As market monetarism starts to become more mainstream, I have started to take some time to think about what yet has to be done to develop this new brand of monetary theory. One issue that recurs in my thoughts is that market monetarism needs to help develop a richer understanding of financial dynamics.
One of the strongest justifications is that a richer understanding of financial linkages would help untangle the dynamics of monetary policy under different regimes. Scott Sumner argues that monetary policy works not with long and variable lags, but rather long and variable leads. Because agents are forward looking, expectations of future nominal GDP significantly affect current economic activity. The strongest evidence for this comes from the financial markets. For the United States, Marcus Nunes has done quite a bit of work charting the immediate effects of monetary policy hints on inflation expectations:
We also see similar evidence in the international arena, whether Japanese, Swiss, Hong Kong, or American.
However, the chart is incomplete. Past studies do suggest that the effect of interest rate cuts are not felt until several months after the initial policy declaration. While there may be identification issues with those studies, they do open up the possibility that monetary policy does not act as quickly as market monetarists would hope. In this context, a hybrid approach may be more accurate. While monetary policy leads the financial sector, it is likely that monetary policy lags in other "real" sectors, such as manufacturing.
This synthesis of both monetary and financial dynamics is especially important given Lars Christensen's argument that "there is probably no better indicator for the monetary policy stance than market prices." We know from the financial literature that certain phenomena, such as excess volatility, seem to defy the typical market monetarist use of the efficient market and rational expectations hypotheses. This is not to say policy would be better guided by the arbitrary decisions of central bankers, but rather that a move to market based signals needs to be grounded on better a theoretical and empirical understanding of how monetary policy and financial signals lead other parts the real economy.
As an example of this, we can take a look at the relationship between TIPS inflation expectations and PCE inflation. For those who don't know, the TIPS spread is the interest rate differential between the 5 year inflation protected treasury and the regular 5 year treasury, and therefore is a measure of what investors expect inflation to be over a five year time horizon.
Under the rational expectations hypothesis, expected future inflation should be a reasonable estimate of actual future inflation. By the efficient market hypothesis, these expectations should then be expressed in the 5 year TIPS spread. However, for the years during which we actually have data on how the 5 year TIPS compared against the actual inflation rate, performance is quite poor:
This evidence suggests that even market forecasts can be unreliable. While they can sometimes be a good indicator of future performance, in other times they can be unacceptably wrong. In the above example, the relationship between the TIPS forecast and actual inflation was so wrong that it was negative. While such data points may be washed out in the long run, the 5 years of flawed predictive capacity that it would have given should give any policy maker pause.
However, the TIPS spread is actually quite a good predictor of contemporaneous inflation. Below I plotted each month's PCE inflation rate with that month's average TIPS spread, and find that the linear prediction (red points) does a good job of measuring current month inflation:
This suggests that while we may not be able to use market signals to predict with precision, market signals do carry significant information content. Instead of waiting for each month's CPI report with bated breath, we could simply consider the financial data that is always available to us. This resembles my conclusion from looking at forecaster data. Given that we have reasonably accurate forecast, monetary policy should target those forecasts. When bad forecasts come in, central bankers can signal that they are ready to ease monetary conditions if the bad conditions materialize themselves. The trick here is to make sure that the information hiding in market prices can make its way into policy, and a better understanding of the relationship between finance and macro is an important step in that direction.