ways that allow workers who lose
their jobs to assess whether entrepreneur-
ial success is viable and, if so, to help them
launch new ventures on a solid, stable
foundation.
restructuring,
ou
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Maryann Feldman and Nichola Lowe
REMERCIEMENTS
depuis
We received generous support for our
recherche
the UNC Office of
Economic and Business Development
and the Odum Institute for Social Science
Research, as well as from the National
Science Foundation (Project #1262392),
the Ewing Marion Kauffman Foundation,
and the U.S. Department of Commerce,
Economic Development Administration.
We also wish to acknowledge the creative
contribution and forensic skills of our
UNC undergraduate and graduate
research team.
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nouveautés / volume 11, number 3/4
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