Testing for serial correlation in hierarchical linear models

Javier Alejo, Gabriel Montes-Rojas () and Walter Sosa-Escudero
Authors registered in the RePEc Author Service: Walter Sosa Escudero ()

Journal of Multivariate Analysis, 2018, vol. 165, issue C, 101-116

Abstract: 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 C(α) 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.

Keywords: Clusters; Random effects; Serial correlation (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.jmva.2017.11.007

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