IDEAS home Printed from https://ideas.repec.org/a/ris/apltrx/0259.html
   My bibliography  Save this article

On endogeneity of consumer expenditures in the estimation of households demand system

Author

Listed:
  • Anastasiia Timofeeva

    (Novosibirsk State Technical University, Novosibirsk, Russia)

Abstract

The paper analyzes one case of the endogeneity problem, namely, the presence of measurement error in consumer expenditures by estimation of the demand system according to the household sample surveys. Based on factor analysis a novel approach is proposed and tested. It allows weakening the bias of demand elasticity estimates and does not require additional information (instrumental variables, repeated observations). Its advantage is the possibility of estimating the parameters of the true consumer expenditures distribution which give an idea of the distortion degree of information on the population expenditures.

Suggested Citation

  • Anastasiia Timofeeva, 2015. "On endogeneity of consumer expenditures in the estimation of households demand system," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 37(1), pages 87-106.
    • Handle: RePEc:ris:apltrx:0259
    as

    Download full text from publisher

    File URL: http://pe.cemi.rssi.ru/pe_2015_1_87-106.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Deaton, Angus, 1986. "Demand analysis," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 3, chapter 30, pages 1767-1839, Elsevier.
    2. Richard Blundell & Xiaohong Chen & Dennis Kristensen, 2007. "Semi-Nonparametric IV Estimation of Shape-Invariant Engel Curves," Econometrica, Econometric Society, vol. 75(6), pages 1613-1669, November.
    3. Hausman, J. A. & Newey, W. K. & Powell, J. L., 1995. "Nonlinear errors in variables Estimation of some Engel curves," Journal of Econometrics, Elsevier, vol. 65(1), pages 205-233, January.
    4. Peter Ebbes, 2007. "A non-technical guide to instrumental variables and regressor-error dependencies (in Russian)," Quantile, Quantile, issue 2, pages 3-20, March.
    5. Jerry Hausman, 2001. "Mismeasured Variables in Econometric Analysis: Problems from the Right and Problems from the Left," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 57-67, Fall.
    6. James B. McDonald, 2008. "Some Generalized Functions for the Size Distribution of Income," Economic Studies in Inequality, Social Exclusion, and Well-Being, in: Duangkamon Chotikapanich (ed.), Modeling Income Distributions and Lorenz Curves, chapter 3, pages 37-55, Springer.
    7. Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.
    8. Brown, Alan & Deaton, Angus S, 1972. "Surveys in Applied Economics: Models of Consumer Behaviour," Economic Journal, Royal Economic Society, vol. 82(328), pages 1145-1236, December.
    9. Peter Ebbes & Michel Wedel & Ulf Böckenholt, 2009. "Frugal IV alternatives to identify the parameter for an endogenous regressor," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(3), pages 446-468, April.
    10. Steven Vanduffel & Tom Hoedemakers & Jan Dhaene, 2005. "Comparing Approximations for Risk Measures of Sums of Nonindependent Lognormal Random Variables," North American Actuarial Journal, Taylor & Francis Journals, vol. 9(4), pages 71-82.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mochen Yang & Edward McFowland & Gordon Burtch & Gediminas Adomavicius, 2022. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem," INFORMS Joural on Data Science, INFORMS, vol. 1(2), pages 138-155, October.
    2. Schennach, Susanne M., 2020. "Mismeasured and unobserved variables," Handbook of Econometrics, in: Steven N. Durlauf & Lars Peter Hansen & James J. Heckman & Rosa L. Matzkin (ed.), Handbook of Econometrics, edition 1, volume 7, chapter 0, pages 487-565, Elsevier.
    3. Sule Alan & Orazio Attanasio & Martin Browning, 2009. "Estimating Euler equations with noisy data: two exact GMM estimators," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(2), pages 309-324, March.
    4. Su, Liangjun & Jin, Sainan, 2012. "Sieve estimation of panel data models with cross section dependence," Journal of Econometrics, Elsevier, vol. 169(1), pages 34-47.
    5. Clements, Kenneth W. & Gao, Grace, 2015. "The Rotterdam demand model half a century on," Economic Modelling, Elsevier, vol. 49(C), pages 91-103.
    6. Karun Adusumilli & Taisuke Otsu, 2015. "Nonparametric instrumental regression with errors in variables," STICERD - Econometrics Paper Series /2015/585, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    7. Chernozhukov, Victor & Fernández-Val, Iván & Kowalski, Amanda E., 2015. "Quantile regression with censoring and endogeneity," Journal of Econometrics, Elsevier, vol. 186(1), pages 201-221.
    8. Anish Agarwal & Keegan Harris & Justin Whitehouse & Zhiwei Steven Wu, 2023. "Adaptive Principal Component Regression with Applications to Panel Data," Papers 2307.01357, arXiv.org, revised Aug 2024.
    9. Song, Suyong, 2015. "Semiparametric estimation of models with conditional moment restrictions in the presence of nonclassical measurement errors," Journal of Econometrics, Elsevier, vol. 185(1), pages 95-109.
    10. Adams, Richard H., Jr. & Cuecuecha,Alfredo & Page,John, 2008. "Remittances, consumption and investment in Ghana," Policy Research Working Paper Series 4515, The World Bank.
    11. Corinna.Ghirelli, 2014. "The scarring effect of early non-employment," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 14/895, Ghent University, Faculty of Economics and Business Administration.
    12. Helena Meier & Tooraj Jamasb & Luis Orea, 2013. "Necessity or Luxury Good? Household Energy Spending and Income in Britain 1991-2007," The Energy Journal, , vol. 34(4), pages 109-128, October.
    13. E.A. Selvanathan, 1987. "The Economic Theory of the Consumer," Economics Discussion / Working Papers 87-05, The University of Western Australia, Department of Economics.
    14. Susanne M. Schennach, 2012. "Measurement error in nonlinear models - a review," CeMMAP working papers 41/12, Institute for Fiscal Studies.
    15. Corinna GHIRELLI, 2015. "Scars of early non-employment in a rigid labour market," LIDAM Discussion Papers IRES 2015008, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    16. Hoderlein, Stefan & Winter, Joachim, 2010. "Structural measurement errors in nonseparable models," Journal of Econometrics, Elsevier, vol. 157(2), pages 432-440, August.
    17. De Nadai, Michele & Lewbel, Arthur, 2016. "Nonparametric errors in variables models with measurement errors on both sides of the equation," Journal of Econometrics, Elsevier, vol. 191(1), pages 19-32.
    18. 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.
    19. C. Dongling, 1993. "Introduction to World Consumption Economics," Economics Discussion / Working Papers 93-23, The University of Western Australia, Department of Economics.
    20. Zhu, Yu, 2002. "Latent total consumption expenditure, unobservable individual preferences and panel data," Economic Modelling, Elsevier, vol. 19(2), pages 277-293, March.

    More about this item

    Keywords

    endogenous regressor; measurement error; consumer expenditures; income elasticity of demand; factor;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ris:apltrx:0259. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Anatoly Peresetsky (email available below). General contact details of provider: http://appliedeconometrics.cemi.rssi.ru/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.