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Estimation of the Solow-Cobb-Douglas economic growth model with a Kalman filter: An observability-based approach
This work presents a novel approach for estimating the Solow-Cobb-Douglas economic growth model. In this case, an Extended Kalman Filter is used for estimating, at the same time, the time-varying parameters of the model and the system state, from subsets of partially available economic data measurem...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6595187/ https://www.ncbi.nlm.nih.gov/pubmed/31294111 http://dx.doi.org/10.1016/j.heliyon.2019.e01959 |
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author | Munguía, Rodrigo Davalos, Jessica Urzua, Sarquis |
author_facet | Munguía, Rodrigo Davalos, Jessica Urzua, Sarquis |
author_sort | Munguía, Rodrigo |
collection | PubMed |
description | This work presents a novel approach for estimating the Solow-Cobb-Douglas economic growth model. In this case, an Extended Kalman Filter is used for estimating, at the same time, the time-varying parameters of the model and the system state, from subsets of partially available economic data measurements. Different from traditional econometric techniques, the proposed EKF approach is applied directly to a state-space representation of the original nonlinear model, where all the model parameters are treated as time-varying parameters. An extensive nonlinear observability analysis was carried out in order to investigate the different subsets of measurements that can be used for estimating the state of the system, and also, in order to find out theoretically necessary conditions to achieve the observability system property. Experiments with real macroeconomic data are presented in order to validate the proposed approach. While the observability analysis offer theoretically conditions for system observability, the experimental results suggest that between the subsets of available economic data, some specific economic data are more relevant than others for better estimating the model. |
format | Online Article Text |
id | pubmed-6595187 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-65951872019-07-10 Estimation of the Solow-Cobb-Douglas economic growth model with a Kalman filter: An observability-based approach Munguía, Rodrigo Davalos, Jessica Urzua, Sarquis Heliyon Article This work presents a novel approach for estimating the Solow-Cobb-Douglas economic growth model. In this case, an Extended Kalman Filter is used for estimating, at the same time, the time-varying parameters of the model and the system state, from subsets of partially available economic data measurements. Different from traditional econometric techniques, the proposed EKF approach is applied directly to a state-space representation of the original nonlinear model, where all the model parameters are treated as time-varying parameters. An extensive nonlinear observability analysis was carried out in order to investigate the different subsets of measurements that can be used for estimating the state of the system, and also, in order to find out theoretically necessary conditions to achieve the observability system property. Experiments with real macroeconomic data are presented in order to validate the proposed approach. While the observability analysis offer theoretically conditions for system observability, the experimental results suggest that between the subsets of available economic data, some specific economic data are more relevant than others for better estimating the model. Elsevier 2019-06-21 /pmc/articles/PMC6595187/ /pubmed/31294111 http://dx.doi.org/10.1016/j.heliyon.2019.e01959 Text en © 2019 Published by Elsevier Ltd. http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Munguía, Rodrigo Davalos, Jessica Urzua, Sarquis Estimation of the Solow-Cobb-Douglas economic growth model with a Kalman filter: An observability-based approach |
title | Estimation of the Solow-Cobb-Douglas economic growth model with a Kalman filter: An observability-based approach |
title_full | Estimation of the Solow-Cobb-Douglas economic growth model with a Kalman filter: An observability-based approach |
title_fullStr | Estimation of the Solow-Cobb-Douglas economic growth model with a Kalman filter: An observability-based approach |
title_full_unstemmed | Estimation of the Solow-Cobb-Douglas economic growth model with a Kalman filter: An observability-based approach |
title_short | Estimation of the Solow-Cobb-Douglas economic growth model with a Kalman filter: An observability-based approach |
title_sort | estimation of the solow-cobb-douglas economic growth model with a kalman filter: an observability-based approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6595187/ https://www.ncbi.nlm.nih.gov/pubmed/31294111 http://dx.doi.org/10.1016/j.heliyon.2019.e01959 |
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