Estimating Production Functions with Robustness Against Errors in the Proxy Variables
45 Pages Posted: 10 Apr 2011 Last revised: 2 Jun 2019
Date Written: January 23, 2019
This paper proposes a new approach to the identification and estimation of production functions. It extends the literature on the structural estimation of production functions, which dates back to the seminal work of Olley and Pakes (1996), by relaxing the scalar-unobservable assumption about the proxy variables. The key additional assumption needed in the identification argument is the existence of two conditionally independent proxy variables (e.g. the investment and the material input). The proposed generalized method of moment (GMM) estimator is flexible and straightforward to apply. The method is applied to study how rapidly firms in the Chilean food-product industry adjust their inputs in response to shocks to their productivity.
Keywords: Production Functions, Proxy Variables, Measurement Errors
JEL Classification: L1, D2
Suggested Citation: Suggested Citation