A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions
AbstractSeveral consumer demand choices are characterized by the choice of multiple alternatives simultaneously. An example of such a choice situation in activity-travel analysis is the type of discretionary (or leisure) activity to participate in and the duration of time investment of the participation. In this context, within a given temporal period (say a day or a week), an individual may decide to participate in multiple types of activities (for example, in-home social activities, out-of-home social activities, in-home recreational activities, out-of-home recreational activities, and out-of-home non-maintenance shopping activities). In this paper, we derive and formulate a utility theory-based model for discrete/continuous choice that assumes diminishing marginal utility as the level of consumption of any particular alternative increases (i.e., satiation). This assumption yields a multiple discreteness model (i.e., choice of multiple alternatives can occur simultaneously). This is in contrast to the standard discrete choice model that is based on assuming the absence of any diminishing marginal utility as the level of consumption of any alternative increases (i.e., no satiation), leading to the case of strictly single discreteness. The econometric model formulated here, which we refer to as the multiple discrete-continuous extreme value (MDCEV) model, has a surprisingly simple and elegant closed form expression for the discrete-continuous probability of not consuming certain alternatives and consuming given levels of the remaining alternatives. To our knowledge, we are the first to develop such a simple and powerful closed-form model for multiple discreteness in the literature. This formulation should constitute an important milestone in the area of multiple discreteness, just as the multinomial logit (MNL) represented an important milestone in the area of single discreteness. Further, the MDCEV model formulated here has the appealing property that it collapses to the familiar multinomial logit (MNL) choice model in the case of single discreteness. Finally, heteroscedasticity and/or correlation in unobserved characteristics affecting the demand of different alternatives can be easily incorporated within the MDCEV model framework using a mixing approach. The MDCEV model and its mixed variant are applied to analyze time-use allocation decisions among a variety of discretionary activities on weekends using data from the 2000 San Francisco Bay Area survey.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Elsevier in its journal Transportation Research Part B: Methodological.
Volume (Year): 39 (2005)
Issue (Month): 8 (September)
Contact details of provider:
Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/548/description#description
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Juster, F. Thomas, 1990. "Rethinking utility theory," Journal of Behavioral Economics, Elsevier, vol. 19(2), pages 155-179.
- Train,Kenneth E., 2009.
"Discrete Choice Methods with Simulation,"
Cambridge University Press, number 9780521747387, October.
- Toshiyuki Yamamoto & Ryuichi Kitamura, 1999. "An analysis of time allocation to in-home and out-of-home discretionary activities across working days and non- working days," Transportation, Springer, vol. 26(2), pages 231-250, May.
- Bhat, Chandra & Lockwood, Allison, 2004. "On distinguishing between physically active and physically passive episodes and between travel and activity episodes: an analysis of weekend recreational participation in the San Francisco Bay area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(8), pages 573-592, October.
- Jaehwan Kim & Greg M. Allenby & Peter E. Rossi, 2002. "Modeling Consumer Demand for Variety," Marketing Science, INFORMS, vol. 21(3), pages 229-250, December.
- Baltas, George, 2004. "A model for multiple brand choice," European Journal of Operational Research, Elsevier, vol. 154(1), pages 144-149, April.
- Lee, L-F., 1990.
"On Efficiency of Methods of Simulated Moments and Maximum Simulated Likelihood Estimation of Discrete Response Models,"
260, Minnesota - Center for Economic Research.
- Lee, Lung-Fei, 1992. "On Efficiency of Methods of Simulated Moments and Maximum Simulated Likelihood Estimation of Discrete Response Models," Econometric Theory, Cambridge University Press, vol. 8(04), pages 518-552, December.
- I. Meloni & L. Guala & A. Loddo, 2004. "Time allocation to discretionary in-home, out-of-home activities and to trips," Transportation, Springer, vol. 31(1), pages 69-96, February.
- Ram Pendyala & Konstadinos Goulias, 2002. "Time use and activity perspectives in travel behavior research," Transportation, Springer, vol. 29(1), pages 1-4, February.
- Bhat, Chandra R., 2003. "Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences," Transportation Research Part B: Methodological, Elsevier, vol. 37(9), pages 837-855, November.
- Chandra Bhat & Rajul Misra, 1999. "Discretionary activity time allocation of individuals between in-home and out-of-home and between weekdays and weekends," Transportation, Springer, vol. 26(2), pages 193-229, May.
- Gramm, Wendy Lee, 1975. "Household Utility Maximization and the Working Wife," American Economic Review, American Economic Association, vol. 65(1), pages 90-100, March.
- Hanemann, W Michael, 1984. "Discrete-Continuous Models of Consumer Demand," Econometrica, Econometric Society, vol. 52(3), pages 541-61, May.
- Pradeep K. Chintagunta, 1993. "Investigating Purchase Incidence, Brand Choice and Purchase Quantity Decisions of Households," Marketing Science, INFORMS, vol. 12(2), pages 184-208.
- Lu, Xuedong & Pas, Eric I., 1999. "Socio-demographics, activity participation and travel behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 33(1), pages 1-18, January.
- D Damm & S R Lerman, 1981. "A theory of activity scheduling behavior," Environment and Planning A, Pion Ltd, London, vol. 13(6), pages 703-718, June.
- Terza, Joseph V & Wilson, Paul W, 1990. "Analyzing Frequencies of Several Types of Events: A Mixed Multinomial-Poisson Approach," The Review of Economics and Statistics, MIT Press, vol. 72(1), pages 108-15, February.
- Puneet Manchanda & Asim Ansari & Sunil Gupta, 1999. "The “Shopping Basket”: A Model for Multicategory Purchase Incidence Decisions," Marketing Science, INFORMS, vol. 18(2), pages 95-114.
- Dubin, Jeffrey A & McFadden, Daniel L, 1984. "An Econometric Analysis of Residential Electric Appliance Holdings and Consumption," Econometrica, Econometric Society, vol. 52(2), pages 345-62, March.
- Munshi, Kaivan, 1993. "Urban passenger travel demand estimation: A household activity approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 27(6), pages 423-432, November.
- John W. Walsh, 1995. "Flexibility in Consumer Purchasing for Uncertain Future Tastes," Marketing Science, INFORMS, vol. 14(2), pages 148-165.
- Gary S. Becker, 1981. "A Treatise on the Family," NBER Books, National Bureau of Economic Research, Inc, number beck81-1, May.
- Bhat, Chandra R. & Gossen, Rachel, 2004. "A mixed multinomial logit model analysis of weekend recreational episode type choice," Transportation Research Part B: Methodological, Elsevier, vol. 38(9), pages 767-787, November.
- Chandra Bhat & Frank Koppelman, 1999. "A retrospective and prospective survey of time-use research," Transportation, Springer, vol. 26(2), pages 119-139, May.
- Sergio Jara-Díaz, 2003. "On the goods-activities technical relations in the time allocation theory," Transportation, Springer, vol. 30(3), pages 245-260, August.
- Hendel, Igal, 1999. "Estimating Multiple-Discrete Choice Models: An Application to Computerization Returns," Review of Economic Studies, Wiley Blackwell, vol. 66(2), pages 423-46, April.
- Bhat, Chandra R., 1998. "A model of post home-arrival activity participation behavior," Transportation Research Part B: Methodological, Elsevier, vol. 32(6), pages 387-400, August.
- Neeraj Arora & Greg M. Allenby & James L. Ginter, 1998. "A Hierarchical Bayes Model of Primary and Secondary Demand," Marketing Science, INFORMS, vol. 17(1), pages 29-44.
- Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
- Jean-Pierre Dubé, 2004. "Multiple Discreteness and Product Differentiation: Demand for Carbonated Soft Drinks," Marketing Science, INFORMS, vol. 23(1), pages 66-81, September.
This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page. reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
If references are entirely missing, you can add them using this form.