Wednesday, June 10, 2015

Dire predictions about firm failure

John Chambers made a prediction that CBS News journalists find really noteworthy:

In one of his last appearances as Cisco (CSCO) CEO, John Chambers offered a stark view of the future for many businesses. He estimated that 40 percent of them wouldn't exist in 10 years because of the rapidly changing technological landscape. 

The article proceeds to pile on, with quotes from eminent scholars:

"He is right in ... characterizing the nature of transformative change that's talking place in the economy," said Rahul Kapoor, assistant professor of management at the Wharton School of Business at the University of Pennsylvania.

Of course, the "transformative change" that we're talking about is actually going on all the time; please read your Schumpeter.

The annual firm failure rate in the US ranges from 8 to 10 percent. We can't quite get a 10-year exit rate without microdata, but we can get a rough, ballpark example from the BDS. Suppose I do the following: count how many firms exist in a given year, count how many firms aged 11+ exist 11 years later, then divide things appropriately. This won't capture the actual failure rate due to things like M&A, but it should give us a magnitude to work from. Figure 1 plots this 10-year exit rate (click for larger image). Interpret as follows: the line at year t gives the percent of year-t firms that won't exist in year t+11.

Figure 1


This rate ranges from 50 to 60 percent, and it has been falling. Chambers may get the prediction right, but if so, it will be because the next ten years will be less "transformative" than the last 30. If the 40 percent figure is cause for alarm, that's only because it would mean the US economy has become even less dynamic (which seems plausible given current trends [pdf]); and even then it's unclear whether we should worry. These numbers are nice because they remind us that young firms make a big contribution to labor markets. (Caveat: as I mentioned above, some of this is M&A, so these data provide an upper bound).

I want to be fair to Chambers: it's possible that, contrary to CBSN's interpretation of his comment, he was actually referring to large, established firms that we generally don't think of as being at high risk of failure. So it's useful to think of these numbers in employment-weighted terms. That is, what will be the employment of firms in existence in year t when we get to year t+11, and how does that compare to year t employment of those firms? Figure 2 plots 10-year exit rates on an employment-weighted basis (click for larger image).

Figure 2


You can see that this rate ranges from 10 to 20 percent, but really it was 10 percent until the Great Recession. 

A similar way to interpret Chambers is to focus only on established firms, and ignore startups. Figure 3 plots 10-year exit rates when we only look at firms age 5 and above (unweighted; click for larger image).

Figure 3


These numbers range from less than 5 to about 15 percent, with a big rise associated with the Great Recession. So in this sense, Chambers' prediction is noteworthy. If employment among today's older firms falls by 40 percent over the next decade, that would be a pretty big deal and require a lot of reallocation. In some senses this could be a plausible prediction: you can see that the Great Recession really moved this number, and we know that said recession was not cleansing in a productivity sense, so our current stock of firms could be a bit weaker than we're used to. But I am going to take a risky stand and predict that 40 percent is an overestimate for this quantity. What is likely to move these numbers that much is a huge recession, not ongoing technological progress, and you can see what even a recession the size of our last one does.

In any case, the way Chambers stated the prediction, and the way the journalists reported it, betrays a serious lack of familiarity with the pace of pedestrian reallocation that occurs in the US economy. Economic transformation is not a big, discrete event; it is a continual process. Journalists reporting on stories like this would do their viewers a big service by providing some quantitative context.