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Title: A practical method to test the validity of the standard Gumbel distribution in logit-based multinomial choice models of travel behavior

Most multinomial choice models (e.g., the multinomial logit model) adopted in practice assume an extreme-value Gumbel distribution for the random components (error terms) of utility functions. This distributional assumption offers a closed-form likelihood expression when the utility maximization principle is applied to model choice behaviors. As a result, model coefficients can be easily estimated using the standard maximum likelihood estimation method. However, maximum likelihood estimators are consistent and efficient only if distributional assumptions on the random error terms are valid. It is therefore critical to test the validity of underlying distributional assumptions on the error terms that form the basis of parameter estimation and policy evaluation. In this paper, a practical yet statistically rigorous method is proposed to test the validity of the distributional assumption on the random components of utility functions in both the multinomial logit (MNL) model and multiple discrete-continuous extreme value (MDCEV) model. Based on a semi-nonparametric approach, a closed-form likelihood function that nests the MNL or MDCEV model being tested is derived. The proposed method allows traditional likelihood ratio tests to be used to test violations of the standard Gumbel distribution assumption. Simulation experiments are conducted to demonstrate that the proposed test yields acceptable Type-I andmore » Type-II error probabilities at commonly available sample sizes. The test is then applied to three real-world discrete and discrete-continuous choice models. For all three models, the proposed test rejects the validity of the standard Gumbel distribution in most utility functions, calling for the development of robust choice models that overcome adverse effects of violations of distributional assumptions on the error terms in random utility functions.« less
 [1] ;  [2] ;  [3] ;  [4]
  1. Tongji Univ., Shanghai (China)
  2. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  3. Maricopa Association of Governments, Phoenix, AZ (United States)
  4. Arizona State Univ., Tempe, AZ (United States)
Publication Date:
Report Number(s):
Journal ID: ISSN 0191-2615
Grant/Contract Number:
Accepted Manuscript
Journal Name:
Transportation Research, Part B: Methodological
Additional Journal Information:
Journal Volume: 106; Journal Issue: C; Journal ID: ISSN 0191-2615
Research Org:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
Country of Publication:
United States
30 DIRECT ENERGY CONVERSION; travel behavior models; discrete choice models; violations of distributional assumptions; test of validity of distributional assumption; multinomial logit model; multiple discrete-continuous extreme value model
OSTI Identifier: