Kalman Filters for Estimating the potential GDP

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