Economics at your fingertips  

A Frequency-Domain Approach to Dynamic Macroeconomic Models

Fei Tan ()

MPRA Paper from University Library of Munich, Germany

Abstract: This article is concerned with frequency-domain analysis of dynamic linear models under the hypothesis of rational expectations. We develop a unified framework for conveniently solving and estimating these models. Unlike existing strategies, our starting point is to obtain the model solution entirely in the frequency domain. This solution method is applicable to a wide class of models and permits straightforward construction of the spectral density for performing likelihood-based inference. To cope with potential model uncertainty, we also generalize the well-known spectral decomposition of the Gaussian likelihood function to a composite version implied by several competing models. Taken together, these techniques yield fresh insights into the model’s theoretical and empirical implications beyond what conventional time-domain approaches can offer. We illustrate the proposed framework using a prototypical new Keynesian model with fiscal details and two distinct monetary-fiscal policy regimes. The model is simple enough to deliver an analytical solution that makes the policy effects transparent under each regime, yet still able to shed light on the empirical interactions between U.S. monetary and fiscal policies along different frequencies.

Keywords: solution method; analytic function; Bayesian inference; spectral density; monetary and fiscal policy (search for similar items in EconPapers)
JEL-codes: C32 C51 C52 C65 E63 H63 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-mac and nep-ore
Date: 2018-10-20
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().

Page updated 2019-03-31
Handle: RePEc:pra:mprapa:90487