A Generalized Approach to Indeterminacy in Linear Rational Expectations Models

57 Pages Posted: 10 Jul 2017

See all articles by Francesco Bianchi

Francesco Bianchi

Duke University

Giovanni Nicolò

Board of Governors of the Federal Reserve System

Multiple version iconThere are 3 versions of this paper

Date Written: July 2017

Abstract

We propose a novel approach to deal with the problem of indeterminacy in Linear Rational Expectations models. The method consists of augmenting the original model with a set of auxiliary exogenous equations that are used to provide the adequate number of explosive roots in presence of indeterminacy. The solution in this expanded state space, if it exists, is always determinate, and is identical to the indeterminate solution of the original model. The proposed approach accommodates determinacy and any degree of indeterminacy, and it can be implemented even when the boundaries of the determinacy region are unknown. Thus, the researcher can estimate the model by using standard packages without restricting the estimates to a certain area of the parameter space. We apply our method to simulated and actual data from a prototypical New-Keynesian model for both regions of the parameter space. We show that our method successfully recovers the true parameter values independent of the initial values.

Keywords: Bayesian methods., General Equilibrium, Indeterminacy, Solution method

JEL Classification: C19, C51, C62, C63

Suggested Citation

Bianchi, Francesco and Nicolò, Giovanni, A Generalized Approach to Indeterminacy in Linear Rational Expectations Models (July 2017). CEPR Discussion Paper No. DP12130. Available at SSRN: https://ssrn.com/abstract=2999659

Francesco Bianchi (Contact Author)

Duke University ( email )

100 Fuqua Drive
Durham, NC 27708-0204
United States

Giovanni Nicolò

Board of Governors of the Federal Reserve System ( email )

20th Street and Constitution Avenue NW
Washington, DC 20551
United States

Register to save articles to
your library

Register

Paper statistics

Downloads
0
Abstract Views
75
PlumX Metrics