ESTIMATION OF LOGIT CHOICE MODELS USING MIXED STATED PREFERENCE AND REVEALED PREFERENCE INFORMATION
Mark A. Bradley, Andrew Daly
Abstract
Mark A. Bradley, Andrew Daly
Abstract
This paper discusses and illustrates the main issues involved in the estimation an dapplication of mixed Revealed Preference-Stated Preference (RP-SP) models: Section 2 provides background on the theoretical framework of the integrated estimation approach, the structure of the model and the specification of the joint utility function. This section includes a statistical derivation of the estimator of the joint likelihood function. Section 3 describes a case study of the tree logit estimation method. This case study was performed on the same data set used previously by Morikawa, meaning that a direct comparison can be made of the logit and probit estimation techniques. Section 4 presents a second case study, a fairly typical case where stated preference data is used to supplement a revealed preference model in order to add into the model a mode choice alternative which does not yet exist. Section 5 provides a brief summary and conclusions regarding the methods and results described in the paper. (A)
OpenAlex reports 192 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
This paper discusses and illustrates the main issues involved in the estimation an dapplication of mixed Revealed Preference-Stated Preference (RP-SP) models: Section 2 provides background on the theoretical framework of the integrated estimation approach, the structure of the model and the specification of the joint utility function. This section includes a statistical derivation of the estimator of the joint likelihood function. Section 3 describes a case study of the tree logit estimation method. This case study was performed on the same data set used previously by Morikawa, meaning that a direct comparison can be made of the logit and probit estimation techniques. Section 4 presents a second case study, a fairly typical case where stated preference data is used to supplement a revealed preference model in order to add into the model a mode choice alternative which does not yet exist. Section 5 provides a brief summary and conclusions regarding the methods and results described in the paper. (A)
Key concepts: Mixed logit, Preference, Econometrics, Logit, Estimator, Probit, Estimation, Section (typography)