Paper title: Kalman Filters for Estimating the potential GDP
DOI: https://doi.org/10.4316/JACSM.201801006
Published in: Issue 1, (Vol. 12) / 2018Download
Publishing date: 2018-04-19
Pages: 39-43
Author(s): VLAD Sorin, BALAN Ionuț
Abstract. The estimation of the potential GDP has a twofold importance: on one hand its accurate estimation allows the correct dimensioning of the macroeconomic policies and on the other hand, the study of potential GDP is a research activity allowing a deeper understanding of the economy works. The methods of estimating the potential GDP can be divided into two categories: statistical and structural. Because the potential GDP is unobservable and cannot be derived directly from the statistical data, we used the Kalman Filter (KF) algorithm to estimate it using a model that connects the unobserved with the observed variables. The results were compared to those obtained by applying a Hodrick – Prescott (HP) filter.
Keywords: HP Filter, Kalman Filter, Potential GDP, Dynamical System, State Space
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