Structural Time Series Models for Business Cycle Analysis

Tommaso Proietti

MPRA Paper from University Library of Munich, Germany

Abstract: The chapter deals with parametric models for the measurement of the business cycle in economic time series. It presents univariate methods based on parametric trend{cycle decom- positions and multivariate models featuring a Phillips type relationship between the output gap and inflation and the estimation of the gap using mixed frequency data. We finally address the issue of assessing the accuracy of the output gap estimates.

Keywords: State; Space; Models.; Kalman; Filter; and; Smoother.; Bayesian; Estimation (search for similar items in EconPapers)
JEL-codes: C22 C32 E32 (search for similar items in EconPapers)
Date: 2008-01-20
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Related works:
Chapter: Structural Time Series Models for Business Cycle Analysis (2009)
Working Paper: Structural Time Series Models for Business Cycle Analysis (2008)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:6854

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