scholarly journals Robust Control and Monetary Policy Delegation

Author(s):  
G. Diana ◽  
M. Sidiropoulos
2002 ◽  
Vol 6 (1) ◽  
pp. 85-110 ◽  
Author(s):  
Alexei Onatski ◽  
James H. Stock

This paper examines monetary policy in a two-equation macroeconomic model when the policymaker recognizes that the model is an approximation and is uncertain about the quality of that approximation. It is argued that the minimax approach of robust control provides a general and tractable alternative to the conventional Bayesian decision theoretic approach. Robust control techniques are used to construct robust monetary policies. In most (but not all) cases, these robust policies are more aggressive than the optimal policies absent model uncertainty. The specific robust policies depend strongly on the formulation of model uncertainty used, and we make some suggestions about which formulation is most relevant for monetary policy applications.


2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Kohei Hasui

AbstractRecent monetary policy studies have shown that the trend productivity growth has non-trivial implications for monetary policy. This paper investigates how trend growth alters the effect of model uncertainty on macroeconomic fluctuations by introducing a robust control problem. We show that an increase in trend growth reduces the effect of the central bank’s model uncertainty and, hence, mitigates the large macroeconomic fluctuations. Moreover, the increase in trend growth contributes to bringing the economy into determinacy regions even if larger model uncertainty exists. These results indicate that trend growth contributes to stabilizing the economy in terms of both variance and determinacy when model uncertainty exists.


2008 ◽  
Vol 12 (S1) ◽  
pp. 126-135 ◽  
Author(s):  
KAI LEITEMO ◽  
ULF SÖDERSTRÖM

We study the effects of model uncertainty in a simple New Keynesian model using robust control techniques. Due to the simple model structure, we are able to find closed-form solutions for the robust control problem, analyzing both instrument rules and targeting rules under different timing assumptions. In all cases but one, an increased preference for robustness makes monetary policy respond more aggressively to cost shocks but leaves the response to demand shocks unchanged. As a consequence, inflation is less volatile and output is more volatile than under the nonrobust policy. Under one particular timing assumption, however, increasing the preference for robustness has no effect on the optimal targeting rule (nor on the economy).


2005 ◽  
Vol 9 (5) ◽  
pp. 651-681 ◽  
Author(s):  
WENLANG ZHANG ◽  
WILLI SEMMLER

We first explore empirical evidence of parameter and shock uncertainties in a state-space model with Markov switching. The evidence indicates that uncertainties in the U.S. economy have been too great to accurately define monetary policy rules. We then explore monetary policy rules under uncertainty with two approaches: the RLS learning algorithm and robust control. The former allows the parameters to be learned for a given model. Yet, as our results of the RLS learning in a framework of optimal control indicate, the state variables do not necessarily converge even in a nonstochastic model. The latter, by permitting uncertainty with respect to model misspecification, allows for a broader framework. Our study on robust control shows that robust optimal monetary policy rules reveal a stronger response to fluctuations in inflation and output than when no uncertainty exists, implying that uncertainty does not necessarily require caution.


2006 ◽  
Author(s):  
Vítor Gaspar ◽  
Otmar Issing ◽  
Oreste Tristani ◽  
David Vestin

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