The Stagnation Regime of the New Keynesian Model and Current US Policy

In Evans, Guse, and Honkapohja (2008) the intended steady state is locally but not globally stable under adaptive learning, and unstable deflationary paths can arise after large pessimistic shocks to expectations. In the current paper a modified model is presented that includes a locally stable stagnation regime as a possible outcome arising from large expectation shocks. Policy implications are examined. Sufficiently large temporary increases in government spending can dislodge the economy from the stagnation regime and restore the natural stabilizing dynamics. More specific policy proposals are presented and discussed.Stagnation, fiscal and monetary policy, deflation trap.

Monetary and Fiscal Policy under Learning in the Presence of a Liquidity Trap

This paper reports on the findings of Evans, Guse, and Honkapohja (2007) concerning the global economic dynamics under learning in a New Keynesian model in which the interest rate rule is subject to the zero lower bound. Under normal monetary and fiscal policy, the intended steady state is locally but not globally stable. Large pessimistic shocks to expectations can lead to deflationary spirals with falling prices and falling output. To avoid this outcome, we recommend augmenting normal policies with inflation threshold policies: if under normal policies inflation would fall below a suitably chosen threshold, these policies should be replaced by aggressive monetary and fiscal policies that guarantee this lower bound on inflation.Adaptive learning; Monetary policy; Fiscal policy; Zero interest rate lower bound; Indeterminacy

Monetary policy, indeterminacy and learning

The development of tractable forward looking models of monetary policy has lead to an explosion of research on the implications of adopting Taylor-type interest rate rules. Indeterminacies have been found to arise for some specifications of the interest rate rule, raising the possibility of inefficient fluctuations due to the dependence of expectations on extraneous "sunspots ". Separately, recent work by a number of authors has shown that sunspot equilibria previously thought to be unstable under private agent learning can in some cases be stable when the observed sunspot has a suitable time series structure. In this paper we generalize the "common factor "technique, used in this analysis, to examine standard monetary models that combine forward looking expectations and predetermined variables. We consider a variety of specifications that incorporate both lagged and expected inflation in the Phillips Curve, and both expected inflation and inertial elements in the policy rule. We find that some policy rules can indeed lead to learnable sunspot solutions and we investigate the conditions under which this phenomenon arises

Robust learning stability with operational monetary policy rules

We consider the robust stability of a rational expectations equilibrium, which we define as stability under discounted (constant gain) least-squares learning, for a range of gain parameters. We find that for operational forms of policy rules, ie rules that do not depend on contemporaneous values of endogenous aggregate variables, many interest-rate rules do not exhibit robust stability. We consider a variety of interest-rate rules, including instrument rules, optimal reaction functions under discretion or commitment, and rules that approximate optimal policy under commitment. For some reaction functions we allow for an interest-rate stabilization motive in the policy objective. The expectations-based rules proposed in Evans and Honkapohja (2003, 2006) deliver robust learning stability. In contrast, many proposed alternatives become unstable under learning even at small values of the gain parameter.commitment; interest-rate setting; adaptive learning; stability; determinacy

Policy interaction, learning and the fiscal theory of prices

We investigate both the rational explosive inflation paths studied by McCallum (2001) and the classification of fiscal and monetary policies proposed by Leeper (1991) for stability under learning of rational expectations equilibria (REE). Our first result is that the fiscalist REE in the model of McCallum (2001) is not locally stable under learning. By contrast, in the setting of Leeper (1991), different possibilities can obtain. We find, in particular, that there are parameter domains for which the fiscal theory solution – in which fiscal variables affect the price level – can be a stable outcome under learning. For other parameter domains, the monetarist solution is the stable equilibrium.inflation; expectations; fiscal and monetary policy; explosive price paths

Adaptive learning and monetary policy design

We review the recent work on interest rate setting, which emphasizes the desirability of designing policy to ensure stability under private agent learning. Appropriately designed expectations based rules can yield optimal rational expectations equilibria that are both determinate and stable under learning. Some simple instrument rules and approximate targeting rules also have these desirable properties. We take up various complications in implementing optimal policy, including the observability of key variables and the required knowledge of structural parameters. An additional issue that we take up concerns the implications of expectation shocks not arising from transitional learning effects.commitment, interest rate setting, adaptive learning, stability, determinacy, expectations shocks

Expectations, Learning and Monetary Policy: An Overview of Recent Research

Expectations about the future are central for determination of current macroeconomic outcomes and the formulation of monetary policy. Recent literature has explored ways for supplementing the benchmark of rational expectations with explicit models of expectations formation that rely on econometric learning. Some apparently natural policy rules turn out to imply expectational instability of private agents?learning. We use the standard New Keynesian model to illustrate this problem and survey the key results about interest-rate rules that deliver both uniqueness and stability of equilibrium under econometric learning. We then consider some practical concerns such as measurement errors in private expectations, observability of variables and learning of structural parameters required for policy. We also discuss some recent applications including policy design under perpetual learning, estimated models with learning, recurrent hyperinflations, and macroeconomic policy to combat liquidity traps and deflation.Imperfect knowledge, learning, interest-rate setting, fluctuations, stability, determinacy.

Adaptive forecasts, hysteresis, and endogenous fluctuations

This paper considers fluctuations and policy in an economic model with multiple steady states due to a production externality. In the absence of policy changes, the driving forces generating fluctuations are exogenous random productivity shocks. However, because there are multiple steady states, large productivity shocks can shift the economy between high-and low- level equilibria, providing an additional endogenous source of fluctuations. The scope for macroeconomic policy is large since changes in policy can also shift the economy between equilibria. In this setting macroeconomic policy exhibits hysteresis (irreversibilities) and threshold effects and can be used to eliminate endogenous fluctuations.Econometric models ; Business cycles

Expectations, Learning, And Monetary Policy: An Overview Of Recent Research

Expectations about the future are central for determination of current macroeconomic outcomes and the formulation of monetary policy. Recent literature has explored ways for supplementing the benchmark of rational expectations with explicit models of expectations formation that rely on econometric learning. Some apparently natural policy rules turn out to imply expectational instability of private agents’ learning. We use the standard New Keynesian model to illustrate this problem and survey the key results about interest-rate rules that deliver both uniqueness and stability of equilibrium under econometric learning. We then consider some practical concerns such as measurement errors in private expectations, observability of variables and learning of structural parameters required for policy. We also discuss some recent applications including policy design under perpetual learning, estimated models with learning, recurrent hyperinflations, and macroeconomic policy to combat liquidity traps and deflation.

Monetary Policy, Indeterminacy and Learning

The development of tractable forward looking models of monetary policy has lead to an explosion of research on the implications of adopting Taylor-type interest rate rules. Indeterminacies have been found to arise for some specifications of the interest rate rule, raising the possibility of inefficient fluctuations due to the dependence of expectations on extraneous “sunspots ”. Separately, recent work by a number of authors has shown that sunspot equilibria previously thought to be unstable under private agent learning can in some cases be stable when the observed sunspot has a suitable time series structure. In this paper we generalize the “common factor ”technique, used in this analysis, to examine standard monetary models that combine forward looking expectations and predetermined variables. We consider a variety of specifications that incorporate both lagged and expected inflation in the Phillips Curve, and both expected inflation and inertial elements in the policy rule. We find that some policy rules can indeed lead to learnable sunspot solutions and we investigate the conditions under which this phenomenon arises.Monetary Policy, sunspots, expectations, learning, stability