Managing Disinflation under Uncertainty

In this paper we analyze disinflation policy when a central bank has imperfect information about private sector inflation expectations but learns about them from economic outcomes, which are in part the result of the disinflation policy itself. The form of uncertainty is manifested as uncertainty about the effect ofpastdisinflation policy on the current output gap. This differs from other studies on learning and control in a monetary policy context (e.g. Ellison (2006) and Svensson and Williams (2007)) that assume uncertainty about the effects of current policy actions on the economy. We derive the central bank's optimal disinflation strategy under active learning (DOP) and compare it with two limiting cases - certainty equivalence policy (CEP), or passive learning, and a Brainard-style cautionary monetary policy (CP). It turns out that under the DOP inflation stays between the levels implied by the CEP and the CP. A novel result - e.g. unlike Beck and Wieland (2002)| is that this holds irrespective of the initial level of inflation. At high levels of inherited inflation the DOP moves closer to the CEP, at low levels of inherited inflation the DOP resembles the CP.Learning, Inflation Expectations, Disinflation Policy, Separation Principle, Kalman Filter, Optimal Control, Dynamic Programming

Information, heterogeneity and market incompleteness in the stochastic growth model

We provide a microfounded account of imperfect information in the stochastic growth model which dramatically changes the properties of the model. We describe heterogenous households that acquire information about aggregates through their participation in markets. If markets are incomplete, household information will be imperfect. We solve the model taking account of the infinite regress of expectations that this lack of information implies. We derive analytical and numerical results to show that imperfect information can significantly change the properties of the model: under virtually all calibrations the impact response of consumption to a positive aggregate technology shock is negative.imperfect information; higher order expectations; Kalman filter; dynamic general equilibrium

Adaptive Policies for Sequential Sampling under Incomplete Information and a Cost Constraint

We consider the problem of sequential sampling from a finite number of independent statistical populations to maximize the expected infinite horizon average outcome per period, under a constraint that the expected average sampling cost does not exceed an upper bound. The outcome distributions are not known. We construct a class of consistent adaptive policies, under which the average outcome converges with probability 1 to the true value under complete information for all distributions with finite means. We also compare the rate of convergence for various policies in this class using simulation

Optimal Growth and Uncertainty: Learning

We introduce learning in a Brock-Mirman environment and study the effect of risk generated by the planner's econometric activity on optimal consumption and investment. Here, learning introduces two sources of risk about future payoffs: structural uncertainty and uncertainty from the anticipation of learning. The latter renders control and learning nonseparable. We present two sets of results in a learning environment. First, conditions under which the introduction of learning increases or decreases optimal consumption are provided. The effect depends on the strengths and directions of the two sources of risk, which may pull in opposite directions. Second, the effects of changes in the mean and riskiness of the distribution of the signal and initial beliefs on optimal consumption are studied.Optimal Growth, Uncertainty, Learning, Dynamic Programming

Learning About the Term Structure and Optimal Rules for Inflation Targeting

In this paper we incorporate the term structure of interest rates in a standard inflation forecast targeting framework. We find that under flexible inflation targeting and uncertainty in the degree of persistence in the economy, allowing for active learning possibilities has effects on the optimal interest rate rule followed by the central bank. For a wide range of possible initial beliefs about the unknown parameter, the dynamically optimal rule is in general more activist, in the sense of responding aggressively to the state of the economy, than the myopic rule for small to moderate deviations of the state variable from its target. On the other hand, for large deviations, the optimal policy is less activist than the myopic and the certainty equivalence policies.Learning;Rational Expectations;Separation Principle;Term Structure of Interest Rates

Optimal resource extraction under stochastic terms of trade

This paper examines the case where a small open economy owns a stock of exhaustible resources like Chromium, Copper etc. which are not consumed domestically but exported. The resource earnings are used to import consumption goods. We will discuss the optimal production of this resource, when the terms of trade (faced by the country) follows an exogenous given time path that is subject to some stochastic fluctuations. It will come about that uncertainty concerning future values of the terms of trade affects the extraction dynamics for the following reasons. First, if the functions involved in the first-order conditions are nonlinear, the expected future value of these functions differs from a world of certainty. Consequently uncertainty has an impact on the behaviour of resource-exporting- countries. Note that this change in behaviour cannot be captured with certaintyequivalence. Second, if the costs of extraction exceed the gain from the resource use for some time due to stochastic fluctuations, the country can keep the resource in the ground but maintain the option of future extraction when depletion will become profitable again. So uncertainty creates an incentive to slow down production.