+7 925 966 4690, 9am6pm (GMT+3), Monday – Friday
ИД «Финансы и кредит»

JOURNALS

  

FOR AUTHORS

  

SUBSCRIBE

    
Economic Analysis: Theory and Practice
 

A review of structural discrete-continuous models of demand incorporating the multiple choice of consumers

Vol. 14, Iss. 39, OCTOBER 2015

PDF  Article PDF Version

Received: 10 August 2015

Received in revised form: 9 September 2015

Accepted: 16 September 2015

Available online: 25 October 2015

Subject Heading: MATHEMATICAL METHODS AND MODELS

JEL Classification: 

Pages: 56-66

Kochkina N.A. National Research University Higher School of Economics - Perm, Perm, Russian Federation
kochkina.nataliya@gmail.com

Subject The need to model and estimate the demand function continues to be relevant. Structural discrete-continuous models of demand appeared in 2000. They enable to provide a mathematical description of choice situations.
     Objectives The objectives are to analyze the existing structural discrete-continuous models of demand, which allow simulating multiple choice of the individual, to compare different models and reveal the most topical areas for future research.
     Results I present a common approach to modeling the multiple choice situations, i.e. formalize the problem of consumer choice. The study includes a critical analysis of the models, considers the existing utility function specifications, and demonstrates their main advantages and disadvantages.
     Conclusions I propose two major areas for future research in this sphere: developing the flexible specifications of the utility function, which make it possible to consider the effects of substitution and complementarity, and designing the algorithms, which enable prompt estimation of such models.

Keywords: multiple choice, discrete-continuous model, demand, structural approach, utility function

References:

  1. Dube J.-P. Multiple Discreteness and Product Differentiation: Demand for Carbonated Soft Drinks. Marketing Science, 2004, vol. 23, no. 1, pp. 66–81.
  2. Hendel I. Estimating Multiple-Discrete Choice Models: An Application to Computerization Returns. The Review of Economic Studies, 1999, vol. 66, no. 2, pp. 423–446.
  3. Hanemann W.M. Discrete-continuous Models of Consumer Demand. Econometrica, 1984, vol. 52, no. 3, pp. 541–561.
  4. Bhat C.R. A Multiple Discrete-continuous Extreme Value Model: Formulation and Application to Discretionary Time-Use Decisions. Transportation Research, Part B, 2005, vol. 39, no. 8, pp. 679–707.
  5. Reiss P.C., Wolak F.A. Structural Econometric Modeling: Rationales and Examples from Industrial Organization. Handbook of Econometrics, 2007, vol. 6A, pp. 4277–4415.
  6. Heckman J.J. Sample Selection Bias as a Specification Error. Econometrica, 1979, vol. 47, no. 1, pp. 153–161.
  7. Dubin J., McFadden D. An Econometric Analysis of Residential Electric Appliance Holdings and Consumption. Econometrica, 1984, vol. 52, no. 2, pp. 345–362.
  8. Lee L.F. Generalized Econometric Models with Selectivity. Econometrica, 1983, vol. 51, no. 2, pp. 507–512.
  9. Munizaga M., Jara-Díaz S., Greeven P., Bhat C. Econometric Calibration of Joint Time Assignment-Mode Choice Model. Transportation Science, 2008, vol. 42, no. 2, pp. 208–219.
  10. Habib K.M.N. Joint Model of Commuting Mode Choice, Work Start Time and Duration. Available at: Link_ for_Commuting_Mode_Choice_Work_start_Time _and_Work_Duration.
  11. Bhat C.R. Modeling the Commute Activity-Travel Pattern of Workers: Formulation and Empirical Analysis. Transportation Science, 2001, vol. 35, no. 1, pp. 61–79.
  12. Ye X., Pendyala R.M. A Probit-Based Joint Discrete-Continuous Model System: Analyzing the Relationship between Timing and Duration of Maintenance Activities. Transportation and Traffic Theory, 2009, vol. 18, pp. 403–423.
  13. Munizaga M., Correia R., Jara-Díaz S.R., Ortúzar J. Valuing Time with a Joint Mode Choice-Activity Model. International Journal of Transport Economics, 2006, vol. 33, no. 2, pp. 193–210.
  14. Kuhn H.W., Tucker A.W. Nonlinear Programming. In: Proceedings of the Second Berkeley Symposium on Mathematical Statistics and Probability. Berkeley, University of California Press, 1951, pp. 481–492.
  15. Satomura S., Kim J., Allenby G. Multiple Constraint Choice Models with Corner and Interior Solutions. Marketing Science, 2011, vol. 30, no. 3, pp. 481–490.
  16. Castro M., Bhat C., Pendyala R., Jara-Diaz S. Accommodating Multiple Constraints in the Multiple Discrete-Continuous Extreme Value (MDCEV) Choice Model. Transportation Research, Part B, 2012, vol. 46, no. 6, pp. 729–743.
  17. Parizat S., Shachar R. When Pavarotti meets Harry Potter at the Super Bowl. Working Paper, Tel Aviv University, 2010.
  18. Lee L., Pitt M. Microeconometric Models of Rationing, Imperfect Markets, and Non-Negativity Constraints. Journal of Econometrics, 1987, vol. 36, pp. 89–110.
  19. Deaton A., Muellbauer J. Economics and Consumer Behavior. Cambridge University Press, 1980.
  20. Kim J., Allenby G.M., Rossi P.E. Modeling Consumer Demand for Variety. Marketing Science, 2002, vol. 21, pp. 229–250.
  21. Bhat C.R. The Multiple Discrete-Continuous Extreme Value (MDCEV) Model: Role of Utility Function Parameters, Identification Considerations, and Model Extensions. Transportation Research Part B, 2008, vol. 42, pp. 274–303.
  22. Mäler K. Environmental Economics: A Theoretical Inquiry. John Hopkins University Press for Resources for the Future, Baltimore, MD, 1974.
  23. Gumbel E.J. Statistics of Extremes. New York, Columbia University Press, 1958.
  24. Von Haefen R.H., Phaneuf D.J. Kuhn – Tucker Demand System Approaches to Nonmarket Valuation. In: Applications of Simulation Methods in Environmental and Resource Economics. Springer, 2005.
  25. Von Haefen R.H. Incorporating Observed Choice into the Construction of Welfare Measures from Random Utility Models. Journal of Environmental Economics & Management, 2003, vol. 45, no. 2, pp. 145–165.
  26. Phaneuf D.J., Herriges J.A. Choice Set Definition Issues in a Kuhn – Tucker Model of Recreation Demand. Marine Resource Economics, 2000, vol. 14, pp. 343–355.
  27. Phaneuf D.J., Kling C.L., Herriges J.A. Estimation and Welfare Calculations in a Generalized Corner Solution Model with an Application to Recreation Demand. Review of Economics and Statistics, 2000, vol. 82, no. 1, pp. 83–92.
  28. Herriges J.A., Kling C.L., Phaneuf D.J. What’s the Use? Welfare Estimates from Revealed Preference Models when Weak Complementarity Does Not Hold. Journal of Environmental Economics and Management, 2004, vol. 47(1), pp. 55–70.
  29. Lee S., Allenby G.M. A Direct Utility Model for Market Basket Data. Fisher College of Business, Working Paper, 2009, no. 1443390. Available at: Link.
  30. Vásquez-Lavín F., Hanemann M. Functional Forms in Discrete-Continuous Choice Models with General Corner Solution. University of California Berkeley, CUDARE Working Paper Series, 2009, no. 1078.
  31. Pinjari A.R., Bhat C.R. A Multiple Discrete-Continuous Nested Extreme Value Model: Formulation and Application to Non-Worker Activity Time-Use and Timing Behavior on Weekdays. Transportation Research, Part B, 2010, vol. 44, no. 4, pp. 562–583.
  32. Pinjari A.R. Generalized Extreme Value (GEV)-based Error Structures for Multiple Discrete-Continuous Choice Models. Transportation Research, Part B, 2011, vol. 45, no. 3, pp. 474–489.
  33. Bhat С., Castro M., Mubassira K. A New Estimation Approach for the Multiple Discrete-Continuous Probit (MDCP) Choice Model. Transportation Research, Part B: Methodological, 2013, vol. 55, pp. 1–22.

View all articles of issue

 

ISSN 2311-8725 (Online)
ISSN 2073-039X (Print)

Journal current issue

Vol. 23, Iss. 3
March 2024

Archive