IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/9452.html
   My bibliography  Save this paper

Omitted Product Attributes in Discrete Choice Models

Author

Listed:
  • Amil Petrin
  • Kenneth Train

Abstract

We describe two methods for correcting an omitted variables problem in discrete choice models: a fixed effects approach and a control function approach. The control function approach is easier to implement and applicable in situations for which the fixed effects approach is not. We apply both methods to a cross-section of disaggregate data on customer's choice among television options including cable, satellite, and antenna. As theory predicts, the estimated price response rises substantially when either correction is applied. All of the estimated parameters and the implied price elasticities are very similar for both methods.

Suggested Citation

  • Amil Petrin & Kenneth Train, 2003. "Omitted Product Attributes in Discrete Choice Models," NBER Working Papers 9452, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:9452
    Note: IO
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w9452.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Albert Madansky, 1964. "Instrumental variables in factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 29(2), pages 105-113, June.
    2. Richard W. Blundell & James L. Powell, 2004. "Endogeneity in Semiparametric Binary Response Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 71(3), pages 655-679.
    3. Brownstone, David & Train, Kenneth, 1998. "Forecasting new product penetration with flexible substitution patterns," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 109-129, November.
    4. Nevo, Aviv, 2001. "Measuring Market Power in the Ready-to-Eat Cereal Industry," Econometrica, Econometric Society, vol. 69(2), pages 307-342, March.
    5. Smith, Richard J & Blundell, Richard W, 1986. "An Exogeneity Test for a Simultaneous Equation Tobit Model with an Application to Labor Supply," Econometrica, Econometric Society, vol. 54(3), pages 679-685, May.
    6. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    7. Kenneth Train ., 2000. "Halton Sequences for Mixed Logit," Economics Working Papers E00-278, University of California at Berkeley.
    8. Pinar Karaca-Mandic & Kenneth Train, 2003. "Standard error correction in two-stage estimation with nested samples," Econometrics Journal, Royal Economic Society, vol. 6(2), pages 401-407, December.
    9. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, November.
    10. Steven Berry & James Levinsohn & Ariel Pakes, 2004. "Differentiated Products Demand Systems from a Combination of Micro and Macro Data: The New Car Market," Journal of Political Economy, University of Chicago Press, vol. 112(1), pages 68-105, February.
    11. J. Miguel Villas-Boas & Russell S. Winer, 1999. "Endogeneity in Brand Choice Models," Management Science, INFORMS, vol. 45(10), pages 1324-1338, October.
    12. Rivers, Douglas & Vuong, Quang H., 1988. "Limited information estimators and exogeneity tests for simultaneous probit models," Journal of Econometrics, Elsevier, vol. 39(3), pages 347-366, November.
    13. Austan Goolsbee & Amil Petrin, 2004. "The Consumer Gains from Direct Broadcast Satellites and the Competition with Cable TV," Econometrica, Econometric Society, vol. 72(2), pages 351-381, March.
    14. Daniel McFadden, 1977. "Modelling the Choice of Residential Location," Cowles Foundation Discussion Papers 477, Cowles Foundation for Research in Economics, Yale University.
    15. Amil Petrin, 2002. "Quantifying the Benefits of New Products: The Case of the Minivan," Journal of Political Economy, University of Chicago Press, vol. 110(4), pages 705-729, August.
    16. David Hensher, 2001. "The valuation of commuter travel time savings for car drivers: evaluating alternative model specifications," Transportation, Springer, vol. 28(2), pages 101-118, May.
    17. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-890, July.
    18. Trajtenberg, Manuel, 1989. "The Welfare Analysis of Product Innovations, with an Application to Computed Tomography Scanners," Journal of Political Economy, University of Chicago Press, vol. 97(2), pages 444-479, April.
    19. Benkard, C. Lanier & Bajari, Patrick, 2001. "Demand Estimation with Heterogeneous Consumers and Unobserved Product Characteristics: A Hedonic Approach," Research Papers 1691, Stanford University, Graduate School of Business.
    20. Heckman, James J. & Robb, Richard Jr., 1985. "Alternative methods for evaluating the impact of interventions : An overview," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 239-267.
    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. Fernández-Antolín, Anna & Guevara, C. Angelo & de Lapparent, Matthieu & Bierlaire, Michel, 2016. "Correcting for endogeneity due to omitted attitudes: Empirical assessment of a modified MIS method using RP mode choice data," Journal of choice modelling, Elsevier, vol. 20(C), pages 1-15.
    2. Thomas E. Guerrero & C. Angelo Guevara & Elisabetta Cherchi & Juan de Dios Ortúzar, 2021. "Addressing endogeneity in strategic urban mode choice models," Transportation, Springer, vol. 48(4), pages 2081-2102, August.
    3. Kim Kyoo il & Petrin Amil, 2015. "Tests for Price Endogeneity in Differentiated Product Models," Journal of Econometric Methods, De Gruyter, vol. 4(1), pages 47-69, January.
    4. Steven T. Berry & Philip A. Haile, 2014. "Identification in Differentiated Products Markets Using Market Level Data," Econometrica, Econometric Society, vol. 82, pages 1749-1797, September.
    5. Kim, Hyunchul & Kim, Kyoo il, 2017. "Estimating store choices with endogenous shopping bundles and price uncertainty," International Journal of Industrial Organization, Elsevier, vol. 54(C), pages 1-36.
    6. Lee Branstetter & Chirantan Chatterjee & Matthew J. Higgins, 2016. "Regulation and welfare: evidence from paragraph IV generic entry in the pharmaceutical industry," RAND Journal of Economics, RAND Corporation, vol. 47(4), pages 857-890, November.
    7. Tongil “TI”Kim, 2021. "When Franchisee Service Affects Demand: An Application to the Car Radiator Market and Resale Price Maintenance," Marketing Science, INFORMS, vol. 40(1), pages 101-121, January.
    8. Cristian Angelo Guevara & Moshe E. Ben-Akiva, 2012. "Change of Scale and Forecasting with the Control-Function Method in Logit Models," Transportation Science, INFORMS, vol. 46(3), pages 425-437, August.
    9. Tovar, Jorge, 2012. "Consumers’ Welfare and Trade Liberalization: Evidence from the Car Industry in Colombia," World Development, Elsevier, vol. 40(4), pages 808-820.
    10. Lurkin, Virginie & Garrow, Laurie A. & Higgins, Matthew J. & Newman, Jeffrey P. & Schyns, Michael, 2017. "Accounting for price endogeneity in airline itinerary choice models: An application to Continental U.S. markets," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 228-246.
    11. Gopalakrishnan, Raja & Guevara, C. Angelo & Ben-Akiva, Moshe, 2020. "Combining multiple imputation and control function methods to deal with missing data and endogeneity in discrete-choice models," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 45-57.
    12. Rachel Griffith & Lars Nesheim & Martin O'Connell, 2018. "Income effects and the welfare consequences of tax in differentiated product oligopoly," Quantitative Economics, Econometric Society, vol. 9(1), pages 305-341, March.
    13. Peter Davis & Pasquale Schiraldi, 2014. "The flexible coefficient multinomial logit (FC-MNL) model of demand for differentiated products," RAND Journal of Economics, RAND Corporation, vol. 45(1), pages 32-63, March.
    14. Susan Athey & Guido W. Imbens, 2007. "Discrete Choice Models With Multiple Unobserved Choice Characteristics," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(4), pages 1159-1192, November.
    15. Federico Ciliberto & GianCarlo Moschini & Edward D. Perry, 2019. "Valuing product innovation: genetically engineered varieties in US corn and soybeans," RAND Journal of Economics, RAND Corporation, vol. 50(3), pages 615-644, September.
    16. Simon P. Anderson & Federico Ciliberto & Jura Liaukonyte & Régis Renault, 2016. "Push-me pull-you: comparative advertising in the OTC analgesics industry," RAND Journal of Economics, RAND Corporation, vol. 47(4), pages 1029-1056, November.
    17. Juan Esteban Carranza & Alejandra Ximena González, 2014. "Estimación de la demanda de vehículos nuevos de los hogares colombianos entre 2001 y 2011," Borradores de Economia 11570, Banco de la Republica.
    18. Louis Grange & Felipe González & Ignacio Vargas & Rodrigo Troncoso, 2015. "A Logit Model With Endogenous Explanatory Variables and Network Externalities," Networks and Spatial Economics, Springer, vol. 15(1), pages 89-116, March.
    19. de Grange, Louis & González, Felipe & Marechal, Matthieu & Troncoso, Rodrigo, 2024. "Estimating multinomial logit models with endogenous variables: Control function versus two adapted approaches," Transportation Research Part A: Policy and Practice, Elsevier, vol. 183(C).
    20. Gregory S. Crawford & Ali Yurukoglu, 2012. "The Welfare Effects of Bundling in Multichannel Television Markets," American Economic Review, American Economic Association, vol. 102(2), pages 643-685, April.

    More about this item

    JEL classification:

    • D0 - Microeconomics - - General
    • L0 - Industrial Organization - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:nbr:nberwo:9452. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.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.