Economics One

Last week I was invited by Macroeconomic Advisers to participate in their interesting annual Washington Policy Seminar, and to be on a panel with Larry Meyer. They called the panel: “Fed Policy: The Good, the Bad, and the Ugly.”  So I prepared a few charts on the Good, the Bad and the Ugly. Since then I have prepared a fourth chart: the Uglier.

Chart 1 is the Good. It plots the amount of Fed-supplied liquidity (measured by reserve balances of the banks at the Fed).  It shows the increase in liquidity at the time of the 9/11 terrorist attacks of 2001, when the payment system was physically damaged, and also the increase in liquidity at the time of the panic of 2008.  These actions represent good monetary policy in the sense that the Fed acted in its lender-of-last resort capacity to provide liquidity in times of stress.  You can see that the injection around 9/11 was properly short-lived. Although the lender of last resort facilities for the panic of 2008 were also short-lived (as shown in the graph), the total amount of reserves was not. The liquidity provisions did not end as in the Chart 1. Instead we got Chart 2.

Chart 2 is the Bad. It shows the explosion of liquidity due to Quantitative Easing (QE) 1 and 2 (blue line) and the recent sharp increase due to QE3 announced in September and December of last year. The blue is what has already happened and the red is a continuation the original QE3 based on the hypothesis that the $85 billion per month would continue until labor market conditions improved (which originally could have been taken to be 6.5% unemployment rate).

Chart 3 is the Ugly. It shows the first tapering announcement only 5 months after the start of the original QE3. Long term interest rates—which never really fell with QE3—were now on the rise.

Chart 4 is the Uglier. It shows the surprise abandonment for now of the New QE3, and the start of a  New New QE3. Who knows when and if that will end.

In a recent paper (summarized here) Alex Nikolsko-Rzhevskyy, David Papell, and Ruxandra Prodan applied statistical tests to identify periods in recent U.S. history when Fed policy was “rules-based”—which they define in practice as Taylor rule periods—and periods when it was discretionary—which they define as non-Taylor rule periods. (They used both a structural change test and a Markov switching test).

Their statistical identification procedures were not based on which periods had better economic performance, only on measures of monetary policy actions.

But now they have now gone back to the data to determine whether the rules-based or discretionary periods delivered better economic performance.  This morning David Papell sent me the following table summarizing their latest results.  For three different performance measures, panels A, B, and C in the table show that Taylor Rule periods had far better economic performance than non-Taylor Rule periods.

David Andolfatto has a interesting technical piece on MacroMania called “Nominal GDP Targeting and the Taylor Rule” in which he derives a relationship between the two, following up on a point by Chris Waller, director of research at the St. Louis Fed.  David starts off with a specific algebraic proposal for NGDP targeting in which the interest rate is on the left-hand side and the difference between NGDP and a target value for NGDP is on the right hand side with a reaction coefficient of 1.   After some algebraic manipulations, he shows that this policy rule is equivalent to a version of the Taylor Rule, though with different reaction coefficients than I originally proposed (here).

While NGDP targeting can certainly be described in the way that David does—with a specific policy instrument and a specific reaction coefficient—it frequently is not specified that way. In fact, sometimes the policy instrument or the reaction coefficient is left unspecified. And in a new research paper, Scott Sumner suggests another way that Fed policy makers might conduct policy in which the monetary base or the interest rate is determined in an iterative manner based on nominal GDP futures without mentioning a reaction coefficient. In all these cases, the comparison with the Taylor Rule is less straightforward. Evan Koenig’s nice All in the Family paper also delves into the relationship between nominal GDP targeting and the Taylor Rule.

In these cases, a good way to compare and evaluate different monetary proposals and rules—and they should be compared and evaluated—is to simulate them in macro models—hopefully dynamic stochastic models.  Because, as Scott Sumner says in his paper, “economists do not agree which models are best,” they should try them out in a host of different models including some of the 50 empirical models in Volker Wieland’s amazing easy-to-use model data base, or with other models if those 50 are not enough. Volker’s aim is to help researchers design better and more robust monetary policy rules.  Of course, there are other evaluation methods including using monetary history and basic monetary theory. But because the dynamics are so important and so hard to work through intuitively, empirical models can help a lot.

In his paper at the recent Jackson Hole conference, Bob Hall criticized nominal GDP targeting, citing his 1994 paper with Greg Mankiw. Bob argues that “A policy of stabilizing nominal GDP growth would require contractionary policies to lower inflation when productivity growth is unusually high. Such a policy might easily trigger a spell at the zero lower bound.” No one at the conference objected to this statement, and I do not recall nominal GDP targeting being mentioned at the conference, though policy rules were mentioned quite a bit. This suggests that more policy evaluation research on the new and different proposals is needed to inform the policy discussion, and it is certainly welcome in my view.