On December 12, 2019, Fed in Print will introduce its new platform for discovering content. Please direct your questions to Anna Oates

Home About Latest Browse RSS Advanced Search

Board of Governors of the Federal Reserve System (US)
Finance and Economics Discussion Series
A Generalized Approach to Indeterminacy in Linear Rational Expectations Models
Francesco Bianchi
Giovanni Nicolo
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 GalĂ­ (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.


Download Full text
Cite this item
Francesco Bianchi & Giovanni Nicolo, A Generalized Approach to Indeterminacy in Linear Rational Expectations Models, Board of Governors of the Federal Reserve System (US), Finance and Economics Discussion Series 2019-033, May 2019.
More from this series
JEL Classification:
Subject headings:
Keywords: Bayesian methods ; General Equilibrium ; Indeterminacy ; Solution method
DOI: 10.17016/FEDS.2019.033
For corrections, contact Ryan Wolfslayer ()
Fed-in-Print is the central catalog of publications within the Federal Reserve System. It is managed and hosted by the Economic Research Division, Federal Reserve Bank of St. Louis.

Privacy Legal