Implementing factor models for unobserved heterogeneity in Stata

被引:2
作者
Sarzosa, Miguel [1 ]
Urzua, Sergio [2 ,3 ]
机构
[1] Purdue Univ, Econ, W Lafayette, IN 47907 USA
[2] Univ Maryland, Econ, College Pk, MD 20742 USA
[3] Natl Bur Econ Res, Cambridge, MA 02138 USA
关键词
st0431; heterofactor; unobserved heterogeneity; factor models; Roy model; maximum likelihood; numerical integration; ABILITIES; CHOICE; MALES;
D O I
10.1177/1536867X1601600116
中图分类号
O1 [数学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 0701 ; 070101 ;
摘要
We introduce a new command, heterofactor, for the maximum likelihood estimation of models with unobserved heterogeneity, including a Roy model. heterof actor fits models with up to four latent factors and allows the unobserved heterogeneity to follow general distributions. Our command differs from Stata's sem command in that it does not rely on the linearity of the structural equations and distributional assumptions for identification of the unobserved heterogeneity. It uses the estimated distributions to numerically integrate over the unobserved factors in the outcome equations by using a mixture of normals in a Gauss Hermite quadrature. heterof actor delivers consistent estimates, including the unobserved factor loadings, in a variety of model structures.
引用
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页码:197 / 228
页数:32
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