Publication type
Journal Article
Authors
Publication date
September 15, 2022
Summary:
In this paper, we highlight an important property of the translog production function for the identification of treatment effects in a model of latent skill formation. We show that when using a translog specification of the skill technology, properly anchored treatment effect estimates are invariant to any location and scale normalizations of the underlying measures. By contrast, when researchers assume a CES production function and impose standard location and scale normalizations, the resulting treatment effect estimates vary with the chosen normalizations. Access to age-invariant measures does not solve this problem since arbitrary scale and location restrictions are still imposed in the initial period. We theoretically prove the normalization invariance of the translog production function and then complete several empirical exercises illustrating the effects of location and scale normalizations for different technologies and types of skills measures.
Published in
Journal of Applied Econometrics
Volume and page numbers
Volume: 37 , p.1256 -1265
DOI
https://doi.org/10.1002/jae.2929
ISSN
8837252
Subjects
Notes
Open Access
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
© 2022 The Authors. Journal of Applied Econometrics published by John Wiley & Sons, Ltd.
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