An Exploration of Trend-Cycle Decomposition Methodologies in Simulated Data / Robert J. Hodrick.

Format:

Book

Author/Creator:

Hodrick, Robert J.

Contributor:

National Bureau of Economic Research.

Series:

Working Paper Series (National Bureau of Economic Research) no. w26750.

NBER working paper series no. w26750

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2020.

Summary:

This paper uses simulations to explore the properties of the HP filter of Hodrick and Prescott (1997), the BK filter of Baxter and King (1999), and the H filter of Hamilton (2018) that are designed to decompose a univariate time series into trend and cyclical components. Each simulated time series approximates the natural logarithms of U.S. Real GDP, and they are a random walk, an ARIMA model, two unobserved components models, and models with slowly changing nonstationary stochastic trends and definitive cyclical components. In basic time series, the H filter dominates the HP and BK filters in more closely characterizing the underlying framework, but in more complex models, the reverse is true.

Notes:

Print version record

February 2020.