Testing for serial correlation in hierarchical linear models
ALEJO, JAVIER; MONTES-ROJAS, GABRIEL; SOSA-ESCUDERO, WALTER
JOURNAL OF MULTIVARIATE ANALYSIS
Año: 2018 vol. 165 p. 101 - 101
This paper proposes a simple hierarchical model and a testing strategy to identify intraclusterbcorrelations, in the form of nested random effects and serially correlated errorbcomponents. We focus on intra-cluster serial correlation at different nested levels, a topicbthat has not been studied in the literature before. A Neyman?s C(á) framework is used to derive LM-type tests that allow researchers to identify the appropriate level of clustering aswell as the type of intra-group correlation. An extensive Monte Carlo exercise shows thatthe proposed tests perform well in finite samples and under non-Gaussian distributions.