Kalman Filters for Estimating the potential GDP

Autor:	Sorin VLAD, Ionut BALAN
Jazyk:	angličtina
Rok vydání:	2018
Předmět:	HP Filter Kalman Filter Potential GDP Dynamical System State Space Mathematics QA1-939 Electronic computers. Computer science QA75.5-76.95
Zdroj:	Journal of Applied Computer Science & Mathematics, Vol 12, Iss 1, Pp 39-43 (2018)
Druh dokumentu:	article
ISSN:	2066-4273 2066-3129 26487454
DOI:	10.4316/JACSM.201801006
Popis:	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.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/603fe2648745447fa7f2007cd80c3506 Zobrazit plný text záznamu View record in DOAJ