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Unemployment dynamics: An unobserved components approach [PDF]
, 1998 The study uses a bivariate unobserved components model for output and the unemployment rate in order to examine stylised facts of the cyclical behaviour of unemployment and to estimate the size of persistence. The model is applied to the U.S., Canada, and major European economies.
Rünstler, Gerhard
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Readings In Unobserved Components Models
2005Abstract 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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Short and long memory unobserved components in hydrological time series
Physics and Chemistry of the Earth, 2006 In this paper a semiparametric approach is introduced to decompose an ARFIMA model in the long memory and short memory unobserved components. The procedure is based on the DECOMEL method which produces a statistical decomposition by minimizing the ...
Marcella Corduas, Domenico Piccolo
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Diagnosing unobserved components in self-adaptive systems
Proceedings of the 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, 2014Availability is an increasingly important quality for today's software-based systems and it has been successfully addressed by the use of closed-loop control systems in self-adaptive systems. Probes are inserted into a running system to obtain information and the information is fed to a controller that, through provided interfaces, acts on the system ...
Paulo Casanova +3 more
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Bootstrap Prediction in Unobserved Component Models
2010One 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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Identification of network components in presence of unobserved nodes
2015 54th IEEE Conference on Decision and Control (CDC), 2015The paper tackles the problem of identifying an individual transfer function in a network of linear dynamical systems in the presence of loops under the assumptions that (i) only a subset of the nodes is observable, and (ii) data are being passively recorded (i.e. it is not possible to intervene on any part of the system by actively injecting an input).
Donatello Materassi, Murti V. Salapaka
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The cyclicality of fiscal policy: New evidence from unobserved components approach
Journal of Macroeconomics, 2017 The cyclicality of fiscal policy: New evidence from unobserved components ...
Omar H M N Bashar +2 more
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2011
For many years, the problem of filtering and the extraction of component signals from noisy time series data has occupied the minds of mathematicians and statisticians from a variety of disciplines. Indeed, three of the most notablemathematicians of the Twentieth Century - Wiener (1941), Kolmogorov (1941), and Kalman (1960) - have all made central ...
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For many years, the problem of filtering and the extraction of component signals from noisy time series data has occupied the minds of mathematicians and statisticians from a variety of disciplines. Indeed, three of the most notablemathematicians of the Twentieth Century - Wiener (1941), Kolmogorov (1941), and Kalman (1960) - have all made central ...
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An Unobserved Components Model of the Yield Curve
Journal of Money, Credit and Banking, 2010We develop an unobserved component model in which the short‐term interest rate is composed of a stochastic trend and a stationary cycle. Using the Nelson–Siegel model of the yield curve as inspiration, we estimate an extremely parsimonious state‐space model of interest rates across time and maturity.
RICHARD STARTZ, KWOK PING TSANG
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Time Series Modelling with Unobserved Components
2015Despite the unobserved components model (UCM) having many advantages over more popular forecasting techniques based on regression analysis, exponential smoothing, and ARIMA, the UCM is not well known among practitioners outside the academic community.
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