Mr. Powell’s data problems
When I was learning applied econometrics, I remember my classmates and I kept hearing a phrase from our professors over and over again: "garbage in, garbage out."
The point they were making is as budding empirical economists it was important we understood "the quality" of the data we are using in our analysis. They pushed us to ask uncomfortable questions such as: "Is the data you are using really measuring what you think it is measuring?" Also, "Are you examining the 'correct' relationships that theory tells you should exist in the data?" If not, the output (and thus inference) from your analysis is garbage.
I wonder if Fed Chair Jay Powell has ever taken an econometrics course? Unfortunately, it appears he hasn't.
Powell the Job Openings Stat
One of Powell's most favorite statistics is the job openings stat from the BLS. Powell has stated on several occasions that he will continue to raise interest rates as long as labor markets remain "tight" – or as long as the job openings greatly exceed the number of unemployed workers.
So, what is this "job openings" statistic and is it really measuring what Powell thinks it is measuring? The JOLT or Job Openings and Labor Turnover statistic is complied each month by the Bureau of Labor Statistics from establishment surveys. They have been putting the statistic together since 1998 and first released to the public in 2002.
The BLS, basically, asks firms: "on the last business day of the month did you have a job opening that you would be willing to fill in 30-days or less" and " is the firm actively recruiting", where according to the BLS:
"Active recruiting means that the establishment is taking steps to fill a position. It may include advertising in newspapers, on television, or on the radio; posting internet notices, posting "help wanted" signs, networking or making "word-of-mouth" announcements; accepting applications; interviewing candidates; contacting employment agencies; or soliciting employees at job fairs, state or local employment offices, or similar sources." – BLS JOLT Technical Note 1997.
Before the BLS started to compile this data economists would depend on the number of jobs printed in the "help wanted" section of newspapers. The logic was, running such an ad in the newspaper was costly, both implicitly and explicitly, to would be employers. Thus, economists reasoned, employers would only run such an ad if they had a position to fill. So, counting help wanted ads in the newspaper would give economists a good sense of how many job openings really existed. While that was useful before internet it did miss "informal" job recruitment such as word of mouth and other methods. So, the creation JOLT by the BLS was arguably a step in the right direction.
The Rise of Ghost Jobs
Since the pandemic though, questions are being raised about what the job openings statistics is really measuring. Are there really as many job openings as the JOLT reports? A recent report from Robin Ryan at Forbes does a nice job of describing the problem of "ghost jobs" where firms will advertise there is a job opening, when in reality, there really isn't any job opening.
As Ryan explains employers may post job openings (sometimes in multiple locations) in order to demonstrate the firm is growing, or because they want a pool of ready to hire applicants in case some of their current employees leave. Firms may also post job opening but a sudden hiring freeze means there really is not a position that can be filled.
Other anecdotal stories from hiring managers say that some firms post "ghost job" ads to placate overworked current employees. Essentially these firms are telling their overworked employees "keep working hard, we are going to bring more people on to help" when, in reality, the firm does not plan to hire any additional workers.
This then raises the question: "What exactly is the 'job openings' part of JOLT actually measuring?" It is unclear how large a problem these "ghost jobs" are and just how badly skewed the job openings stat is. But, it should be clear, that Powell and Fed should be cautious about being so dependent on this statistic when deciding on raising interest rates.
Money Supply Worries
If the Fed should downplay the JOLT (there are other reasons why the Fed's emphasis on labor market data is questionable – more about that in another post) what statistic should the Fed be watching? An oldie but a goodie is: "Money Supply Growth."
While markets and the macroeconomy certainly have changed a great deal since Milton Friedman stated in 1963 that "inflation is always and everywhere a monetary phenomena", the basic idea still may apply.
Friedman based his statement on the historical analysis he undertook with Anna Schwartz. From this he concluded monetary policy should follow a "monetary rule" where the money supply should grow only 3 to 4% a year to keep inflation under control. But with financial innovations changing the definition of "what is money" and new financial institutions competing with banks, his monetary rule proved to be impossible to implement. In addition, because of all of these changes going on in markets the direct correlation between money supply growth and inflation broke down by the mid-1980s.
But, the general idea of the link between money supply, inflation and economic growth still holds, even if we have huge problems in precisely measuring the money supply.
M2 rapid fall
Which is why Jamie McGeever's recent article in Reuters is so interesting. As McGeever points out M2 fell in February by a seasonally adjusted 2.4% year on year. That is not a decline in the rate of increase, that is an actual decline in M2. That is the first time that has happened since the 1940s. Keep in mind that the February decline is BEFORE the recent bank runs which may result in cash hoardings, or at least declines in borrowing/lending, which could push M2 down even further.
Again, it hard to determine what EXACTLY the outcome of such a rapid fall in one of the broadest measurements of money supply really means. But, as the people in McGeever's article suggest, it should a least suggest that Fed stop raising interest rates and even consider cutting them. A declining money supply has, in the past, led to deflation and sever economic downturns, including many economic depressions. You read that right: depressions, not just recessions. Keep in mind, a declining money supply does not guarantee an economic depression will occur, but a declining money supply is cause for concern.
One thing we do know, and that Mr. Powell does not seem to be aware of, is that changes in monetary policy work with a lag. If he has over tightened, it might take a while to reverse course.
Mr. Powell: there is the door
Perhaps then it is time for Mr. Powell to realize he has been over reliant on data, like the jobs opening data, that may not be measuring what he thinks it is measures. In addition, he and Fed may be overlooking data, like money supply and lending data, that if properly understood and contextualized might suggest they need to change course. Thus, Mr. Powell may have data problems that he does not understand.
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