Efficient estimators : the use of neural networks to construct pseudo panels

dc.creatorCottrell, Marie
dc.creatorGaubert, Patrice
dc.date2007-01-05
dc.date.accessioned2026-07-07T08:08:35Z
dc.date.available2026-07-07T08:08:35Z
dc.descriptionPseudo panels constituted with repeated cross-sections are good substitutes to true panel data. But individuals grouped in a cohort are not the same for successive periods, and it results in a measurement error and inconsistent estimators. The solution is to constitute cohorts of large numbers of individuals but as homogeneous as possible. This paper explains a new way to do this: by using a self-organizing map, whose properties are well suited to achieve these objectives. It is applied to a set of Canadian surveys, in order to estimate income elasticities for 18 consumption functions..
dc.identifierhttps://arxiv.org/abs/math/0701154
dc.identifierhttp://arxiv.org/abs/math/0701154
dc.identifierProceedings of the conference WSOM 2003 Kitakiushu, Japan (2003) 331-339
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/131311
dc.subjectStatistics Theory
dc.titleEfficient estimators : the use of neural networks to construct pseudo panels
dc.typetext

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