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What Happens When Demand Is Estimated With A Misspecified Model?

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  • DONGLING HUANG
  • CHRISTIAN ROJAS
  • FRANK BASS

Abstract

We conduct Monte Carlo experiments to investigate the biases of assuming a misspecified demand model. We study continuous models (linear, log‐linear and AIDS), and discrete choice models (logit) in the context of differentiated products and aggregate data. Estimating demand with the ‘wrong’ model yields varying degrees of bias in estimated elasticities, but the logit model can yield unbiased estimates for a certain size of the assumed market potential. Merger simulations confirm the key importance of market potential in logit estimation suggesting that a discrete choice model may be preferable even when the discreteness of the purchase decision is questionable.

Suggested Citation

  • Dongling Huang & Christian Rojas & Frank Bass, 2008. "What Happens When Demand Is Estimated With A Misspecified Model?," Journal of Industrial Economics, Wiley Blackwell, vol. 56(4), pages 809-839, December.
  • Handle: RePEc:bla:jindec:v:56:y:2008:i:4:p:809-839
    DOI: 10.1111/j.1467-6451.2008.00361.x
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    Cited by:

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    6. Ryo Sakamoto & Kyle Stiegert, 2018. "Comparing competitive toughness to benchmark outcomes in retail oligopoly pricing," Agribusiness, John Wiley & Sons, Ltd., vol. 34(1), pages 44-60, December.
    7. Heng, Yan & Peterson, Hikaru, 2014. "Estimating Demand for Differentiated Eggs Using Scanner Data," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170457, Agricultural and Applied Economics Association.
    8. Zulehner, Christine & Gugler, Klaus Peter & Weichselbaumer, Michael, 2015. "Analysis of mergers in first-price auctions," CEPR Discussion Papers 10799, C.E.P.R. Discussion Papers.
    9. Cohen, Michael & Cotterill, Ronald, 2008. "The Impact of Retail Store Brands on Manufacturer Brands: A Generalization of Steiner’s Elasticity Model," Research Reports 149933, University of Connecticut, Food Marketing Policy Center.
    10. Nathan H. Miller & Marc Remer & Conor Ryan & Gloria Sheu, 2016. "Pass-Through and the Prediction of Merger Price Effects," Journal of Industrial Economics, Wiley Blackwell, vol. 64(4), pages 683-709, December.
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    12. Badruddoza, Syed & Amin, Modhurima & McCluskey, Jill, 2019. "Assessing the Importance of an Attribute in a Demand SystemStructural Model versus Machine Learning," Working Papers 2019-5, School of Economic Sciences, Washington State University.
    13. Dongling Huang & Christian Rojas, 2013. "The Outside Good Bias in Logit Models of Demand with Aggregate Data," Economics Bulletin, AccessEcon, vol. 33(1), pages 198-206.
    14. Hirsch, Stefan, 2022. "Product placement in the meat substitute sector: Evidence from a spatial demand model," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322181, Agricultural and Applied Economics Association.
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