Identification of dynamic latent factor models of skill formation with translog production

Publication type

Journal Article


Publication date

September 15, 2022


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






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.



Latest findings, new research

Publications search

Search all research by subject and author


Researchers discuss their findings and what they mean for society


Background and context, methods and data, aims and outputs


Conferences, seminars and workshops

Survey methodology

Specialist research, practice and study

Taking the long view

ISER's annual report


Key research themes and areas of interest