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Incorporating a multiple discrete-continuous outcome in the generalized heterogeneous data model: Application to residential self-selection effects analysis in an activity time-use behavior model

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  • Bhat, Chandra R.
  • Astroza, Sebastian
  • Bhat, Aarti C.
  • Nagel, Kai

Abstract

This paper makes both a methodological contribution as well as an empirical contribution. From a methodological perspective, we propose a new econometric approach for the estimation of joint mixed models that include a multiple discrete choice outcome and a nominal discrete outcome, in addition to the count, binary/ordinal outcomes, and continuous outcomes considered in traditional structural equation models. These outcomes are modeled together by specifying latent underlying unobserved individual lifestyle, personality, and attitudinal factors that impact the many outcomes, and generate the jointness among the outcomes. From an empirical perspective, we analyze residential location choice, household vehicle ownership choice, as well as time-use choices, and investigate the extent of association versus causality in the effects of residential density on activity participation and mobility choices. The sample for the empirical application is drawn from a travel survey conducted in the Puget Sound Region in 2014. The results show that residential density effects on activity participation and motorized auto ownership are both associative as well as causal, emphasizing that accounting for residential self-selection effects are not simply esoteric econometric pursuits, but can have important implications for land-use policy measures that focus on neo-urbanist design.

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  • Bhat, Chandra R. & Astroza, Sebastian & Bhat, Aarti C. & Nagel, Kai, 2016. "Incorporating a multiple discrete-continuous outcome in the generalized heterogeneous data model: Application to residential self-selection effects analysis in an activity time-use behavior model," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 52-76.
  • Handle: RePEc:eee:transb:v:91:y:2016:i:c:p:52-76
    DOI: 10.1016/j.trb.2016.03.007
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    References listed on IDEAS

    as
    1. Bhat, Chandra R., 2000. "A multi-level cross-classified model for discrete response variables," Transportation Research Part B: Methodological, Elsevier, vol. 34(7), pages 567-582, September.
    2. Bhat, Chandra R. & Eluru, Naveen, 2009. "A copula-based approach to accommodate residential self-selection effects in travel behavior modeling," Transportation Research Part B: Methodological, Elsevier, vol. 43(7), pages 749-765, August.
    3. Xiaoguang Wang & Joe Grengs & Lidia Kostyniuk, 2013. "Visualizing Travel Patterns with a GPS Dataset: How Commuting Routes Influence Non-Work Travel Behavior," Journal of Urban Technology, Taylor & Francis Journals, vol. 20(3), pages 105-125, July.
    4. Lissy La Paix & Michel Bierlaire & Elisabetta Cherchi & Andrés Monzón, 2013. "How urban environment affects travel behaviour: integrated choice and latent variable model for travel schedules," Chapters, in: Stephane Hess & Andrew Daly (ed.), Choice Modelling, chapter 10, pages 211-228, Edward Elgar Publishing.
    5. Terence Reilly & Robert M. O'Brien, 1996. "Identification of Confirmatory Factor Analysis Models of Arbitrary Complexity," Sociological Methods & Research, , vol. 24(4), pages 473-491, May.
    6. Golob, Thomas F., 2003. "Structural equation modeling for travel behavior research," Transportation Research Part B: Methodological, Elsevier, vol. 37(1), pages 1-25, January.
    7. Mokhtarian, Patricia L. & Cao, Xinyu, 2008. "Examining the impacts of residential self-selection on travel behavior: A focus on methodologies," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 204-228, March.
    8. Hwang, Jinsoo & Han, Heesup, 2014. "Examining strategies for maximizing and utilizing brand prestige in the luxury cruise industry," Tourism Management, Elsevier, vol. 40(C), pages 244-259.
    9. Pinjari, Abdul Rawoof & Bhat, Chandra R. & Hensher, David A., 2009. "Residential self-selection effects in an activity time-use behavior model," Transportation Research Part B: Methodological, Elsevier, vol. 43(7), pages 729-748, August.
    10. Kim, Jinwon & Brownstone, David, 2013. "The impact of residential density on vehicle usage and fuel consumption: Evidence from national samples," Energy Economics, Elsevier, vol. 40(C), pages 196-206.
    11. Munkin, Murat K. & Trivedi, Pravin K., 2008. "Bayesian analysis of the ordered probit model with endogenous selection," Journal of Econometrics, Elsevier, vol. 143(2), pages 334-348, April.
    12. Cynthia Chen & Hongmian Gong & Robert Paaswell, 2008. "Role of the built environment on mode choice decisions: additional evidence on the impact of density," Transportation, Springer, vol. 35(3), pages 285-299, May.
    13. Brownstone, David & Fang, Hao (Audrey), 2014. "A vehicle ownership and utilization choice model with endogenous residential density," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 7(2), pages 135-151.
    14. Bhat, Chandra R. & Guo, Jessica Y., 2007. "A comprehensive analysis of built environment characteristics on household residential choice and auto ownership levels," Transportation Research Part B: Methodological, Elsevier, vol. 41(5), pages 506-526, June.
    15. Cao, Xinyu & Mokhtarian, Patricia & Handy, Susan, 2008. "Examining The Impacts of Residential Self-Selection on Travel Behavior: Methodologies and Empirical Findings," Institute of Transportation Studies, Working Paper Series qt08x1k476, Institute of Transportation Studies, UC Davis.
    16. Wendy Bohte & Kees Maat & Bert van Wee, 2009. "Measuring Attitudes in Research on Residential Self‐Selection and Travel Behaviour: A Review of Theories and Empirical Research," Transport Reviews, Taylor & Francis Journals, vol. 29(3), pages 325-357, February.
    17. Corinne Autant‐Bernard & James P. LeSage, 2011. "Quantifying Knowledge Spillovers Using Spatial Econometric Models," Journal of Regional Science, Wiley Blackwell, vol. 51(3), pages 471-496, August.
    18. Bhat, Chandra R., 2015. "A new generalized heterogeneous data model (GHDM) to jointly model mixed types of dependent variables," Transportation Research Part B: Methodological, Elsevier, vol. 79(C), pages 50-77.
    19. Bhat, Chandra R. & Sen, Sudeshna & Eluru, Naveen, 2009. "The impact of demographics, built environment attributes, vehicle characteristics, and gasoline prices on household vehicle holdings and use," Transportation Research Part B: Methodological, Elsevier, vol. 43(1), pages 1-18, January.
    20. Katsikatsou, Myrsini & Moustaki, Irini & Yang-Wallentin, Fan & Jöreskog, Karl G., 2012. "Pairwise likelihood estimation for factor analysis models with ordinal data," LSE Research Online Documents on Economics 43182, London School of Economics and Political Science, LSE Library.
    21. Bhat, Chandra R., 2008. "The multiple discrete-continuous extreme value (MDCEV) model: Role of utility function parameters, identification considerations, and model extensions," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 274-303, March.
    22. Kobe Boussauw & Tijs Neutens & Frank Witlox, 2012. "Relationship between Spatial Proximity and Travel-to-Work Distance: The Effect of the Compact City," Regional Studies, Taylor & Francis Journals, vol. 46(6), pages 687-706, September.
    23. Bhat, Chandra R., 2001. "Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 677-693, August.
    24. Bernardo, Christina & Paleti, Rajesh & Hoklas, Megan & Bhat, Chandra, 2015. "An empirical investigation into the time-use and activity patterns of dual-earner couples with and without young children," Transportation Research Part A: Policy and Practice, Elsevier, vol. 76(C), pages 71-91.
    25. Bhat, Chandra R., 2005. "A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions," Transportation Research Part B: Methodological, Elsevier, vol. 39(8), pages 679-707, September.
    26. Cristiano Varin & Paolo Vidoni, 2005. "A note on composite likelihood inference and model selection," Biometrika, Biometrika Trust, vol. 92(3), pages 519-528, September.
    27. Katsikatsou, Myrsini & Moustaki, Irini & Yang-Wallentin, Fan & Jöreskog, Karl G., 2012. "Pairwise likelihood estimation for factor analysis models with ordinal data," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4243-4258.
    28. Bhat, Chandra R., 2011. "The maximum approximate composite marginal likelihood (MACML) estimation of multinomial probit-based unordered response choice models," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 923-939, August.
    29. Van Acker, Veronique & Mokhtarian, Patricia L. & Witlox, Frank, 2014. "Car availability explained by the structural relationships between lifestyles, residential location, and underlying residential and travel attitudes," Transport Policy, Elsevier, vol. 35(C), pages 88-99.
    30. Keane, Michael P, 1992. "A Note on Identification in the Multinomial Probit Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(2), pages 193-200, April.
    31. Bhat, Chandra R. & Astroza, Sebastian & Sidharthan, Raghuprasad & Alam, Mohammad Jobair Bin & Khushefati, Waleed H., 2014. "A joint count-continuous model of travel behavior with selection based on a multinomial probit residential density choice model," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 31-51.
    32. Steven Farber & Antonio Páez & Ruben Mercado & Matthew Roorda & Catherine Morency, 2011. "A time-use investigation of shopping participation in three Canadian cities: is there evidence of social exclusion?," Transportation, Springer, vol. 38(1), pages 17-44, January.
    33. Li, Guoxin & Li, Guofeng & Kambele, Zephaniah, 2012. "Luxury fashion brand consumers in China: Perceived value, fashion lifestyle, and willingness to pay," Journal of Business Research, Elsevier, vol. 65(10), pages 1516-1522.
    34. Tim Schwanen & Patricia L. Mokhtarian, 2007. "Attitudes toward travel and land use and choice of residential neighborhood type: Evidence from the San Francisco bay area," Housing Policy Debate, Taylor & Francis Journals, vol. 18(1), pages 171-207, January.
    35. Joan Walker & Jieping Li, 2007. "Latent lifestyle preferences and household location decisions," Journal of Geographical Systems, Springer, vol. 9(1), pages 77-101, April.
    36. Bhat, Chandra R. & Singh, Sujit K., 2000. "A comprehensive daily activity-travel generation model system for workers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 34(1), pages 1-22, January.
    37. Bhat, Chandra R. & Steed, Jennifer L., 2002. "A continuous-time model of departure time choice for urban shopping trips," Transportation Research Part B: Methodological, Elsevier, vol. 36(3), pages 207-224, March.
    38. Bhat, Chandra R. & Koppelman, Frank S., 1993. "A conceptual framework of individual activity program generation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 27(6), pages 433-446, November.
    39. Bert van Wee, 2009. "Self‐Selection: A Key to a Better Understanding of Location Choices, Travel Behaviour and Transport Externalities?," Transport Reviews, Taylor & Francis Journals, vol. 29(3), pages 279-292, January.
    40. Andrew Daly & Stephane Hess & Bhanu Patruni & Dimitris Potoglou & Charlene Rohr, 2012. "Using ordered attitudinal indicators in a latent variable choice model: a study of the impact of security on rail travel behaviour," Transportation, Springer, vol. 39(2), pages 267-297, March.
    41. Bhat, Chandra R. & Dubey, Subodh K., 2014. "A new estimation approach to integrate latent psychological constructs in choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 68-85.
    42. Corinne Autant-Bernard & James Lesage, 2011. "Quantifying knowledge spillovers using spatial econometric tools," Post-Print halshs-00617709, HAL.
    43. John Gliebe & Frank Koppelman, 2002. "A model of joint activity participation between household members," Transportation, Springer, vol. 29(1), pages 49-72, February.
    44. Abdul Rawoof Pinjari & Chandra R. Bhat, 2011. "Activity-based Travel Demand Analysis," Chapters, in: André de Palma & Robin Lindsey & Emile Quinet & Roger Vickerman (ed.), A Handbook of Transport Economics, chapter 10, Edward Elgar Publishing.
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    Cited by:

    1. Astroza, Sebastian & Bhat, Prerna C. & Bhat, Chandra R. & Pendyala, Ram M. & Garikapati, Venu M., 2018. "Understanding activity engagement across weekdays and weekend days: A multivariate multiple discrete-continuous modeling approach," Journal of choice modelling, Elsevier, vol. 28(C), pages 56-70.
    2. Bhat, Chandra R., 2018. "A new flexible multiple discrete–continuous extreme value (MDCEV) choice model," Transportation Research Part B: Methodological, Elsevier, vol. 110(C), pages 261-279.
    3. Leung, Kevin Y.K. & Astroza, Sebastian & Loo, Becky P.Y. & Bhat, Chandra R., 2019. "An environment-people interactions framework for analysing children's extra-curricular activities and active transport," Journal of Transport Geography, Elsevier, vol. 74(C), pages 341-358.
    4. Enam, Annesha & Konduri, Karthik C. & Pinjari, Abdul R. & Eluru, Naveen, 2018. "An integrated choice and latent variable model for multiple discrete continuous choice kernels: Application exploring the association between day level moods and discretionary activity engagement choi," Journal of choice modelling, Elsevier, vol. 26(C), pages 80-100.
    5. Lavieri, Patrícia S. & Dai, Qichun & Bhat, Chandra R., 2018. "Using virtual accessibility and physical accessibility as joint predictors of activity-travel behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 527-544.
    6. Mothafer, Ghasak I.M.A. & Yamamoto, Toshiyuki & Shankar, Venkataraman N., 2018. "A multivariate heterogeneous-dispersion count model for asymmetric interdependent freeway crash types," Transportation Research Part B: Methodological, Elsevier, vol. 108(C), pages 84-105.
    7. Bhat, Chandra R. & Pinjari, Abdul R. & Dubey, Subodh K. & Hamdi, Amin S., 2016. "On accommodating spatial interactions in a Generalized Heterogeneous Data Model (GHDM) of mixed types of dependent variables," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 240-263.
    8. Dong, Chunjiao & Shao, Chunfu & Clarke, David B. & Nambisan, Shashi S., 2018. "An innovative approach for traffic crash estimation and prediction on accommodating unobserved heterogeneities," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 407-428.

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