Caballero Pintado, María VictoriaMatilla-García, MRuís Marín, ManuelMatilla García, Mariano2024-12-022024-12-022017-09-26Caballero-Pintado, M. V., Matilla-García, M., & Marín, M. R. (2019). Symbolic correlation integral. Econometric Reviews, 38(5), 533-556. DOI: https://doi.org/10.1080/07474938.2017.1365431Taylor and Francis Grouphttps://doi.org/10.1080/07474938.2017.1365431https://hdl.handle.net/20.500.14468/24614Este es el manuscrito aceptado del artículo. La versión registrada fue publicada por primera vez en Econometric Reviews, 38(5), 533-556., está disponible en línea en el sitio web del editor: https://doi.org/10.1080/07474938.2017.1365431 This is the accepted manuscript of the article. The registered version was first published in Econometric Reviews, 38(5), 533-556., and is available online at the publisher's website: https://doi.org/10.1080/07474938.2017.1365431This paper aims to introduce the concept of symbolic correlation integral SC that is extensively used in many scientific fields. The new correlation integral SC avoids the noisy parameter 𝜀 of the classical correlation integral, defined by Grassberger and Procaccia (Citation1983) and extensively used for constructing correlation-integral-based statistics, as in the BDS test. Once the free parameter 𝜀 disappears, it is possible to construct a nonparametric powerful test for independence that can also be used as a diagnostic tool for model selection. The symbolic correlation integral is also extended to deal with multivariate models, and a test for causality is proposed as an example of the theoretical power of the new concept. With extensive Monte Carlo simulations, the paper shows the good size and power performance of symbolic correlation-integral-based tests.eninfo:eu-repo/semantics/openAccess53 Ciencias EconómicasartículoBDS statisticcausality testscorrelation integralindependence testssymbolic dynamics