A neural network demand system with heteroskedastic errors.

In this paper we consider estimation of demand systems with flexible functional forms, allowing an error term with a general conditional heteroskedasticity function that depends on observed covariates, such as demographic variables. We propose a general model that can be estimated either by quasi-ma...

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Detalles Bibliográficos
Publicado en:Journal of Econometrics Vol. 147; no. 2; pp. 359 - 372
Autores principales: McAleer, Michael, Medeiros, Marcelo C., Slottje, Daniel
Formato: Artículo
Publicado: Elsevier Science December 2008
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: December 2008
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      pub: Elsevier Science
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        10.1016/j.jeconom.2008.09.031
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        atl: A neural network demand system with heteroskedastic errors.
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        au:
          McAleer, Michael
          Medeiros, Marcelo C.
          Slottje, Daniel
      su:
        Error analysis in mathematics
        Variances
        Artificial neural networks
        Economic demand
        Mathematical models
      sug:
        subj:
          Error analysis in mathematics
          Variances
          Artificial neural networks
          Economic demand
          Mathematical models
      ab: In this paper we consider estimation of demand systems with flexible functional forms, allowing an error term with a general conditional heteroskedasticity function that depends on observed covariates, such as demographic variables. We propose a general model that can be estimated either by quasi-maximum likelihood (in the case of exogenous regressors) or generalized method of moments (GMM) if the covariates are endogenous. The specification proposed in the paper nests several demand functions in the literature and the results can be applied to the recently proposed Exact Affine Stone Index (EASI) demand system of [Lewbel, A., Pendakur, K., 2008. Tricks with Hicks: The EASI implicit Marshallian demand system for unobserved heterogeneity and flexible Engel curves. American Economic Review (in press)]. Furthermore, flexible nonlinear expenditure elasticities can be estimated. Copyright (c) 2008 Elsevier B.V.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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