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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," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00122817, HAL.
  • Handle: RePEc:hal:cesptp: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. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    2. 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.
    3. 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).
    4. 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.
    5. Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 109-126.
    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," Cahiers de la Maison des Sciences Economiques r99009, Université Panthéon-Sorbonne (Paris 1).
    7. 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.
    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. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-326, June.
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    Cited by:

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    2. Andreas Karpf, 2014. "Expectation Formation and Social Influence," Documents de travail du Centre d'Economie de la Sorbonne 14005, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.

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    Pseudo panels; self-organizing maps;

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