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Company Towns: When One Employer Dominates a Local Market

Midland, Texas employs petroleum engineers at seventy-one times the national rate. That is what a single-industry labor market looks like in the data.

Short answer

A company town shows up as extreme occupational concentration. Midland's petroleum engineers sit at 71 times their national share; Huntsville's aerospace engineers at 44 times; Lexington Park's at 34. Concentration that high means excellent pay and a genuine market while the industry is healthy, and almost no alternative if it is not — the same fact producing both outcomes.

What seventy-one times looks like

Midland, Texas has a labor market of 113,700 people and about 940 petroleum engineers in it. That is 71 times the rate you would expect from its size, and a median of $172,070.

Huntsville, Alabama concentrates aerospace engineers at 44 times, with 4,880 of them at $131,090. Lexington Park, Maryland manages 34 times in a labor market of only 64,950 — a town of about sixty-five thousand jobs, a fair number of which exist because of one naval air station.

These are not large numbers of people. They are large shares of small places, and that is exactly what makes them company towns.

The case for going

Specialist pay, in a place with small-metro costs. A petroleum engineer earning $172,070 in Midland is in a different financial position from one earning the same in Houston, and the gap is mostly housing.

You also get colleagues who do what you do, employers who understand the work, and a local labor market where your specific experience is the thing being bought rather than a curiosity on a resume. For a narrow specialization that can be worth more than a coastal salary.

The case against, which is the same fact

Your income, your employer and your house are all exposed to one industry. When it turns, it does not turn for you alone: the other employers in town are in the same business, and so are the people you would be selling your house to.

That is a concentrated bet whether or not anybody described it as one. Most people who take these jobs have not thought of the house as part of the position, and it is.

The question that measures your exposure

If your employer closed tomorrow, how many others within commuting distance need what you do?

In a dense general market the answer is dozens. In a company town it is often one or two, and sometimes none — and the honest version of that answer changes what you should do about savings, about your network, and about how portable you keep your skills.

How to hold the job without holding all the risk

Keep your skills portable to the general version of your occupation. The local specialization is what makes you valuable in town and worthless outside it, so keep one foot in the wider discipline.

Maintain a network beyond the metro. That takes years and cannot be built during a downturn, which is precisely when you need it.

Treat the house as part of the bet. Renting for the first stretch, or buying below what the salary would support, is a reasonable hedge in a one-industry town and an odd decision anywhere else.

Reading a metro before you move

Look at the whole occupational distribution, not just yours. A metro where one industry dominates every list behaves differently from one that merely happens to employ you. And check the second career in your household — depth in one occupation is not depth generally, and dual-career households are where these places most often fail.

How to tell a company town from a specialist cluster

Both look the same in a concentration figure, and they behave completely differently.

A specialist cluster has many employers doing related work: Huntsville’s aerospace concentration spans federal installations, prime contractors and the suppliers around them, so a single program ending is survivable. A company town has one payer and a service economy attached to it, and when that payer contracts, so does everything else including the housing market.

The published data will not distinguish them for you. Counting the employers who actually post jobs for your occupation in that metro will, and it takes an afternoon.

The wage figure hides how it is set

In a dense market the median is the outcome of employers bidding against each other. In a one-employer town it is a number somebody chose, and it can be generous — companies in remote locations often pay well above the national figure precisely because they have to.

But a generous number set by one payer moves differently from a competitive one. It holds up in good years and it is renegotiated in bad ones, and you have no second bidder to test it against. That is worth understanding as a feature of the position rather than discovering during the first downturn.

Common questions

What does a company town look like in data?

Extreme occupational concentration — Midland's petroleum engineers at 71 times the national rate, Huntsville's aerospace engineers at 44.

Is the pay good?

Frequently excellent. Midland's petroleum engineers have a median of $172,070, usually with far lower housing costs than a coastal metro.

What is the risk?

Your income, your employer and your home are exposed to the same industry, and local alternatives are in the same business.

What question reveals the exposure?

If your employer closed tomorrow, how many other employers within commuting distance need what you do?

How do I hold such a job safely?

Keep skills portable to the general version of the occupation, maintain a network outside the metro, and treat the house as part of the same bet.

How concentrated can a company town get?

Midland, Texas employs petroleum engineers at 71 times the national rate — about 940 people in a labor market of 113,700, at a median of $172,070.

Should I rent or buy in a one-industry town?

Renting at first is a reasonable hedge, because a downturn hits your income and your largest asset at the same time and the local buyers are in the same industry.

CS

Charles Slocs

Data and research

Charles Slocs builds the data side of this site — pulling the federal wage and employment series, matching job titles to occupation codes, and working out what the numbers do and do not support. He writes the pages that are mostly a question about evidence: what a survey measured, how wide the spread really is, and which published figure is out of date.

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