Grupos de Investigación

Testing for serial correlation in hierarchical linear models

ISSNAño: 2018
AutorAutor/es: Alejo, Javier, Montes Rojas, G. y Sosa Escudero, W.
EditorialEditorial: Journal of Multivariate Analysis
Nº de PáginasNº de Páginas: 101-116
This paper proposes a simple hierarchical model and a testing strategy to identify intra-cluster correlations, in the form of nested random effects and serially correlated error components. We focus on intra-cluster serial correlation at different nested levels, a topic that has not been studied in the literature before. A Neyman’s  framework is used to derive LM-type tests that allow researchers to identify the appropriate level of clustering as well as the type of intra-group correlation. An extensive Monte Carlo exercise shows that the proposed tests perform well in finite samples and under non-Gaussian distributions.
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