A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Addressing endogeneity in strategic urban mode choice models
https://orcid.org/0000-0003-3690-256X
Abstract Endogeneity is a potential anomaly in econometric models, which may cause inconsistent parameter estimates. Transport models are prone to this problem and applications that properly correct for it are scarce. This paper focuses on how to address this issue in the case of strategic urban mode choice models (i.e., the third stage of classic strategic transport models), possibly the main tool for the assessment of costly transport projects. To address this problem, we propose and validate, for the first time, adequate instruments that may be obtained from data that is already available in this context. The proposed method is implemented using the Control Function approach, which we use to detect and correct for endogeneity in a case study in Valparaiso, Chile. The effects arising from the neglected endogeneity in this case study reflect on an overestimation between 26–49% of the subjective value of time and an underestimation of 33–75% of modal elasticities.
Addressing endogeneity in strategic urban mode choice models
https://orcid.org/0000-0003-3690-256X
Abstract Endogeneity is a potential anomaly in econometric models, which may cause inconsistent parameter estimates. Transport models are prone to this problem and applications that properly correct for it are scarce. This paper focuses on how to address this issue in the case of strategic urban mode choice models (i.e., the third stage of classic strategic transport models), possibly the main tool for the assessment of costly transport projects. To address this problem, we propose and validate, for the first time, adequate instruments that may be obtained from data that is already available in this context. The proposed method is implemented using the Control Function approach, which we use to detect and correct for endogeneity in a case study in Valparaiso, Chile. The effects arising from the neglected endogeneity in this case study reflect on an overestimation between 26–49% of the subjective value of time and an underestimation of 33–75% of modal elasticities.
Addressing endogeneity in strategic urban mode choice models
https://orcid.org/0000-0003-3690-256X
Abstract Endogeneity is a potential anomaly in econometric models, which may cause inconsistent parameter estimates. Transport models are prone to this problem and applications that properly correct for it are scarce. This paper focuses on how to address this issue in the case of strategic urban mode choice models (i.e., the third stage of classic strategic transport models), possibly the main tool for the assessment of costly transport projects. To address this problem, we propose and validate, for the first time, adequate instruments that may be obtained from data that is already available in this context. The proposed method is implemented using the Control Function approach, which we use to detect and correct for endogeneity in a case study in Valparaiso, Chile. The effects arising from the neglected endogeneity in this case study reflect on an overestimation between 26–49% of the subjective value of time and an underestimation of 33–75% of modal elasticities.
Addressing endogeneity in strategic urban mode choice models
Guerrero, Thomas E. (author) / Guevara, C. Angelo (author) / Cherchi, Elisabetta (author) / Ortúzar, Juan de Dios (author)
Transportation ; 48
2020
Article (Journal)
Electronic Resource
English
BKL:
55.80$jVerkehrswesen$jTransportwesen: Allgemeines
/
55.80
Verkehrswesen, Transportwesen: Allgemeines
/
74.75$jVerkehrsplanung$jVerkehrspolitik
/
74.75
Verkehrsplanung, Verkehrspolitik
Endogeneity in Residential Location Choice Models
| British Library Online Contents | 2006
Endogeneity in Residential Location Choice Models
| British Library Conference Proceedings | 2006
Correcting for endogeneity in behavioral choice models with social influence variables
| Online Contents | 2011