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Bibliographic Details
Main Authors: Doraszelski, Ulrich, Li, Lixiong
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2511.21578
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author Doraszelski, Ulrich
Li, Lixiong
author_facet Doraszelski, Ulrich
Li, Lixiong
contents We develop a generalized control function approach to production function estimation. Our approach accommodates settings in which productivity evolves jointly with other unobservable factors such as latent demand shocks and the invertibility assumption underpinning the traditional proxy variable approach fails. We provide conditions under which the output elasticity of the variable input -- and hence the markup -- is nonparametrically point-identified. A Neyman orthogonal moment condition ensures oracle efficiency of our GMM estimator. A Monte Carlo exercise shows a large bias for the traditional approach that decreases rapidly and nearly vanishes for our generalized control function approach.
format Preprint
id arxiv_https___arxiv_org_abs_2511_21578
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A Generalized Control Function Approach to Production Function Estimation
Doraszelski, Ulrich
Li, Lixiong
Econometrics
We develop a generalized control function approach to production function estimation. Our approach accommodates settings in which productivity evolves jointly with other unobservable factors such as latent demand shocks and the invertibility assumption underpinning the traditional proxy variable approach fails. We provide conditions under which the output elasticity of the variable input -- and hence the markup -- is nonparametrically point-identified. A Neyman orthogonal moment condition ensures oracle efficiency of our GMM estimator. A Monte Carlo exercise shows a large bias for the traditional approach that decreases rapidly and nearly vanishes for our generalized control function approach.
title A Generalized Control Function Approach to Production Function Estimation
topic Econometrics
url https://arxiv.org/abs/2511.21578