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Specification of household engel curves by nonparametric regression

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Author Info
Herman Bierens
Hettie Pott-Buter

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Abstract

This paper demonstrates the usefulness of nonparametric regression analysis for functional specfication of houshold Engel curves. After a brief review in section 2 of the literature on demand functions and equivalence scales and the functional specifications used, we first discuss in section 3 the issues of using income versus total expenditure, the origin and nature of the error terms in the light of utility theroy, and the interpretation of empirical demand functions. we shall reach the unorthodox view that household demand functions should be interpreted as conditional expectations relative to prices, household composition and either income or the conditional expectation of total expenditure (rather that total expenditure itself), where the latter conditional expectation is taken relative to income, prices and household composition. these two forms appear to be equivalent. this result also solves the simultaneity problem: the error variance matrix is no longer singular. Moreover, the errors are in general heteroskedastic. In section 4 we discuss the model and the data, and in section 5 we review the nonparametric kernal regression approach. In section 6 we derive the functional form of our household engel curves from nonparametric regression results, using the 1980 budget survey for the netherlands, in order to avoid model misspecification. thus the modl is derived directly from the data, without restricting its functional form. the nonparametric regression results are then translated to suitable parametric functional specifications, i.e., we choose parametric functional forms in accordance with the nanparametric regression results. these parametric specification are estimated by least squares, and various parameter restrictions are tested in order to simplify the models. this yields very simple final specifications of the household engel curves involved, namely linear functions of income and the number of children in two age groups.

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Publisher Info
Article provided by Taylor and Francis Journals in its journal Econometric Reviews.

Volume (Year): 9 (1990)
Issue (Month): 2 ()
Pages: 123-184
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Handle: RePEc:taf:emetrv:v:9:y:1990:i:2:p:123-184

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  1. Pedro Gozalo & Oliver Linton, 1994. "Local Nonlinear Least Squares Estimation: Using Parametric Information Nonparametrically," Cowles Foundation Discussion Papers 1075, Cowles Foundation, Yale University. [Downloadable!]
  2. Richard Blundell & Xiaohong Chen & Dennis Kristensen, 2003. "Nonparametric IV estimation of shape-invariant Engel curves," CeMMAP working papers CWP15/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies. [Downloadable!]
  3. Giorgio Fagiolo, 2001. "Engel Curves Specification in an Artificial Model of Consumption Dynamics with Socially Evolving Preferences," LEM Papers Series 2001/16, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy. [Downloadable!]
  4. Richard Blundell & Martin Browning & Ian Crawford, 2005. "Best nonparametric bounds on demand responses," CeMMAP working papers CWP12/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies. [Downloadable!]
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  5. Oliver Linton, 1993. "Second Order Approximation in the Partially Linear Regression Model," Cowles Foundation Discussion Papers 1065, Cowles Foundation, Yale University. [Downloadable!]
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  6. Martina Menon & Federico Perali & Luca Piccoli, 2008. "The passive drinking effect: Evidence from Italy," PSE Working Papers 2008-33, PSE (Ecole normale supérieure). [Downloadable!]
  7. Joachim Engel & Alois Kneip, 1996. "Recent approaches to estimating Engel curves," Journal of Economics, Springer, vol. 63(2), pages 187-212, June. [Downloadable!] (restricted)
  8. Cristian Huse, 2004. "Comparing Nonparametric Regression Quantiles," Econometric Society 2004 Latin American Meetings 165, Econometric Society. [Downloadable!]
  9. Jorge Barrientos Marin, 2006. "Estimation And Testing An Additive Partially Linear Model In A System Of Engel Curves," Working Papers. Serie AD 2006-23, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie). [Downloadable!]
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  10. Oliver LINTON, . "Applied nonparametric methods," Statistic und Oekonometrie 9312, Humboldt Universitaet Berlin. [Downloadable!]
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  11. Ricardo Cao & Miguel Delgado & Wenceslao González-Manteiga, 1997. "Nonparametric curve estimation: An overview," Investigaciones Economicas, Fundación SEPI, vol. 21(2), pages 209-252, May. [Downloadable!]
  12. Juan Gabriel Rodríguez & Rafael Salas, 2004. "A Bistochastic Nonparametric Estimator," Economic Working Papers at Centro de Estudios Andaluces E2004/22, Centro de Estudios Andaluces. [Downloadable!]
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