Birnbaum-Saunders sample selection model.
J Appl Stat
; 48(11): 1896-1916, 2021.
Article
em En
| MEDLINE
| ID: mdl-35706436
The sample selection bias problem occurs when the outcome of interest is only observed according to some selection rule, where there is a dependence structure between the outcome and the selection rule. In a pioneering work, J. Heckman proposed a sample selection model based on a bivariate normal distribution for dealing with this problem. Due to the non-robustness of the normal distribution, many alternatives have been introduced in the literature by assuming extensions of the normal distribution like the Student-t and skew-normal models. One common limitation of the existent sample selection models is that they require a transformation of the outcome of interest, which is common R + -valued, such as income and wage. With this, data are analyzed on a non-original scale which complicates the interpretation of the parameters. In this paper, we propose a sample selection model based on the bivariate Birnbaum-Saunders distribution, which has the same number of parameters that the classical Heckman model. Further, our associated outcome equation is R + -valued. We discuss estimation by maximum likelihood and present some Monte Carlo simulation studies. An empirical application to the ambulatory expenditures data from the 2001 Medical Expenditure Panel Survey is presented.
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1
Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Revista:
J Appl Stat
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
Brasil
País de publicação:
Reino Unido