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The long view: New data and methods in regional economic development

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Director of Economic Analysis, Indiana Business Research Center, Kelley School of Business, Indiana University

Which of the two activities are more important for economic development? Helping your neighbor move their piano, or posting a YouTube video on how to tune a piano (after it has gone out of tune after moving it)?

How would you know which is more important? What data do you need and how would you get the data?

This rather frivolous scenario concerns many of the types of questions Indiana University, together with research partners from other universities, will investigate in the coming years with a recent award from the U.S. Economic Development Administration.1

The Regional Economic Development (RED) project has several intersecting goals. In the main, we want to facilitate development strategies and polices that fit precisely with a region’s characteristics and capacities. Every region is different. They have different histories, resources, institutions and economic linkages. The RED project will integrate several academic disciplinary domains to build models to better inform policies and strategies to promote economic growth. Part of this new model building will tap traditional data sources that have not heretofore been integrated—and, even more excitingly for data scientists, regional scientists and economic policymakers, unconventional data sources that include social media, web-scraping and mouse clicks. These new sources of data may, in the future, become the means to measure economic activity in almost real time.

Without going too far into the weeds, this article provides a high-level look at some of the RED project’s aspirations by discussing its three elements:

  1. Regional economic development
  2. New data  
  3. New methods

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 income and higher standards of living. Fair enough. But why the “regional”? Why not just economic development?

The adjective “regional” is important because everything we do occurs in space—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. While our office supplies vendor may be in Wisconsin, we Hoosiers certainly 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.

In fact, 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 based on commuting patterns, which is simply another 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 in the Louisville MSA. Scott County is connected to Louisville because so many of the county residents work there. One might say that an MSA defines the labor shed and the worker-employer interconnectedness, but the regional labor force is only one dimension, or layer. The region that a Scott County resident considers herself to be in may be much different from the region that her employer operates in.

Austin, Indiana, is 300 miles—a half day’s drive—from a vast majority of the automobile production in the country. It may be the author’s speculation, but 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 (see Figure 1). A region becomes larger when one considers the movement of goods rather than the daily movement of people.

Figure 1: Counties within 300 miles of Austin, Indiana

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Source: StatsAmerica Big Radius Tool

There are other relevant geographic boundaries. The state typically applies many labor and environmental regulations. The relevant boundaries for knowledge or financial capital may be national or international. Know-how developed in a laboratory in Texas may be transferred immediately via telecommunications. While regions are usually considered in terms of labor force, employers and commuting, there are additional layers and dimensions that may influence the state of, or rate of growth in, the economy.

New data

Many of those dimensions are not well represented by the socio-economic data that governments collect. Federal, state and local government entities collect data on a wide array of topics. These data are folded into official statistics that are used to present a data picture of what a region, state or the country looks like. These data also provide a set of measures of economic performance and progress.

Through no fault of their own, the data that these government entities collect and report are subject to significant 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, there are still lags. Moreover, the official statistics may not be collected in new areas of activity or may suffer from survey fatigue—people are just tired of filling out surveys and won’t complete the government forms (even when they should by law).

Think for a moment: 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 aims 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 is looking at what new and unconventional data—data that are out there but have yet to be tapped—may be able to help answer these and other important questions. Consider the gig economy. While not informal in the sense of transactions occurring under the table, a 1099 tax form is the same for landscapers as it is for hairdressers. How do we measure the changes in the workforce, occupational needs and educational needs when a large swath of workers are classified as “not classified?” Unconventional data may help make that opaque category more transparent.

New methods

Finally, new methods is the third element of the RED project that is also taking the long view. The current state of the art for regional economic development is an economic analytic core, with other disciplines added on as needed. 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 project will build 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 will apply 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. The modeling exercise will 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. We are of the conviction that 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.

Conclusion

In the 1950s, there was little research on human capital. One might even say that the construct and term were controversial. As the 1950s moved into the 1960s, economists and education researchers increasingly studied the importance of knowledge and education on economic growth and personal income. Several decades and Nobel laureates later, the concept of human capital and its importance in fostering rising standards of living are well established. In the 1950s and 1960s, human capital was an emerging area of research. Today, the average person on the street would understand what one means when speaking of human capital.

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.2 The RED research team seeks to understand the forces that propel—and the obstacles that hinder—regional economic development. Regional economic growth sustains rising standards of living and, following, improved health and other desirable social outcomes.

Some regions prosper; others languish. Why? The research questions for RED are of paramount interest to policymakers, as well as businesses and nonprofits. No two regions are alike. 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. There have been admirable analyses and policy proposals—creative class and cluster-based development strategies, for example—but like the case of South Korea’s export-led growth, not all regions can pursue the same strategy at the same time and expect success. The RED research agenda will develop a framework for precision policy—policy specifically targeted for a particular region. The framework will, by necessity, be “scalable.” That is, the modeling framework will begin modestly but will be flexible enough to assimilate additional disciplines and data sets in the future as the model grows in its dimensions.

We see the RED project as occupying a distinctive space. When it is concluded, the project team may not be able to answer the question about whether building social capital (helping a neighbor to move a piano) or transferring skills and knowledge (posting a how-to on piano tuning) is more important for economic development. However, we will have a better idea about where to look for and capture the data, a stronger conceptual framework to analyze the data, and a better understanding of the expected effects on economic development.

Notes

  1. “IU researchers awarded $1.4 million grant to promote regional economic development,” News at IU, September 14, 2017, https://news.iu.edu/stories/2017/09/iu/releases/14-regional-economic-development.html.
  2. A theoretical framework for regional economic development is not well established. Even in their ambitious textbook on the subject, Stimson and colleagues make no claim to having arrived at a theory of regional economic development. “Quite deliberately this book is not about the theory of regional economic development, although it provides the reader with an overview of key theoretical and conceptual contexts within which the economic development process takes place.” See R.J. Stimson, R. R. Stough, and B. H. Roberts, Regional Economic Development: Analysis and Planning Strategy (New York: Springer Science & Business Media, 2006), IX.