Characterizing the impact of discrete indicators to correct for endogeneity in discrete choice models

• Published in: Journal of choice modelling 2022-03, Vol.42, p.100342, Article 100342
• Main Authors: Guerrero, Thomas E., Guevara, C. Angelo, Cherchi, Elisabetta, Ortúzar, Juan de Dios
• Format: Article
• Language: English
• Subjects: Discrete and continuous indicators; Discrete choice models; Endogeneity; Multiple indicator solutions method
• ISSN: 1755-5345; 1755-5345
• DOI: 10.1016/j.jocm.2021.100342

Endogeneity is a common problem in econometric modelling that may lead to estimating inconsistent parameters. In the scientific literature, the Multiple Indicator Solutions (MIS) method is used to correct for endogeneity. This approach uses indicators that, in practice, tend to be collected as discrete using Likert scales; however, theoretically, the MIS method is derived considering continuous indicators. To close this research gap, this paper focuses on characterizing the impact of discrete indicators when correcting for endogeneity using the MIS method in the case of discrete choice models (DCM). Our findings show that (i) under some conditions, using discrete indicators instead of continuous ones seems not to be a problem, however, (ii) there is also evidence that indicates that the correction could fail under not unusual circumstances. •Endogeneity is an anomaly that may yield inconsistent model parameters.•We designed a Monte Carlo experiment and applied a SP survey, to examine the impact of using discrete indicators.•Our findings show that the algorithm used to produce discrete indicators affects the endogeneity correction.•Using real data, we show that the correction with continuous indicators worked better than with discrete indicators.