Regional President Speech

Discussion of 2014 USMPF Monetary Policy Report Narayana Kocherlakota FRB-Minneapolis

Disclaimer The views expressed in this talk are my own. • They may not be shared by others in the Federal Reserve System ... • Especially my colleagues on the Federal Open Market Committee. •

Acknowledgements I thank Ron Feldman, Terry Fitzgerald, Samuel Schulhofer-Wohl and Kei-Mu Yi for comments.

Monetary Policy and Financial Stability Motivation for the Monetary Policy Report (MPR): • Easy monetary policy could create risk of financial instability. My view: It is preferable to mitigate such risks using supervisory tools. • But in reality: Supervision may leave residual systemic risk. • This is especially true given the kinds of risks described in the MPR. • How should this residual risk affect monetary policy?

My Discussion ... First: A framework to incorporate systemic risk mitigation into monetary • policymaking. — Theme: Systemic risk creates a mean-variance trade-off for policy. Second: Lessons from the MPR given this framework. •

Outline 1. Financial Stability and Monetary Policy: A Mean-Variance Framework 2. Lessons from the 2014 Monetary Policy Report 3. Conclusion

A MEAN-VARIANCE FRAMEWORK

Simple Model Monetary policymaker (MP)’s goal is to set a gap  equal to zero. • —  could equal inflation minus target —  could equal output minus its efficient level — OR  could equal some combination of the above MP can increase  by raising accommodation  • After MP chooses ,  is also affected by a number of shocks, including • shocks to the financial system.

The Central Banker’s Problem 2 MP’s loss is given by the square of the gap (that is,  ) • — Standard: MP wants gap to equal zero. — Equally bad to have positive or negative gaps. Recall:  depends on shocks realized after  is chosen. • MP chooses  so as to minimize the mean loss associated with : • 2 ( ) |

Usual Approach Mean loss equals squared mean gap + variance of gap: • 2 [( )] +  ( ) | | Typical assumption: MP can’t influence variance of shocks. • Then, minimizing expected loss is same as minimizing squared mean gap: • 2 [( )] | Solution is to choose accommodation  that eliminates mean gap: ∗ • (  ) = 0 ∗ |

Incorporating Financial Stability Risks Suppose higher  increases the risk of financial instability that lowers  • Then, higher  increases  ( ) • | MP’s problem is to choose  so as to minimize: • 2 [( )] +  ( ) | | Now: MP’s choice of  trades off mean versus variance. •

Mean-Variance Trade-Off Trade-off means that MP’s appropriate choice  will result in: ∗∗ • (  )  0 ∗∗ | That is, on average, the gap is negative under appropriate policy. • MP gives up some mean  in order to get less risk in . • But exactly how much mean  should MP give up? •

Comparing Two Monetary Policy Alternatives It is appropriate for MP to choose  over  if  reduces risk sufficiently ∗ • relative to  : ∗ 2  (  )  ( )  ( ) ∗ | − | | Central banks know a lot about assessing the RHS — that is, the mean of •  given choice  — In my view: The RHS remains large for current choice of  Key question is about the LHS: • How do we assess the difference in the risk implied by policy choices?

A Possibly Helpful Simplification Suppose that a crisis causes the gap  to fall by ∆ • Suppose that monetary accommodation  implies that the probability of • a crisis is () Then (assuming statistical independence of the crisis from other shocks): • 2  (  )  ( ) [( ) ()]∆ ∗ ∗ | − | ≈ − Then: Given any policy choice  or  , we need to assess: ∗ • The implied probability of a crisis and its impact ∆ on 

THE MONETARY POLICY REPORT

Some Important Messages Financial instability can arise from financial institutions that are: • — non-banks — relatively nonleveraged — solvent Asset flows contain key information about financial system risks. • Good news: These ideas do shape Fed surveillance of financial system. •

Amplification of Monetary Policy Changes Basic mechanism in the MPR: Low  (easy money) leads to low risk • premium. High  (tight money) leads to high risk premium. • As a result: Seemingly small changes in monetary policy stance can have • big effects on financial market conditions. Authors are persuasive that this was an element in “taper tantrum”. •

Implications of the Report for Monetary Policy Choices The mechanism in the MPR implies that: • Easing monetary policy increases later risk of rapid tightening in fin. mkt. • conditions. — Easing policy lowers current risk premium. — But — eventually — policy and risk premium have to normalize. — Lowering risk premium risks a rapid future increase in risk premium. How should monetary policymakers take this risk into account? •

Using the Mean-Variance Framework The mean-variance framework provides a useful policy guide. • Key question: How does the increased financial market risk map into • macroeconomic risk? Specifically: How much does  () increase because of the increased • risk of rapid tightening in financial market conditions? More simply, given accommodation : • — What is the probability  of a rapid tightening in fin. mkt. conditions? — What is the impact ∆ on  of that change?

Information about ∆: The 2013 Experience Financial market conditions tightened rapidly from May to August. • — Mortgage rates and 10-year yields rose by over 1 percentage point. Arguably: This large increase in yields only happened because monetary • policy (QE3) had lowered yields so much. Question: Was 2013:H2 GDP lower because financial market condi- • tions tightened so fast? And if GDP was lower, by how much? •

CONCLUSIONS

Financial Stability Framework: What We Need To Know Mean-variance framework implies that policymakers need to assess: •  ( )  (  ) 0 | − | Possibly could simplify this problem to gauging: • 2 [() ( )]∆ 0 −

Monetary Policy Report and the Challenges Ahead The MPR suggests that these assessments are not easy. • Financial instability may not be associated with usual suspects: • — Leverage, capital, liquidity, etc., etc. Also: The rate of change (not just level) of financial market conditions • could affect macro outcomes. There is considerable need for new theory and empirics.