A Generalized Approach to Indeterminacy in Linear Rational Expectations Models

60 Pages Posted: 25 Jul 2019 Last revised: 21 Oct 2019

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: 2019-05

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 state space with a set of auxiliary exogenous equations 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 using standard packages without restricting the estimates to the determinacy region. We apply our method to estimate the New-Keynesian model with rational bubbles by Galí (2017) over the period 1982:Q4 until 2007:Q3. We find that the data support the presence of two degrees of indeterminacy, implying that the central bank was not reacting strongly enough to the bubble component.

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

JEL Classification: C19, C63, C51, C62

Suggested Citation

Bianchi, Francesco and Nicolò, Giovanni, A Generalized Approach to Indeterminacy in Linear Rational Expectations Models (2019-05). FEDS Working Paper No. 2019-033. Available at SSRN: https://ssrn.com/abstract=3423243 or http://dx.doi.org/10.17016/FEDS.2019.033

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
12
Abstract Views
54
PlumX Metrics