Generalized Extreme Value models for count data: Application to worker telecommuting frequency choices

Transportation Research Part B: Methodological

Volumn 83, Issue , 2016, Pages 104-120

  Paleti, Rajesh ^a  

^a Old Dominion University   (United States)

Author keywords

Count data; GEV models; Negative Binomial model; Poisson model; Random Utility Maximization; Telecommuting

Indexed keywords

BINS; MAXIMUM LIKELIHOOD; MAXIMUM LIKELIHOOD ESTIMATION;

COUNT DATUM; GENERALIZED EXTREME VALUE; NEGATIVE BINOMIAL MODELS; NONNEGATIVE INTEGERS; POISSON MODEL; PREDICTIVE PERFORMANCE; RANDOM UTILITY MAXIMIZATIONS; RANDOM UTILITY MODEL;

TELECOMMUTING;

COMPUTER SIMULATION; LOGIT ANALYSIS; NUMERICAL MODEL; OPTIMIZATION; POISSON RATIO; TELECOMMUTING;

EID: 84949552273     PISSN: 01912615     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.trb.2015.11.008     Document Type: Article

References (34)

1. Ahmed M., Huang H., Abdel-Aty M., Guevara B. Exploring a Bayesian hierarchical approach for developing safety performance functions for a mountainous freeway. Accident Analysis & Prevention 2011, 43(4):1581-1589.
2. Asgari H., Jin X., Mohseni A. Choice, frequency, and engagement: framework for telecommuting behavior analysis and modeling. Transportation Research Record: Journal of the Transportation Research Board 2014, 2413:101-109.
3. Bernardino A., Ben-Akiva M. Modeling the process of adoption of telecommuting: comprehensive framework. Transportation Research Record: Journal of the Transportation Research Board 1996, 1552:161-170.
4. Bhat C.R., Paleti R., Castro M. A new utility-consistent econometric approach to multivariate count data modeling. Journal of Applied Econometrics 2015, 30(5):806-825.
5. Bhat C.R., Paleti R., Singh P. A spatial multivariate count model for firm location decisions. Journal of Regional Science 2014, 54(3):462-502.
6. Bhat C.R., Pulugurta V. A comparison of two alternative behavioral choice mechanisms for household auto ownership decisions. Transportation Research Part B 1998, 32(1):61-75.
7. Bowman J.L., Ben-Akiva M.E. Activity-based disaggregate travel demand model system with activity schedules. Transportation Research Part A 2001, 35(1):1-28.
8. Burda M., Harding M., Hausman J. Understanding Choice Intensity: A Poisson Mixture Model With Logit-Based Random Utility Selective Mixing 2009, Mimeo.
9. Castro M., Paleti R., Bhat C.R. A latent variable representation of count data models to accommodate spatial and temporal dependence: Application to predicting crash frequency at intersections. Transportation Research Part B 2012, 46(1):253-272.
10. Daly A. Improved methods for trip generation. Transportation Planning Methods: Volume 11: Proceedings of Seminar F held at PTRC European Transport Forum 1997, P415.
11. Daly A., Miller S. Advances in modelling traffic generation. European Transport Conference Proceedings 2006.
12. de Jong G., Daly A., Pieters M., van der Hoorn T. The logsum as an evaluation measure: Review of the literature and new results. Transportation Research Part A 2007, 41(9):874-889.
13. Fosgerau M., Bierlaire M. Discrete choice models with multiplicative error terms. Transportation Research Part B 2009, 43(5):494-505.
14. Greene W. Functional forms for the negative binomial model for count data. Economics Letters 2008, 99(3):585-590.
15. Gurmu S. Generalized hurdle count data regression models. Economics Letters 1998, 58(3):263-268.
16. Hausman J.A., Abrevaya J., Scott-Morton F.M. Misclassification of the dependent variable in a discrete-response setting. Journal of Econometrics 1998, 87(2):239-269.
17. Hausman J.A., Leonard G.K., McFadden D. A utility-consistent, combined discrete choice and count data model assessing recreational use losses due to natural resource damage. Journal of Public Economics 1995, 56(1):1-30.
18. Kohli S., Daly A. The use of logsums in welfare estimation: application in PRISM. Proceedings of the European Transport Conference 2006.
19. Lord D., Washington S.P., Ivan J.N. Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes: balancing statistical fit and theory. Accident Analysis & Prevention 2005, 37(1):35-46.
20. Manjón Antolín M.C., Arauzo Carod J.M. Locations and relocations: modelling, determinants, and interrelations. The Annals of Regional Science 2011, 47(1):131-146.
21. McFadden D. Modelling the choice of residential location, Institute of Transportation Studies 1978, University of California.
22. Narayanamoorthy S., Paleti R., Bhat C.R. On accommodating spatial dependence in bicycle and pedestrian injury counts by severity level. Transportation Research Part B 2013, 55:245-264.
23. Ortuzar J., Willumsen L.G. Modelling transport 2011, John Wiley & Sons.
24. Paleti R., Bhat C., Pendyala R. Integrated model of residential location, work location, vehicle ownership, and commute tour characteristics. Transportation Research Record: Journal of the Transportation Research Board 2013, 2382:162-172.
25. Qin X., Ivan J.N., Ravishanker N., Liu J. Hierarchical Bayesian estimation of safety performance functions for two-lane highways using Markov chain Monte Carlo modeling. Journal of Transportation Engineering 2005, 131(5):345-351.
26. Singh P., Paleti R., Jenkins S., Bhat C.R. On modeling telecommuting behavior: option, choice, and frequency. Transportation 2013, 40(2):373-396.
27. Small K.A. A Discrete Choice Model for Ordered Alternatives 1984, University of California Irvine, Irvine, CA.
28. Small K.A. A discrete choice model for ordered alternatives. Econometrica: Journal of the Econometric Society 1987, 409-424.
29. Smith M.S., Kauermann G. Bicycle commuting in Melbourne during the 2000s energy crisis: A semiparametric analysis of intraday volumes. Transportation Research Part B 2011, 45(10):1846-1862.
30. Walls M., Safirova E., Jiang Y. What drives telecommuting?: Relative impact of worker demographics, employer characteristics, and job types. Transportation Research Record: Journal of the Transportation Research Board 2007, 2010:111-120.
31. White H. Maximum likelihood estimation of misspecified models. Econometrica 1982, 50(1):1-25.
32. Winkelmann R. Econometric Analysis of Count Data 2013, Springer Science & Business Media.
33. Yao E., Morikawa T. A study of on integrated intercity travel demand model. Transportation Research Part A 2005, 39(4):367-381.
34. Zhao Y., Kockelman K.M. Household vehicle ownership by vehicle type: application of a multivariate negative binomial model. Proceedings of the 81st Annual Meeting of the Transportation Research Board 2002.