Unobserved Components And Time Series Econometrics


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Unobserved Components and Time Series Econometrics


Unobserved Components and Time Series Econometrics

Author: Siem Jan Koopman

language: en

Publisher: Oxford University Press

Release Date: 2015


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Presents original and up-to-date studies in unobserved components (UC) time series models from both theoretical and methodological perspectives.

Unobserved Components and Time Series Econometrics


Unobserved Components and Time Series Econometrics

Author: Siem Jan Koopman

language: en

Publisher: Oxford University Press

Release Date: 2015-11-19


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This volume presents original and up-to-date studies in unobserved components (UC) time series models from both theoretical and methodological perspectives. It also presents empirical studies where the UC time series methodology is adopted. Drawing on the intellectual influence of Andrew Harvey, the work covers three main topics: the theory and methodology for unobserved components time series models; applications of unobserved components time series models; and time series econometrics and estimation and testing. These types of time series models have seen wide application in economics, statistics, finance, climate change, engineering, biostatistics, and sports statistics. The volume effectively provides a key review into relevant research directions for UC time series econometrics and will be of interest to econometricians, time series statisticians, and practitioners (government, central banks, business) in time series analysis and forecasting, as well to researchers and graduate students in statistics, econometrics, and engineering.

Time Series Modelling with Unobserved Components


Time Series Modelling with Unobserved Components

Author: Matteo M. Pelagatti

language: en

Publisher: CRC Press

Release Date: 2015-07-28


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Despite 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. Time Series Modelling with Unobserved Components rectifies this deficiency by giving a practical o