The Bet Beneath the Building
August 2026 | Written By Mark Schneider and Christopher Collins
What you really own when you own real estate — and how to see it in the data
Section 1 — LQ in 30 Seconds
A location quotient, or LQ, shows what a city does more or less of than the national average. Say Las Vegas has 25% of its jobs in leisure-hospitality versus 10% nationally; Las Vegas’s leisure-hospitality industry would then have an LQ of 2.5.
Above 1.0 = Above Average
~1.0 = Average
Below 1.0 = Below Average
Section 2 — Why the Underlying Industry Matters
Most real estate market analysis starts with the common statistics: population growth, job growth, migration, household formation and supply.
Those numbers tell us what is happening, but they do not always tell us why.
Imagine two markets that each added 50,000 jobs. On the surface, they may look the same. But what industries those 50,000 jobs came from matters. Fifty thousand jobs tied to a growing, high-wage industry can represent a very different economic outcome than 50,000 jobs tied to an industry facing structural or cyclical pressure.
Real estate sits downstream of those industries:
Industry → Jobs → Households → Real Estate Demand
That means, whether you realize it or not, where you own real estate is also an indirect bet on the industries supporting that market.
If you believe semiconductor investment will continue to expand rapidly in the U.S., owning real estate in a market like Phoenix can give you another way to participate in that thesis through its second-order impact on jobs, households and real estate demand.
If you believe traditional film and television production in cities like Los Angeles faces structural headwinds, you may choose to underweight markets heavily dependent on it.
LQ helps make those underlying bets visible.
Section 3 — Position + Direction
You should think about LQ in two ways:
Position: What industries is this market heavily exposed to today?
Direction: Which industries are becoming more or less important to the city itself — and how are those industries changing nationally?
Position shows you the bet you own today. Direction shows you how that bet is changing.
Neither is inherently good or bad. A high or low LQ can be attractive, and so can a rising or falling one.
You decide whether you like the bet.
Section 4 — Looking Beneath the Map
Denver and Raleigh at first glance feel like very different real estate markets. One is a Rocky Mountain metro known for lifestyle migration; the other is a Sun Belt market anchored by the Research Triangle.
But by economic exposure, they are nearly the same market. As of July 2026, both are concentrated in Professional & Business Services (LQs of 1.35 and 1.40) and Information (1.48 and 1.73), both are light on manufacturing at roughly half the national weight, and both sit almost exactly at the national average in government and leisure. Across all ten sectors, Denver and Raleigh have among the most similar profiles of any two major metros in the country.
LQ helps you spot this overlap. The map can make you feel diversified when economically you may just be doubling down on the same bet.
Section 5 — What Job Growth Can Miss
A rising LQ does not necessarily mean an industry is growing, and a falling LQ does not necessarily mean it is shrinking.
Austin: Government added roughly 85,500 jobs from 1995 to 2026, yet its LQ fell from 1.51 to 1.02 because other industries grew even faster, making government less important to the city’s economy.
Detroit: Manufacturing lost roughly 137,000 jobs over the same period, yet its LQ rose from 1.23 to 1.45 because the rest of America diversified away from manufacturing faster than Detroit.
Austin added government jobs but became less dependent on government. Detroit lost manufacturing jobs but became more dependent on manufacturing. That is what LQ can reveal that job growth alone cannot.
Section 6 — How to Read a Market in Five Questions
What is the market exposed to?
How concentrated is that exposure?
Is it becoming more or less important over time?
What is happening to those industries nationally?
Do you want that bet?
As a quick concentration check, look at the market's top LQs alongside the number of jobs behind them.
Section 7 — What LQ Can’t Tell You
LQ is based on jobs, so it does not capture wages, productivity or economic output. Broad industry categories are also only a starting point — you still need to understand the companies and sub-industries driving them.
The data is not perfect either. Remote work has made where a job “belongs” less clear, while changes in metro boundaries or industry classifications can create noise over longer periods.
Most importantly, LQ is not a forecast. It does not tell you which industries will grow, which markets will outperform, or whether today’s concentrations will persist.
Section 8 — The Bet Beneath the Building
MetroLQ can help you lean into broader investment theses through real estate, understand the economic exposures you actually own, and see how those exposures are changing over time.
It won’t tell you what bet to make. It helps you understand the bets you are already making — and where you may want to make the next one.
Works Cited
Data
U.S. Bureau of Labor Statistics. State and Metro Area Employment, Hours, and Earnings, and Current Employment Statistics. All employees, not seasonally adjusted. Accessed August 2026. https://www.bls.gov/sae/
All location quotients, employment levels and growth rates in this paper are calculated by Clear Bay Capital from that source. Austin and Detroit figures span June 1995 to May 2026; Denver and Raleigh reflect July 2026. Metro and national figures are matched to the same calendar month so seasonal patterns do not distort the comparison. MetroLQ updates as new data is released, so figures in the tool will move past those cited here.
Economic base theory
Geltner, David, Norman G. Miller, Jim Clayton, and Piet Eichholtz. Commercial Real Estate Analysis and Investments. 3rd ed. OnCourse Learning, 2014.
Ling, David C., and Wayne R. Archer. Real Estate Principles: A Value Approach. 4th ed. McGraw-Hill, 2013.
Walsh, Joseph. “Economic Base Analysis: Location Quotients.” University of Wisconsin–Madison, Wisconsin School of Business.