IDEAS home Printed from https://ideas.repec.org/p/thk/wpaper/inetwp203.html
   My bibliography  Save this paper

The Perils of Antitrust Econometrics: Unrealistic Engel Curves, Inadequate Data, and Aggregation Bias

Author

Listed:
  • Gabriel A. Lozada

    (University of Utah)

Abstract

Some economists argue antitrust policy should be based on empirical methods used by the Industrial Organization subdiscipline of economics, but non-economists must understand that those methods contain certain highly restrictive assumptions. Those assumptions involve econometric "identification," and treating aggregate demand as if it were generated by a representative consumer (Muellbauer's "generalized linear" preferences). We derive new results illustrating how restrictive the representative consumer assumption is; we explain aggregation bias in Almost Ideal Demand System models; and we show that data limitations make it even harder to justify economists' restricting aggregate demands as one would the demand of a single individual.

Suggested Citation

  • Gabriel A. Lozada, 2023. "The Perils of Antitrust Econometrics: Unrealistic Engel Curves, Inadequate Data, and Aggregation Bias," Working Papers Series inetwp203, Institute for New Economic Thinking.
    • Handle: RePEc:thk:wpaper:inetwp203
    DOI: 10.36687/inetwp203
    as

    Download full text from publisher

    File URL: https://doi.org/10.36687/inetwp203
    Download Restriction: no
    File URL: https://www.ineteconomics.org/uploads/papers/WP_203-Lozada.pdf
    File Function: First version, 2022
    Download Restriction: no
    File URL: https://libkey.io/10.36687/inetwp203?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Blundell, Richard & Stoker, Thomas M., 2007. "Models of Aggregate Economic Relationships that Account for Heterogeneity," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 68, Elsevier.
    2. Barnett, William A. & Serletis, Apostolos, 2008. "Consumer preferences and demand systems," Journal of Econometrics, Elsevier, vol. 147(2), pages 210-224, December.
    3. Barnett, William A. & Serletis, Apostolos, 2008. "Measuring Consumer Preferences and Estimating Demand Systems," MPRA Paper 12318, University Library of Munich, Germany.
    4. Stoker, Thomas M, 1993. "Empirical Approaches to the Problem of Aggregation Over Individuals," Journal of Economic Literature, American Economic Association, vol. 31(4), pages 1827-1874, December.
    5. John Muellbauer, 1975. "Aggregation, Income Distribution and Consumer Demand," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 42(4), pages 525-543.
    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. Barnett, William A. & Serletis, Apostolos, 2008. "Consumer preferences and demand systems," Journal of Econometrics, Elsevier, vol. 147(2), pages 210-224, December.
    2. Rowland, Christopher S. & Mjelde, James W. & Dharmasena, Senarath, 2017. "Policy implications of considering pre-commitments in U.S. aggregate energy demand system," Energy Policy, Elsevier, vol. 102(C), pages 406-413.
    3. Simona Bigerna & Carlo Andrea Bollino & Maria Chiara D’Errico, 2020. "A general expenditure system for estimation of consumer demand functions," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 37(3), pages 1071-1088, October.
    4. Resende Filho, M A & Bressan, V G F & Braga, M J & Bressan, A A, 2011. "Sobre a Demanda Agregada por Carnes no Mercado Brasileiro [On the Demand for Meat in Brazil]," MPRA Paper 31818, University Library of Munich, Germany.
    5. Sun, Changyou, 2015. "An investigation of China's import demand for wood pulp and wastepaper," Forest Policy and Economics, Elsevier, vol. 61(C), pages 113-121.
    6. Hossain, A K M Nurul & Serletis, Apostolos, 2020. "Technical change in U.S. industries," Economic Modelling, Elsevier, vol. 91(C), pages 579-600.
    7. Hickman, William & Mortimer, Julie Holland, 2016. "Demand Estimation with Availability Variation," SocArXiv qe69j, Center for Open Science.
    8. Fujioka Soichiro & Fukushige Mototsugu, 2019. "The Future of Demand for Food Away from Home and Prepared Food: Cohort and Age Effects in Japan," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 17(1), pages 1-17, May.
    9. Fleissig, 2015. "Changes in aggregate food demand over the business cycle," Applied Economics Letters, Taylor & Francis Journals, vol. 22(17), pages 1366-1371, November.
    10. LaFrance, Jeffrey T., 1999. "U.S. Food and Nutrient Demand and the Effects of Agricultural Policies," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt52h9v4dq, Department of Agricultural & Resource Economics, UC Berkeley.
    11. Andrea Saayman & Isabel Cortés-Jiménez, 2013. "Modelling Intercontinental Tourism Consumption in South Africa: A Systems-of-Equations Approach," South African Journal of Economics, Economic Society of South Africa, vol. 81(4), pages 538-560, December.
    12. Apostolos Serletis & Libo Xu, 2020. "Demand systems with heteroscedastic disturbances," Empirical Economics, Springer, vol. 58(4), pages 1913-1921, April.
    13. Apostolos Serletis & Libo Xu, 2020. "Conditional Correlation Demand Systems," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 77-86, June.
    14. Ali Jadidzadeh and Apostolos Serletis, 2016. "Sectoral Interfuel Substitution in Canada: An Application of NQ Flexible Functional Forms," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    15. Biing‐Hwan Lin & Steven T. Yen & Diansheng Dong & David M. Smallwood, 2010. "Economic Incentives For Dietary Improvement Among Food Stamp Recipients," Contemporary Economic Policy, Western Economic Association International, vol. 28(4), pages 524-536, October.
    16. Ellison, Martin & Tischbirek, Andreas, 2014. "Unconventional government debt purchases as a supplement to conventional monetary policy," Journal of Economic Dynamics and Control, Elsevier, vol. 43(C), pages 199-217.
    17. Clements, Kenneth W. & Gao, Grace, 2015. "The Rotterdam demand model half a century on," Economic Modelling, Elsevier, vol. 49(C), pages 91-103.
    18. Boonsaeng, Tullaya & Carpio, Carlos E., 2015. "Data Collection Period and Food Demand System Estimation using Cross Sectional Data," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205576, Agricultural and Applied Economics Association.
    19. Jin, Man, 2018. "Measuring substitution in China's monetary-assets demand system," China Economic Review, Elsevier, vol. 50(C), pages 117-132.
    20. LaFrance, Jeffrey T., 2008. "The structure of US food demand," Journal of Econometrics, Elsevier, vol. 147(2), pages 336-349, December.

    More about this item

    Keywords

    Antitrust econometrics; Almost Ideal Demand System (AIDS); New Brandeis School;
    All these keywords.

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • L4 - Industrial Organization - - Antitrust Issues and Policies
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling

    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:thk:wpaper:inetwp203. 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: Pia Malaney (email available below). General contact details of provider: https://edirc.repec.org/data/inetnus.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.