Author

Shawn Osell

Publication Date

2017

Document Type

Dissertation/Thesis

First Advisor

Ryu, Duchwan

Degree Name

M.S. (Master of Science)

Department

Department of Statistics

LCSH

Statistics||Economics

Abstract

Dynamic Stochastic General Equilibrium models (DSGE) are the workhorse of macroeconomic theory. In this monograph, we estimate the parameters of a DSGE model that reflect specific assumptions that macroeonomists make about certain behaviors through a hypothetical economy. After building a DSGE model, we then apply Bayesian statistical methods to estimate the parameters of the model. The Kalman Filter and Markov Chain Monte Carlo (MCMC) methods are utilized to approximate a linear, Gaussian estimation of the model's parameters. Then several non-linear applications, known as Sequential Monte Carlo (SMC) methods, are reviewed and applied to the quadratic DSGE model. SMC applications are considered better estimates of parameters, especially when the data is non-linear, or when the data contains significant outliers.

Comments

Advisors: Duchwan Ryu.||Committee members: Nader Ebrahimi; Alan Polansky.||Includes bibliographical references.

Extent

iii, 50 pages

Language

eng

Publisher

Northern Illinois University

Rights Statement

In Copyright

Rights Statement 2

NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.

Media Type

Text

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