Steps toward identifying central bank policy preferences

This paper takes the parameters in central bank loss functions as fundamental preferences to be estimated from the data. It is these preferences (along with target values) that define the policy regime in operation and that potentially change with senior central bank appointments. Optimizing central banks apply policy rules whose feedback coefficients are functions of its preferences. Consequently, under some conditions, it is possible to back out estimates of the preference parameters from estimated policy reaction functions. This paper establishes conditions under which a policy regime can be identified and illustrates these conditions using a number of popular models.Monetary policy ; Banks and banking, Central

Consumption-habits in a new Keynesian business cycle model

Consumption-habits have become an integral component in new Keynesian models. However, consumption-habits can be modeled in a host of different ways and this diversity is reflected in the literature. I examine whether different approaches to modeling consumption habits have important implications for business cycle behavior. Using a standard new Keynesian business cycle model, I show that, to a first-order log-approximation, the consumption Euler equation associated with the additive functional form for habit formation encompasses the multiplicative function form. Empirically, I show that whether consumption habits are internal or external has little effect on the model's business cycle characteristics.Business cycles

Model uncertainty and monetary policy

Model uncertainty has the potential to change importantly how monetary policy should be conducted, making it an issue that central banks cannot ignore. In this paper, I use a standard new Keynesian business cycle model to analyze the behavior of a central bank that conducts policy with discretion while fearing that its model is misspecified. I begin by showing how to solve linear-quadratic robust Markov-perfect Stackelberg problems where the leader fears that private agents form expectations using the misspecified model. Next, I exploit the connection between robust control and uncertainty aversion to present and interpret my results in terms of the distorted beliefs held by the central bank, households, and firms. My main results are as follows. First, the central bank's pessimism leads it to forecast future outcomes using an expectations operator that, relative to rational expectations, assigns greater probability to extreme inflation and consumption outcomes. Second, the central bank's skepticism about its model causes it to move forcefully to stabilize inflation following shocks. Finally, even in the absence of misspecification, policy loss can be improved if the central bank implements a robust policy.Monetary policy

Model Uncertainty and Monetary Policy

Model uncertainty has the potential to change importantly how monetary policy should be conducted, making it an issue that central banks cannot ignore. In this paper, I use a standard new Keynesian business cycle model to analyze the behavior of a central bank that conducts policy with discretion while fearing that its model is misspecified. My main results are as follows. First, policy performance can be improved if the discretionary central bank implements a robust policy. This important result is obtained because the central bank's desire for robustness directs it to assertively stabilize inflation, thereby mitigating the stabilization bias associated with discretionary policymaking. In effect, a fear of model uncertainty can act similarly to a commitment mechanism. Second, exploiting the connection between robust control and uncertainty aversion, I show that the central bank's fear of model misspecification leads it to forecast future outcomes under the belief that inflation (in particular) will be persistent and have large unconditional variance, raising the probability of extreme outcomes. Private agents, however, anticipating the policy response, make decisions under the belief that inflation will be more closely stabilized, that is, more tightly distributed, than under rational expectations. Third, as a technical contribution, I show how to solve an important class of linear-quadratic robust Markov-perfect Stackelberg problems.Model uncertainty, robustness, uncertainty aversion, time-consistency.

Solving for optimal simple rules in rational expectations models

This paper presents techniques to solve for optimal simple monetary policy rules in rational expectations models, assuming discretion. The techniques described are notable for the flexibility they provide over the structure of the policy rule being solved for. Specifically, not all state variables need enter the policy rule allowing rules optimal conditional on a given information set to be easily constructed. The algorithms described are compared to related solution methods, and applied to the model in Clarida, Gali, and Gertler (1999).Econometric models ; Rational expectations (Economic theory)

Timeless perspective policymaking: When is discretion superior?

In this paper I show that discretionary policymaking can be superior to timeless perspective policymaking and identify model features that make this outcome more likely. Developing a measure of conditional loss that treats the auxiliary state variables that characterize the timeless perspective equilibrium appropriately, I use a New Keynesian DSGE model to show that discretion can dominate timeless perspective policymaking when the Phillips curve is relatively flat, due, perhaps, to firm-specific capital (or labor) and/or Kimball (1995) aggregation in combination with nominal price rigidity. These results suggest that studies applying the timeless perspective might also usefully compare its performance to discretion, paying careful attention to how policy performance is evaluated.Monetary policy

Physical Fitness of Physical Therapy Students

Physical fitness norms do not exist for physical therapists or physical therapy students. This lack, in part, reflects the complexity of physical fitness and the scarcity of data reported on physical fitness norms of other populations. This report describes the methods used and the results obtained for 16 physical fitness factors of 98 female and 13 male physical therapy upperclassmen and discusses the implications of physical fitness in the practice of physical therapy. Means, standard deviations, ranges, and percentile rankings are given by sex for each of the 16 fitness factors. The purpose of this study was to begin to establish physical fitness norms. As physical fitness norms are established, it will be possible to determine how norms of physical therapists and physical therapy students compare with established values