Marketing Letters

, Volume 13, Issue 3, pp 207–220 | Cite as

Structural Applications of the Discrete Choice Model

  • Jean-PIerre DubÉ (CHAIR)
  • Pradeep Chintagunta
  • Amil Petrin
  • Bart Bronnenberg
  • Ron Goettler
  • P. B. Seetharaman
  • K. Sudhir
  • Raphael Thomadsen
  • Ying Zhao


A growing body of empirical literature uses structurally-derived economic models to study the nature of competition and to measure explicitly the economic impact of strategic policies. While several approaches have been proposed, the discrete choice demand system has experienced wide usage. The heterogeneous, or “mixed”, logit in particular has been widely applied due to its parsimonious structure and its ability to capture flexibly substitution patterns for a large number of differentiated products.

We outline the derivation of the heterogeneous logit demand system. We then present a number of applications of such models to various data sources. Finally, we conclude with a discussion of directions for future research in this area.

structural modeling firm conduct policy simulation consumer welfare 


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  1. Allenby, G. M. (1989). ''A Unified Approach to Identifying, Estimating and Testing Demand Structures with Aggregate Scanner Data,'' Marketing Science, 8, 265–280.Google Scholar
  2. Allenby, G. M., and P. E. Rossi. (1991). ''There Is No Aggregation Bias: Why Macro Logit Models Work,'' Journal of Business and Economic Statistics, 9, 1–13.Google Scholar
  3. Baker, J. B., and T. F. Bresnahan. (1985). ''The Gains from Merger or Collusion in Product-Differentiated Industries,'' The Journal of Industrial Economics, 33, 427–444.Google Scholar
  4. Berry, S. (1994). ''Estimating Discrete-Choice Models of Product Differentiation,'' Rand Journal of Economics, 25, 242–262.Google Scholar
  5. Berry, S., M. Carnall and P. T. Spiller. (1997). ''Airline Hubs: Costs, Markups and the Implications of Customer Heterogeneity,'' Yale University, Working Paper.Google Scholar
  6. Berry, S., J. Levinsohn, and A. Pakes. (1995). ''Automobile Prices in Market Equilibrium,'' Econometrica, 63, 841–890.Google Scholar
  7. Berry, S., and A. Pakes. (2001). ''Estimating the Pure Hedonic Discrete Choice Model,'' Working Paper, Yale University.Google Scholar
  8. Besanko, D., S. Gupta and D. Jain. (1998). ''Logit Demand Estimation Under Competitive Pricing Behavior: An Equilibrium Framework,'' Management Science, November.Google Scholar
  9. Besanko, D., J.-P. Dube, and S. Gupta. (2001). ''Heterogeneity and Target Marketing Using Aggregate Retail Data: A Structural Approach,'' Working Paper, Kellogg Graduate School of Management.Google Scholar
  10. Bresnahan, T. F., S. Stern, and M. Trajtenberg. (1997). ''Market Segmentation and the Sources of Rents from Innovation: Personal Computers in the Late 1980s,'' The Rand Journal of Economics, 28, S17–S44.Google Scholar
  11. Bronnenberg, B., and V. Mahajan. (2001). ''Unobserved Retailer Behavior in Multi-Market Data: Joint Spatial Dependence in Market Shares and Promotion Variables,'' Working Paper, UCLA.Google Scholar
  12. Brown, D. J., and R. Matzkin. (1996). ''Testable Restrictions on the Equilibrium Manifold,'' Econometrica, 64, 1249–1262.Google Scholar
  13. Brown, D. J., and R. Matzkin. (1998). ''Estimation of Nonparametric Functions in Simultaneous Equations Models, with an Application to Consumer Demand,'' Working Paper, Yale University.Google Scholar
  14. Capps, C. et al. (2000). ''Consumer Travel and Geographic Market Definition: An Application to Hospital Mergers,'' Working Paper, University of Illinois at Urbana-Champaign.Google Scholar
  15. Chintagunta, P. (1994). ''Heterogeneous Logit Model Implications for Brand Positioning,'' Journal of Marketing Research, 31, 304–311.Google Scholar
  16. Chintagunta, P. (2001a). ''Investigating Category Profit Maximization at a Retail Chain,'' Journal of Marketing Research, forthcoming.Google Scholar
  17. Chintagunta, P. (2001b). ''Endogeneity and Heterogeneity in a Probit Demand Model: Estimation Using Aggregate Data,'' Marketing Science, forthcoming.Google Scholar
  18. Chintagunta, P., D. Jam, and N. Vilcassim. (1991). ''Investigating Heterogeneity in Brand Preferences in Logit Models,'' Journal of Marketing Research, 28, 417–428.Google Scholar
  19. Chintagunta, P., J. P. Dube, and V. Singh. (2002a). ''Market Structure Across Stores: An Application of a Random Coefficients Model with Store Level Data,'' in P. H. Franses and A. L. Montgomery, eds., Econometric Models in Marketing (Advances in Econometrics, 16), JAI Press.Google Scholar
  20. Chintagunta, P., J. P. Dube, and V. Singh. (2002b). ''Balancing profitability and customer value: An application to zone-pricing by a supermarket chain,'' Working Paper, The University of Chicago Graduate School of Business.Google Scholar
  21. Cohen, A. (2000). ''Package Size and Discrimination in Paper Towels,'' Working Paper, University of Virginia.Google Scholar
  22. Dalal, S. R., and R. W. Klein. (1988). ''A Flexible Class of Discrete Choice Models,'' Marketing Science, 7, 232–235.Google Scholar
  23. Davis, P. (1997). ''Spatial Competition in Retail Markets,'' Yale University, Working Paper.Google Scholar
  24. Dubé, J. P. (2001). ''Product Differentiation and Mergers in the Carbonated Soft Drink Industry,'' Working Paper, University of Chicago Graduate School of Business.Google Scholar
  25. Elrod, T. (1988). ''Choice Map: Inferring a product market map from panel data,'' Marketing Science, 7, 21–40.Google Scholar
  26. Elrod, T., and M. P. Keane. (1995). ''A factor-analytic probit model for representing the market structure in panel data,'' Journal of Marketing Research, 32, 1–16.Google Scholar
  27. Erdem, T., and M. P. Keane. (1996). ''Decision-Making under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets,'' Marketing Science, 15, 1–20.Google Scholar
  28. Fader, P. S., and B. G. S. Hardie. (1996). ''Modeling Consumer Choice Among SKUs,'' Journal of Marketing Research, 33, 442–452.Google Scholar
  29. Goettler, R., and R. Shachar. (2001). ''Spatial Competition in the Network Television Industry,'' Working Paper, Carnegie Mellon.Google Scholar
  30. Goldberg, P. K. (1995). ''Product Differentiation and Oligopoly in International Markets: The case of the U.S. Automobile Industry,'' Econometrica, 63, 891–951.Google Scholar
  31. Goolsbee, A., and A. Petrin. (2001). ''Consumer Gains from Direct Broadcast Satellites and the Competition with Cable TV,'' Working Paper, The University of Chicago GSB.Google Scholar
  32. Guadagni, P. M. and J. D. C. Little (1983), ''A Logit Model of Brand Choice Calibrated on Scanner Data.'' Marketing Science, 2, 203–238.Google Scholar
  33. Hausman, J. A. (1997). ''Valuation of New Goods Under Perfect and Imperfect Competition.'' In T. Bresnahan, and R. J. Gordon (eds.), The Economics of New Goods, Chicago: University of Chicago Press.Google Scholar
  34. Kadiyali, V., K. Sudhir, and V. R. Rao. (2000). ''Structural Analysis of Competitive Behavior,'' International Journal of Research in Marketing, 18, 161–485.Google Scholar
  35. Kamakura, W. A., and G. J. Russell. (1989). ''A Probabilistic Choice Model for Market Segmentation and Elasticity Structure,'' Journal of Marketing Research, 26, 379–390.Google Scholar
  36. Leslie, P. J. (2001). ''Price Discrimination in Broadway Theatre,'' Working Paper, UCLA.Google Scholar
  37. Manuszak, M. D. (2000). ''Firm Conduct and Product Differentiation in the Hawaiian Retail Gasoline Industry,'' Working Paper, Carnegie Mellon University.Google Scholar
  38. McCullough, G., and P. E. Rossi. (1994). ''An exact likelihood analysis of the multinomial probit model,'' Journal of Econometrics, 64, 207.Google Scholar
  39. McFadden, D. (1973). ''Conditional Logit Analysis of Discrete Choice Behavior.'' In P. Zarembka (ed.), Frontiers of Econometrics, New York: Academic Press.Google Scholar
  40. McFadden, D., and K. Train. (2000). ''Mixed MNL Models for Discrete Response,'' Journal of Applied Economerics, 15, 447–470.Google Scholar
  41. Moul, C. (2001). ''Saturation and the Demand for Motion Pictures,'' Working Paper, Washington University St. Louis.Google Scholar
  42. Nevo, A. (2001). ''Measuring Market Power in the Ready-To-Eat Cereal Industry,'' Econometrica, 69, 307–340.Google Scholar
  43. Nevo, A. (2000). ''Mergers and Differentiated Products: The Case of the Ready-to-Eat Cereal Industry,'' The Rand Journal of Economics, 31, 395–421.Google Scholar
  44. Pakes, A., and P. McGuire. (1994). ''Computing Markov-perfect Nash equilibria: Numerical implications of a dynamic differentiated product model,'' The Rand Journal of Economics, 79, 555–589.Google Scholar
  45. Petrin, A. (1999). ''Quantifying the Benefits of New Products: The Case of the Mini-van,'' Working Paper, University of Chicago.Google Scholar
  46. Pinkse, J., M. E. Slade, and C. Brett. (2001). ''Spatial Price Competition: A Semiparametric Approach,'' Econometrica, forthcoming.Google Scholar
  47. Small, K. A., and H. S. Rosen. (1981). ''Applied Welfare Economics with Discrete Choice Models,'' Econometrica, 49, 105–130.Google Scholar
  48. Sudhir, K. (2001a). ''Competitive Pricing Behavior in the Auto Market: A Structural Analysis,'' Marketing Science, 20, 42–60.Google Scholar
  49. Sudhir, K. (2001b). ''Structural Analysis of Competitive Pricing in the Presence of a Strategic Retailer,'' Marketing Science, 20, 244.Google Scholar
  50. Sudhir, K., P. Chintagunta, and V. Kadiyali. (2001). ''Investigating Patterns of Time-Varying Competitive Behavior,'' Working Paper, Yale School of Management.Google Scholar
  51. Thomadsen, R. (2001). ''Price Competition in Industries with Geographic Differentiation: The Case of the Hamburger Segment of the Fast Food Industry,'' Working Paper, Columbia University.Google Scholar
  52. Trajtenberg, M. (1989). ''The Welfare Analysis of Product Innovations, with an Application to Computed Tomography Scanners,'' The Journal of Political Economy, 87, 444–479.Google Scholar
  53. Villas-Boas, M., and R. Winer. (1999). ''Endogeneity in Brand Choice Models,'' Management Science, 45(10), 1324–1338.Google Scholar
  54. Villas-Boas, M., and Y. Zhao. (2001). ''The Ketchup Marketplace: Retailer, Manufacturers, and Individual Consumers,'' Working Paper, UC Berkeley.Google Scholar

Copyright information

© Kluwer Academic Publishers 2002

Authors and Affiliations

  • Jean-PIerre DubÉ (CHAIR)
    • 1
  • Pradeep Chintagunta
    • 1
  • Amil Petrin
    • 1
  • Bart Bronnenberg
    • 2
  • Ron Goettler
    • 3
  • P. B. Seetharaman
    • 4
  • K. Sudhir
    • 5
  • Raphael Thomadsen
    • 6
  • Ying Zhao
    • 7
  1. 1.Graduate School of BusinessUniversity of ChicagoUSA
  2. 2.Anderson SchoolUniversity of California Los AngelesUSA
  3. 3.School of Industrial AdministrationCarnegie Mellon UniversityUSA
  4. 4.Olin SchoolWashington University at St. LouisUSA
  5. 5.SOMYale UniversityUSA
  6. 6.Graduate School of BusinessColumbia UniversityUSA
  7. 7.Hong Kong University of Science and TechnologyHong Kong

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