Spatial choice modelling: New opportunities to incorporate space into substitution patterns

Progress in Human Geography

Volumn 28, Issue 6, 2004, Pages 746-766

  Hunt, Len M ^a,c   Boots, Barry ^a   Kanaroglou, Pavlos S ^b  

^a WILFRID LAURIER UNIVERSITY   (Canada)

^b MCMASTER UNIVERSITY   (Canada)

^c ONTARIO MINISTRY OF NATURAL RESOURCES   (Canada)

Author keywords

Choice set; Competing destinations model; Generalized extreme value model; Mixed logit; Spatial choice modelling; Substitution

Indexed keywords

COMPETITIVENESS; MODELING; SPATIAL ANALYSIS; SUBSTITUTION;

EID: 11144271429     PISSN: 03091325     EISSN: None     Source Type: Journal    
DOI: 10.1191/0309132504ph517oa     Document Type: Article

References (85)

1. Albert, J.H. and Chib, S. 1993: Bayesian analysis of binary and polychotomous response data. Journal of the American Statistical Association 88, 669-79.
2. Allenby, G.M. and Lenk, P.J. 1994: Modeling household purchase behavior with logistic normal regression. Journal of the American Statistical Association 89, 1218-31.
3. Ben-Akiva, M.E. and Lerman, S.R. 1985: Discrete choice analysis: theory and application to travel demand. Cambridge, MA: MIT Press.
4. Ben-Akiva, M.E., Bolduc, D. and Walker, J. 2001: Specification, identification, and estimation of the logit kernel (or continuous mixed logit) model. Unpublished working paper, available at http://web.mit.edu/jwalker/www/JW_LK.pdf (last accessed 27 August 2004).
5. Ben-Akiva, M.E., McFadden, D., Train, K.E., Walker, J., Bhat, C.R., Bierlaire, M., Bolduc, D., Boersch-Supan, A., Brownstone, D., Bunch, D.S., Daly, A., De Palma, A., Gopinath, D.A, Karlstrom, A. and Minizaga, M.A. 2002: Hybrid choice models: progress and challenges. Marketing Letters 13, 163-75.
6. Bhat, C.R. 1997: Covariance heterogeneity in nested logit models: econometric structure and application to intercity travel. Transportation Research, Part B 31, 11-21.
7. Bhat, C.R. 1998: An analysis of travel mode and departure time choice for urban shopping trips. Transportation Research, Part B 32, 361-71.
8. Bhat, C.R. 2000: A multi-level cross-classified model for discrete response variables. Transportation Research, Part B 34, 567-82.
9. Bhat, C.R. 2001: Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model. Transportation Research, Part B 35, 677-93.
10. Bhat, C.R. 2002: Recent methodological advances relevant to activity and travel behaviour analysis. In Mahmassani, H.S., editor, In perpetual motion: travel behavior research opportunities and application challenges, New York: Pergamon, 381-414.
11. Bhat, C.R. 2003: Random utility-based discrete choice models for travel demand analysis. In Goulais, K., editor, Transportation system planning: methods and application, Boca Raton, FL: CRC Press, 1-30.
12. Bhat, C.R. and Guo, J. 2004: A mixed spatially correlated logit model: formulation and application to residential choice modeling. Transportation Research, Part B 38, 147-68.
13. Bhat, C.R. and Zhao, H. 2002: The spatial analysis of activity stop generation. Transportation Research, Part B 36, 557-75.
14. Bierlaire, M. 2001: A theoretical analysis of the cross-nested logit. Available online at http://roso.epfl.ch/mbi/papers/crossnested-report.pdf (last accessed 17 August 2004).
15. Bolduc, D. 1992: Generalized autoregressive errors in the multinomial probit model. Transportation Research, Part B 26, 155-70.
16. Bolduc, D., Dagenais, M.G. and Gaudry, M.J.I. 1989: Spatially autocorrelated errors in origin-destination models: a new specification applied to aggregate mode choice. Transportation Research, Part B 23, 361-72.
17. Bolduc, D., Fortin, B. and Fournier, M. 1996: The effect of incentive policies on the practice location of doctors: a multinomial probit analysis. Journal of Labor Economics 14, 703-32.
18. Bolduc, D., Fortin, B. and Gordon, S. 1997: Multinomial probit estimation of spatially interdependent choices: an empirical comparison of two new techniques. International Regional Science Review 20, 77-101.
19. Bolduc, D., Laferriere, R. and Santarossa, G. 1995: Spatial autoregressive error components in travel flow models: an application to aggregate mode choice. In Anselin, L. and Florax, R.J.G.M., editors, New directions in spatial econometrics, New York: Springer, 96-108.
20. Boots, B.N. and Kanaroglou, P.S. 1988: Incorporating the effects of spatial structure in discrete choice models of migration. Journal of Regional Science 28, 495-509.
21. Borgers, A. and Timmermans, H. 1987a: A context-sensitive model of spatial choice behaviour. In Golledge, R.G. and Timmermans, H., editors, Behavioural modelling in geography and planning, London: Croom Helm, 159-78.
22. Borgers, A. and Timmermans, H. 1987b: Choice mode specification, substitution and spatial structure effects. Regional Science and Urban Economics 17, 29-47.
23. Boyd, J.H. and Mellman, R.E. 1980: The effect of fuel economy standards on the U.S. automotive market: an hedonic demand analysis. Transportation Research, Part A 14, 367-78.
24. Bresnahan, T.F., Stern, S. and Trajtenberg, M. 1997: Market segmentation and the sources of rents from innovation: personal computers in the late 1980s. RAND Journal of Economics 28, S17-S44.
25. Cardell, N. and Dunbar, F.C. 1980: Measuring the societal impacts of automobile downsizing. Transportation Research, Part A 14, 423-34.
26. Cascetta, E. and Papola, A. 2001: Random utility models with implicit availability/perception of choice alternatives for the simulation of travel demand. Transportation Research, Part C 9, 249-63.
27. Daganzo, C. 1979: Multinomial probit: the theory and its application to demand forecasting. New York: Academic Press.
28. Daly, A.J. and Zachary, S. 1978: Improved choice models. In Hensher, D.A. and Dalvi, Q., editors, Determinants of travel choice Westmead: Saxon House, 159-78.
29. Domencich, T.A. and McFadden, D. 1975: Urban travel demand: a behavioral analysis: a Charles River Associates research study Contributions to economic analysis no. 93, Amsterdam: North-Holland Publishing.
30. Ferguson, M.R. and Kanaroglou, P.S. 1997: An empirical evaluation of the aggregated spatial choice model. International Regional Science Review 20, 53-75.
31. Fleming, M. 2004: Techniques for estimating spatially dependent discrete choice models. In Florax, R., Anselin, L. and Rey, S., editors, Advances in spatial econometrics, Heidelberg: Springer-Verlag.
32. Fotheringham, A.S. 1981: Spatial structure and distance-decay parameters. Annals of the Association of American Geographers 71, 425-36.
33. Fotheringham, A.S. 1983: A new set of spatial-interaction models: the theory of competing destinations. Environment and Planning A 15, 15-36.
34. Fotheringham, A.S. 1984: Spatial flows and spatial patterns. Environment and Planning A 16, 529-43.
35. Fotheringham, A.S. 1986: Modelling hierarchical destination choice. Environment and Planning A 18, 401-18.
36. Fotheringham, A.S. 1988: Consumer store choice and choice set definition. Marketing Science 7, 299-310.
37. Fotheringham, A.S. and O'Kelly, M.E. 1989: Spatial interaction models: formulations and applications. Amsterdam: Kluwer Academic.
38. Fotheringham, A.S., Nakaya, T., Yano, K., Openshaw, S. and Ishikawa, Y. 2001: Hierarchical destination choice and spatial interaction modelling: a simulation experiment. Environment and Planning A 33, 901-20.
39. Garrido, R.A. and Mahmassani, H.S. 2000: Forecasting freight transportation demand with the space-time multinomial probit model. Transportation Research, Part B 34, 403-18.
40. Golledge, R.G. and Timmermans, H.J.P. 1990: Applications of behavioural research on spatial problems I: cognition. Progress in Human Geography 42, 57-99.
41. Hausman, J.A. and Wise, D.A. 1978: A conditional probit model for qualitative choice: discrete decisions recognizing interdependence and heterogeneous preferences. Econometrica 46, 403-26.
42. Haynes, K.E. and Fotheringham, A.S. 1990: The impact of space on the application of discrete choice models. The Review of Regional Studies 20, 39-49.
43. Hensher, D.A. and Greene, W.H. 2003: The mixed logit model: the state practice. Transportation 30, 133-76.
44. Kamakura, W.A. and Srivastava, R.K. 1984: Predicting choice shares under conditions of brand interdependence. Journal of Marketing Research 21, 420-34.
45. Kanaroglou, P.S. and Ferguson, M.R. 1996: A discrete spatial choice model for aggregate destinations. Journal of Regional Science 36, 271-90.
46. Kanaroglou, P.S. and Ferguson, M.R. 1998: The aggregated spatial choice model vs. the multinomial logit: an empirical comparison using migration microdata. The Canadian Geographer 42, 218-31.
47. Koppelman, F.S. and Sethi, V. 2000: Closed form discrete choice models. In Hensher, D.A. and Button, K.J., editors, Handbook of transport modeling. Volume I: transport modeling, Oxford: Pergamon Press, 211-22.
48. Koppelman, F.S. and Wen, C.-H. 2000: The paired combinatorial logit model: properties, estimation and application. Transportation Research, Part B 34, 75-89.
49. Lo, L. 1990: A translog approach to consumer spatial behavior. Journal of Regional Science 30, 393-413.
50. Louviere, J.J., Hensher, D.A. and Swait, J.F. 2000: Stated choice methods: analysis and applications. New York: Cambridge University Press.
51. Louviere, J.J., Street, D., Carson, R., Ainslie, A., Deshazo, J.R., Cameron, T., Hensher, D.A., Kohn, R. and Marley, T. 2002: Dissecting the random component of utility. Marketing Letters 13, 177-93.
52. Luce, R. 1959: Individual choice behavior: a theoretical analysis. New York: Wiley.
53. Manski, C.F. 1973: The analysis of qualitative choice. Unpublished PhD dissertation, Department of Economics, Massachusetts Institute of Technology, Cambridge, MA.
54. Manski, C.F. 1977: The structure of random utility models. Theory and Decision 8, 229-54.
55. Manski, C.F. and Lerman, S.R. 1981: On the use of simulated frequencies to approximate choice probabilities. In Manski, C.F. and McFadden, D., editors, Structural analysis of discrete data, Cambridge, MA: MIT Press, 305-19.
56. McCulloch, R. and Rossi, P.E. 1994: An exact likelihood analysis of the multinomial probit model. Journal of Econometrics 64, 207-40.
57. McFadden, D. 1974: Conditional logit analysis of qualitative choice behavior. In Zarembka, P., editor, Frontiers in econometrics New York: Academic Press, 105-42.
58. McFadden, D. 1975: On independence structure and simultaneity in transportation demand analysis. Working paper no. 7511, Urban Travel Demand Forecasting Project, Department of Economics, University of California, Berkeley, CA.
59. McFadden, D. 1978: Modelling the choice of residential location. In Karlqvist, A., Lundqvist, L., Snickars, F. and Weibull, J.W., editors, Spatial interaction theory and planning models, Amsterdam: North Holland Publishing, 75-96.
60. McFadden, D. 1981: Econometric models of probabilistic choice. In Manski, C.F. and McFadden, D., editors, Structural analysis of discrete data, Cambridge, MA: MIT Press, 199-272.
61. McFadden, D. 1989: A method of simulated moments for estimation of discrete response models without numerical integration. Econometrica 57, 995-1026.
62. McFadden, D. 2000: Disaggregate behavioral travel demand's RUM side: a 30-year perspective. Available online at http://emlab.berkeley. edu/wp/mcfadden0300.pdf (last accessed 27 August 2004).
63. McFadden, D. and Train, K.E. 2000: Mixed MNL models for discrete response. Journal of Applied Econometrics 15, 447-70.
64. Meyer, R.J. 1980: A descriptive model of constrained residential search. Geographical Analysis 12, 21-32.
65. Miron, J.R. and Lo, L. 1997: A selection bias approach to destination choice. Geographical Analysis 29, 145-68.
66. Pellegrini, P.A. and Fotheringham, A.S. 1999: Intermetropolitan migration and hierarchical destination choice: a disaggregate analysis from the US public use microdata samples. Environment and Planning A 31, 1093-118.
67. Pellegrini, P.A. 2002: Modelling spatial choice: a review and synthesis in a migration context. Progress in Human Geography 26, 487-510.
68. Pellegrini, P.A., Fotheringham, A.S. and Lin, G. 1997: An empirical evaluation of parameter sensitivity to choice set definition in shopping destination choice models. Papers in Regional Science 76, 257-84.
69. Peters, T., Adamowicz, W.L. and Boxall, P.C. 1995: Influence of choice set considerations in modeling the benefits from improved water quality. Water Resources Research 31, 1781-87.
70. Small, K.A. 1987: A discrete choice model for ordered alternatives. Econometrica 55, 409-24.
71. Swait, J.F. 2001: Choice set generation within the generalized extreme value family of discrete choice models. Transportation Research, Part B 35, 643-66.
72. Thill, J.C. 1992: Choice set formation for destination choice modelling. Progress in Human Geography 16, 361-82.
73. Thill, J.C. and Horowitz, J.L. 1997: Travel-time constraints on destination-choice sets. Geographical Analysis 29, 108-23.
74. Thurstone, L. 1927: A law of comparative judgment. Psychological Review 34, 273-86.
75. Timmermans, H.J.P. and Golledge, R.G. 1990: Applications of behavioural research on spatial problems II: preference and choice. Progress in Human Geography 14, 311-54.
76. Train, K.E. 1999: Mixed logit models for recreation demand. In Herriges, J.A. and Kling, C.L., editors, Valuing recreation and the environment, Northampton, MA: Edward Elgar, 121-40.
77. Train, K.E. 2001: A comparison of hierarchical Bayes and maximum simulated likelihood for mixed logit. Available online at http://elsa.berkeley.edu/users/train/compare.pdf (last accessed 27 August 2004).
78. Train, K.E. 2003: Discrete choice methods with simulation. New York: Cambridge University Press.
79. Vovsha, P. 1997: The cross-nested logit model: application to mode choice in the Tel-Aviv metropolitan area. Paper presented at the 1997 Annual Transportation Research Board Meeting, Washington, D.C.
80. Walker, J. 2001: Extended discrete choice models: integrated framework, flexible error structures, and latent variables. Unpublished PhD dissertation, Massachusetts Institute of Technology, Cambridge, MA.
81. Walker, J. 2002: The mixed logit (or logit kernel) model: dispelling misconceptions of identification. Transportation Research Record 1805, 86-98.
82. Walker, J. and Ben-Akiva, M.E. 2002: Generalized random utility model. Mathematical Social Sciences 43, 303-43.
83. Wen, C.-H. and Koppelman, F.S. 2001: The generalized nested logit model. Transportation Research, Part B 35, 627-41.
84. Williams, H.C.W.L. 1977: On the formation of travel demand models and economic evaluation measures of user benefit. Environment and Planning A 9, 285-344.
85. Williams, H.C.W.L. and Ortuzar, J.D. 1982: Behavioural theories of dispersion and the mis-specification of travel demand models. Transportation Research, Part B 16, 167-219.