Calibrated models of the business cycle typically assume a certain frequency at which economic agents take decisions. In this paper I show that the local stability properties of dynamic stochastic general equilibrium macro models may depend on the length of a period in the model economy. This...

Abstract: The partial information rational expectations solution to a general linear multivariate expectational macro-model is found when agents are uncertain about the true values of the model’s parameters. Necessary and sufficient conditions for convergence to the full information rational...

We derive necessary and suffcient conditions for simple monetary policy rules that guarantee equilibrium determinacy in the New Keynesian monetary model. Our modeling framework is derived from a fully specified optimization model that is still amenable to analytical characterisation. The...

This paper considers a prototypical monetary business cycle model for the U.S. economy, in which the equilibrium is undetermined if monetary policy is ‘inactive? In previous multivariate studies it has been common practice to restrict parameter estimates to values for which the equilibrium is...

Earlier studies of the seigniorage inflation model have found that the high-inflation steady state is not stable under adaptive learning. We reconsider this issue and analyze the full set of solutions for the linearized model. Our main focus is on stationary hyperinflationary paths near the...

The analysis of this paper examines the uniqueness of equilibria in a broad class of dynamic monetary models that satisfy Lucas's (1972) natural rate hypothesis (NRH). For a given demand specification, the resulting bounds for determinacy on monetary policy's interest rate rule are the same for...

We propose a novel approach to deal with the problem of indeterminacy in linear rational expectations models. The method consists of augmenting the original state space with a set of auxiliary exogenous equations to provide the adequate number of explosive roots in presence of indeterminacy. The...

We examine the nonlinear model Xt = Et F(xt+1) . Markov SSEs exist near an indeterminate steady state, X = F(X), provided F´(X)> 1. We show that there exist Markov SSEs that are E-stable, and therefore locally stable under adaptive learning, if F´(X)< -1.

We consider the stability under adaptive learning of the complete set of solutions to the model when . In addition to the fundamentals solution, the literature describes both finite-state Markov sunspot solutions, satisfying a resonant frequency condition, and autoregressive solutions depending...

We propose a novel approach to deal with the problem of indeterminacy in Linear Rational Expectations models. The method consists of augmenting the original state space with a set of auxiliary exogenous equations to provide the adequate number of explosive roots in presence of indeterminacy. The...