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Can Household Risk-Aversion Measures Predict Fed Policy?

by Jon Hill
June 14, 2012

risk aversion

The so-called Taylor Rule in monetary policy suggests how the Federal Reserve should adjust interest rates based on movements in inflation and economic output.  Although the Fed has never explicitly followed such a rule, it described fairly well the path of interest rate policy under much of Alan Greenspan’s tenure as chairman.

Our own primitive “Geo-Graphics Rule” suggests that from 2000 to 2008 the Fed also tended to move rates in line with household (and nonprofit) risk aversion, which we define in terms of the ratio of their currency, deposits (mostly insured), and money market fund holdings to their total financial assets.  The predictive power of our “rule” was strong (with an R² of 0.77, meaning that it was able to predict 77% of the variation in the Fed Funds rate), even measured against Taylor (with an R² of 0.69 from 1987 to 1999, and 0.51 from 1987 to 2006, using John Taylor’s 1993 formula and CBO measures of potential GDP).

Household risk aversion soared as the financial crisis unfurled in 2008 and 2009, at which point our Geo-Graphics Rule suggests that the Fed Funds rate should have gone deeply negative.  In its stead, the Fed cut the rate to near-zero and engaged in “quantitative easing” (QE) to expand its balance sheet, mimicking the effect of negative interest rates.

Household risk aversion has bounced around since 2011, as has the Fed Funds rate predicted by our rule.  Actual Fed policy has generally been more accommodative than predicted over the past 18 months.  Today’s Fed Funds rate should, on past experience, be near 1%.

What does the Geo-Graphics Rule say about prospects for more QE going forward?  The Fed’s Flow of Funds data are released with a three month lag, so we won’t know where today’s risk-aversion measure stands until late September.  Given recent market volatility, it is likely back on the rise.  A modest one percentage point move upward would suggest another round of QE before the end of the year.

We thank our former colleague Neil Bouhan for his contribution to this post.

Taylor: Discretion Versus Policy Rules in Practice
Chart Book: Economic Recovery
Video: Conducting Monetary Policy at the Zero Bound
Kansas City Fed: Taylor Rule Deviations and Financial Imbalances

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  • Posted by Alex

    Interesting and I like the idea but a few thoughts and comments. First, the simple rule expressed in Taylor 1993 is a blunt instrument indeed. It assumes coefficients on the output and inflation gap that are a.) normalized to one and b.) equally weighted. Second, It is widely accepted that rates set by central banks are ‘sticky.’ That is, they are reluctant to change rates in strict adherence to what Taylor (1993) would suggest. Better Taylor rules account for this with a lag term. Third, even the Taylor rule (depending on the version) would have predicted negative interest rates in the depths of the crisis. Fourth, there is a high degree of endogegnaity in the specification: deposit and MM rates are likely to be nearly perfectly correlated with the FFR so one would expect people to adjust their portfolio into/out of deposits and MMFs in response to changes in the FFR (not just risk perception). Fifth, R^2 is a measure of “goodness of fit” not explanatory or causal power. What is the t-statistic on your coefficient compared to those on the Taylor rule? Finally, how do you know its not reverse causality? That is, in some ways I think your measure is more interesting for gauging the portfolio decisions in response to QE than vice a versa. Interesting post.

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