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A simple method to estimate discrete-type random coefficients logit models

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  • Doi, Naoshi

Abstract

This paper proposes a new method for estimating random coefficients logit models using aggregate data. The method analytically obtains the value of the econometric error term and thus does not require numerical calculations, in contrast to the contraction mapping established by Berry et al. (1995). The proposed approach drastically reduces the computation time and is applicable for models with discrete-type heterogeneity in consumer tastes. The approach requires additional data on total sales for each consumer type, though such data do not have to be observed at the product-level. This data requirement implies that the method mainly captures observed heterogeneity.

Suggested Citation

  • Doi, Naoshi, 2022. "A simple method to estimate discrete-type random coefficients logit models," International Journal of Industrial Organization, Elsevier, vol. 81(C).
    • Handle: RePEc:eee:indorg:v:81:y:2022:i:c:s0167718722000017
    DOI: 10.1016/j.ijindorg.2022.102825
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    1. Randy Brenkers & Frank Verboven, 2006. "Liberalizing A Distribution System: The European Car Market," Journal of the European Economic Association, MIT Press, vol. 4(1), pages 216-251, March.
    2. Jean‐Pierre Dubé & Jeremy T. Fox & Che‐Lin Su, 2012. "Improving the Numerical Performance of Static and Dynamic Aggregate Discrete Choice Random Coefficients Demand Estimation," Econometrica, Econometric Society, vol. 80(5), pages 2231-2267, September.
    3. 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.
    4. Steven Berry & Michael Carnall & Pablo T. Spiller, 1996. "Airline Hubs: Costs, Markups and the Implications of Customer Heterogeneity," NBER Working Papers 5561, National Bureau of Economic Research, Inc.
    5. Guido W. Imbens & Tony Lancaster, 1994. "Combining Micro and Macro Data in Microeconometric Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(4), pages 655-680.
    6. Alon Eizenberg & Alberto Salvo, 2015. "The Rise of Fringe Competitors in the Wake of an Emerging Middle Class: An Empirical Analysis," American Economic Journal: Applied Economics, American Economic Association, vol. 7(3), pages 85-122, July.
    7. Greene, William H. & Hensher, David A., 2003. "A latent class model for discrete choice analysis: contrasts with mixed logit," Transportation Research Part B: Methodological, Elsevier, vol. 37(8), pages 681-698, September.
    8. Steven T. Berry & Philip A. Haile, 2014. "Identification in Differentiated Products Markets Using Market Level Data," Econometrica, Econometric Society, vol. 82(5), pages 1749-1797, September.
    9. 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.
    10. Cardell, N. Scott, 1997. "Variance Components Structures for the Extreme-Value and Logistic Distributions with Application to Models of Heterogeneity," Econometric Theory, Cambridge University Press, vol. 13(2), pages 185-213, April.
    11. Steve Berry & Oliver B. Linton & Ariel Pakes, 2004. "Limit Theorems for Estimating the Parameters of Differentiated Product Demand Systems," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 71(3), pages 613-654.
    12. Doi, Naoshi & Ohashi, Hiroshi, 2019. "Market structure and product quality: A study of the 2002 Japanese airline merger," International Journal of Industrial Organization, Elsevier, vol. 62(C), pages 158-193.
    13. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-890, July.
    14. Myrto Kalouptsidi, 2012. "From market shares to consumer types: Duality in differentiated product demand estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(2), pages 333-342, March.
    15. Federico Ciliberto & Jonathan W. Williams, 2014. "Does multimarket contact facilitate tacit collusion? Inference on conduct parameters in the airline industry," RAND Journal of Economics, RAND Corporation, vol. 45(4), pages 764-791, December.
    16. David Besanko & Jean-Pierre Dubé & Sachin Gupta, 2003. "Competitive Price Discrimination Strategies in a Vertical Channel Using Aggregate Retail Data," Management Science, INFORMS, vol. 49(9), pages 1121-1138, September.
    17. 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.
    18. Brunner, Daniel & Heiss, Florian & Romahn, André & Weiser, Constantin, 2017. "Reliable estimation of random coefficient logit demand models," DICE Discussion Papers 267, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    19. Jinhyuk Lee & Kyoungwon Seo, 2015. "A computationally fast estimator for random coefficients logit demand models using aggregate data," RAND Journal of Economics, RAND Corporation, vol. 46(1), pages 86-102, March.
    20. Laura Grigolon & Frank Verboven, 2014. "Nested Logit or Random Coefficients Logit? A Comparison of Alternative Discrete Choice Models of Product Differentiation," The Review of Economics and Statistics, MIT Press, vol. 96(5), pages 916-935, December.
    21. Harikesh Nair, 2007. "Intertemporal price discrimination with forward-looking consumers: Application to the US market for console video-games," Quantitative Marketing and Economics (QME), Springer, vol. 5(3), pages 239-292, September.
    22. Steven Berry & Panle Jia, 2010. "Tracing the Woes: An Empirical Analysis of the Airline Industry," American Economic Journal: Microeconomics, American Economic Association, vol. 2(3), pages 1-43, August.
    23. Naoshi Doi, 2022. "Choice of Policy Instruments with Endogenous Quality: Per‐Passenger and Per‐Flight Airport Charges in Japan," Journal of Industrial Economics, Wiley Blackwell, vol. 70(1), pages 44-88, March.
    24. Toshiaki Iizuka, 2007. "Experts' agency problems: evidence from the prescription drug market in Japan," RAND Journal of Economics, RAND Corporation, vol. 38(3), pages 844-862, September.
    25. 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.
    26. Christopher Conlon & Jeff Gortmaker, 2020. "Best practices for differentiated products demand estimation with PyBLP," RAND Journal of Economics, RAND Corporation, vol. 51(4), pages 1108-1161, December.
    27. Keane, Michael P. & Wasi, Nada, 2016. "How to model consumer heterogeneity? Lessons from three case studies on SP and RP data," Research in Economics, Elsevier, vol. 70(2), pages 197-231.
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    Cited by:

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    3. Kandelhardt, Johannes, 2023. "Flexible estimation of random coefficient logit models of differentiated product demand," DICE Discussion Papers 399, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).

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    More about this item

    Keywords

    Demand estimation; Random-coefficient discrete choice model; Latent class model;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

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