Robert J. Tetlow

Errors in the Measurement of the Output Gap and the Design of Monetary Policy

Abstract We exploit data on historical revisions to real-time estimates of the output gap to examine the implications of measurement error for the design of monetary policy, using the Federal Reserve’s model of the U.S. economy, FRB/US. Measurement error brings about a substantial deterioration in economic performance, although the problem can be mitigated somewhat by reducing the coefficient on the output gap in policy rules. We also show that it is usually optimal to place some weight on the level of the output gap in the conduct of policy, but under extreme conditions it may be preferable to focus on output growth.

Robust monetary policy with misspecified models: Does model uncertainty always call for attenuated policy?

We explore Knightian model uncertainty as an explanation for the observed excess persistence and attenuation in estimated interest-rate reaction functions for the United States, relative to what optimal feedback rules would suggest. Two types of uncertainty are identified: (i) unstructured model uncertainty captured in additive shock error processes that result from omitted-variable misspecifications, and (ii) structured model uncertainty, where one or more parameters are posited as the source of misspecification. We estimate a forward-looking model of the U.S. economy, and find that rules for this model that are robust against unstructured model uncertainty, or against one-time parametric shifts, are more aggressive than the optimal linear quadratic rule. However, policies designed to protect the economy against the worst-case consequences of misspecified dynamics are less aggressive and good approximations of the estimated rule. Some drawbacks of robust policies are discussed. Finally, a connection between the degree of structure an authority ascribes to the uncertainty it faces and the extent and likelihood of policy attenuation in response to that uncertainty is explored.

Financial Stress and Economic Dynamics: The Transmission of Crises

The recent financial crisis and the associated decline in economic activity have raised some important questions about economic activity and its links to the financial sector. This paper introduces an index of financial stress - an index that was used in real time by the staff of the Federal Reserve Board to monitor the crisis - and shows how stress interacts with real activity, inflation and monetary policy. We define what we call a stress event - a period affected by stress in both shock variances and model coefficients - and describe how financial stress affects macroeconomic dynamics. We also examine what constitutes a useful and credible measure of stress and the role of monetary policy. We address these questions using a richly parameterized Markov-switching VAR model, estimated using Bayesian methods. Our results show that allowing for time variation is important: the constant-parameter, constant-shock-variance model is a poor characterization of the data. We find that periods of high stress coefficients in general, and stress events in particular, line up well with financial events in recent U.S. history. We find that a shift to a stress event is highly detrimental to the outlook for the real economy, and that conventional monetary policy is relatively weak during such periods. Finally, we argue that our findings have implications for DSGE modeling of financial events insofar as researchers wish to capture phenomena more consequential than garden-variety business cycle fluctuations, pointing away from linearized DSGE models toward either MS-DSGE models or fully nonlinear models solved with global methods.

Real-Time Model Uncertainty in the United States: 'Robust' Policies Put to the Test

I study forty-six vintages of FRB/US, the principal macro model used by the Federal Reserve, as measures of real-time model uncertainty and examine the robustness of commonly applied, simple monetary policy rules. Model uncertainty turns out to be a substantial problem: key model properties differ in important ways across model vintages, as do the optimized parameterizations of candidate rules. Among the simple monetary policy rules considered are rules that eschew feedback on the output gap, rules that target nominal income growth, and rules that allow for time variation in the equilibrium real interest rate. Many rules that previous research has shown to be robust in artificial economies would have failed to provide adequate stabilization in the real-time, realworld environment seen by the Federal Reserve staff. I identify certain policy rules that would have performed relatively well, and characterize their key features to draw more general lessons about the design of monetary policy under model uncertainty.

Optimal Control of Large, Forward-Looking Models: Efficient Solutions and Two Examples

An optimal control tool is described that is particularly useful for computing rules of large-scale models where users might otherwise have difficulty determining the state vector a priori and where the inversion of large, sparse matrices is involved. A small-scale demonstration is presented, as are data on performance with the Board of Governors large-scale rational expectations macroeconometric model, FRB/US.

Melting Down: Systemic Financial Instability and the Macroeconomy

We integrate systemic financial instability in an empirical macroeconomic model for the euro area. We find that at times of widespread financial instability the macroeconomy functions fundamentally differently from tranquil times. We employ a richly specified Markov-Switching Vectorautoregression model to capture the dynamic relationships between a set of core macroeconomic variables and a novel indicator of systemic financial stress. Both the parameters that capture the transmission of shocks through the economy and the variances of the shocks change at times of high stress in the financial system. In particular, the negative output effects of sizeable increases in financial stress are much larger after such a regime change than during tranquil times. Macroprudential and monetary policy makers are well advised to take these nonlinearities into account.