Trend-Cycle Decomposition and Forecasting Using Bayesian Multivariate Unobserved Components

Mohammad Jahan-Parvar, Charles Knipp and Pawel J. Szerszen
Additional contact information
Pawel J. Szerszen: https://www.federalreserve.gov/econres/pawel-j-szerszen.htm

No 2024-100, Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.)

Abstract: We propose a generalized multivariate unobserved components model to decompose macroeconomic data into trend and cyclical components. We then forecast the series using Bayesian methods. We document that a fully Bayesian estimation, that accounts for state and parameter uncertainty, consistently dominates out-of-sample forecasts produced by alternative multivariate and univariate models. In addition, allowing for stochastic volatility components in variables improves forecasts. To address data limitations, we exploit cross-sectional information, use the commonalities across variables, and account for both parameter and state uncertainty. Finally, we find that an optimally pooled univariate model outperforms individual univariate specifications, andperforms generally closer to the benchmark model.

Keywords: Bayesian estimation; Maximum likelihood estimation; Online forecasting; Out-of-sample forecasting; Parameter uncertainty; Sequential Monte Carlo methods; Trend-cycle decomposition (search for similar items in EconPapers)
JEL-codes: C11 C22 C32 C53 (search for similar items in EconPapers)
Pages: 28 p.
Date: 2024-12-30
New Economics Papers: this item is included in nep-dcm, nep-ecm, nep-ets and nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.federalreserve.gov/econres/feds/files/2024100pap.pdf (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: https://EconPapers.repec.org/RePEc:fip:fedgfe:2024-100

DOI: 10.17016/FEDS.2024.100

Access Statistics for this paper

More papers in Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.) Contact information at EDIRC.
Bibliographic data for series maintained by Ryan Wolfslayer ; Keisha Fournillier ().