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

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  • Marie Cottrell

    (SAMOS - Statistique Appliquée et MOdélisation Stochastique - UP1 - Université Paris 1 Panthéon-Sorbonne, MATISSE - UMR 8595 - Modélisation Appliquée, Trajectoires Institutionnelles et Stratégies Socio-Économiques - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Patrice Gaubert

    (LEMMA - Laboratoire d’Economie, de Modélisation et de Mathématiques Appliquées - ULCO - Université du Littoral Côte d'Opale)

Abstract

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..

Suggested Citation

  • Marie Cottrell & Patrice Gaubert, 2003. "Efficient estimators : the use of neural networks to construct pseudo panels," Post-Print hal-00122817, HAL.
    • Handle: RePEc:hal:journl:hal-00122817
    Note: View the original document on HAL open archive server: https://hal.science/hal-00122817
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    References listed on IDEAS

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    1. François Gardes & Greg J, Duncan & Patrice Gaubert & Christophe Starzec, 2002. "Panel and Pseudo-Panel Estimation of Cross-Sectional and Time Series Elasticities of Food Consumption : The Case of American and Polish Data," Working Papers 2002-02, Center for Research in Economics and Statistics.
    2. Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 109-126.
    3. Gardes, Francois & Langlois, Simon & Richaudeau, Didier, 1996. "Cross-section versus time-series income elasticities of Canadian consumption," Economics Letters, Elsevier, vol. 51(2), pages 169-175, May.
    4. Marie Cottrell & Patrice Gaubert & Patrick Letremy & Patrick Rousset, 1999. "Analyzing and representing multidimensional quantitative and qualitative data: Demographic study of the Rhône valley. The domestic consumption of the Canadian families," Cahiers de la Maison des Sciences Economiques r99009, Université Panthéon-Sorbonne (Paris 1).
    5. Verbeek, Marno & Nijman, Theo, 1993. "Minimum MSE estimation of a regression model with fixed effects from a series of cross-sections," Journal of Econometrics, Elsevier, vol. 59(1-2), pages 125-136, September.
    6. Marie Cottrell & Patrice Gaubert & Patrick Letremy & Patrick Rousset, 1999. "Analyzing and representing multidimensional quantitative and qualitative data: Demographic study of the Rhône valley. The domestic consumption of the Canadian families," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-03707207, HAL.
    7. Cottrell, M. & Gaubert, P. & Rousset, P. & Letremy, P., 1999. "Analyzing and Representing Multidimentional Quantitative an Qualitative Data: Demographic Study of the Rhone Valley. The Domestic Consumption of the Canadian Families," Papiers d'Economie Mathématique et Applications 1999-09, Université Panthéon-Sorbonne (Paris 1).
    8. James Banks & Richard Blundell & Arthur Lewbel, 1997. "Quadratic Engel Curves And Consumer Demand," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 527-539, November.
    9. Nilton Cardoso & François Gardes, 1996. "Estimations de lois de consommation sur un pseudo-panel d'enquêtes de l'Insee ( 1979,1984,1989)," Économie et Prévision, Programme National Persée, vol. 126(5), pages 111-125.
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    Pseudo panels; self-organizing maps;

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