IDEAS home Printed from https://ideas.repec.org/p/sip/dpaper/08-045.html

Estimating Price Elasticities with Non-Linear Errors in Variables

Author

Listed:
  • Aprajit Mahajan

    (Department of Economics, Stanford University)

Abstract

This paper estimates a price elasticity using a flexible demand specification on survey data where prices are observed with error are correlated with household characteristics. The demand function is modelled as being a polynomial (and more generally also including trigonometric terms) in the unobserved true prices and the form of the dependency between the observed (mismeasured) prices and household characteristics is modelled parametrically. I identify and estimate the model by adapting the approach of Hausman, Newey, Ichimura, and Powell (1991) and Schennach (2004). The exible specifications allow us to observe that price elasticities vary across the price distribution, something missed in previous work using linear demand specifications.

Suggested Citation

  • Aprajit Mahajan, 2009. "Estimating Price Elasticities with Non-Linear Errors in Variables," Discussion Papers 08-045, Stanford Institute for Economic Policy Research.
    • Handle: RePEc:sip:dpaper:08-045
    as

    Download full text from publisher

    File URL: http://www-siepr.stanford.edu/repec/sip/08-045.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Deaton, Angus, 1987. "Estimation of own- and cross-price elasticities from household survey data," Journal of Econometrics, Elsevier, vol. 36(1-2), pages 7-30.
    2. Susanne M. Schennach, 2004. "Estimation of Nonlinear Models with Measurement Error," Econometrica, Econometric Society, vol. 72(1), pages 33-75, January.
    3. John Kennan, 1989. "Simultaneous Equations Bias in Disaggregated Econometric Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 56(1), pages 151-156.
    4. Gallant, A. Ronald, 1981. "On the bias in flexible functional forms and an essentially unbiased form : The fourier flexible form," Journal of Econometrics, Elsevier, vol. 15(2), pages 211-245, February.
    5. Alberto Abadie & Guido W. Imbens, 2008. "On the Failure of the Bootstrap for Matching Estimators," Econometrica, Econometric Society, vol. 76(6), pages 1537-1557, November.
    6. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-326, June.
    7. Hausman, Jerry A. & Newey, Whitney K. & Ichimura, Hidehiko & Powell, James L., 1991. "Identification and estimation of polynomial errors-in-variables models," Journal of Econometrics, Elsevier, vol. 50(3), pages 273-295, December.
    8. Geert Ridder & Yingyao Hu, 2004. "Estimation of Nonlinear Models with Measurement Error Using Marginal Information," Econometric Society 2004 North American Summer Meetings 21, Econometric Society.
    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. Xiaohong Chen & Yingyao Hu & Arthur Lewbel, 2007. "Nonparametric identification and estimation of nonclassical errors-in-variables models without additional information," CeMMAP working papers CWP18/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Yingyao Hu & Arthur Lewbel & Susanne M. Schennach, 2007. "Nonparametric identification of the classical errors-in-variables model without side information," CeMMAP working papers CWP14/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Xiaohong Chen & Yingyao Hu, 2006. "Identification and Inference of Nonlinear Models Using Two Samples with Arbitrary Measurement Errors," Cowles Foundation Discussion Papers 1590, Cowles Foundation for Research in Economics, Yale University.
    4. Chen, Xiaohong & Hu, Yingyao & Lewbel, Arthur, 2008. "Nonparametric identification of regression models containing a misclassified dichotomous regressor without instruments," Economics Letters, Elsevier, vol. 100(3), pages 381-384, September.
    5. Dennis Epple & Brett Gordon & Holger Sieg, 2010. "A New Approach to Estimating the Production Function for Housing," American Economic Review, American Economic Association, vol. 100(3), pages 905-924, June.
    6. Natalia, Khorunzhina & Wayne Roy, Gayle, 2011. "Heterogenous intertemporal elasticity of substitution and relative risk aversion: estimation of optimal consumption choice with habit formation and measurement errors," MPRA Paper 34329, University Library of Munich, Germany.
    7. Barnett, William A. & Serletis, Apostolos, 2008. "Consumer preferences and demand systems," Journal of Econometrics, Elsevier, vol. 147(2), pages 210-224, December.
    8. Qing Li, 2014. "Identifiability of mean-reverting measurement error with instrumental variable," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(2), pages 118-129, May.
    9. Barnett, William A. & Serletis, Apostolos, 2008. "The Differential Approach to Demand Analysis and the Rotterdam Model," MPRA Paper 12319, University Library of Munich, Germany.
    10. Agénor Lahatte, 2010. "Autocorrélation spatiale et modèle de demande traitant des valeurs unitaires," Économie et Prévision, Programme National Persée, vol. 193(2), pages 101-117.
    11. Biørn, Erik, 2017. "Identification and Method of Moments Estimation in Polynomial Measurement Error Models," Memorandum 01/2017, Oslo University, Department of Economics.
    12. Dizon,Felipe Jr Fadullon & Josephson,Anna Leigh & Wang,Zetianyu, 2022. "Intra-Household Inequality in Food Consumption and Diets in the Philippines," Policy Research Working Paper Series 10170, The World Bank.
    13. Aprajit Mahajan, 2006. "Identification and Estimation of Regression Models with Misclassification," Econometrica, Econometric Society, vol. 74(3), pages 631-665, May.
    14. Auerbach, Alan J. & Hines, James Jr., 2002. "Taxation and economic efficiency," Handbook of Public Economics, in: A. J. Auerbach & M. Feldstein (ed.), Handbook of Public Economics, edition 1, volume 3, chapter 21, pages 1347-1421, Elsevier.
    15. Toshinobu Matsuda, 2006. "A trigonometric flexible consumer demand system," Canadian Journal of Economics, Canadian Economics Association, vol. 39(1), pages 145-162, February.
    16. Douglas Fisher & Adrian R. Fleissig & Apostolos Serletis, 2006. "An Empirical Comparison of Flexible Demand System Functional Forms," World Scientific Book Chapters, in: Money And The Economy, chapter 13, pages 247-277, World Scientific Publishing Co. Pte. Ltd..
    17. William Barnett & Ousmane Seck, 2006. "Rotterdam vs Almost Ideal Models: Will the Best Demand Specification Please Stand Up?," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 200605, University of Kansas, Department of Economics.
    18. Geert Ridder & Yingyao Hu, 2004. "Estimation of Nonlinear Models with Measurement Error Using Marginal Information," Econometric Society 2004 North American Summer Meetings 21, Econometric Society.
    19. Daniel Wilhelm, 2015. "Identification and estimation of nonparametric panel data regressions with measurement error," CeMMAP working papers CWP34/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. De loecker, Jan & Collard-Wexler, Allan, 2016. "Production Function Estimation with Measurement Error in Inputs," CEPR Discussion Papers 11399, Centre for Economic Policy Research.

    More about this item

    Keywords

    ;

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D40 - Microeconomics - - Market Structure, Pricing, and Design - - - General

    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:sip:dpaper:08-045. 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: Anne Shor The email address of this maintainer does not seem to be valid anymore. Please ask Anne Shor to update the entry or send us the correct address (email available below). General contact details of provider: https://edirc.repec.org/data/cestaus.html .

    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.