A two recursive equation model to correct for endogeneity in latent class binary probit models

Mauricio Sarrias

Journal of choice modelling, 2021, vol. 40, issue C

Abstract: This article proposes a two recursive equation model to correct for endogeneity in latent class Probit models. Concretely, it is assumed that there exists an endogenous and continuous variable defined as a predictor, while unobserved heterogeneity is conceptualized as a vector of parameters that varies across individuals following a discrete distribution. A Maximum Likelihood Estimator is provided to estimate the model parameters based on normally distributed random terms and a free code in R software is provided to carry out the estimation procedure. A small Monte Carlo experiment is carried out to analyze the properties of the estimator. Finally, the estimator is applied to analyze the heterogeneous effects of weight on mental well-being.

Keywords: Instrumental variable; Probit model; Latent class; Unobserved heterogeneity; MLE (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eejocm:v:40:y:2021:i:c:s1755534521000348

DOI: 10.1016/j.jocm.2021.100301

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