When Can Trend-Cycle Decompositions Be Trusted?

34 Pages Posted: 21 Dec 2016

See all articles by Manuel Gonzalez-Astudillo

Manuel Gonzalez-Astudillo

Board of Governors of the Federal Reserve System

John Roberts

Board of Governors of the Federal Reserve System

Date Written: 2016-12-19

Abstract

In this paper, we examine the results of GDP trend-cycle decompositions from the estimation of bivariate unobserved components models that allow for correlated trend and cycle innovations. Three competing variables are considered in the bivariate setup along with GDP: the unemployment rate, the inflation rate, and gross domestic income. We find that the unemployment rate is the best variable to accompany GDP in the bivariate setup to obtain accurate estimates of its trend-cycle correlation coefficient and the cycle. We show that the key feature of unemployment that allows for precise estimates of the cycle of GDP is that its nonstationary component is "small" relative to its cyclical component. Using quarterly GDP and unemployment rate data from 1948:Q1 to 2015:Q4, we obtain the trend-cycle decomposition of GDP and find evidence of correlated trend and cycle components and an estimated cycle that is about 2 percent below its trend at the end of the sample.

Keywords: Unobserved components model, Trend-cycle decomposition, Trend-cycle correlation

JEL Classification: C13, C32, C52

Suggested Citation

Gonzalez-Astudillo, Manuel and Roberts, John, When Can Trend-Cycle Decompositions Be Trusted? (2016-12-19). FEDS Working Paper No. 2016-099. Available at SSRN: https://ssrn.com/abstract=2888331 or http://dx.doi.org/10.17016/FEDS.2016.099

Manuel Gonzalez-Astudillo (Contact Author)

Board of Governors of the Federal Reserve System ( email )

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

John Roberts

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
33
Abstract Views
174
PlumX Metrics