arXiv Open Access 2024

Bayesian estimation of finite mixtures of Tobit models

Caio Waisman
Lihat Sumber

Abstrak

This paper outlines a Bayesian approach to estimate finite mixtures of Tobit models. The method consists of an MCMC approach that combines Gibbs sampling with data augmentation and is simple to implement. I show through simulations that the flexibility provided by this method is especially helpful when censoring is not negligible. In addition, I demonstrate the broad utility of this methodology with applications to a job training program, labor supply, and demand for medical care. I find that this approach allows for non-trivial additional flexibility that can alter results considerably and beyond improving model fit.

Topik & Kata Kunci

Penulis (1)

C

Caio Waisman

Format Sitasi

Waisman, C. (2024). Bayesian estimation of finite mixtures of Tobit models. https://arxiv.org/abs/2411.09771

Akses Cepat

Lihat di Sumber
Informasi Jurnal
Tahun Terbit
2024
Bahasa
en
Sumber Database
arXiv
Akses
Open Access ✓