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Estimation And Testing An Additive Partially Linear Model In A System Of Engel Curves

  • Jorge Barrientos Marin

    (Universidad de Alicante)

The form of the Engel curve has long been a subject of discussion in appliedeconometrics and until now there has no been definitive conclusion about its form. In this paperan additive partially linear model is used to estimate semiparametrically the effect of totalexpenditure in the context of the Engel curves. Additionally, we consider the non-parametricinclusion of some regressors which traditionally have a non linear effect such as age andschooling. To that end we compare an additive partially linear model with the fullynonparametric one using recent popular test statistics. We also provide the p-values computedby bootstrap and subsampling schemes for the proposed test statistics. Empirical analysis basedon data drawn from the Spanish Expenditure Survey 1990-91 shows that modelling the effectsof expenditure, age and schooling on budget share deserves a treatment better than that adoptedin simple semiparametric analysis.

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Paper provided by Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie) in its series Working Papers. Serie AD with number 2006-23.

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Length: 26 pages
Date of creation: Nov 2006
Date of revision:
Publication status: Published by Ivie
Handle: RePEc:ivi:wpasad:2006-23
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  1. Panayiota Lyssiotou & Panos Pashardes & Thanasis Stengos, 2002. "Age effects on consumer demand: an additive partially linear regression model," Canadian Journal of Economics, Canadian Economics Association, vol. 35(1), pages 153-165, February.
  2. 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.
  3. Whitney K. Newey & James L. Powell, 2003. "Instrumental Variable Estimation of Nonparametric Models," Econometrica, Econometric Society, vol. 71(5), pages 1565-1578, 09.
  4. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-26, June.
  5. Hengartner, Nicolas W. & Sperlich, Stefan, 2005. "Rate optimal estimation with the integration method in the presence of many covariates," Journal of Multivariate Analysis, Elsevier, vol. 95(2), pages 246-272, August.
  6. Richard W. Blundell & Martin Browning & Ian A. Crawford, 2003. "Nonparametric Engel Curves and Revealed Preference," Econometrica, Econometric Society, vol. 71(1), pages 205-240, January.
  7. Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, vol. 56(4), pages 931-54, July.
  8. Härdle, Wolfgang & Huet, Sylvie & Mammen, Enno & Sperlich, Stefan, 1998. "Semiparametric additive indices for binary response and generalized additive models," SFB 373 Discussion Papers 1998,95, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  9. Gozalo, Pedro L. & Linton, Oliver B., 2001. "Testing additivity in generalized nonparametric regression models with estimated parameters," Journal of Econometrics, Elsevier, vol. 104(1), pages 1-48, August.
  10. Richard Blundell & Alan Duncan & Krishna Pendakur, 1998. "Semiparametric estimation and consumer demand," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(5), pages 435-461.
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