EconBase
← All papers

Bayesian estimation of finite mixtures of Tobit models

Caio Waisman

arXiv 14 Nov 2024 · Econometrics

arXiv:2411.09771 · PDF · DOI · OpenAlex · Extracted main text

Abstract

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.

Citation extraction

35
references
51
in-text mentions
35
distinct cited
0
self-citations
7,977
main-text words

appendix boundary found by none_found · 100% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Chib, S (1992) Bayes inference in the Tobit censored regression model0.81142100%
2Deb, P. and Trivedi, P. K (1997) Demand for medical care by the elderly: A finite mixture approach0.81142100%
3Dehejia, R. H. and Wahba, S (1999) Causal effects in nonexperimental studies: Reevaluating the evaluation of training programs0.81142100%
4Lalonde, R. J (1986) Evaluating the econometric evaluations of training programs with experimental data0.81142100%
5Jedidi, K., Ramaswamy, V., and Desarbo, W. S (1993) A maximum likelihood method for latent class regression involving a censored dependent variable0.73732100%
6Diebolt, J. and Robert, C. P (1994) Estimation of finite mixture distributions through Bayesian sampling0.64422100%
7Keane, M. and Stavrunova, O (2011) A smooth mixture of Tobits model for healthcare expenditure0.51121100%
8Amemiya, T (1973) Regression analysis when the dependent variable is truncated normal0.40511100%
9Arellano-Valle, R. B., Castro, L. M., González-Farías, G., and Muñoz… (2012) Student-$t$ censored regression model: Properties and inference0.40511100%
10Busse, M. R., Israeli, A., and Zettelmeyer, F (2017) Repairing the damage: The effect of price knowledge and gender on auto repair price quotes0.40511100%

Showing the top 10 of 35 scored citations.