Proietti, Tommaso (2010): Trend Estimation.

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Abstract
Trend estimation deals with the characterization of the underlying, or long–run, evolution of a time series. Despite being a very pervasive theme in time series analysis since its inception, it still raises a lot of controversies. The difficulties, or better, the challenges, lie in the identification of the sources of the trend dynamics, and in the definition of the time horizon which defines the long run. The prevalent view in the literature considers the trend as a genuinely latent component, i.e. as the component of the evolution of a series that is persistent and cannot be ascribed to observable factors. As a matter of fact, the univariate approaches reviewed here assume that the trend is either a deterministic or random function of time.
Item Type:  MPRA Paper 

Original Title:  Trend Estimation 
Language:  English 
Keywords:  Time series models; unobserved components. 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C10  General C  Mathematical and Quantitative Methods > C2  Single Equation Models ; Single Variables > C22  TimeSeries Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes 
Item ID:  21607 
Depositing User:  Tommaso Proietti 
Date Deposited:  25. Mar 2010 06:08 
Last Modified:  12. Feb 2013 21:40 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/21607 