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Using Economic Data Wisely
This article appeared in Northspan's May 2017 FYI Newsletter

A partner in Northspan’s Northland Connection program recently asked us to run some numbers on regional competitiveness data for the Duluth metropolitan area, which includes St. Louis, Douglas, and Carlton Counties. The data can help ground the storylines people tell about Duluth, whether they’re lauding a more diversified economy that has helped spur a Duluth renaissance or lamenting low population growth, poverty, or related concerns. We compared the Duluth metropolitan area to 12 peer cities, mostly in the Upper Midwest. This work often only raises more questions than it answers, but it does give a high-level overview of the economic state of affairs.

In short: it’s complicated. Duluth’s population growth is the second-lowest of the 13 metropolitan areas, but its wage growth is comparatively strong. Duluth has more years of negative GDP growth than the other cities, but its ratio of jobs created to population added since 2005 is the second-highest among the 13 cities. Healthcare, which is one of Duluth’s biggest growth areas, has a positive upward pull on wages, whereas some other sectors, such as recreation and accommodation and the arts, do not. A growing education sector creates opportunities that Duluth could better harness; for example, the city produces a relatively large number of college graduates with STEM degrees, but doesn’t have terribly high employment in those fields. There are many stories we can tell here, and some of them are genuinely instructive for improving economic outcomes.

It’s all too easy to throw up data-driven maps of different metropolitan areas and label them successes or failures. But an honest understanding of the data requires a deeper dive, and a more intimate knowledge of the facts on the ground. In Duluth’s case, the basic methodology can complicate things before we even get started: government data collection on economic performance adds up the counties that the U.S. Census deems part of a metro area, and St. Louis County has a land area larger than the state of Connecticut. This means that about 75,000 Iron Rangers in northern St. Louis County, likely to their considerable surprise, are labeled residents of the Duluth metro area by most economic analyses. This has major implications for the data, and sure enough, Duluth’s best years according to the data align with iron ore mining booms, while the years where GDP tanks coincide with the downturns. The nearest mine, however, is an hour drive from Duluth proper, and while Duluth’s economy certainly has its ties to regional mining through supply chains and transportation, the story here is much more complicated than the data would suggest.

We tell this story not to draw any immediate conclusions over where the Duluth economy should go, or how to frame it within a broader region—that would require more research and engagement with our partners—but to show how easily data can mislead, and how valuable analysis needs to go much deeper. Both Duluth and the Iron Range need to understand the factors on the ground in each location, and go beyond the most basic statistics to think strategically about how to encourage future growth.

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