Introduction

Policies to promote entrepreneurship and innovation within geographically defined industrial concentrations have become a dominant economic development strategy. A myriad of initiatives attempt to capture the higher than average wages and productivity associated with agglomeration economies. The Obama Administration, the European Union, and the Chinese government all have national policy initiatives with specific territorial objectives (Dühr, Colomb, and Nadin 2010; Kostka and Mol 2013; Yu and Jackson 2011). More local levels of government, recognizing that the locus of innovative activity is decidedly smaller scale, also attempt to create technology-based economic development to secure their community’s economic future (Feldman, Lanahan, and Lendel 2013). Despite good intentions and the investment of large sums of public funds, empirical evidence on the impact of government cluster-based initiatives is disappointing (cf. Lerner 2009). There is an urgent need to clarify the underlying nature of agglomeration economies, the logic of economic development, and the role of government investment. The counterintuitive policy implication is that rather than specific targeted initiatives, broad investment gives rise to agglomeration economies and creates the conditions that allow industries and innovation to flourish.

This chapter will review the theoretical basis for economic development policy based on the natural tendency of innovation to cluster spatially. Certain places become the locus of creative, inventive activity at specific times when individuals are in close contact, exchanging ideas, and creating economic and social value. Consider Florence under the Medici, Paris in the 1920s, Great Britain during the Industrial Revolution, or Silicon Valley in more recent times. The question of why certain places prosper and achieve a higher standard of living has preoccupied economists since Adam Smith’s Wealth of Nations. Krugman (1991) observed that rather than converging as predicted by neoclassical economics, national economies were becoming more divergent over time, which counters the theoretical predictions of neoclassical growth theory.

This prompted his series of lectures published as Geography and Trade. Others, notably Robert Lucas and Paul Romer, challenge the classic assumption of constant or decreasing return to scale by pointing out that knowledge is subject to increasing returns due to externalities inherent in the creation and application of knowledge. Rather than diminish, the value of knowledge actually increases with use due to network effects and path dependencies. Empirical work has documented these effects but offers little guidance for policymakers.

Michael Porter’s (1990) Competitive Advantage of Nations introduced geographic considerations to the field of management, providing a model of conditions that supported industry, emphasizing the benefits of localized competition. This work, however, highlights preconditions that influence innovation and ignores the social process inherent in the creation of institutions that support creative activity and the genesis of spatially defined innovative industries. To better guide public investment, this chapter draws on recent work for the US Department of Commerce Economic Development Administration that provides a definition of economic development (Feldman et al. forthcoming). This more expansive view of economic development articulates a new role for government as the agent of collective investment in capacity and suggests that businesses that benefit from knowledge spillovers may be instrumental partners in institution building. The best economic development policy may be predicated on a longer-term and more capacious perspective. Continuously working toward measurable increases in regional capacity will best harness the natural tendency of innovative activity to cluster spatially and led to greater prosperity.

Geography as a Platform to Organize Innovative Activity

Just as firms are one means to organize economic activity, geography provides a platform to organize resources and relationships for economic activity. Beyond the natural advantages of resource endowments, proximity to markets, or climate, certain places have internal dynamics that increase the productivity of investments and result in higher innovation and creativity (Romanelli and Feldman 2007; Rosenthal and Strange 2003; see also in this volume Iammarino and McCann, Chapter 14 and Lorenzen and Mudambi, Chapter 10). These internal dynamics are socially constructed and involve a wide variety of actors including business owners, entrepreneurs, researchers, venture capitalists, policymakers, and politicians. Most importantly, since it is difficult to predict future technological change and market evolution, the greater the number of individuals who are able to participate in creative endeavors the higher the probability that a place, be it a city, region, or nation, is able to capture the resulting benefits.

The resources required to produce innovation are typically not confined to the boundaries of a single firm. While firms contract for external resources, often important considerations, such as unexpected results or unintended findings, which might be valuable insights, will not be part of the product stipulated by the contract and an important source of new ideas may be lost. Pisano (1996) observed this for the pharmaceutical industry and predicted a loss of innovative capacity, which has proven true (Pisano 2012).

Geography and place-specific interactions can shape industries. If you enjoy coffee or fine wine, then you know that there is something about the soil, the climate, the angle of the sun, the age of the trees, and the growing and harvesting traditions that create something unique. Even the best vineyards experience different vintages, reflecting the numerous variations that determine quality. While quality winemaking is diffusing around the world with product now exported from Chile, Argentina, Australia, New Zealand, and South Africa, wines have become more complex and differentiated rather than homogeneous. Connoisseurs talk about terroir, a French term used to denote the special characteristics that geography bestows. The term can be translated literally as “dirt” but more poetically as a “sense of place.” The term captures the total effect that the local environment has on the product, when the total effect is more than the sum of its parts.

While outsourcing allows firms to lower production costs, technologically sophisticated firms compete on the basis of differentiated performance and innovation. While firms are the entities that take ideas to the market and realize value from innovation, even the largest multinationals are embedded in ecosystems that support and sustain their activity (see Ietto-Gillies, this volume, Chapter 6). These systems are globally connected but typically are focused in certain locations – collections of firms within one specialized industry or technology, concentrated within the same geographic area.

Marshall (1890) noted this tendency, citing three reasons: an infrastructure of related and supporting industries, the presence of deep, specialized skilled labor pools, and the presence of non-pecuniary externalities due to proximity to a strong knowledge base that facilitates knowledge exchange. Marshall maintains that a specialized industry and related firms are likely to agglomerate together because they can rely on a deep pool of skilled labor and can share knowledge, either through locally mediated market-based value chain transaction or though non-market mediated knowledge spillovers. Economic actors whether firms, entrepreneurs, scientists, or workers can search for solutions to their problem through formal and informal channels more easily due to geographical proximity. Experience with a technology or industry increases the stock of available knowledge locally, yielding better ideas. That is, economic agents benefit from easy communication, sharing ideas and serendipity – the unexpected but highly relevant chance occurrence. In addition, industrial agglomeration reduces transaction costs.

Examining Britain at the height of its industrial power, Marshall tapped into a phenomenon that can be observed throughout human history as certain locations become the locus for certain activity – the right place at the right time. Economists, of course, tend to focus on the localization of industrial activity. Shortly after Marshall wrote The Principles of Economics, the Twelfth Census of the United States in 1900 discusses the universal characterization of the localization of industries and references a medieval English manuscript from 1250 that documents industry localization (US Census Office 1902: ccix–ccx).

Within an industrial cluster, it may be easy to find suppliers, so that firms may reduce shipping costs. A good example is automobile manufacturing in Japan. Many components suppliers are located nearby so automobile firms do not need to purchase components from distant areas. Moreover, Pisano and Shih (2009) argue that, while outsourcing at great distance has become a popular corporate strategy, industry localization creates collective operational capabilities that underpin new product and process development and hold the seeds for the next generation of innovative products.

Arrow (1962) and Romer (1986) extend Marshall’s externalities argument into what has become known as Marshall-Arrow-Romer (MAR) externalities. Arrow argues that workers improve their capability from regularly doing the same type of work – learning by doing. When many similar firms are located together, workers may easily move between jobs, doing similar tasks and gaining greater expertise. Firms improve their productivity by employing workers with high capabilities. As workers move they transfer know-how between firms. Romer maintains that similar firms are willing to agglomerate due to benefits from increasing returns to scale. While most physical goods are subject to constant or decreasing returns, one of the unique characteristics of knowledge is that it increases rather than decreases with use. The evidence is that firms benefit (Dekle 2002; Glaeser et al. 1992) and that workers receive higher wages derived from higher productivity and gains as a result of increasing returns (Wheaton and Lewis 2002).

Of all economic activity, innovation benefits most from location. Innovation is the ability to blend and weave different types of knowledge into something new, different, and unprecedented that has economic value. Similar to art, innovation is a creative expression. However, unlike art, the measure of innovation is not in the eye of the beholder, but in acceptance within the marketplace that brings commercial rewards to the innovating entities and returns to society in terms of economic well-being, prosperity, and growth.

The importance of geographic location to innovative activity in a world increasingly dominated by instant messaging, mobile telephones, and email may seem surprising and even paradoxical. After all, new telecommunications technologies have triggered a virtual spatial revolution as geographically diverse activities may be linked electronically in almost real-time transactions. However, there are geographical boundaries of knowledge spillover among firms due to tacitness of knowledge, and innovative activities tend to be concentrated in a geographical boundary due to the geographical boundaries of knowledge spillover (see Guy, this volume, Chapter 28 for a similar argument from an institutional perspective). Audretsch and Feldman (1996) find that after controlling for the geographical concentration in production, there is a greater propensity for innovative activity to cluster in industries where knowledge spillovers are dominant. Since knowledge spillovers are likely to be geographically concentrated in a region, innovative activities are also likely to cluster in the region at the same time. This compelling result suggests that the key element for innovation is knowledge spillover. In other words, in spite of the fact that firms still benefit from agglomeration, innovative activities are likely to be vibrant more in an area where knowledge spillovers are prevalent than in an area where knowledge spillovers are weak (Feldman et al. 2014). For instance, even if physical agglomerations of firms exist, innovation may be weak if there are no knowledge spillovers among firms.

Innovation is more geographically concentrated than invention. Invention is the first stage of the innovation process. Due to the creation of large patent databases there are many studies that focus on invention, which should not be confused with innovation. The limitations of patents are well known. Even though patents are geographically concentrated, reflecting a concentration of research and development (R&D) activity, this does not necessarily translate into economic advantage for those locations. Innovation is more geographically concentrated than production. Even after controlling for the geographic distribution of production, innovation exhibits a pronounced tendency to cluster spatially (Audretsch and Feldman 1996).

On the other hand, important ingredients of new knowledge creation and innovation may be ignored if externalities from knowledge spillover among related firms are primarily emphasized (Feldman and Audretsch 1999). Jacobs (1969) argues that complementary knowledge across diverse firms is one of the main sources for innovation, helping firms create new knowledge. The most important source of knowledge spillover, according to Jacobs, derives from industrial diversity rather than industrial specialization, and cities are the greatest place for innovation since cities have the most diverse source of knowledge. That is, diverse firms in a city produce new knowledge that creates vibrant innovative activities, helping other firms gain and harness new knowledge. Of course, the difficulty lies in predicting how diverse pieces will be assembled to solve the innovation puzzle. Our definition of genius is something that once articulated become obvious – the elegance of a solution that defied prior thinking and was difficult to anticipate.

The question of whether specialization or diversity of economic activities is better for innovation has been a fierce debate that has policy implications. Specialization of economic activities implies MAR externalities, while diversity of economic activities indicates Jacobs’s externalities (see Table 13.1).

If the specialization argument by Marshall, Arrow, and Romer is correct, policymakers should promote specialized economic activities (e.g., focusing on one industry such as Bio-tech, Nano-tech, or Information and Communication Technology). On the other hand, if the diversity argument by Jacobs is true, the way in which diverse economic activities can be accelerated should be the overriding concern among policymakers. Glaeser et al. (1992) analyze the relationship between employment growth of large industries in 170 Standard Metropolitan Areas between 1956 and 1987 and both externalities. They find strong evidence that diversity in a city contributes to growth while MAR externalities do not encourage employment growth. This result is consistent with Jacobs’s argument that knowledge spillovers between industries promote innovation and growth. Feldman and Audretsch (1999) also examine which types of economic activities promote innovative activities, focusing on six groups of industries: Agri-business, Chemical engineering, Office machinery, Industrial machinery, High-tech computing, and Biomedical. They reveal that diversity across complementary economic activities sharing a common science base generates more innovative activities. However, the result does not support the specialization thesis. In other words, diverse economic activities in a region help firms create more knowledge spillovers, which in turn are conductive to innovative activities. As diversity across complementary economic activities increases in a given location, the location generates knowledge spillovers, which help boost economic growth in the location. On the other hand, specialization implies that the industrial structure may have become too tailored to an industrial activity or that the industry has become concentrated because it has become mature.

These research findings offer intuitive policy ideas to policymakers who have tried just to mimic successful industrial clusters, focused primarily on industrial specialization and targeted at a core industry such as biotech or information and communication technology without considering the context of their location. As previous literatures illustrated, just following the trend may not be a good strategy. The important fact is that knowledge spillovers among firms are a conduit for innovation that is one of the pivotal sources of capacity building. In other words, what surely matters may not be industrial specialization or diversity, but how to promote knowledge spillovers among firms. In this sense, understanding the context of location certainly matters.

Policies to build industrial clusters often fail due to lack of understanding of the context and history of the location. Successful industrial clusters are socially constructed and take a long time to realize their potential. Given this reality, policymakers should first examine the context of location, such as industry structure and infrastructure in their region. By better understanding their geographical area, policymakers know what their strengths and weaknesses are and can consider them as they think about overcoming disadvantages and reinforcing advantages. They should then consider creating connections among existing firms so that firms can make positive externalities, generating knowledge spillovers across industries. In case of poor regional capacity, policymakers should focus mainly on investing in building regional capacity so that diverse economic activities can be promoted. As the research conducted by Feldman and Audretsch (1999) shows, fostering conditions that help create diverse economic activities is crucial. If a region is too specialized in a particular industry, policymakers should attract complementary industries in order to generate more knowledge spillovers across industries rather than within industries. While policymakers search for the appropriate recipes the best advice is to focus on local ingredients.

Harnessing the Natural Tendency of Innovative Clustering

Some economists are skeptical of place-based economic development strategies, arguing that a tradeoff exists between local gains and national welfare (Einiö and Overman 2012). The controversy is that resources are simply being redistributed from one local economy to another and to the detriment of overall national welfare. A 2009 World Bank report advocates for a “spatially blind” (or people-based) approach rather than place-based, as the “most effective way of generating efficiency, guaranteeing equal opportunities, and improving the lives of individuals where they live and work” (World Bank 2009). The report asserts that encouraging people-mobility enables people to live in places where they will likely be more economically productive which, in turn, increases individual incomes, productivity, and aggregate growth, and leads to a more even geographical distribution of wealth.

On the other hand, 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. The place-based approach asserts that one-size-fits-all policies, that do not consider the regional context of the area they are trying to assist, may have unanticipated (and potentially negative) consequences (Barca, McCann, and Rodríguez-Pose 2012).

Enterprise zones or enterprise initiatives are one policy for place-based economic development that has been extensively evaluated. To attract firms within enterprise zones, government provides many incentives, such as property or income tax exemptions for firms. Once firms are located in enterprise zone, they can qualify for additional subsidies. Policymakers expect that enterprise zones may result in mitigating the unemployment rate as well as helping a region boost economic growth in the long term. In spite of such expectations, however, little evidence supports the impact of enterprise zones. Bondonio and Engberg (2000) and Elvery (2009) focus on enterprise zones in the United States and find that the impact on employment is not significant. Gobillon, Magnac, and Selod (2012) focus on French enterprise zones implemented in 1997. They find a significant impact, but only in the short run. Einiö and Overman (2012) investigate the Local Enterprise Growth Initiative (LEGI) introduced in 2005 in the United Kingdom. The result indicates that LEGI has a positively significant impact on employment and the number of businesses as well as unemployment rate. However, they find evidence that these impacts displace activity from the areas surrounding the targeted areas. The conclusion of these studies is that enterprise zone policies are not effective in aggregate but only shift the location of firms and jobs between jurisdictions. These results show that artificially defined place-based strategies for economic development are inefficient and do not lead to industrial development. However, given that the immediately available policies for the development of industrial clusters do not yield any outcome, there is a need for profound rethinking of the theoretical basis of economic development policymaking.

Theoretical work tends to focus on the default, mathematically tractable, assumption of constant returns to scale. However, the major contribution of the new growth theories is to recognize that knowledge benefits from increasing returns to scale rather than the constant or decreasing returns associated with physical commodities. Activities that create knowledge and the sharing of knowledge create increasing returns that would lead to increased national welfare. But at this point neither theoretical nor empirical economics can adequately address this question. Policymakers cannot afford to wait. As Kline and Moretti (2013: 34) conclude, “Second best may, in practice, be very attractive relative to the status quo.”

When considering the development of industrial clusters there are two diametrically opposing models. One model, practiced in China, relies on government dictating the growth of designated science cities. This is a very top-down approach to economic development that has been successful in Singapore and Taiwan: the central government dictates that a specific location will have a concentration of R&D and accomplishes this in a relatively short period of time. The verdict is still out as to whether these locations will be successful at creating a sustained competitive advantage given that innovation is more complex than simply conducting R&D.

The other model occurs in the United States and other market economies and relies on self-organization and local initiative. In market economies the central government cannot dictate the actions of private companies, but may only offer incentives to encourage company location decisions and investments in R&D. The closest that we have to a government-induced clusters is Research Triangle Park (RTP) in North Carolina, which was the result of state and local government actions. RTP was a very long undertaking beginning in the 1920s and is now the largest research park in the world (Link 1995). But what is most critical are the processes that took place subsequently as the industrial landscape developed (Feldman and Lowe 2014). Through the articulation of a vision and consistent policy efforts a successful cluster was built. There are many other examples of government trying to build clusters in market economies, but the results typically look very different from what was originally intended (Leslie and Kargon 1996).

While economic development officials and government planners want to define long-term strategies, it is difficult, if not impossible, to predict scientific discoveries, new technologies, and new opportunities. IBM, an industry leader, underestimated the potential of the computer industry, creating an opportunity for new firms to create personal computers. Few people predicted the potential of the Internet and how it would change the way we access information and communicate. Moreover, successful entrepreneurs make their own luck, adjusting and adapting to survive. Instead of wisely considered, far-sighted solutions, entrepreneurial activity is by necessity messy, adaptive, and unpredictable. Economic development strategies need to be equally adaptive.

The biggest problem is that it is impossible to predict which technologies are going to yield any pay-off. By the time a new industry, for example, biotech or nanotechnology, has a defined name and is on its way to becoming a household name, it is probably too late for other places to decide that they will participate as major centers. Creating a cluster in a market economy is a messy social process. Designing an effective economic development strategy may be the ultimate local innovation.

Evaluation Challenges for Economic Development Policies and Projects

Along with challenges of creating effective economic development strategy, policymakers have been faced with policy evaluation challenges. This section enumerates some of the measurement problems inherent in evaluating economic development programs as a prelude to a new approach, which is introduced in the following section. Calls for government accountability require program evaluation efforts that typically fall short of rigorous standards (GAO 2012). Despite the significant efforts devoted to evaluating economic development programs, the inherent complexity of innovation complicates research design.

The highest scientific standard is to discern causality. In medical studies there are no patients to randomly assign to receive medication while others get a placebo while in educational evaluations students may be randomly assigned to classrooms or schools. There are examples of experiments that examine the impact of subsidized medical insurance on health outcomes or quasi-experiments that assess the effects of individual choices such as attending college on lifetime earnings and job satisfaction. Evaluation of outcomes is easiest when comparing similar programs or inputs. Economic development cluster initiatives engage a wide range of activities from building infrastructure to incubating businesses. This variety is warranted because the projects serve heterogeneous communities and different technologies. Evaluation would be facilitated if the projects offered identical services, but that would not advance the needs of local entrepreneurs and businesses nor the objective of local economic development officials.

With economic development programs it is difficult to attribute a specific outcome, such as an increase in sales or employment, to one specific program or intervention. There are no pure treatment effects for economic development programs and initiatives and the idea of random assignment is not politically feasible. The best that we can do is to try to find a matched set of control firms that are similar, in terms of their characteristics. Feldman, Kemeny, and Lanahan (2014) provide an example in an examination of the Trade Adjustment Assistance for Firms program (TAAF). The control group was predicated on a five times match of firms in the same three-digit industry and zip codes. The results suggest that the TAAF program funded firms that were initially worse off than the control group in terms of sales. Two years after the program the treated firms had higher sales. No results were found for employment – a concern for economic development programs. Interviews revealed that firms were reluctant to lay off employees when sales were down because of the close relationships that developed in small firms. For the same reason the treated firms were reluctant to hire new employees until sales could be sustained over a longer period of time. Thus, the returns to economic development are affected by multiple individual decisions, and intervening influences that come from multiple motivations.

While it is possible to examine individual firms the analysis become less tractable when we consider regions. Case studies of the development of regional economies reveal an extremely complex process in which public investment is an important element, but only one of many important elements. Complex systems are notoriously difficult to model. There is no reason to believe that optimizing the performance of any one component of a complex system will optimize or even necessarily improve the performance of the system overall.

Current thinking is that economic development projects are not simply a series of transactions, but instead contribute to building an ecosystem (Hwang and Horowitt 2012). The building of ecosystem capacity can reduce transaction costs and increase knowledge flows, resulting in multiple unexpected outcomes. These are considered to be functional impacts rather than pure economic impacts that accrue as a function of undertaking a project or making an investment at a scale significantly larger than the original investment. It is necessary to move beyond economic impact studies to more fully capture the returns to a wide range of public economic development investments.

Moreover, the amount of funding provided for economic development initiatives, while important to recipients, is minuscule in relation to the size of a regional economy. The attribution of good outcomes to specific programs, investments, or events is probably more about good luck, publicity, and hype, rather than true causality demonstrated by sound economic analysis. Even when programs are effective, changes in the macro economy, while exogenous, may wipe out any hard-earned gains. Macroeconomic conditions certainly affect regional outcomes in ways that are not entirely predictable and certainly beyond control at a regional level.

Often successful efforts to build new companies results in an infusion of venture capital, a merger or acquisition, or some other change to ownership that induces relocation. As a result the economic development effects on, for example, local employment are negatively impacted. The result of the efforts that built a successful company can then – by commonly used metrics – appear as failure. In reality, the local area has benefited from the example of what is possible for an entrepreneurial company. This might incite others to start companies or invest in early-stage activity. The founders may stay in the region and become serial entrepreneurs. Key employees will have learned skills that will benefit their next employer. As a result of the economic development effort that was mistakenly judged to be a failure on employment, capacity in the region for the next round will actually have increased.

Finally, there are significant time lags involved in realizing the benefits of government investments that do not conform to political election or budgetary cycles. Mansfield (1991) noted that the time lag between an academic research discovery and new product innovation was seven years. Many economists have followed, trying various approaches to estimate the lag associated with the realization of benefits from investment in R&D. The consensus is that the time lags between investment in research and realized commercial advances are lengthy, uncertain, and vary significantly among fields (Merrill and Olson 2011). In fact, a National Academy of Sciences publication (2001) 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 outcome for economic development is simply making progress on a variety of measures, with attention to correcting deficits and remediating problems.

A New Definition of Economic Development

Economic development is often referenced but rarely defined. This section draws on work by Feldman et al. (forthcoming), that was inspired by a request from the US Department of Commerce. In particular, when it comes to economic development, the policy debate is often hijacked toward outcomes, because of lack of a clear definition of economic development. Furthermore, the term “economic development” is often conflicted with economic growth or seen to reflect a professional practice (see Table 13.2). In order to better understand economic development policies this section builds a definition of economic development based on Feldman et al. (forthcoming).

Unlike economic development, the definition of economic growth is based upon strong theoretical grounding. Consider argument by David Ricardo (1891), Robert Solow (1956), and many others. Economy is a kind of apparatus that produces economic output, which is a function of inputs such as capital, labor, and technology. The mechanism is simple. The more inputs are added the greater outputs will be expected. Given this, one may expect that growth occurs when outputs increase. In this sense, economic growth is associated with an increase or decrease in outputs, so economic growth is easily measured and quantified. On the other hand, defining economic development may not be as simple as economic growth.

Rather it is very complicated since economic development is often qualitative and hard to measure. Economic development influences the microeconomic function of the economy, affecting the quality of inputs, bringing the business opportunity to firms, and in turn creating the conditions that enable long-run economic growth. Based on a review of the literature, Feldman et al. (forthcoming), inspired by Sen (1999), argue that economic development is defined as the development of capacities that expand economic actors’ capabilities. These actors may include individuals, firms, or industries that are likely to exert their potentials based on the development of capacities. Rather than simple counts of jobs, economic development is concerned with the quality of jobs, the caliber of business practices, and the density of social capital.

Development can be regarded as fortifying autonomy and substantive freedom, which promotes individuals’ participation in economic life (Sen 1999). Thus, economic development occurs when individuals have the opportunity to actively engage and contribute to society and are likely to realize their potential. This promotes the advancement of the whole society. In this sense, the expansion of capacities provides the basis for the realization of individual, firm, and community potential, which, in turn, contributes to the advancement of society.

According to Schumpeter (1934), economic development involves relocating capital from already established methods to new and innovative methods, which enhances productivity. In Schumpeter’s view, economic development entails a fundamental transformation of an economy including the industrial structure, the educational and occupational characteristics of the population, and the entire social and institutional framework. For instance, not only did mass production in the textiles industry drive the industrial revolution, but it also influenced other complementary sectors and in turn diffused widely, increasing quality of life. While economic growth is measured by putting inputs to an existing economic framework, the aim of economic development is to change the economic framework so that people work more productively and shift their positions from simple repeat work to higher value-added activities. Thus, economic development is realized through innovation, lowered transaction costs, and the utilization of capabilities toward the responsible production and diffusion of goods and services. Here the specification of the objective of economic development as increased prosperity and quality of life seem to be guiding principles for any democratically elected government.

Rodrik, Subramanian, and Trebbi (2004) argue that the development of high-quality institutions plays a major role in economic growth. They promote productive activities, capital accumulation, skill acquisition, invention, and technology transfer (North and Thomas 1973) because they can provide well-regulated conditions for economic development. In other words, the reason why effective institutions matter is that they help individuals and businesses make investment decisions, since high-quality institutions can reduce uncertainty and risk and provide stable and predictable systems. Thus, to further build the definition, economic development requires effective institutions grounded in norms of openness, tolerance for risk, appreciation for diversity, and confidence in the realization of mutual gain for the public and the private sector. Thus, innovation is a vehicle for economic development rather than an end itself.

It is often found that many countries, especially sub-Saharan Africa, Central and South America, and Oceania, have some experience of significant increases in economic output without development due to either natural population growth or large-scale resource extraction (Acemoglu, Johnson, and Robinson 2002; De Soto 2000; Moyo 2009). In spite of their tremendous economic growth, these countries with insufficient economic development suffer from significant income inequality and limited educational attainment (Wolfson 1997) and have experienced low health outcomes such as mortality rate and life expectancy much below the average values in developed nations (Vandemoortele 2009). What this implies is that long-term outcomes such as quality of life and widespread prosperity cannot be achieved without sufficient economic development. That is, weak economic development restrains capacity-building that leads to economic growth in the future. Economic development can be a foundation for future economic growth, stimulating the agents’ potentials and in turn enabling long-run economic growth. Finally, economic development is essential to creating the conditions for economic growth and ensuring our economic future.

In sum, economic development is defined as the development of capacities that expand economic actors’ capabilities. Economic development is defined as the expansion of capacities that contribute to the advancement of society through the realization of individuals’, firms’, and communities’ potential. It is a sustained increase in prosperity and quality of life realized through innovation, lowered transaction costs, and the utilization of capabilities toward the responsible production and diffusion of goods and services. Economic development requires effective institutions grounded in norms of openness, tolerance for risk, appreciation for diversity, and confidence in the realization of mutual gain for the public and the private sector. Economic development is essential to creating the conditions for economic growth and ensuring our economic future.

The question then becomes how to best invest resources in order to generate economic development. This requires delving into the process of generating clusters or what Braunerhjelm and Feldman (2006) term cluster genesis.

Cluster Genesis

Scholars and practitioners have tried to find the factors that play a critical role in building clusters of firms and revealed some main ingredients such as high-quality institutions, research universities, venture capitalists, and a strong supply of local entrepreneurs. Yet, these attributes are the result of a fully functioning industrial cluster and do not inform how policymakers might go about creating vibrant local industry. Many attempts to establish industrial clusters have ended in failure since the presence of the key factors themselves does not guarantee prosperous industrial clustering. For instance, the Johns Hopkins hospital in Baltimore, thought of as one of the top medical schools in the world, was not an early leader in the biotechnology industry (Feldman and Desrochers 2003). The question arises: in spite of well-prepared factors such as venture capitalists, research centers, and large amounts of public and private investment for building industrial clusters, why does this happen? When it comes to the cluster strategy, thus, the most important point is not about ingredients for industrial clustering but to understand how these ingredients reciprocate the dynamic process of creating industrial clusters. While fully formed industrial clusters may look alike, what truly matters is the process: the way institutions are built and social capital is created during the creation of industrial clusters. Cluster development is a sequential and temporal process rather than just a static event.

Assume that the same amount of resources is invested in certain places that are seemingly identical, why do some places prosper while other places fail to flourish? This question is a fundamental question of economists who seek to find out the driving force of technological change. In spite of the importance, only few studies offer an answer. Some triggering events can spark the emergence of industrial clusters. Koo and Choi (2013) argue that the continuous emergence of successful venture firms after some initial seeding event can accelerate cluster development. As more successful firms emerge in a given region, there will be increases in local entrepreneurship. Considering successful industrial clusters, the actions of entrepreneurs can be a possible answer. Entrepreneurs discover opportunities, take risks, mobilize resources, create new firms, and may bring prosperity to a region. They play a pivotal role in the creation of institutions and building regional capacity that will enable regions to sustain economic growth (Feldman, Francis, and Bercovitz 2005; James 1998; Rodrik 2003). Entrepreneurs not only benefit from location but also influence the transformation of their local communities. Prosperity in a region is not deterministic, but efforts from entrepreneurs can affect the prosperity of places. Entrepreneurs can be considered local champions – individuals who they live and work in a region and have strong dedication to their region.

Feldman (2014) considers the case of Greenwood located in the Mississippi Delta, a small city that about 100 years ago was well known for its cotton industry. After experiencing mechanization and globalization, it became the poorest region in the poorest state in the United States. Greenwood experienced a lack of tax revenue and limited subsequent investment. It seemed that no federal or state government program could be a magical remedy. However, Fred Carl, who is the owner of Viking Range Corporation, a cutting-edge professional kitchen appliance company, brought new hope to Greenwood. While Carl was working as a building contractor, he realized that consumers wanted high-quality residential stoves that looked and cooked like commercial stoves. He identified this opportunity and created an entire new industry segment. Against the trend of offshoring production, Carl located manufacturing operations in his hometown of Greenwood, gathering financing from local investors. His efforts resulted in 1500 workers being hired with numerous benefits and educational opportunities – employing more workers than the local hospital, the typical largest employer in most small and medium-sized cities.

Fred Carl’s story is not a special case but can be seen as part of a general trend. Often the story of successful places is strongly connected with the story of an individual who played a role in creating institutions and building the capacity of a local economy. For instance, Fred Terman is widely regarded as the founding father of Silicon Valley. Although he earned his Sc.D. degree at MIT, he returned to his home and served as the Dean of Engineering at Stanford University. He led the creation of Stanford Industrial Park in the 1950s. Many companies such as Hewlett-Packard and General Electric moved into Stanford Industrial Park, making the area innovative. Eventually Palo Alto became “Silicon Valley” as the hotspot for digital innovation. Like Fred Terman, George Kozmetsky, who was the founder of Teledyne, is one of the local champions in Texas. He established the Institute for Innovation, Creativity, and Capital (IC2) at the University of Texas. IC2 served as a mentor for over 260 computer companies. Ewing Marion Kauffman provides another example of a local champion. He was born and raised in Missouri and lived in Kansas City. After working as a salesman for a pharmaceutical company, Kauffman established his own pharmaceutical company in Kansas City, an unfavorable place in the 1950s, rather than in Philadelphia-New Jersey corridor, where the industry was concentrated. When he sold his company to Merrell Dow in 1989, the company had grown to become one of the global companies with $1 billion in sales and over 3400 employees. The company provided lots of benefits, which included educational and training benefit, profit-sharing plans, and employee stock options, to employees. Kauffman established the Kauffman Foundation in 1966. The Foundation is now dedicated to improvement of communities, education, the arts, and social programs in Kansas City (Feldman and Graddy-Reed 2014). Burlingham (2007) calls this phenomenon Small Giants: Companies That Choose to Be Great Instead of Big.

Local champions are motivated by objectives that extend beyond profits. But they take responsibility for the stewardship of the place and have a dedication to their local community. In other words, they are not seeking short-term profit maximization, but dedicated to prosperity in their home community and discovering new opportunities that may bring about new profits. These stories indicate that regions can become prosperous when entrepreneurs actively engage in extra-market activities. Moreover, local champions can advocate for the types of government interventions that will help their individual firms but can also promote an industry and a place. Of course, the reality of too great a reliance on the private sector can lead to an imbalance that favors profits over citizens’ rights. Moreover, businesses change ownership and management, fail or relocate. While local champions may be a critical catalyst for developing clusters in local economies there is a need to define a role for government and to change the conversation about economic development.

While industrial clustering is a natural outcome it relies on the existence of underlying capacities. Rather than being the result of market forces, the underlying capacities require long-term investment in capacity building.

Reconsidering the Role of Government in Economic Development

Capacity-building in a jurisdiction that requires economic development is beyond the mandate of any private firm, industry associations, or other economic institution. The principal inclusive vehicle for organizing economic, social, and civic life is government. Government, most simply, is a vehicle for collective action: an agent for whom the principal is its citizens, both residents and businesses. Even the most devoted libertarian recognizes the limits of the market, while the most ardent free-marketer recognizes that government was the only entity capable of saving the financial sector from free-fall. The focus on capacity-building harkens back to an older American tradition that began with Alexander Hamilton, defining a role of government as the provider of resources and incentives that enable private enterprise to flourish. The difficult balance is for government to provide for the realization of potential while maintaining incentives; to provide scaffolding for economic transactions, while not over-regulating; and to make investments that advance the public interest and encourage the full participation of private individuals and organizations while not prying into special interests.

In contrast to a resource economy, where geographically uneven endowments predetermine place-based development strategies, contemporary economic development depends upon public and private investments in individual and group capacity. This capacity is constructed over time and requires a consistency of action that stays true to the objectives of promoting the citizen’s well-being. Government investment provides skills, capabilities, programs, and incentives that private sector investment can build upon. Thus, virtuous self-reinforcing cycles of economic development yield the desired social and economic outcomes of prosperity and more sustainable economic growth.

The Reagan Thatcher Agenda and its corollary the Washington Consensus have run their course, yet with little agreement on the policies to implement and investments for government to make. While macroeconomic considerations have dominated the policy agenda there is increased urgency to address the microeconomic foundations of innovation and production. Investment in capacity, rather than austerity policies, provides the basis for economic development. Over the past 50 years, discussions of economic development have moved from a preoccupation with lagging regions and eradication of poverty to a new focus on innovation and international competitiveness. These concerns are universally relevant to a full range of jurisdictions and communities.

The increased contemporary emphasis on innovation and entrepreneurship as a source of economic growth redefines the role for government and provides rationale for government investment. Innovation comprises the complex and multifaceted process under which creativity leads to practical application, commercialization, and ultimately economic and societal gain. Considerable effort has been put toward understanding the process of innovation and identifying the factors that increase economic growth and prosperity for a region. While there is broad consensus that innovation serves as an integral catalyst in leading the trajectory of an economy and even society forward, the emphasis in economic development policy remains on traditional attraction and retention incentives, often directed at specific businesses. This is largely a zero-sum game with little or no broader effects for economic development. In addition, local governments tend to do more of the same policies over time, adding incremental changes to preexisting strategies, rather than a wholesale reconsideration of their investment strategy.

There is growing evidence to suggest that public institutions have chosen to take on an expanded role within the innovation process (Block and Keller 2009; Schrank and Whitford 2009). The nature of scientific research has changed due to increasing demands to solve society’s most pressing problems. This has led to the decentralization of industrial networks, or open innovation. Rather than confined to the R&D labs of large corporations, collaborative activity is now embedded in networks between both public and private institutions, large and small firms. This degree of decentralization encourages more organizations to work in concert with one another and also fosters a greater dependence on government programs to coordinate the operations of these networks (Schrank and Whitford 2009). Evidence suggests that at a time when market fundamentalism has come to guide policy debates, government has actually become more and more immersed in the economy through technology policies in particular (Block and Keller 2009).

As innovation and entrepreneurship move to center stage as critical elements for economic and societal progress, there is a need to redefine the role of the public sector. Rather than relying on the market-based rationales for public investment it is important to consider the potential role of the public sector in building and bolstering capacity. Rather than viewing individuals, or even firms, as objects on the receiving end of public initiatives, it is important to view them as active creative agents. After all, we can never predict when genius might emerge. The best economic development strategy is to enable as many actors to productively participate in the economy to the fullest of their ability. This prioritizes improving quality of life and well-being by enhancing capabilities and ensuring that agents have freedom to achieve.

The paradox of place-specific economic development policy is that broad-based government investments in education and infrastructure are critical to future economic growth. Targeting certain sectors, specific industries, or isolated components of the innovation ecosystem is unlikely to succeed if basic capacity is lacking. Government is the only entity with the long-term perspective and command of resources to engage in the economic development activities that promote industrial agglomeration and ultimately economic growth.

Conclusion

This chapter has reviewed the theoretical basis for economic development policy based on what the literature informs about the clustering of innovation. Table 13.3 provides definitions for the key concepts discussed. Innovative activity has a natural and pronounced tendency to cluster that provides the basis for creating new firms, new industries, and widespread prosperity and economic growth. Unfortunately, there is little theoretical guidance for policymakers responsible for making investment that will lead to economic development.

For too long the conceptualization underling place-based industrial policy relied on creating a set of preconditions such as venture capital. This emphasis has not yielded the desired results. The argument promoted here is that the social construction of the conditions conducive to the creation and genesis of spatially defined innovative industries is a process that requires a longer time horizon and investments in basic capacity that enable participation by diverse actors in a local economy.

While the concept of economic development preoccupies our collective imagination the term is often not well defined or defined in a limited manner that does not accommodate the situation of the full range of places faced with restructuring and economic uncertainly. All too often the emphasis is on innovation as an end in itself rather than as a mechanism that can create prosperity and greater well-being. This requires paying attention to the distribution of risk and returns. The chapter draws on recent work for the US Department of Commerce that provides a definition of economic development (Feldman et al. forthcoming). In the absence of a definition there is a tendency to conflate economic development with economic growth or to rely on private sector constructs such as rate of return that are inappropriate for government investments. This more expansive view of economic development articulates a new role for government as the agent of collective investment in capacity and suggests that businesses that benefit from knowledge spillovers and local capacity may be an instrumental partner in institution-building. The best economic development policy may be predicated on a longer-term and more expansive perspective that continuously works toward measurable increases in regional capacity. The best policies to harness the natural tendency of innovative activity to cluster may be policies and investments that allow economic agents the capacity to be creative and fully engaged in the economy and society.

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