An article about a fiction and the employment report

Skip the fiction, look at the employment report

In an article “A Grand Unified Theory of the Jobless Recovery” by Derek Thompson in THE ATLANTIC, the author goes to great lengths to explain why “In most recessions in the last 60 years, jobs recovered soon after the economy healed. But in the last three downturns -- the early '90s, the early '00s, and today -- companies continued to slash jobs and hold off hiring for months, even years, after profits returned.” He then proceeds to look for whom or what to blame. He trots out his pet set of villains. So far, so good, that’s what journalists do.

Problem is he never bothers to show whether “companies continued to slash jobs and hold off hiring for months, even years, after profits returned” is anything new. It’s not. Recoveries don’t come from having the same set of employers hire back people. Recoveries have always come mainly from new or different companies hiring. Interestingly, it tends to be smaller companies and often start ups from the current or the last cycle. But alas, facts don’t fit his story, so he ignores them.

The author of the article makes a fairly common mistake. When people discuss the lag in employment recoveries, they often analyze a fictitious and meaningless relationship. For example, they’ll look at or include a totally meaningless graph. They’ll show a chart of employment growth plotted against the months since the end of the recession. To have any relevance one has to assume that 1) recession dating is accurate at the monthly level, 2) there has been no change in how quickly we can recognize recession endings, and 3) profits automatically recover with GDP.

Let’s examine each of these. First, one reaction to monthly recession end dates is an incredulous; “you’ve got to be kidding.” Why, even the monthly employment pattern is not perfect. Granted, shifting employment growth numbers generally stay consistent with the overall trajectory, but not always. But, neither the data nor the state of the ART of recession dating justifies the attention the relationship gets. Think about how often GDP gets revised and how significant GPD revisions are. It’s fiction to think we know exactly the month when a recession ends. Further, changing the start date for the recovery significantly changes the patterns of recovery.

Second, it is ridiculous to assume no change in recession dating. Economist would like to think there is some progress in the discipline, but one doesn’t have to rely on what economists would like to think. (However, it’s interesting to note that using recession end dates gets real close to relying on what economists would like to think). One would also think someone from the chattering class might also be aware that there is more, and, in some cases, better data available over time. Further, one would have to be asleep not to recognize it is disseminated faster and more broadly.

Third, the faster and greater data availability provides a nice transition to the aspect of the relationship that makes it meaningless. Employment doesn’t increase because recessions end. There are numerous owners of bankrupt and defunct businesses that wish it were so. In fact, as owners of Fannie and Freddie, we all should wish it were so. However, profits drive employment growth. Profits require a viable business model and good management.

Since existing companies have a vested interest in their existing business model, their role in the recovery of employment is limited. This process of churn, or “creative destruction” to use the term Schumpeter made famous, isn’t something journalists or even governments can stop. They can impede it rather than facilitate it. Perhaps that has something to do with jobless recoveries.

So, to be interesting, the analysis should focus on the recovery of profits. Keeping with the data avalanche theme, should it be pretax or post tax profits; profits measured by general accepted accounting practice or tax accounting practice; profits of all businesses including partnership and proprietor income or just corporate profits, or estimate quarterly profits or the actual end of the fiscal year “real” profits? That would certainly be more interesting, but it still wouldn’t be meaningful. As anyone who has ever made a business decision knows, it is estimates of FUTURE profits that lead to hiring and investment.

As the article’s author notes, “Something's not right.” Perhaps rather than grand unified theories that target pet peeves, investing some time in collecting some facts would be a better use of time. Take Friday’s jobs report as an example. In previous postings, The Hedged Economist pointed out that at this point in a healthy recovery there is usually a “noticeable” divergence in the growth of employment as reported from the household survey verses as reported from the employer survey. The household survey captures people who become self employed, start businesses, or are hired by small companies. They generally aren’t counted by the employer survey.

By “noticeable” I mean more that measurable. The media, knowing they live by “if it bleeds it leads,” should by now, have to be explicitly dismissing the household numbers to support their disaster scenarios. But, they haven’t had to. “Something's not right.” However, to support grand unified theories of what’s not right, one has to ignore the facts. The facts are, something is different this time. It is this time, not some grand unified theory, which needs to be understood.

The picture isn’t pretty. The evidence that the needed churn isn’t happening is there. In addition to the behavior of the two different measures of employment, Friday’s report included other data with telling implications: namely, the revisions. The BLS is aware of the limitation of the employer survey (i.e., not adequately representing new and small businesses). It tries to adjust the data to correct for the undercount using what is called the business birth-death model. That adjustment has its primary impact on the last few months of data. The data is then revised when better, some would say real, data become available. Those were the months for which the employment data was revised down. The unavoidable implication is that fewer jobs are being created by new and small business than they expected. This absence of churn among employers deserves more attention.

If the churn is necessary for recovery, perhaps more organized study of how people change jobs would help. There’s a good chance that the people who stay unemployed are those who keep looking for a job doing what they use to do. If what they use to do was so valuable, they’d still be doing it. Just as employers churn, the skills and knowledge that leads to successful employment churn. If that’s the case, learning to learn and equipping people with multiple skills, not unified theories, are the solution.