Change of Scale and Forecasting with the Control-Function Method in Logit Models

Published Online:https://doi.org/10.1287/trsc.1110.0404

References

  • Amemiya T. The estimation of a simultaneous equation generalized probit model. Econometrica (1978) 46(5):1193–1205CrossrefGoogle Scholar
  • Ben-Akiva M., Lerman S.Discrete Choice Analysis, Theory and Application to Travel Demand (1985) (MIT Press, Cambridge, MA) Google Scholar
  • Berry S., Levinsohn J., Pakes A. Automobile prices in market equilibrium. Econometrica (1995) 63(4):841–90CrossrefGoogle Scholar
  • Bhat C., Guo J. A mixed spatially correlated logit model: Formulation and application to residential choice modeling. Transportation Res. Part B (2004) 38(2):147–168CrossrefGoogle Scholar
  • Chesher A. Instrumental variables models for discrete outcomes. Econometrica (2010) 78(2):575–601CrossrefGoogle Scholar
  • Cramer J. Robustness of logit analysis: Unobserved heterogeneity and mis-specified disturbances. Oxford Bull. Econom. Statist. (2007) 69(4):545–555CrossrefGoogle Scholar
  • Daly A. Elasticity, model scale and error. Presented at the European Transport Conf. (2008) Leeuwenhorst, The NetherlandsAccessed December 2010, http://www.etcproceedings.org/Google Scholar
  • Guevara C. Endogeneity and sampling of alternatives in spatial choice models. (2010) . Ph.D. Thesis, Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MAGoogle Scholar
  • Guevara C., Ben-Akiva M. Endogeneity in residential location choice models. Transportation Res. Record (2006) 1977:60–66CrossrefGoogle Scholar
  • Hausman J. Specification tests in econometrics. Econometrica (1978) 46(6):1251–1272CrossrefGoogle Scholar
  • Hausman J., Bresnahan T. F., Gordon R. J. Valuation of new goods under perfect and imperfect competition. The Economics of New Goods, Studies in Income and Wealth (1996) 58(National Bureau of Economic Research, Chicago) 207–248Google Scholar
  • Heckman J. Dummy endogenous variables in a simultaneous equation system. Econometrica (1978) 46(4):931–959CrossrefGoogle Scholar
  • Jara-Díaz S., Guevara C. Behind the subjective value of travel time savings: The perception of work, leisure and travel from a joint mode choice—Activity model. J. Transport Econom. Policy (2003) 37(1):29–46Google Scholar
  • Karaca-Mandic P., Train K. Standard error correction in two-stage estimation with nested samples. Econometrics J. (2003) 6(2):401–407CrossrefGoogle Scholar
  • Lee L. Specification error in multinomial logit models. J. Econometrics (1982) 20(2):197–209CrossrefGoogle Scholar
  • Levine J. Rethinking accessibility and jobs-housing balance. J. Amer. Planning Assoc. (1998) 64(2):133–149CrossrefGoogle Scholar
  • Martínez F., Henríquez R. The RB&SM: A random bidding and supply land use equilibrium model. Transportation Res. B (2007) 41(6):632–651CrossrefGoogle Scholar
  • Martinez L., Viegas J. Effects of transportation accessibility on residential property values: A hedonic price model in the Lisbon metropolitan area. Transportation Res. Record (2009) 2115:127–137CrossrefGoogle Scholar
  • Martinez L., Abreu J., Viegas J. Assessment of residential location satisfaction in Lisbon metropolitan area. Presented at The 89th Transportation Res. Board Annual Meeting (2010) Washington, DCConference DVD. http://pubsindex.trb.org/orderform.htmlGoogle Scholar
  • Nevo A. Measuring market power in the ready-to-eat cereal industry. Econometrica (2001) 69(2):307–342CrossrefGoogle Scholar
  • Newey W. Semiparametric estimation of limited dependent variable models with endogenous explanatory variables. Annales de L'insee (1985) 59/60:219–237Google Scholar
  • Park S., Gupta S. A simulated maximum likelihood estimator for the random coefficient logit model using aggregate data. J. Marketing Res. (2009) 46(4):531–542CrossrefGoogle Scholar
  • Petrin A., Train K. Omitted product attributes in discrete choice models. (2003) . NBER Working Papers 9452, National Bureau of Economic Research, IncGoogle Scholar
  • Quigley J. Housing demand in the short run: An analysis of polytomous choice. Explorations Econom. Res. (1976) 3(1):76–102Google Scholar
  • R Development Core Team R: A language and environment for statistical computing. (2008) . R Foundation for Statistical Computing, Vienna. Retrieved December 2010 from http://www.R-project.orgGoogle Scholar
  • Rivers D., Vuong Q. Limited information estimators and exogeneity tests for simultaneous probit models. J. Econometrics (1988) 39(3):347–366CrossrefGoogle Scholar
  • Ruud P. Sufficient conditions for the consistency of maximum likelihood estimation despite misspecification of distribution in multinomial discrete models. Econometrica (1983) 51(1):225–228CrossrefGoogle Scholar
  • Sermons M., Koppelman F. Representing the differences between female and male commute behavior in residential location choice models. J. Trans. Geography (2001) 9(2):101–110CrossrefGoogle Scholar
  • Villas-Boas A., Winer R. Endogeneity in brand choice models. Management Sci. (1999) 45(10):1324–1338LinkGoogle Scholar
  • Waddell P. A multinomial logit model of race and urban structure. Urban Geography (1992) 13(2):127–141CrossrefGoogle Scholar
  • Waddell P., Wang L., Liu X., Brail R. UrbanSim: An evolving planning support system for evolving communities. Planning Support Systems for Cities and Regions (2008) (Lincoln Institute for Land Policy, Cambridge, MA) 103–138Google Scholar
  • Walker J., Li J., Srinivasan S., Bolduc D. Travel demand models in the developing world: Correcting for measurement errors. Transportation Lett.: Internat. J. Transportation Res. (2010) 2(4):231–243CrossrefGoogle Scholar
  • Wooldridge J.Econometric Analysis of Cross-Section and Panel Data (2002) (MIT Press, Cambridge, MA) Google Scholar
  • Yatchew A., Griliches Z. Specification error in probit models. Rev. Econom. Statist. (1985) 67(1):134–139CrossrefGoogle Scholar
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