Results 261 to 270 of about 26,074 (306)

IDENTIFICATION OF UNOBSERVED COMPONENTS MODELS

Journal of Time Series Analysis, 1989
Abstract. Unobserved components ARIMA models are common in time series applications. However, fitting models of this type leads to problems of model identification. In this paper we derive a methodology to check whether a proposed model is identifiable.
Luiz K Hotta
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Unobserved Components Model(s): Output Gaps and Financial Cycles

SSRN Electronic Journal, 2023
The Global Financial Crisis established that policymakers should consider the stage of the financial cycle to better evaluate the cyclical position of the economy when designing monetary policy decisions. If financial variables are omitted from the estimations of the output gap, a common and unobserved indicator of the business cycle, important ...
Guillochon, Justine, Le Roux, Julien
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Unobserved components models in economics and finance

IEEE Control Systems, 2009
State-space methods permit a flexible treatment of unobserved components models. Furthermore, data irregularities such as missing observations are easily handled. For example, irregularly spaced observations can be dealt with since, as discussed in [3, Chap.
Andrew Harvey, Siem Jan Koopman
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An Unobserved Components Model to Forecast Austrian GDP [PDF]

, 2006
This paper deals with forecasting quarterly Austrian GDP growth using monthly conjunctural indicators and state space models. The latter provide an efficient econometric framework to analyse jointly data with different frequencies. Based on a Kalman filter technique we estimate a monthly GDP growth series as an unobserved component using monthly ...
Gerhard Fenz, Martin Spitzer
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Reconciling output gaps: Unobserved components model and Hodrick–Prescott filter [PDF]

Journal of Economic Dynamics and Control, 2017
© 2017 Elsevier B.V. This paper reconciles two widely used trend–cycle decompositions of GDP that give markedly different estimates: the correlated unobserved components model yields output gaps that are small in amplitude, whereas the Hodrick–Prescott ...
Joshua C C Chan
exaly   +4 more sources

Unobserved Components Models

2023
Unobserved components models (UCMs), sometimes referred to as structural time-series models, decompose a time series into its salient time-dependent features. These typically characterize the trending behavior, seasonal variation, and (nonseasonal) cyclical properties of the time series.
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Readings In Unobserved Components Models

2005
Abstract This book presents a collection of readings which give the reader an idea of the nature and scope of unobserved components (UC) models and the methods used to deal with them. It contains four parts, three of which concern recent theoretical developments in classical and Bayesian estimation of linear, nonlinear, and non ...
Harvey, A, PROIETTI, TOMMASO
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An Unobserved Components Model that Yields Business and Medium‐Run Cycles

Journal of Money, Credit and Banking, 2013
We generalize the unobserved components (UC) model to allow the permanent component to have different dynamics than the transitory components when decomposing U.S.
Mark E Wohar
exaly   +1 more source

Bootstrap Prediction in Unobserved Component Models

2010
One advantage of state space models is that they deliver estimates of the unobserved components and predictions of future values of the observed series and their corresponding Prediction Mean Squared Errors (PMSE). However, these PMSE are obtained by running the Kalman filter with the true parameters substituted by consistent estimates and ...
Alejandro F. Rodríguez, Esther Ruiz
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