Monetary Policy Rules Under Uncertainty: Empirical Evidence, Adaptive Learning, and Robust Control

Zhang, Wenlang; Semmler, Willi

doi:10.1017/s1365100505040332

Cited by 5 publications

(3 citation statements)

References 64 publications

(163 reference statements)

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“…First, our findings are relevant to recent attempts to study monetary policy preferences based on individual voting information from monetary policy committees. 3 Belden (1989), Havrilesky and Gildea (1991), Chappell et al (2005), Meade (2005), Zhang and Semmler (2005), Gerlach-Kristen (2008, Riboni and Ruge-Murcia (2008), and Besley et al (2008) use data on the voting behavior of members of either the FOMC or the Bank of England's Monetary Policy Committee to uncover policy preferences. Ruge-Murcia (2003) analyzes whether central bankers' preferences are asymmetric around an inflation target and reports asymmetric preference parameters for Canada, Sweden, and the United Kingdom.…”

Section: Introductionmentioning

confidence: 99%

Using Forecasts to Uncover the Loss Function of Federal Open Market Committee Members

2016

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We revisit the sources of the bias in Federal Reserve forecasts and assess whether a precautionary motive can explain the forecast bias. In contrast to the existing literature, we use forecasts submitted by individual Federal Open Market Committee (FOMC) members to uncover members' implicit loss function. Our key finding is that the loss function of FOMC members is asymmetric: FOMC members incur a higher loss when they underpredict (overpredict) inflation and unemployment (nominal and real growth) as compared to their making an overprediction (underprediction) of similar size. We also find that an asymmetric loss function, in some cases, weakens evidence against forecast rationality, though results depend on the variable being projected and the subgroup of FOMC members being studied. Furthermore, we add to the recent controversy on the relative quality of FOMC forecasts compared to staff forecasts. Our results suggest that differences in predictive ability could indeed stem from differences in preferences.

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Section: Introductionmentioning

confidence: 99%

Using Forecasts to Uncover the Loss Function of Federal Open Market Committee Members

2016

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“…This distinction has relevant implications for the behavior of economic agents, and, therefore, for economic theory in general. That is why a rapidly growing literature on ambiguity aversion is emerging including, among others, macroeconomic topics such as business cycles and monetary policy (Hansen et al 1999;Cagetti et al 2002;Zhang and Semmler 2005;Ulrich 2010;Ilut and Schneider 2012), game theory topics (e.g. Eichberger and Kelsey 2011) and finance topics including optimal portfolio choice (e.g.…”

Section: Introductionmentioning

confidence: 99%

The price of risk and ambiguity in an intertemporal general equilibrium model of asset prices

Faria

Correia‐da‐Silva²

2012

Ann Finance

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We consider a version of the intertemporal general equilibrium model of Cox et al. (Econometrica 53:363-384, 1985) with a single production process and two correlated state variables. It is assumed that only one of them, Y 2 , has shocks correlated with those of the economy's output rate and, simultaneously, that the representative agent is ambiguous about its stochastic process. This implies that changes in Y 2 should be hedged and its uncertainty priced, with this price containing risk and ambiguity components. Ambiguity impacts asset pricing through two channels: the price of uncertainty associated with the ambiguous state variable, Y 2 , and the interest rate. With ambiguity, the equilibrium price of uncertainty associated with Y 2 and the equilibrium interest rate can increase or decrease, depending on: (i) the correlations between the shocks in Y 2 and those in the output rate and in the other state variable; (ii) the diffusion functions of the stochastic processes for Y 2 and for the output rate; and (iii) the gradient of the value function with respect to Y 2 . As applications of our generic setting, we deduct the model of Longstaff and Schwartz (J Financ 47:1259(J Financ 47: -1282(J Financ 47: , 1992) for interest-rate-sensitive contingent claim pricing and the variance-risk price specification in the option pricing model of Heston (Rev Financ Stud 6:327-343, 1993). Additionally, it is obtained a variance-uncertainty price specification that can be used to obtain a closed-form solution for option pricing with ambiguity about stochastic variance.

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“…In this paper we extend the standard model by introducing nonlinearity into the Phillips curve. As the linear Phillips curve seems to be at odds with empirical evidence and basic economic intuition, a similar procedure has already been undertaken in a series of papers over the last few years, e.g., Schaling (1999), Semmler and Zhang (2004), Zhang and Semmler (2003), Nobay and Peel (2000), Tambakis (1999), and Dolado et al (2004). However, these papers were mainly concerned with analyzing the problem of inflation bias, deriving an interest rate rule which is nonlinear.…”

Section: Introductionmentioning

confidence: 99%

Chaotic dynamics in optimal monetary policy

Gomes

Mendes

et al. 2007

Eur. Phys. J. B

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There is by now a large consensus in modern monetary policy. This consensus has been built upon a dynamic general equilibrium model of optimal monetary policy as developed by, e.g., Goodfriend and King (1997), Clarida et al. (1999), Svensson (1999) andWoodford (2003). In this paper we extend the standard optimal monetary policy model by introducing nonlinearity into the Phillips curve. Under the specific form of nonlinearity proposed in our paper (which allows for convexity and concavity and secures closed form solutions), we show that the introduction of a nonlinear Phillips curve into the structure of the standard model in a discrete time and deterministic framework produces radical changes to the major conclusions regarding stability and the efficiency of monetary policy. We emphasize the following main results: (i) instead of a unique fixed point we end up with multiple equilibria; (ii) instead of saddle-path stability, for different sets of parameter values we may have saddle stability, totally unstable equilibria and chaotic attractors; (iii) for certain degrees of convexity and/or concavity of the Phillips curve, where endogenous fluctuations arise, one is able to encounter various results that seem intuitively correct. Firstly, when the Central Bank pays attention essentially to inflation targeting, the inflation rate has a lower mean and is less volatile; secondly, when the degree of price stickiness is high, the inflation rate displays a larger mean and higher volatility (but this is sensitive to the values given to the parameters of the model); and thirdly, the higher the target value of the output gap chosen by the Central Bank, the higher is the inflation rate and its volatility.

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Monetary Policy Rules Under Uncertainty: Empirical Evidence, Adaptive Learning, and Robust Control

Cited by 5 publications

References 64 publications

Using Forecasts to Uncover the Loss Function of Federal Open Market Committee Members

Using Forecasts to Uncover the Loss Function of Federal Open Market Committee Members

The price of risk and ambiguity in an intertemporal general equilibrium model of asset prices

Chaotic dynamics in optimal monetary policy

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