What does it mean to be data dependent? The term immediately conjures up the image of studious Economists working their mathematics to perfectly calibrate the proper monetary policy response. It is attached to the Federal Reserve, and other central banks, but its application is much broader. Businesses are, obviously, data dependent and often in the same way as the FOMC.
There is somewhat of a dichotomy as to how the phrase has come to be used. In strict monetary policy terms, it has evolved from the minor debacle over forward guidance. Without rehashing that silliness (Odyssian vs. Delphic), we are left with what should be straight forward. The Fed, as any business, surveys the economic climate and makes decisions based on subjective interpretations of those surveys.
This is a modern invention for any central bank. In the good ol' days, the institution wouldn't need to do this. The bank would content itself with a narrow focus on, you know, money. In fact, in the traditional framework central bankers of ages past would have been appalled at what monetary policy has become – an effort to at least guide, if not completely control, the marginal economic direction.
Without any money in monetary policy, the pursuit has devolved into data dependence. This is even more complicated still. Not only does it require selection of the “right” data set, you also have to be mindful of time horizons. In a lot of cases, time is a bigger factor than any catalog list of statistics.
In October 2016, Cleveland Fed President Loretta Mester described the challenge. Speaking about uncertainty, she told the Shadow Open Market Committee of her disquiet upon seeing the reported results of a CNBC survey conducted earlier that year. According to Mester's recall, nearly half of financial professionals (meaning economists, fund managers, and market strategists) believed the FOMC's stated commitment to data dependence pertained mostly to immediate figures.
Mester:
The concept of “data dependence” was meant to reinforce the idea that the economy is dynamic and will be hit by economic disturbances that can't be known in advance. Some shocks will result in an accumulation of economic information that changes the medium-run outlook for the economy and the risks around the outlook in a way to which monetary policy will want to respond. But some of these shocks will not materially change the outlook or policymakers' view of appropriate policy. Unfortunately, referring to policy as “data-dependent” could be giving the wrong impression that policy is driven by short-run movements in a couple of different data reports.
A few among us know this problem well, being described constantly as “transitory.” The issue, again, is not just for policymakers to consider but economic agents, as well. How does one go about sorting which unfavorable current data to ignore in favor of a longer-term outlook, and those troubling statistics that indicate one should shift one's medium or even longer-term outlook because of them?
The idea of “transitory” is quite simple; it is the Fed attempting to do the former. They are saying, in effect, yes, we see that inflation is low (or economic growth for that matter) but we are ignoring it because we believe in our medium-term outlook which we don't believe will be swayed by the misses (even as they accumulate). The data dependence, then, is not really about those concerning deviations but moreover any other data that might suggest their short-term nature (like the unemployment rate).
