Discussion of

“Modeling Model Uncertainty” by

Alexei Onatski and Noah Williams Ulf S¨oderstr¨om Sveriges Riksbank June 2002

Ulf S¨ oderstr¨ om

Discussion of Onatski and Williams

Purpose of paper • Estimate amount of model uncertainty using Rudebusch and Svensson (1999) model • Evaluate optimal robust Taylor-type rules (MinMax) • Two approaches to modeling uncertainty: 1. Model Error Modeling (MEM): full model 2. Set Membership Identification (SM): Phillips curve only More general than traditional robust control theory (Hansen and Sargent, 2001) • Four types of uncertainty simultaneously: 1. Shocks 2. Parameters and specification 3. Choice of reference model 4. Data

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Discussion of Onatski and Williams

Main result: “Robust” policy rules are not robust 1. Sensitive to specification of uncertainty and modeling technique 2. Estimated uncertainty ⇒ infinite loss in worst case model Scale down uncertainty to obtain sensible policy recommendations 3. Rules more or less aggressive than without uncertainty: • All frequencies: (slightly) more aggressive • Business cycle frequencies: less aggressive

Conclusion • Model and calibration/estimation of uncertainty crucial

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Discussion 1. Stability of Taylor rule 2. Aggressiveness of robust rules 3. Forward-looking behavior 4. Minor comments

Discussion of Onatski and Williams

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Discussion of Onatski and Williams

1 Why is the Taylor rule not robust? • Taylor rule viewed as robust in this class of models (cf. Taylor, 1999) • Simple rule too restrictive? Optimal rules more robust? • How large set of models is allowed? – Positive IS slope? – Brainard: Corr( instrument,shock )  0: move in “wrong” direction Statistical vs “economic” significance • Bounds on loss function value less intuitive • Nice discussion in Section 2: Reasonable Taylor rule destabilizing in reasonable model Similar examples in Sections 3 and 4?

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Discussion of Onatski and Williams

2 Are robust rules more or less aggressive? • MEM: Slightly (?) more aggressive at all frequencies less aggressive at BC frequencies • Brainard intuition attractive: – more uncertainty: do less – extreme uncertainty: do nothing But many exceptions: – Covariances (Brainard, 1967) – Inflation dynamics (Craine, 1979; S¨oderstr¨om, 2002); Not true here – Interest rate smoothing? • Taylor rule vs. fully optimal rule? – Is fully optimal rule more or less aggressive?

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Parameter uncertainty in RS model

Discussion of Onatski and Williams

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Parameter uncertainty with interest rate smoothing

Discussion of Onatski and Williams

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Optimal policy rules and robustness

Discussion of Onatski and Williams

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Discussion of Onatski and Williams

3 Forward-looking behavior • RS model reduced form? (not invariant to policy rule) • Strength of traditional RC: can handle forward-looking models • Estimation and analysis more difficult? Methods not suitable? • Rudebusch (2001): generalization with forward-looking elements

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Robustness and forward-looking behavior

Discussion of Onatski and Williams

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Discussion of Onatski and Williams

4 Minor issue • Technical, not easily digested – Difficult issues – New methods • More intuition and examples would be helpful (cf. Section 2)

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Final remarks • Very nice and interesting paper! New methods for analyzing uncertainty. • Very important issues! • Policy conclusions? – Formal models of little practical help? – Warning: Commitment to simple rule dangerous, reasonable rule may be destabilizing – Case for more “discretion” in monetary policy? – Monetary policy as much an art as a science. . .

Discussion of Onatski and Williams

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Discussion of Onatski and Williams

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References Brainard, William, “Uncertainty and the effectiveness of policy,” American Economic Review 57 (2), 411–425, May 1967. Craine, Roger, “Optimal monetary policy with uncertainty,” Journal of Economic Dynamics and Control 1 (1), 59–83, February 1979. Hansen, Lars Peter and Thomas J. Sargent, Robust Control and Filtering for Macroeconomics, book manuscript, Stanford University, April 2001. Rudebusch, Glenn D. and Lars E. O. Svensson, “Policy rules for inflation targeting,” in Taylor, John B. (ed.), Monetary Policy Rules, Chicago University Press, 1999. Rudebusch, Glenn D., “Term structure evidence on interest rate smoothing and monetary policy inertia,” Working Paper No. 2001-02, Federal Reserve Bank of San Francisco, January 2001. Forthcoming, Journal of Monetary Economics. S¨oderstr¨om, Ulf, “Monetary policy with uncertain parameters,” Scandinavian Journal of Economics 104 (1), 125–145, March 2002. Taylor, John B., Monetary Policy Rules, Chicago University Press, 1999.

Modeling Model Uncertainty

Business cycle frequencies: less aggressive ... Taylor rule viewed as robust in this class of models (cf. Taylor, 1999) ... Brainard, William, “Uncertainty and the effectiveness of policy,” American Economic Review 57 (2), 411–425, May 1967.

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