Federal Reserve Vice Chairman Richard Clarida delivered a speech emphasizing the data dependent nature of Fed policy. There were signals on the path of policy, but the path is subject to the evolution of the economy. The Fed isn’t going to tell you exactly where rates are headed anymore. Welcome to the post-forward guidance world.
Clarida presents an optimistic description of the economy. In particular, he watches the inflation data:
The inflation data in the year to date for the price index for personal consumption expenditures (PCE) have been running at or close to our 2 percent objective, including on a core basis‑‑that is, excluding volatile food and energy prices. While my base case is for this pattern to continue, it is important to monitor measures of inflation expectations to confirm that households and businesses expect price stability to be maintained.
Survey and TIPS-based inflation expectations give him to reason for concern. Then he asks:
What might explain why inflation is running at or close to the Federal Reserve’s long-run objective of 2 percent, and not well above it, when growth is strong and the labor market robust?
The answer is faster potential growth due to productivity gains and labor force growth. He expects demographics to eventually catch up to labor force growth but remains optimistic that in the short run we can squeeze some more labor out of the prime-age group. Regarding productivity growth, he sees both structural and cyclical factors at play. Clarida see business investment as an important indicator of structural productivity growth and expresses what I would call disappointment with the third quarter investment numbers. Still:
One data point does not make a trend, but an improvement in business investment will be important if the pickup in productivity growth that we have seen in recent quarters is to be sustained.
One takeaway is that if we get ongoing above-trend growth in a low-investment economy, then we would expect the currently low inflation rates to tick higher.
Clarida presents a very nice description of the intersection of data dependence, monetary policy, and communications:
It is important to state up-front that data dependence is not, in and of itself, a monetary policy strategy. A monetary policy strategy must find a way to combine incoming data and a model of the economy with a healthy dose of judgment–and humility!–to formulate, and then communicate, a path for the policy rate most consistent with our policy objectives. In the case of the Fed, those objectives are assigned to us by the Congress, and they are to achieve maximum employment and price stability. Importantly, because households and firms must make long-term saving and investment decisions and because these decisions‑‑directly or indirectly‑‑depend on the expected future path for the policy rate, the central bank should find a way to communicate and explain how incoming data are or are not changing the expected path for the policy rate consistent with best meeting its objectives.4 Absent such communication, inefficient divergences between public expectations and central bank intentions for the policy rate path can emerge and persist in ways that are costly to the economy when reversed.
He further explains two different ways in which data might impact policy decisions. The first is by tracking the data relative to the forecast:
If, for example, incoming data in the months ahead were to reveal that inflation and inflation expectations are running higher than projected at present and in ways that are inconsistent with our 2 percent objective, then I would be receptive to increasing the policy rate by more than I currently expect will be necessary.
But data can impact policy in a second way by causing policy makers to update their estimates of key parameters, notably the natural rates of unemployment and interest. For example:
I would expect to revise my estimates of r* and u* as appropriate if incoming data on future inflation and unemployment diverge materially and persistently from my baseline projections today.
Which is a signal of what we can all suspect to coming: If inflation remains low with unemployment below the current estimates of the natural rate of unemployment, then he will lower his estimates of key parameters accordingly. Assuming a constant path of actual unemployment, the impact will be to revise down the expect rate path.
The immediate implications for policy:
This process of learning about r* and u* as new data arrive supports the case for gradual policy normalization, as it will allow the Fed to accumulate more information from the data about the ultimate destination for the policy rate and the unemployment rate at a time when inflation is close to our 2 percent objective.
Clarida still supports gradual policy normalization, edging up interest rates until the data tell him enough is enough. What does this mean? It could mean a lot of things depending on the evolution of the economy. But one example of a potential outcome is that if downward pressure on unemployment ended but inflation remains low, Clarida would not see a need to push rates into a restrictive zone.
There has been some attention to Clarida’s shift from “some further gradual adjustment” to “gradual policy normalization.” I think this debate distracts from what otherwise was a very nice speech outlining the data-dependence approach. That said, my interpretation of the shift away from “some” was yet another effort to roll back forward guidance. Clarida doesn’t want to leave the impression that policy is on a pre-set course. How many more hikes? Could be one. Could be six.
Bottom Line: The Fed is data dependent. Growth will almost certainly slow in 2019. If it looks like to slow sufficiently to halt the slide in the unemployment rate while inflation remains low, the Fed will slow the pace of rate hikes. If unemployment continues to slide while inflation remains low, then the gradual pace of rates will continue longer. If unemployment slides and inflation ticks up, the Fed will probably hike a little faster.