Monetary policy rules, asset prices and adaptive learning

2013 ◽  
Vol 9 (3) ◽  
pp. 251-258 ◽  
Author(s):  
Vicente da Gama Machado
2018 ◽  
Vol 22 (8) ◽  
pp. 2107-2140 ◽  
Author(s):  
Emanuel Gasteiger

Yes, indeed; at least for macroeconomic policy interaction. We examine a Neo-Classical economy and provide the conditions for policy arrangements to successfully stabilize the economy when agents have either rational or adaptive expectations. For a contemporaneous-data monetary policy rule, the monetarist solution is unique and stationary under a passive fiscal/active monetary policy regime if monetary policy appropriately incorporates expectational heterogeneity. In contrast, the active fiscal/passive monetary policy regime's fiscalist solution is prone to explosiveness due to empirically plausible expectational heterogeneity. Nevertheless, this can be a well-defined, rather orthodox equilibrium. For operational monetary policy rules, only the results for the fiscalist solution prevail. Moreover, our results are plausible from an adaptive learning viewpoint.


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.


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