1. Regional economic development
Most people have a pretty good idea about what regional economic development means. It means jobs, right? Better still, it means jobs with rising incomes and higher standards of living. But why the “regional”? Why not just economic development?
The adjective “regional” is important because everything we do occurs in a defined location. While we may spend a fair amount of time in a virtual world of devices and videoconferences, humans are subject to physical constraints and opportunities tied to a physical location. While our office supplies vendor may be in Wisconsin, we don’t take our children to Wisconsin for soccer practice. There is a limit to how far we will go for routine play, shopping and work activities.
Regarding that limit as to how far we will go for work—and each person has their own threshold of how far is too far—is how the federal government defines one type of region. A metropolitan statistical area (MSA) is ostensibly based on commuting patterns, which is one way of measuring the interconnectedness of a bundle of counties. While the average denizen of Scott County, Indiana, may not say that they are from Louisville, Kentucky, they are part of the Louisville MSA. One might say that an MSA defines worker-employer interconnectedness, but the regional labor force is only one dimension. The region that Scott County residents consider themselves connected to may be much different from the region that their employers operate in. Example: Austin, Indiana, is 300 miles—a half day’s drive—from a vast majority of the automobile production in the country. Austin Tri-Hawk Automotive, Inc. in Scott County likely considers its region to include the plants and firms it supplies up and down the auto manufacturing ladder from Michigan down to Alabama. A region becomes larger when one considers the movement of goods as well as the daily movement of people.
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This article goes beyond counting patents as a measure of innovation and looks to hidden or “latent” innovation. Innovation is tricky to measure but considering how important it is, knowing its different dimensions is critical. In this article, we highlight innovation as how unique a region’s input supply chain is, and, secondly, how unique or specialized the consumers of a firm’s products are, and finally how specific or differentiated consumers or industries are (low ubiquity). In sum, high complexity and uniqueness is more innovative. Low complexity and being common across geographic space is less innovative, rather like a commodity.
Author: Timothy F. Slaper |
2021 |
innovation; product complexity; input-output; specialization; commodities |
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Economic developers may or may not be familiar with the term “agglomeration economies” but, more than likely, intuitively understand it as the economic benefits that arise from firms locating near each other. Like birds of a feather, inter-related firms cluster together. Agglomeration is closely related to, but distinct from, industry clusters as commonly understood. The latter are familiar to many due in part to Michael Porter and colleagues’ work. The forces of agglomeration, however, include many dynamics that are not easily measured or for which it is difficult to collect data, e.g., knowledge spillovers. As a result, agglomeration economies are both more comprehensive and somewhat concealed.
Author: Riley E. Zipper |
2020 |
agglomeration; knowledge spillovers; industry clusters |
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A “pathway to hope” is what the often ignored inner-city and rural constituencies of the U.S. population need and want. The forces that build that pathway to hope include economic growth, available jobs, good educational resources, access to healthy food and water, access to health services, transportation, etc. This is a wicked problem. Not wicked in an evil sense, but wicked in a big, hairy, complicated sense. A problem that doesn’t have a start, end, or well-defined middle. Making rural or urban places better connected globally via broadband, or preparing students for the workforce of the future, these challenges are all interconnected and in common—and wicked. So where do we start?
Author: Timothy F. Slaper |
2019 |
Rural economic development; complex adaptive systems; case study analysis |
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Recent large-scale economic development (ED) initiatives like Amazon’s search for “HQ2” have underscored the need for ED practitioners and policymakers to be able to measure their community’s development capacity. The immensity of available data that could be used to do so, however, can be quite overwhelming. The IBRC's work with Metrics for Development (M4D) involves collecting relevant data that can be used to gauge a county’s capacity for economic development and packaging it so policymakers, ED practitioners and the public can derive meaningful insights for their communities. This article is an overview of the M4D data set and presents some important findings about development capacity in counties across the United States.
Author: Riley E. Zipper |
2019 |
economic development; health; social capital; productivity |
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This article shows that customers, workers, and universities, among others, drive innovation. This research suggests that these sources are critical for developing different types of innovation. Universities as a source of innovation activity are especially important. Other sources, such as suppliers and people in industry do not seem to be as important as a source of innovation. Few studies on innovation empirically analyze the links between firm innovation and the sources of that innovative activity on types of innovation. This study provides one of the first tests to identify how important sources of new information (suppliers, customers, other business people in the industry, workers and universities) are associated with types of innovations (products, processes, operations and marketing).
Author: Mehmet Akif Demircioglu, David B. Audretsch, and Timothy F. Slaper |
2019 |
Innovation; rural; urban; sources of innovation |
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Who decides where foreign direct investment (FDI) will land geographically, and how do these folks make their decisions to invest in one place rather than another? The authors find that firms tend to be attracted to regions that have an absolute concentration of employment in their industry cluster—that is other among related industries. Second, high-tech industries also differ from non-high-tech industries in terms of their FDI attraction profile, an important consideration for economic development practitioners. The locations of FDI projects are not largely determined by industry cluster specialization, but rather align with the benefits of highly concentrated clusters, which magentically attract incoming investment into counties.
Author: Timothy F. Slaper, Ping "Claire" Zheng |
2018 |
foreign direct investment; aggolomeration economies; industry clusters; specialization |
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Firms are more likely to invest in new or expanded facilities in regions that have a high absolute concentration of employment in their specific industry. While the research is sparse on whether regions with specialized industry clusters magnetically attract investment from firms outside the region, we show that agglomeration externalities create benefits for related industries to co-locate. To what degree do these externalities attract similar or complementary industries? We address whether, and to what degree, industry clustering externalities magnetically attract new operations and employment into a region. Using greenfield foreign direct investment data at the U.S. county level, we conclude that firms are more likely to invest in new or expanded facilities in regions that have a high absolute concentration of employment in their specific industry.
Author: Timothy F. Slaper, Ping "Claire" Zheng |
2017 |
foreign direct investment; industry clusters; industry LQ; agglomeration economies |
2. New data
Many of those dimensions, such as supply chains, are not well represented by the socio-economic data that governments collect. These data are folded into official statistics that are used to present a picture of a region, state or the country. These data also provide a set of measures of economic performance and progress.
The data that these government entities report are subject to significant time lags between when something happened and when the data are released that show what happened. As information technologies have become more entrenched and diffused, people have asked for better data more quickly. While the turnaround for official statistics has generally improved, those same official statistics may not be collected in new areas of activity or may suffer from survey fatigue.
Does the government collect and publish data on social, business or political networks? Networks are a big deal, but the official statistics are currently missing out on this dimension of modern communication and economic transactions. The RED project aimed to take the first baby steps in wedding social media and network data with traditional measures of economic performance. Can certain types of social media communication presage changes in economic activity? Are there signals in a network of friends that might indicate they are forming a team and launching a startup? Considering how robust a community is or how strong their resiliency to economic or natural shocks like hurricanes, does social media or some other communication signal provide insight into their region’s bonding and social adhesion? The RED project research looked at what new and unconventional data might help answer these and other important questions.
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Innovation, a leading driver of economic and productivity growth, is difficult to measure—quantitatively or qualitatively. The typical go-to measure for innovation is patent counts. A patent is the government's stamp of approval that the technology described in the patent application is distinct from other technologies in previous patents. For this reason, making patents in a region is a good proxy for innovation in a region. This article examines the extent of patent creation in the Great Lakes region of the United States and argues that patent and technology concentration and growth in a region suggests a brighter economic future.
Author: Timothy F. Slaper |
2021 |
patents; innovation; knowledge spillovers; regional specialization |
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Got good data? The IBRC does. Regional economic researchers use public data extensively in their work—for example, to study sectoral employment growth across U.S. regions. Trouble is, often a statistical agency like BLS or the Census must suppress reporting the due to confidentiality concerns. The more geographically granular, like county or sub-county areas, the greater chance that data are often suppressed in order to protect against identifying specific establishments. The lack of granular data limits the utility of the research for economic development practitioners, who need to keep tabs on how specific industries are doing in their region, as well as researchers and policymakers with a view to making good empirical decisions. The IBRC has estimated those suppressed data points for several types of data.
Author: Ping "Claire" Zheng |
2020 |
data; geographic boundaries |
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Regional scientists increasingly recognize the limitations of traditional measures for a population or regional characteristic when explaining the disparate outcomes between regions. This research seeks to understand how regions' differing “personalities” can help describe variance in economic prosperity. The authors use the "Big 5" personality profiles of a region to assess a region’s make-up, combined with General Social Survey items and several other common regional characteristics. The authors used four target economic performance measures as dependent variables: per capita income, employment rates, income mobility and rates of entrepreneurship. Based on the results, the authors conclude that the personality of place or region needs additional study to understand how a population’s mindset can affect economic outcomes.
Author: Raphael E. Cuomo, Daniel B. Davis, Josh D. Shapiro, Mary L. Walshok |
2020 |
personality; entreprenuership; economic development; business formation |
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Does religion matter in economic development? Literature shows that religiosity can provide individual resilience to life shocks as well as regional resilience to disasters caused by natural hazards. Few studies examine the role of religiosity on a region's resilience to recession. They find a modest and statistically significant association between religious belief and regional resilience. Using survey results from the Gosling-Potter Internet Project (Gozlab) and General Social Surveys, the authors found that religiosity is the strongest predictor of the 16 psychosocial variables examined in association with the speef of job recovery from pre- to post-Great Recession employment data.
Author: Raphael E. Cuomo, Daniel B. Davis, Stephan J. Goetz, Josh D. Shapiro, Mary L. Walshok |
2020 |
economic resilience; religion; regional economics; Great Recession |
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In the paper, we find that the concentration of a region’s visits to website resources for entrepreneurship and business development are statistically related to business start-up and, particularly, growth activity. The website-based behavior data is close to real time and at a geographically granular level. While data capture and analysis related to entrepreneurship website activity is in its infancy, this analysis points to the potential of this data source to nowcast business formation and growth at a regional level.
Author: Timothy F. Slaper, Alyssa Bianco, Peter E. Lenz |
2018 |
big data; forecasting; entreprenuership; unconventional data |
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Some regions prosper; others languish. Why? This is the research question for the IBRC and collaborators for the “regional economic development project” (RED). No two regions are alike. Research on RED is still emerging and is ripe for multidisciplinary methods and inquiries from multiple fields, including data science, education, entrepreneurship, economics, sociology, psychology, health, network science and others. Depending upon a particular region’s characteristics, what policy mechanisms are the most effective to ignite economic growth? There is no academic field, no one-stop policy shop, providing decision makers, practitioners and thought leaders with a comprehensive framework for improving regional economic performance. The goal of the RED research agenda will develop a framework for precision policy—policy specifically targeted for a particular region.
Author: Timothy F. Slaper |
2017 |
regional economic development; economic performance; regional analysis; big data; multi-disciplinary analysis |
3. New methods
Finally, new methods is the third element of the RED research. The current state of the art for regional economic development research is an economic analytic core, with other disciplines added along the way. In the field of economics, there has been an increasing interest in agent-based modeling, that is, describing economic actors as agents operating in an environment who respond to information, incentives and constraints. The idea is to see how a change in policy or some other intervention would change outcomes. For example, if the student loan program suddenly disappeared, what would happen to the students, universities and the economy?
The RED research teams built models to test out how changes in a region (or some other higher-level policy environment) will affect the economy using this agent-based approach. These models applied a complex adaptive system (CAS) framework. While probably overused as a term, we’ll use the concept of an ecosystem as a type of CAS. The ecosystem has many smaller systems and subsystems that interrelate and are mutually dependent. There is recirculation of biomass from waste to food to waste. They have certain physical endowments and are not closed. They take in energy and exchange atmosphere from the outside.
Regional economies are not unlike those ecosystems and these new models help answer questions like: What happens when the electrical grid goes to 50 percent distribution for three months? What happens when a large employer closes operations? How does the region rewire? We are not saying that these are easy and quick models to build or easy questions to answer. The state of the art of CAS and linked data ecosystems is sufficiently developed that we can begin the journey to build models that are tailored to a specific region and that can provide relevant policy responses to advance economic development and regional resilience.
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Urban areas tend to attract the attention of policymakers and politicians. It is where the people are. This work, however, changes the focus. This article examines less populous and rural regions from a complex systems perspective. Using a metric called tightness to measure latent interdependence between economic entities (industries, occupations, for example), the authors examine the skills space and industry structure of metropolitan, micropolitan (smaller cities) and rural regions in the United States. Measures of economic complexity depend on scale/size/spatial aggregation. While the least and most populous regions both show the greatest tightness between industries and labor skill sets, the authors find that what makes up the skills—the type and composition—can differ across regions.
Author: Keith Waters, Shade T. Shutters |
2021 |
economic resilience; regional networks; rural; skills; industry |
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Entrepreneurship (E-ship) and business formation is an engine for economic growth. For this reason, economic development practitioners and economic policy makers (EDPs) focus on the regional characteristics and conditions that encourage E-ship. The IBRC, in an effort to distill many of the needed elements for sparking E-ship, developed a comprehensive set of measures in what we call, the Entrepreneurship Readiness Index. The E-primed Index leverages a broad array of research and data sources assess a region's ability to foster business startups and growth, for example: innovation capacity and ecosystem support, social capital, inter-industry relationships, regional economic networks, the regional cultural amenities and densities (arts and design occupations) and even the degree to which a regional population searches for E-ship resources.
Author: Ping "Claire" Zheng |
2020 |
entreprenuership; regional data; innovation; start-up eco-systems; business formation |
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The structure of regional economies play a critical role in determining a region's productivity and its resilience to shocks. The authors construct a network of interdependent economic components to operationalize the concept of economic structure. To measure the interdependence between economic components, they adopt the view that regional economies are analogous to ecosystems and use techniques of co-occurrence analysis to infer interactions between industries. For each U.S. metropolitan statistical area, they create an aggregate measure of tightness that captures the degree of interconnectedness among a region's industries. They find that industry tightness is positively correlated with a region's economic productivity but negatively correlated with its change in productivity following the Great Recession. That is, regions with higher industry tightness tend to be more productive but less resilient to recession. Thus, this study contributes to a deeper understanding of the tradeoff between productivity and resilience, as well as the drivers of this tradeoff.
Author: Shade T. Shutters, Keith Waters |
2020 |
economic resilience; industrial structure; productivity; industry concentration |
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Cities are among the best examples of complex systems. The adaptive components of a city, such as its people, firms, institutions and physical infrastructure, form intricate and often non-intuitive connections and interdependencies with each other. These connections can be quantified and represented as links of a network that make the latent structural elements of urban systems visible. In this article, the authors use aspects of information theory to estimate and visualize the interdependence network—also known as tightness—among labor skills, illuminating parts of the hidden economic structure of cities. Regions with higher tightness tend to be more productive, but also more likely to be more sensitive to shocks.
Author: Shade T. Shutters, Keith Waters |
2020 |
urban; occupational skills; regional networks; structural interdependence |
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How to minimize employment losses due to disruptions such as technological change, trade wars or other economic shocks is a persistent question for economic development pracititions. How can a policymaker address labor gaps as efficiently as possible? Using network analysis, the authors find the key missing skills and determine with occupations are "close" to each other in terms of the skills they share. They provide a case study of a proposed worker retraining pathway to show the potential of this method as a policy tool.
Author: Keith Waters, Shade T. Shutters |
2020 |
economic resilience; regional networks; occupational skills; worker retraining |
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The location quotient (LQ) is dead. Long live the new type of LQ that measures both regional co-location of firms—somewhat like industry clusters—as well as industry interdependence (or common supply chains and input-output relationships). This research proposes a new proximity-adjusted location quotient (PA-LQ) that accounts for both the co-location of related industries in a county as well as the spatial connections of related industries located in contiguous counties—or just one county over. The PA-LQ outperforms the "standard" LQ in statistically explaining the effect of industry concentration on employment growth.
Author: Zheng Tian, Paul D. Gottlieb, Stephan J. Goetz |
2019 |
agglomeration; location qoutient; regional development; industry structure |
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Social capital and agglomeration are inherently linked, and are key to entrepreneurship. In this study, the author develops novel measures of regional social capital in the nonprofit organization space. He also constructs metrics for Marshall's agglomeration mechanisms. Related variety is key to promoting entrepreneurship across all industries. There is also an interplay between social proximity and own industry concentration.
Author: Jae Beum Cho |
2019 |
entreprenuership; social capital; nonprofits |