Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/281098 
Authors: 
Year of Publication: 
2022
Series/Report no.: 
Queen’s Economics Department Working Paper No. 1494
Publisher: 
Queen's University, Department of Economics, Kingston (Ontario)
Abstract: 
This paper considers transformations of nonlinear semiparametric mean functions that yield moment conditions for estimation. Such transformations are said to be information equivalent if they yield the same asymptotic efficiency bound. I derive a unified theory of algebraic equivalence for moment conditions created by a given linear transformation. The main equivalence result states that under standard regularity conditions, transformations that create conditional moment restrictions in a given empirical setting need only to have an equal rank to reach the same efficiency bound. Examples are included, where I compare feasible and infeasible transformations of both nonlinear models with multiplicative heterogeneity and linear models with arbitrary unobserved factor structures.
Subjects: 
Semiparametric efficiency
nonlinear regression
generalized least squares
fixed-T
JEL: 
C14
C33
C36
Document Type: 
Working Paper

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