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(2003)
Efficient estimators : the use of neural networks to construct pseudo panels
Marie Cottrell 1, 2, Patrice Gaubert 3
(2003)

Pseudo 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..
1 :  Statistique Appliquée et MOdélisation Stochastique (SAMOS)
Université Paris I - Panthéon-Sorbonne
2 :  Modélisation Appliquée, Trajectoires Institutionnelles et Stratégies Socio-Économiques (MATISSE)
CNRS : UMR8595 – Université Paris I - Panthéon-Sorbonne
3 :  LEMMA (LEMMA)
Université du Littoral Côte d'Opale
Mathématiques/Statistiques

Sciences de l'Homme et Société/Economies et finances
Pseudo panels – self-organizing maps
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