Travel demand models in the developing world: correcting for measurement errors

REFERENCES

• Baker J, Basu R, Cropper M, Lall S, Takeuchi A (2005) Urban poverty and transport: The case of Mumbai. World Bank Policy Research Working Paper 3693.
   Google Scholar
• Ben-Akiva M, McFadden D, Train K, Walker J, Bhat C, Bierlaire M, Bolduc D, Boersch-Supan A, Brownstone D, Bunch D, Daly A, de Palma A, Gopinath D, Karlstrom A, Munizaga A (2002) Hybrid choice models: Progress and challenges. Marketing Letters 13(3), 163–175.
   Web of Science ®Google Scholar
• Ben-Akiva M, Lerman SR (1985) Discrete Choice Analysis: Theory and Application to Travel Demand. Cambridge MA: The MIT Press.
   Google Scholar
• Berry S, Levinsohn J, Pakes A (1995) Automobile prices in market equilibrium. Econometrica 63, 841–889.
   Web of Science ®Google Scholar
• Berry S, Levinsohn J, Pakes A (2004) Differentiated products demand system from a combination of micro and macro data: The new car market. Journal of Political Economy 112, 68–105.
   Web of Science ®Google Scholar
• Bhatta BP, Larsen CH (2007) Measurement errors in data used in transportation models and their consequences in parameter estimates. Presented at the 11th World Conference on Transport Research, Berkeley CA.
   Google Scholar
• Bonen KA (1989) Structural Equations with Latent Variables. Wiley.
   Google Scholar
• Buzas JS, Tosteson TD, Stefanski LA (2003) Measurement Error. Institute of Statistics Mimeo Series 2544.
   Google Scholar
• Bwire H (2008) A Unified Framework for Selecting a Travel Demand Forecasting Model for Developing Countries. Transportation Planning and Technology 31(3), 347–368.
   Web of Science ®Google Scholar
• Chengdu Statistics Bureau (2001) Chengdu Statistical Yearbook.
   Google Scholar
• Deaton A (1985) The demand for personal travel in devel-oping countries: an empirical analysis. Transportation Research Record 1037, 59–66.
   Google Scholar
• Deng X (2006) Economic costs of motor vehicle emissions in China: A case study. Transportation Research Part D: Transport and Environment. Volume 11, Issue 3, 216–226.
   Web of Science ®Google Scholar
• Dargay J, Gately D (1999) Income's effect on car and vehi-cle ownership, worldwide: 1960-2015. Transportation Research A 33, 101–138.
   Google Scholar
• Dargay J, Gately D, Sommer M (2007) Vehicle Ownership and Income Growth, Worldwide: 1960–2030 Energy Journal 28(4).
   Web of Science ®Google Scholar
• Dissanayake D, Morikawa T (2002) Household travel behav-ior in developing countries: Nested logit model of vehicle ownership, mode choice, and trip chaining. Transportation Research Record 1805, 45–52.
   Google Scholar
• Goetzke F, Andrade PM (2009) Walkability as a sum-mary measure in a spatially autoregressive mode choice model: An instrumental variable approach. Advances in Spatial Sciences, Springer.
   Google Scholar
• Guevara CA (2010) Endogeneity and sampling of alternatives in spatial choice models. PhD Dissertation, MIT, USA.
   Google Scholar
• Guevara C, Ben-Akiva M (2006) Endogeneity in residential location choice models. Transportation Research Record 77, 60–66.
   Google Scholar
• Greene WH (2003) Econometric Analysis. Prentice Hall. Grumbine RE (2007) China's emergence and the prospects for global sustainability. BioScience 57(3), 249–255.
   Google Scholar
• Gunn HF, Whittaker JC (1981) Estimation errors for well-fitting gravity models. Working Paper 149. Institute for Transport Studies, University of Leeds.
   Google Scholar
• Heckman J, Robb R (1985) Alternative methods for evaluat-ing the impacts of interventions: An overview. Journal of Econometrics 30, 239–267.
   Web of Science ®Google Scholar
• Ibrahim SAK, Radin URS, Habshah M, Kassim H, Stevenson M, Hariza A (2006) Mode choice model for vulnerable motorcyclists in Malaysia. Traffic Injury Prevention 7(2), 150–154.
   Google Scholar
• International Monetary Fund (2006) World Economic Outlook Database. www.imf.org/external/pubs/ftIweo/2006/01/data/index.htm. Accessed May 2007.
   Google Scholar
• Jiang Y, Feng L, Wu H, Xu R (2007) Challenges and policy options for sustainable urban transportation development in China. Presented at the Transportation Research Board 86th Annual Meeting, Washington DC.
   Google Scholar
• Khisty CJ. Sriraj PS (1996) Use of scenario-building transpor-tation model for developing countries. Transportation Research Record 1563, 16–25.
   Google Scholar
• Kim HK, Wu SK, Hunger M (2006) A case study on measur-ing travel time, speed, and delay using GPS-instrumented test vehicles. Applications of Advanced Technology in Transportation, 9th International Conference, Chicago IL.
   Google Scholar
• Landry PF, Shen M (2005) Reaching migrants in survey research: the use of the Global Positioning System to reduce coverage bias in China. Political Analysis 13(1), 1–22.
   Web of Science ®Google Scholar
• Liu G (2006) A behavioral model of work-trip mode choice in Shanghai. Discussion Papers No. 444, Statistics Norway, Research Department.
   Google Scholar
• Louviere J, Train K, Ben-Akiva M, Bhat C, Brownstone D, Cameron TA, Carson RT, DeShazo JR, Fiebig D, Greene W, Hensher D, Waldman D (2005) Recent progress on endogeneity in choice modeling. Marketing Letters 16(3–4), 255–265.
   Google Scholar
• McFadden D (2000) Disaggregate behavioral travel demand's RUM Side: A 30-year retrospective. Presented at the International Association of Travel Behavior Research, Australia.
   Google Scholar
• Newman P, Kenworthy J (1999) Sustainability and Cities: Overcoming Automobile Dependence. Island Press. Washington, DC.
   Google Scholar
• Ortúzar J de D, Ivelic AM (1987) Effects of using more accu-rately measured level of service variables in the specifi-cation and stability of mode choice models. Proceeding 15th PTRC Summer Annual Meeting P290, 117–130. PTRC, London.
   Google Scholar
• Ortúzar J de D, Willumsen LG (2001) Modeling Transport. Wiley.
   Google Scholar
• Pannell CW (2002) China's continuing urban transition. Environment and Planning A 34, 1571–1589.
   Web of Science ®Google Scholar
• Santoso D, Tsunokawa K (2005) Spatial transferability and updating analysis of mode choice models in develop-ing countries. Transportation Planning and Technology 28(5), 341–355.
   Web of Science ®Google Scholar
• Santoso DS, Tsunokawa K (2010) Comparison of updat-ing techniques in transferability analysis of work trip mode choice models in developing countries. Journal of Advanced Transportation 44, 89–102.
   Web of Science ®Google Scholar
• Schipper L, Ng WS, Huizenga C (2007) Sustainable transport development in three medium sized Asian cities. Paper presented at the Transportation Research Board 86th Annual Meeting, Washington DC.
   Google Scholar
• Schneider A, Seto KC, Webster DR (2005) Urban growth in Chengdu, Western China: application of remote sensing to assess planning and policy outcomes. Environment and Planning B 32, 323–345.
   Web of Science ®Google Scholar
• Shalizi Z (2007) Energy and emissions: Local and global effects of the rise of China and India. World Bank Policy Research Working Paper 4209, April 2007.
   Google Scholar
• Srinivasan KK, Pradhan GN, Naidu GM (2007) Commute Mode Choice in a Developing Country Role of Subjective Factors and Variations in Responsiveness Across Captive, Semicaptive, and Choice Segments. Transportation Research Record 2038, 53–61.
   Google Scholar
• Steimetz SSC, Brownstone D (2005) Estimating commuters 'value of time' with noisy data: a multiple imputation approach. Transportation Research B 36, 865–889.
   Google Scholar
• Tadi RR, Khasnabis S (1990) Error analysis: A tool for select-ing travel demand models. Mathematical and Computer Modelling 14, 1170–1176.
   Web of Science ®Google Scholar
• Train K (2009) Discrete Choice Models with Simulation, sec-ond edition, Cambridge University Press.
   Google Scholar
• Train K, Winston C (2007) Vehicle choice behavior and the declining market share of U.S. automakers. International Economic Review 48, 1469–1496.
   Web of Science ®Google Scholar
• Walker JL, Ehlers E, Banerjee I, Dugundji ER (2010) Correcting for endogeneity in behavioral choice models with social influence variables. Transportation Research Part A, forthcoming.
   Google Scholar
• Walker J, Ben-Akiva M (2002) Generalized random utility model. Mathematical Social Sciences 43(3), 303–343.
   Web of Science ®Google Scholar
• World Bank (1997) Infrastructure notes: The value of time in economic evaluation of transport projects, lessons from recent research. Transport NO. OT-5. Prepared by KM Gwilliam.
   Google Scholar
• Yagi S, Mohammadian A (2009) An activity-based micro-simulation model of travel demand in the Jakarta met-ropolitan area. Journal of Choice Modelling 3(1), 32–57.
   Google Scholar
• Zhang KH, Song S (2003) Rural-urban migration and urban-ization in China: Evidence from time-series and cross-section analyses. China Economic Review 14, 386–400.
   Web of Science ®Google Scholar