Manufacturing: a fantasy


You may not realize it, but we apparently are living in a manufacturer's paradise. A study released last week by three economists at the University of Connecticut concluded Connecticut has the seventh-lowest cost for manufacturers for each $1 of goods produced.

Specifically, as reported by The Connecticut Mirror, Connecticut manufacturers spend an average of 79.3 cents to produce each dollar's worth of manufactured goods, compared with a national average of 83.3 cents. The state with the lowest margin for manufacturers was Vermont, at 95.9 cents; the state with the highest margin, Oregon, at 70.6 cents. Totals for nearby states: New York, 78.1 cents; Massachusetts, 83 cents; New Jersey, 84.1 cents; and Rhode Island, 93 cents.

The study's authors heaped especial scorn on Gregory Hayes, chief financial officer of United Technologies Corp., who, when asked about where to locate manufacturing plants, replied: "Any place outside of Connecticut is low-cost." Replied the UConn report's authors: "There's no denying the popular perception ... that Connecticut is an unattractive business location. ... But are these oft-cited rankings supported by sound analyses of available economic data? And if they are correct, why don't even more firms flee Connecticut for lower-wage states?"

The study and its authors' interpretation of their findings call to mind the opening scene of the Marx Brothers movie "A Night at the Opera." Groucho is supposed to dine with Mrs. Teasdale, an aging society dame, but he apparently has stood her up. Then the frame widens, and Groucho is shown at a neighboring table, laughing and flirting with a young blonde. Mrs. Teasdale confronts Groucho, who denies he was entertaining the blonde instead of her. Says Mrs. Teasdale: "But I saw you with my own two eyes." Groucho replies: "Well, who are you going to believe, me or your own two eyes?"

The same question can be put to the authors of the UConn study. When a purportedly scientific study such as theirs reaches conclusions that are greatly at odds with observable reality, then there is likely a flaw in either the study or its interpretation.

In the case of the UConn study, the flaw is fairly obvious: The statistic doesn't measure what the authors claim it does. It's as if they are trying to measure temperature with a barometer. As a result, they ask the wrong question. Instead of wondering why more firms haven't left the state, they should be asking what firms haven't already fled.

Waterbury still calls itself the Brass City, but where are its brass mills? Meriden still is known as the Silver City, but where are its silver manufacturers? Danbury is the Hat City, but when was the last time it produced any hats? Naugatuck used to be the Rubber City, but where are its rubber plants? Why, despite the UConn study, does it seem Connecticut could justifiably change its nickname from the Nutmeg State to the Abandoned Factory State?

The problem with the UConn study is it isn't measuring the vital, manufacturing economy of Connecticut in the 1950s and 1960s. Instead, its authors are using numbers from the ruins of that economy, numbers generated by a relative handful of companies that somehow managed to hang on.

The study's measure — cost-to-produce vs. sale price — is strictly an indicator of essential profit margin. And viewed that way, Connecticut is exposed as a horrific place for manufacturing, which, after all, entails the production of goods in mass quantities so the maker can rely on sales volume rather than profit margin per sale.

What the study really shows is that to survive in Connecticut, a manufacturer needs to have the seventh-highest profit margin in the nation. What the study really shows is that only companies that make the most profitable of products, such as submarines or presidential helicopters, can hang on in Connecticut. Meanwhile, employers who used to provide jobs for thousands of workers to make goods with smaller profit margins — including everything from brass fittings to tennis shoes — have had to flee.

The way to choose which interpretation of the data is correct is to decide who you're going to believe, the three UConn economists or your own two eyes.