Designing a contemporaneity index: Detecting regional similarities in South America, 1961–2018
This study presents an operational characterization of contemporaneity among variables based on the transformation of their corresponding time series into symbolic ones by applying either a Markov switching approach or the symbolic aggregate approximation method. Then, the authors extract vectors fr...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2023 |
| País: | Argentina |
| Institución: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/211098 |
| Acceso en línea: | http://hdl.handle.net/11336/211098 |
| Access Level: | acceso abierto |
| Palabra clave: | SIMBOLIC SERIES REGIMES CONTEMPORANEITY https://purl.org/becyt/ford/5.2 https://purl.org/becyt/ford/5 |
| Sumario: | This study presents an operational characterization of contemporaneity among variables based on the transformation of their corresponding time series into symbolic ones by applying either a Markov switching approach or the symbolic aggregate approximation method. Then, the authors extract vectors from the resulting symbolic time series, characterizing the pattern of change or permanence in time. The scalar product between the vectors corresponding to two variables yields the index of contemporaneity between them. The study apply this method to detect a ranking of synchronic patterns of evolution of gross domestic product (GDP) and investment between several South American economies. |
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