| dc.creator | Alejo, Javier | |
| dc.creator | Montes Rojas, Gabriel Victorio | |
| dc.creator | Sosa Escudero, Walter | |
| dc.date | 2018-05 | |
| dc.date | 2020-08-10T17:33:20Z | |
| dc.date.accessioned | 2023-07-14T20:34:30Z | |
| dc.date.available | 2023-07-14T20:34:30Z | |
| dc.identifier | http://sedici.unlp.edu.ar/handle/10915/101815 | |
| dc.identifier | https://ri.conicet.gov.ar/11336/87244 | |
| dc.identifier | issn:0047-259X | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/7439778 | |
| dc.description | 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. | |
| dc.description | Centro de Estudios Distributivos, Laborales y Sociales | |
| dc.format | application/pdf | |
| dc.format | 101-116 | |
| dc.language | en | |
| dc.rights | http://creativecommons.org/licenses/by-nc-sa/4.0/ | |
| dc.rights | Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) | |
| dc.subject | Ciencias Económicas | |
| dc.subject | Clusters | |
| dc.subject | Random effects | |
| dc.subject | Serial correlation | |
| dc.title | Testing for serial correlation in hierarchical linear models | |
| dc.type | Articulo | |
| dc.type | Preprint | |
