A framework for transportation and land use integration as a parallel constrained multiple discrete-continuous extreme value (PC-MDCEV) home production model

References

• Allenby, G. M., J. Kim, and P. E. Rossi. 2017. “Economic Models of Choice.” In Handbook of Marketing Decision Models, 2nd ed., edited by B. Wirenga, and R. van der Lans, 199–222. Springer International Publishing. https://doi.org/10.1007/978-3-319-56941-3
   Google Scholar
• Alonso, W. 1964. Location and Land Use: Toward a General Theory of Land Rent. Cambridge: Harvard University Press.
   Google Scholar
• Amato, P. R., D. R. Johnson, A. Booth, and S. J. Rogers. 2003. “Continuity and Change in Marital Quality Between 1980 and 2000.” Journal of Marriage and Family 65 (1): 1–22. https://doi.org/10.1111/j.1741-3737.2003.00001.x.
   Web of Science ®Google Scholar
• Aptech. 2018. GAUSS. www.aptech.com.
   Google Scholar
• Arentze, T. A., D. Ettema, and H. J. P. Timmermans. 2010. “Incorporating Time and Income Constraints in Dynamic Agent-Based Models of Activity Generation and Time Use: Approach and Illustration.” Transportation Research Part C: Emerging Technologies 18 (1): 71–83. https://doi.org/10.1016/j.trc.2009.04.016.
   Web of Science ®Google Scholar
• Astroza, S., A. R. Pinjari, C. R. Bhat, and S. R. Jara-Díaz. 2017. “A Microeconomic Theory-Based Latent Class Multiple Discrete-Continuous Choice Model of Time Use and Goods Consumption.” Transportation Research Record: Journal of the Transportation Research Board 2664 (1): 31–41. https://doi.org/10.3141/2664-04
   Google Scholar
• Becker, G. S. 1965. “A Theory of the Allocation of Time.” The Economic Journal 75 (299): 493. https://doi.org/10.2307/2228949.
   Web of Science ®Google Scholar
• Ben-Akiva, M., and B. Francois. 1983. "Mu-Homogenous Generalized Extreme Value Model." Working Paper. Department of Civil Engineering, MIT.
   Google Scholar
• Bhat, C. R. 2005. “A Multiple Discrete-Continuous Extreme Value Model: Formulation and Application to Discretionary Time-use Decisions.” Transportation Research Part B: Methodological 39 (8): 679–707. https://doi.org/10.1016/j.trb.2004.08.003.
   Web of Science ®Google Scholar
• Bhat, C. 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 42 (3): 274–303. https://doi.org/10.1016/j.trb.2007.06.002.
   Web of Science ®Google Scholar
• Bhat, C. R. 2018. “A New Flexible Multiple Discrete–Continuous Extreme Value (MDCEV) Choice Model.” Transportation Research Part B: Methodological 110: 261–279. https://doi.org/10.1016/j.trb.2018.02.011.
   Web of Science ®Google Scholar
• Bhat, C. R., M. Castro, and A. R. Pinjari. 2015. “Allowing for Complementarity and Rich Substitution Patterns in Multiple Discrete-Continuous Models.” Transportation Research Part B: Methodological 81 (P1): 59–77. https://doi.org/10.1016/j.trb.2015.08.009
   Google Scholar
• Boyce, D., and H. Williams. 2015. Forecasting Urban Travel. Cheltenham: Edward Elgar Publishing Ltd.
   Google Scholar
• Browning, M., F. Bourguignon, and P.-A. Chiappori. 1994. “Income and Outcomes: A Structural Model of Intrahousehold Allocation.” Lechene Source: Journal of Political Economy. Accessed May 27, 2019. https://www.jstor.org/stable/pdf/2138780.pdf?refreqid=excelsior%3A9ee856035eaf0532983e7d346493147f.
   Google Scholar
• Browning, M., and P. A. Chiappori. 1998. “Efficient Intra-Household Allocations: A General Characterization and Empirical Tests.” Accessed May 27, 2019. https://www.jstor.org/stable/pdf/2999616.pdf?refreqid=excelsior%3A04270399e3d1f5851a7cb1775dd3621b.
   Google Scholar
• Chiappori, P. A. 1997. “Introducing Household Production in Collective Models of Labor Supply.” Journal of Political Economy 105 (1): 191–209. https://doi.org/10.1086/262071.
   Web of Science ®Google Scholar
• Chiappori, P. A., A. de Palma, and N. Picard 2014. “Couple Residential Location and Spouses Workplaces.” In III Workshop on Urban Economics, June 9-10, Barcelona: 34. Accessed September 28, 2017. http://www.sustaincity.org/publications/WP_3.3_Couple_Chaippori_de_Palma_Picard.pdf .
   Google Scholar
• Chiappori, P.-A., and M. Mazzocco. 2017. “Static and Intertemporal Household Decisions.” Journal of Economic Literature 55 (3): 985–1045. https://doi.org/10.1257/jel.20150715.
   PubMed Web of Science ®Google Scholar
• Christensen, L. R., D. W. Jorgenson, and L. J. Lau. 1975. “Transcendental Logarithmic Utility Functions.” The American Economic Review 65 (3): 367–383. http://www.jstor.org/stable/1804840.
   Web of Science ®Google Scholar
• Cineli, B. 2020. “Money Management and Gender Equality: An Analysis of Dual-Earner Couples in Western Europe.” Family Relations, 803–819. https://doi.org/10.1111/fare.12465.
   Web of Science ®Google Scholar
• City of Toronto. 2022. 2021 Census: Population and Dwelling Counts. https://www.toronto.ca/wp-content/uploads/2022/02/92e3-City-Planning-2021-Census-Backgrounder-Population-Dwellings-Backgrounder.pdf.
   Google Scholar
• Deaton, A., and J. Muellbauer. 1980. “An Almost Ideal Demand System.” The American Economic Review 70 (3): 312–326. http://www.jstor.org/stable/1805222%5Cn http://www.jstor.org/stable/1805222?seq=1&cid=pdf-reference#references_tab_contents%5Cn http://about.jstor.org/terms.
   Web of Science ®Google Scholar
• DeSerpa, A. C. 1971. “A Theory of the Economics of Time.” The Economic Journal 81 (324): 828–846. https://doi.org/10.2307/2230320.
   Web of Science ®Google Scholar
• DMTI. 2016. Enhanced points of interest (EPOI) data. Accessed September 27, 2020. http://geo1.scholarsportal.info/#r/details/_uri@=4122041611.
   Google Scholar
• Duranton, Gilles, and Matthew A Turner. 2018. “Urban Form and Driving: Evidence from US Cities.” Journal of Urban Economics 108 (C): 170–191. https://doi.org/10.1016/j.jue.2018.10.003
   Google Scholar
• Eliasson, J. 2010. “The Influence of Accessibility on Residential Location.” In Residential Location Choice, edited by F. Pagliara, 137–164. Springer International Publishing. https://doi.org/10.1007/978-3-642-12788-5_7.
   Google Scholar
• Ettema, D., K. De Jong, H. Timmermans, and A. Bakema 2005. “PUMA: Multi-Agent Modelling of Urban Systems.” In Modelling Land-Use Change, 237–258. Dordrecht: Springer.
   Google Scholar
• Glaeser, E. L., J. Kolko, and A. Saiz. 2001. “Consumer City.” Journal of Economic Geography 1 (1): 27–50. https://doi.org/10.1093/jeg/1.1.27.
   Google Scholar
• Gliebe, J., and F. Koppelman. 2005. “Modeling Household Activity–Travel Interactions as Parallel Constrained Choices.” Transportation 32 (5): 449–471. https://doi.org/10.1007/s11116-005-5328-0.
   Web of Science ®Google Scholar
• Greene, J. 2014. Moral Tribes: Emotion, Reason, and the Gap between us and Them. Penguin Books. https://doi.org/10.1017/CBO9781107415324.004.
   Google Scholar
• Hägerstrand, T. 1970. “What About People in Regional Science?” Papers of the Regional Science Association 24 (1): 6–21. https://doi.org/10.1007/BF01936872
   Google Scholar
• Hamermesh, D. S. 2019. Spending Time: The Most Valuable Resource. Oxford University Press. Accessed September 2, 2020. https://www.amazon.ca/Spending-Time-Most-Valuable-Resource/dp/0190853832.
   Google Scholar
• Hawkins, J., and K. N. Habib. 2018. “Integrated Models of Land Use and Transportation for the Autonomous Vehicle Revolution.” Transport Reviews 39: 66–83. https://doi.org/10.1080/01441647.2018.1449033.
   Web of Science ®Google Scholar
• Hawkins, J., and K. N. Habib. 2021. “The Influence of Built Form on Patterns of Household Consumption: Evidence from American Household Expenditure.” In 100th Annual Meeting of the Transportation Research Board. Washington, DC. Accessed October 14, 2021. https://www.researchgate.net/publication/349735428_The_Influence_of_Built_Form_on_Patterns_of_Household_Consumption_Evidence_from_American_Household_Expenditure.
   Google Scholar
• Hawkins, J., and K. N. Habib. 2022. “A Multi-Source Data Fusion Framework for Joint Population, Expenditure, and Time Use Synthesis.” Transportation 50: 1323–1346. https://doi.org/10.1007/s11116-022-10279-8.
   Web of Science ®Google Scholar
• Hawkins, J., A. Weiss, and K. N. Habib. 2019. “Household-level Dynamics in Residential Location Choice Modelling with a Latent Auction Method.” Environment and Planning B: Urban Analytics and City Science 2: 314–330.
   Google Scholar
• Hössinger, R., F. Aschauer, S. Jara-Díaz, Simona Jokubauskaite, Basil Schmid, Stefanie Peer, Kay W. Axhausen, and Regine Gerike. 2019. “A Joint Time-Assignment and Expenditure-Allocation Model: Value of Leisure and Value of Time Assigned to Travel for Specific Population Segments.” Transportation 47 (3): 1439–1475. https://doi.org/10.1007/s11116-019-10022-w.
   PubMed Web of Science ®Google Scholar
• Hunt, J. D., and J. E. Abraham. 2009. PECAS for Spatial Economic Modelling: Theoretical Foundations. https://www.hbaspecto.com/resources/PECASTheoreticalFormulation.pdf.
   Google Scholar
• Jara-Díaz, S. R. 2003. “On the Goods-Activities Technical Relations in the Time Allocation Theory.” Transportation 30 (3): 245–260. https://doi.org/10.1023/A:1023936911351.
   Web of Science ®Google Scholar
• Jara-Díaz, S., and D. Candia. 2020. “A New Look at the Value of Leisure in Two-Worker Households.” Economics of Transportation 24: 100193. https://doi.org/10.1016/j.ecotra.2020.100193
   Web of Science ®Google Scholar
• Jara-Díaz, S. R., and F. J. Martínez. 1999. “On the Specification of Indirect Utility and Willingness to Pay for Discrete Residential Location Models.” Journal of Regional Science 39 (4): 675–688. https://doi.org/10.1111/0022-4146.00155.
   Web of Science ®Google Scholar
• Jara-Díaz, S. R., M. A. Munizaga, P. Greeven, Reinaldo Guerra, and Kay Axhausen. 2008. “Estimating the Value of Leisure from a Time Allocation Model.” Transportation Research Part B: Methodological 42 (10): 946–957. https://doi.org/10.1016/j.trb.2008.03.001.
   Web of Science ®Google Scholar
• Jokubauskaitė, S., R. Hössinger, F. Aschauer, Regine Gerike, Sergio Jara-Díaz, Stefanie Peer, Basil Schmid, Kay W. Axhausen, and Friedrich Leisch. 2019. “Advanced Continuous-Discrete Model for Joint Time-use Expenditure and Mode Choice Estimation.” Transportation Research Part B: Methodological 129: 397–421. https://doi.org/10.1016/j.trb.2019.09.010.
   Web of Science ®Google Scholar
• Konduri, K. C., S. A. Tagle, B. Sana, Ram M. Pendyala, and Sergio R Jara-Díaz. 2011. “A Joint Analysis of Time Use and Consumer Expenditure Data: An Examination of Two Alternative Approaches to Deriving Values of Time.” Transportation Research Record: Journal of the Transportation Research Board 2231 (1): 53–60. Accessed June 18, 2018. http://karthikkonduri.weebly.com/uploads/6/0/9/8/6098127/jointtimeuseexpendituremodels_kondurisebastiansanapendyalajaradiaz_trbversion_aug2010.pdf.
   Google Scholar
• Kooreman, P., and S. Wunderink. 1996. “Household Versus Individual Economic Behaviour.” In The Economics of Household Behaviour, 32–46. Macmillan Education UK. https://doi.org/10.1007/978-1-349-25436-1.
   Google Scholar
• Lavin, V., F. Hanemann, and W. Michael 2008. “Functional Forms in Discrete/Continuous Choice Models with General Corner Solution.” Accessed September 10, 2018. https://escholarship.org/uc/item/7z25t659.
   Google Scholar
• López-Ospina, H., F. J. Martínez, and C. E. Cortés. 2015. “A Time-Hierarchical Microeconomic Model of Activities.” Transportation 42 (2): 211–236. https://doi.org/10.1007/s11116-014-9530-9.
   Web of Science ®Google Scholar
• Lowry, I. S. 1964. A Model of Metropolis. https://www.rand.org/content/dam/rand/pubs/research_memoranda/2006/RM4035.pdf.
   Google Scholar
• Martinez, F. J. 2018. Microeconomic Modeling in Urban Science. 1st ed. Elsevier. https://doi.org/10.1007/978-1-349-25436-1.
   Google Scholar
• Mercer. 2023. Cost of Living. https://www.mercer.com/our-thinking/career/cost-of-living.html#city-ranking.
   Google Scholar
• Mills, E. 1967. “An Aggregative Model of Resource Allocation in a Metropolitan Area.” American Economic Review 62 (2): 197–210.
   Google Scholar
• Mincer, J. 1963. “Market Prices, Opportunity Costs, and Income Effects.” In Measurement in Economics, edited by C. Christ, 67–82. Stanford, CA: Stanford University Press.
   Google Scholar
• Moeckel, R. 2011. “Simulating Household Budgets for Housing and Transport.” In International Conference on Computers in Urban Planning and Urban Management, 1–14. http://silo.zone/doc/2011_moeckel_cupum.pdf.
   Google Scholar
• Moeckel, R. 2017. “Constraints in Household Relocation : Modeling Land-use / Transport Interactions That Respect Time and Monetary Budgets.” The Journal of Transport and Land Use 10 (2): 1–18. https://doi.org/10.5198/jtlu.2016.810.
   Google Scholar
• Moeckel, R., B. Schwarze, K. Spierkermann, and M. Wegener. 2007. “Microsimulation for Integrated Urban Modelling.” 11th World Conference on Transport Research, Berkeley, USA.
   Google Scholar
• Mondal, A., and C. R. Bhat. 2020. A New Closed Form Multiple Discrete-Continuous Extreme Value (MDCEV) Choice Model with Multiple Linear Constraints.
   Google Scholar
• Murphy, D. 2018. “Home Production, Expenditure, and Economic Geography.” Regional Science and Urban Economics 70: 112–126. https://doi.org/10.1016/j.regsciurbeco.2018.03.003.
   Web of Science ®Google Scholar
• Muth, R. F. 1969. Cities and Housing: The Spatial Pattern of Urban Residential Land Use. Chicago: University of Chicago Press.
   Google Scholar
• Newman, P., and J. Kenworthy. 1999. Sustainability and Cities : Overcoming Automobile Dependence / | University of Toronto Libraries, 1st ed. Washington, DC: Island Press. https://search.library.utoronto.ca/details?2963740.
   Google Scholar
• Pinjari, A. R., B. Augustin, V. Sivaraman, Ahmadreza Faghih Imani, Naveen Eluru, and Ram M. Pendyala. 2016. “Stochastic Frontier Estimation of Budgets for Kuhn-Tucker Demand Systems: Application to Activity Time-use Analysis.” Transportation Research Part A: Policy and Practice 88: 117–133. https://doi.org/10.1016/j.tra.2016.03.013.
   Web of Science ®Google Scholar
• Pinjari, A. R., and C. Bhat. 2010. “A Multiple Discrete-Continuous Nested Extreme Value (MDCNEV) Model: Formulation and Application to non-Worker Activity Time-use and Timing Behavior on Weekdays.” Transportation Research Part B: Methodological 44 (4): 562–583. https://doi.org/10.1016/j.trb.2009.08.001.
   Web of Science ®Google Scholar
• Pinjari, A. R., and C. Bhat. 2021. “Computationally Efficient Forecasting Procedures for Kuhn-Tucker Consumer Demand Model Systems: Application to Residential Energy Consumption Analysis.” Journal of Choice Modelling 39: 100283. https://doi.org/10.1016/j.jocm.2021.100283.
   Web of Science ®Google Scholar
• Pinjari, A. R., and V. Sivaraman. 2013. “A Time- and Money- Constrained Model of Household Vacation Travel Behavior: Formulation and Application of a Kuhn-Tucker Demand Model System.” In review, Transportation Research – Part B. Accessed October 18, 2018. http://abdulpinjari.weebly.com/uploads/9/6/7/8/9678119/pinjari_sivaraman_july4_2012_final_tr-b.pdf.
   Google Scholar
• Piovani, D., E. Arcaute, G. Uchoa, A. Wilson, and M. Batty. 2018. “Measuring Accessibility Using Gravity and Radiation Models.” Royal Society Open Science 5 (9): 171668. https://doi.org/10.1098/rsos.171668.
   PubMed Web of Science ®Google Scholar
• Putman, S. H. 1970. “Developing and Testing an Intra-Regional Model.” Regional Studies 4 (4): 473–490. https://doi.org/10.1080/09595237000185471
   Web of Science ®Google Scholar
• Putman, S. H. 1974. “Preliminary Results from an Integrated Transportation and Land Use Models Package.” Transportation 3 (3): 193–224. https://doi.org/10.1007/BF00165487.
   Web of Science ®Google Scholar
• Rappaport, J. 2008. “Consumption Amenities and City Population Density.” Regional Science and Urban Economics 38 (6): 533–552. https://doi.org/10.1016/j.regsciurbeco.2008.02.001
   Web of Science ®Google Scholar
• Rappaport, J. 2009. “The Increasing Importance of Quality of Life.” Journal of Economic Geography 9 (6): 779–804. https://doi.org/10.1093/jeg/lbp009.
   Web of Science ®Google Scholar
• Roback, J. 1982. “Wages, Rents, and the Quality of Life.” Journal of Political Economy 90 (6): 1257–1278. Accessed August 18, 2019. https://www-jstor-org.myaccess.library.utoronto.ca/stable/pdf/1830947.pdf?refreqid=excelsior%3Af642480fa41148dc3797601892775d4a
   Web of Science ®Google Scholar
• Rosenthal, S. S., and W. C. Strange. 2008. AGGLOMERATION AND HOURS WORKED. Accessed November 18, 2019. http://www.ipums.org.
   Google Scholar
• Salvini, P., and E. J. Miller. 2005. “ILUTE: An Operational Prototype of a Comprehensive Microsimulation Model of Urban Systems.” Networks and Spatial Economics 5 (2): 217–234. https://doi.org/10.1007/s11067-005-2630-5
   Web of Science ®Google Scholar
• Smailes, A. E. 1971. “Urban Systems.” Transactions of the Institute of British Geographers 53 (53): 1. https://doi.org/10.2307/621654.
   Google Scholar
• Statistics Canada. 2007. CANSIM table 282-0028. Accessed September 28, 2020. https://www150.statcan.gc.ca/n1/pub/71-222-x/2008001/sectionh/h-hours-heures-eng.htm.
   Google Scholar
• Statistics Canada. 2018. 2016 Census of Population. https://www12.statcan.gc.ca/census-recensement/alternative_alternatif.cfm?t=98-301-x2016001-eng.pdf&keng=4323&kfra=4480&l=eng&loc=/census-recensement/2016/ref/dict/98-301-x2016001-eng.pdf.
   Google Scholar
• Statistics Canada. 2022. Focus on Geography Series, 2021 Census of Population. https://www12.statcan.gc.ca/census-recensement/2021/as-sa/fogs-spg/page.cfm?lang=E&topic=1&dguid=2021S0503535.
   Google Scholar
• Tajaddini, A., G. Rose, K. M. Kockelman, and Hai L. Vu. 2020. “Models and Technologies for Smart, Sustainable and Safe Transportation Systems.” Models and Technologies for Smart, Sustainable and Safe Transportation Systems. https://doi.org/10.5772/INTECHOPEN.93827.
   Google Scholar
• van Nostrand, C., V. Sivaraman, and A. R. Pinjari. 2013. “Analysis of Long-Distance Vacation Travel Demand in the United States: A Multiple Discrete-Continuous Choice Framework.” Transportation 40 (1): 151–171. https://doi.org/10.1007/s11116-012-9397-6
   Web of Science ®Google Scholar
• Waddell, P. 2002. “UrbanSim: Modeling Urban Development for Land Use, Transportation, and Environmental Planning.” Journal of the American Planning Association 68 (3): 297–314. https://doi.org/10.1080/01944360208976274.
   Web of Science ®Google Scholar
• Waddell, P., G. Boeing, M. Gardner, and E. Porter 2018. “An Integrated Pipeline Architecture for Modeling Urban Land Use, Travel Demand, and Traffic Assignment.”
   Google Scholar
• Zach, F., S. Erker, and G. Stoeglehner. 2019. “Factors Influencing the Environmental and Economic Feasibility of District Heating Systems—a Perspective from Integrated Spatial and Energy Planning.” Energy, Sustainability and Society 9 (1). https://doi.org/10.1186/s13705-019-0202-7.
   PubMedGoogle Scholar
• Zheng, K., E. Yao, and Y. Zhang. 2021. “A Joint Model of Household Time use and Task Assignment for Elderly Couples with Multiple Constraints.” PLoS One 16 (3 March): e0247187. https://doi.org/10.1371/journal.pone.0247187.
   PubMed Web of Science ®Google Scholar