Modeling value of travel time to competitors by different ways logit models: what you win and lose that?

• Autor(a) principal: Francisco Gildemir Ferreira da Silva
• Data de Publicação: 2011
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da UFC
• Texto Completo: http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=7352
• topic: Modelos de Escolha Discreta; Valor do Tempo de Viagem; Transporte de Passageiros; Discrete Choice Models; Travel Time Values; Passenger Transportation; CIENCIAS SOCIAIS APLICADAS

Economists since 1965 search a way to measure the value of time. This paper addresses empirical results from a theoretical background proposed in the particular case of transport. The Tuong and Hensher (1985) paper unified the theory and empirical measurement however, over the years various methods for estimation of discrete choice models were not used to measure the values of travel time. This thesis measures the value of travel time of the intercity transport users in Cearà using four models: unstructured type McFadden and the other three, as proposed in Tuong and Hensher (1985a) (Becker, and DeSerpa and Tuong Hensher via Taylor expansion). Additional to the traditional logit model, it estimates the same models using the methodology developed by Morikawa (1989) and simulated maximum likelihood estimation and Bayesian to logit models like in Train (2003). The result indicates that it should use the estimation methods and different functional forms sparingly, because depending on the parameters obtained can be found values for travel time considerably different. On the other hand, the functional forms can be good for prediction. A choice of estimation methods such as enrichment suggests less distortion from standard model. A choice of functional form indicates the use the model of Becker or DeSerpa because of their small oscillation regardless of the estimation methods used. Already a combined choice of estimation method and functional form suggests Becker or DeSerpa with Simulated Maximum Likelihood estimation to obtain values of travel time and to forecasts.