OF THE 600,000 or so new businesses created in America every year, just 50% will survive through to their fourth year. Fewer still will grow to anything beyond mom-and-pop sized stores. And just a tiny fraction has any chance of becoming the next Facebook, Twitter or Uber. To date, policymakers have focussed on the number of new businesses as the bellwether of entrepreneurial health—a figure which, to their alarm, has yet to fully recover from the effect of the 2008 recession. A new statistical method attempts to evaluate the quality of new businesses over quantity.

Jorge Guzman and Scott Stern from the Sloan School of Management at the Massachusetts Institute of Technology have mined troves of publicly available data on each of the 1.6m new business created in California between 2001 and 2011. Within their dataset, among the hundreds of thousands of no-hopers, lie rubies such as Twitter and Uber. Messrs Guzman and Stern wanted to find out whether there is any way of predicting the success of a new business based solely on the information available to them within the first years of its creation.

The academics judge whether a company is successful or not based on whether it is acquired or listed on the stockmarket within its first six years. Just 501 of the 835,946 companies started in California between 2001 and 2006 fell into this category: equivalent to a six in 10,000 chance of “success”. Using this subset of data the researchers attempt to predict, on a post-hoc basis, which startups will be successes based upon three simple factors: the name of the firm, its type and place of registration, and whether the business has a registered patent or trademark.

The results, published in the journal Science, found that business success can be reliably predicted by a whether a firm is named after its founder (those that do are 70% less likely to be successful); the length of a the business name (names that are less than three words long are 50% more likely to grow); and whether the name of company—“nano” or “moog” for example—is associated with technology clusters (those that are, are 92% more likely to be successful). Meanwhile, registering a trademark and incorporating your firm increases the likelihood of success by five and six times respectively. And registering your company in Delaware and having a patent increases the likely success 200-fold.

As ever, the academics are at pains to point out that these variables are not causative, but simply proxies for the unobservable characteristics of startups. A name signals the broad intentions of a business, whether global or parochial. Intellectual property rights are indicative of innovation, and registering a business in Delaware is associated with the venture-capital investment that is necessary for early growth.

Messrs Guzman and Stern go on to calculate the “entrepreneurial quality” of each of the 754,000 new businesses created in the Golden State between 2007 and 2011. The map above shows the quality of startups in all 3,242 zip-code areas in California. Somewhat unsurprisingly, 94025 (home to Facebook) and 94043 (home to Google and LinkedIn) standout as among the best locations: they have about 25 times the entrepreneurial quality of the median zip code in the state. The quality score associated with those zip codes, of around 4.5%, can be interpreted as 4.5 out of every 1,000 businesses created between 2007 and 2011 can be expected to list or be bought within their first six years.

By ignoring geographical variables in the model it is possible to estimate the benefit that startups get from being based in any one location. During 2001 to 2006, Silicon Valley startups had 60% more successful firms than predicted by the academic’s model, whereas Los Angeles had 13% fewer. This may be indicative of the buckets of cash swashing round the valley or some other unobserved geographic-specific variable.

Creating a successful startup can be a crap shoot. Even startups that show all the tell-tale signs of a successful firm—Nano Moog™ registered in Delaware with a patent to its name—would still have just a 5% chance of success. There are many other factors plus a good dose of luck that determine whether a company will grow or not. But with this new metric policymakers can begin to worry less about the quantity of startups and focus more on their quality.