| Paper title: |
Kalman Filters for Estimating the potential GDP |
| DOI: | https://doi.org/10.4316/JACSM.201801006 |
| Published in: | Issue 1, (Vol. 12) / 2018 |
| 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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