IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/13407.html
   My bibliography  Save this paper

The Effects of Product Ageing on Demand: The Case of Digital Cameras

Author

Listed:
  • Lou, Weifang
  • Prentice, David
  • Yin, Xiangkang

Abstract

The static differentiated product demand model when applied to products with rapid product turnover and declining prices, yields implausible results. One response is to explicitly model the inter-temporal choices of consumers but computational demands require restrictive assumptions on consumer heterogeneity and limits on the characteristics included in the model. We propose, instead, to supplement the static model with a control for the age that each product has been in the market. This approach is applied to the US digital camera market and we find we obtain more plausible estimates. Our results are consistent with inter-temporal price discrimination by firms. Furthermore, our results suggest that ignoring the effects of product ageing may result in substantially overestimated price elasticities and technological progress and underestimated price-cost markups.

Suggested Citation

  • Lou, Weifang & Prentice, David & Yin, Xiangkang, 2008. "The Effects of Product Ageing on Demand: The Case of Digital Cameras," MPRA Paper 13407, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:13407
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/13407/1/MPRA_paper_13407.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Daniel A. Ackerberg & Marc Rysman, 2005. "Unobserved Product Differentiation in Discrete-Choice Models: Estimating Price Elasticities and Welfare Effects," RAND Journal of Economics, The RAND Corporation, vol. 36(4), pages 771-788, Winter.
    2. Martin Shubik, 2010. "Innovation and Equilibrium?," Chapters, in: Dimitri B. Papadimitriou & L. Randall Wray (ed.), The Elgar Companion to Hyman Minsky, chapter 8, Edward Elgar Publishing.
    3. Igal Hendel & Aviv Nevo, 2006. "Sales and consumer inventory," RAND Journal of Economics, RAND Corporation, vol. 37(3), pages 543-561, September.
    4. Gautam Gowrisankaran & Marc Rysman, 2012. "Dynamics of Consumer Demand for New Durable Goods," Journal of Political Economy, University of Chicago Press, vol. 120(6), pages 1173-1219.
    5. Nevo, Aviv, 2001. "Measuring Market Power in the Ready-to-Eat Cereal Industry," Econometrica, Econometric Society, vol. 69(2), pages 307-342, March.
    6. James Levinsohn & Steven Berry & Ariel Pakes, 1999. "Voluntary Export Restraints on Automobiles: Evaluating a Trade Policy," American Economic Review, American Economic Association, vol. 89(3), pages 400-430, June.
    7. Ackerberg, Daniel & Lanier Benkard, C. & Berry, Steven & Pakes, Ariel, 2007. "Econometric Tools for Analyzing Market Outcomes," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 63, Elsevier.
    8. repec:cdl:compol:217 is not listed on IDEAS
    9. Carranza, Juan Esteban, 2010. "Product innovation and adoption in market equilibrium: The case of digital cameras," International Journal of Industrial Organization, Elsevier, vol. 28(6), pages 604-618, November.
    10. Steven T. Berry, 1994. "Estimating Discrete-Choice Models of Product Differentiation," RAND Journal of Economics, The RAND Corporation, vol. 25(2), pages 242-262, Summer.
    11. Daniel A. Ackerberg, 2003. "Advertising, learning, and consumer choice in experience good markets: an empirical examination," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(3), pages 1007-1040, August.
    12. Igal Hendel & Aviv Nevo, 2006. "Measuring the Implications of Sales and Consumer Inventory Behavior," Econometrica, Econometric Society, vol. 74(6), pages 1637-1673, November.
    13. Junji Xiao, 2008. "Technological advances in digital cameras: Welfare analysis on easy-to-use characteristics," Marketing Letters, Springer, vol. 19(2), pages 171-181, June.
    14. Aviv Nevo, 2000. "Mergers with Differentiated Products: The Case of the Ready-to-Eat Cereal Industry," RAND Journal of Economics, The RAND Corporation, vol. 31(3), pages 395-421, Autumn.
    15. Steven Berry & James Levinsohn & Ariel Pakes, 1995. "Voluntary Export Restraints on Automobiles: Evaluating a Strategic TradePolicy," NBER Working Papers 5235, National Bureau of Economic Research, Inc.
    16. Aviv Nevo, 2000. "A Practitioner's Guide to Estimation of Random‐Coefficients Logit Models of Demand," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 9(4), pages 513-548, December.
    17. Chen, Jiawei & Esteban, Susanna & Shum, Matthew, 2008. "Demand and supply estimation biases due to omission of durability," Journal of Econometrics, Elsevier, vol. 147(2), pages 247-257, December.
    18. Igal Hendel & Aviv Nevo, 2006. "Sales and Consumer Inventory," RAND Journal of Economics, The RAND Corporation, vol. 37(3), pages 543-561, Autumn.
    19. 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.
    20. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-890, July.
    21. Christopher R. Knittel & Konstantinos Metaxoglou, 2008. "Estimation of Random Coefficient Demand Models: Challenges, Difficulties and Warnings," NBER Working Papers 14080, National Bureau of Economic Research, Inc.
    22. Tülin Erdem & Michael Keane & T. Öncü & Judi Strebel, 2005. "Learning About Computers: An Analysis of Information Search and Technology Choice," Quantitative Marketing and Economics (QME), Springer, vol. 3(3), pages 207-247, September.
    23. Inseong Song & Pradeep Chintagunta, 2003. "A Micromodel of New Product Adoption with Heterogeneous and Forward-Looking Consumers: Application to the Digital Camera Category," Quantitative Marketing and Economics (QME), Springer, vol. 1(4), pages 371-407, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Victor Aguirregabiria & Victor Aguirregabiria & Aviv Nevo & Aviv Nevo, 2010. "Recent Developments in Empirical IO: Dynamic Demand and Dynamic Games," Working Papers tecipa-419, University of Toronto, Department of Economics.
    2. Weifang Lou, 2009. "Estimating the Impact of a Potential Process Innovation and the Optimal Strategy of Licensing," Working Papers 2009.03, School of Economics, La Trobe University.
    3. Lou, Weifang & Prentice, David & Yin, Xiangkang, 2012. "What difference does dynamics make? The case of digital cameras," International Journal of Industrial Organization, Elsevier, vol. 30(1), pages 30-40.

    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. Weifang Lou, 2009. "Estimating the Impact of a Potential Process Innovation and the Optimal Strategy of Licensing," Working Papers 2009.03, School of Economics, La Trobe University.
    2. Christopher R. Knittel & Konstantinos Metaxoglou, 2008. "Estimation of Random Coefficient Demand Models: Challenges, Difficulties and Warnings," NBER Working Papers 14080, National Bureau of Economic Research, Inc.
    3. Lou, Weifang & Prentice, David & Yin, Xiangkang, 2012. "What difference does dynamics make? The case of digital cameras," International Journal of Industrial Organization, Elsevier, vol. 30(1), pages 30-40.
    4. 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.
    5. De Loecker, Jan, 2011. "Recovering markups from production data," International Journal of Industrial Organization, Elsevier, vol. 29(3), pages 350-355, May.
    6. Victor Aguirregabiria & Margaret Slade, 2017. "Empirical models of firms and industries," Canadian Journal of Economics, Canadian Economics Association, vol. 50(5), pages 1445-1488, December.
    7. Gautam Gowrisankaran & Marc Rysman, 2012. "Dynamics of Consumer Demand for New Durable Goods," Journal of Political Economy, University of Chicago Press, vol. 120(6), pages 1173-1219.
    8. Matthew Backus & Christopher Conlon & Michael Sinkinson, 2021. "Common Ownership and Competition in the Ready-to-Eat Cereal Industry," NBER Working Papers 28350, National Bureau of Economic Research, Inc.
    9. Chen, Jiawei & Esteban, Susanna & Shum, Matthew, 2008. "Demand and supply estimation biases due to omission of durability," Journal of Econometrics, Elsevier, vol. 147(2), pages 247-257, December.
    10. Steven T. Berry & Philip A. Haile, 2021. "Foundations of Demand Estimation," Cowles Foundation Discussion Papers 2301, Cowles Foundation for Research in Economics, Yale University.
    11. Gonca P. Soysal & Lakshman Krishnamurthi, 2012. "Demand Dynamics in the Seasonal Goods Industry: An Empirical Analysis," Marketing Science, INFORMS, vol. 31(2), pages 293-316, March.
    12. Donna, Javier D., 2018. "Measuring Long-Run Price Elasticities in Urban Travel Demand," MPRA Paper 90059, University Library of Munich, Germany.
    13. Adam Copeland, 2014. "Intertemporal substitution and new car purchases," RAND Journal of Economics, RAND Corporation, vol. 45(3), pages 624-644, September.
    14. Masakazu Ishihara & Andrew T. Ching, 2019. "Dynamic Demand for New and Used Durable Goods Without Physical Depreciation: The Case of Japanese Video Games," Marketing Science, INFORMS, vol. 38(3), pages 392-416, May.
    15. Charles J. Romeo, 2016. "Incorporating Prior Information into A GMM Objective For Mixed Logit Demand Systems," Journal of Industrial Economics, Wiley Blackwell, vol. 64(2), pages 336-363, June.
    16. Mariuzzo, Franco & Walsh, Patrick Paul & Whelan, Ciara, 2010. "Coverage of retail stores and discrete choice models of demand: Estimating price elasticities and welfare effects," International Journal of Industrial Organization, Elsevier, vol. 28(5), pages 555-578, September.
    17. Sun, Yutec & Ishihara, Masakazu, 2019. "A computationally efficient fixed point approach to dynamic structural demand estimation," Journal of Econometrics, Elsevier, vol. 208(2), pages 563-584.
    18. Tovar, Jorge, 2012. "Consumers’ Welfare and Trade Liberalization: Evidence from the Car Industry in Colombia," World Development, Elsevier, vol. 40(4), pages 808-820.
    19. Chan, Tat Y. & Narasimhan, Chakravarthi & Yoon, Yeujun, 2017. "Advertising and price competition in a manufacturer-retailer channel," International Journal of Research in Marketing, Elsevier, vol. 34(3), pages 694-716.
    20. 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.

    More about this item

    Keywords

    Discrete Choice; Demand Dynamics; Forward-Looking Behavior; Heterogeneous Preferences;
    All these keywords.

    JEL classification:

    • L0 - Industrial Organization - - General
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • L63 - Industrial Organization - - Industry Studies: Manufacturing - - - Microelectronics; Computers; Communications Equipment

    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:pra:mprapa:13407. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.