A generalized ordered Probit model

被引：9

作者：

Johnston, Carla ^{[1
]}

McDonald, James ^{[2
]}

Quist, Kramer ^{[3
]}

机构：

[1] Univ Calif Berkeley, Dept Econ, Berkeley, CA 94720 USA

[2] Brigham Young Univ, Dept Econ, Provo, UT 84602 USA

[3] MIT, Dept Econ, Cambridge, MA 02139 USA

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2020年 / 49卷 / 07期

关键词：

SGT; partially adaptive estimation; semiparametric; categorical data; ordered response models;

D O I：

10.1080/03610926.2019.1565780

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

The ordered probit and logit models, based on the normal and logistic distributions, can yield biased and inconsistent estimators when the distributions are misspecified. A generalized ordered response model is introduced which can reduce the impact of distributional misspecification. An empirical exploration of various determinants of life satisfaction suggests possible benefits of allowing for diverse distributional characteristics. These improvements are confirmed using a Monte Carlo study to contrast the performance of the flexible parametric specifications to the probit and logit specifications.

引用

页码：1712 / 1729

页数：18

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