What question did this study set out to answer?

This research aims to estimate production functions by leveraging firms' subjective expectations of future output and inputs.

May 16, 2026

Leveraging Subjective Expectations for Production Functions

Key Points

This research aims to estimate production functions by leveraging firms' subjective expectations of future output and inputs.
Comparison of NPR's estimator with traditional dynamic panel data and proxy variable methods.
Analysis of nonlinear productivity processes and their implications under oligopolistic competition.
Evaluation of input demand relations and their effect on productivity estimations.
NPR's method shows better robustness in oligopolistic competition compared to traditional methods.
When linear, NPR shares commonalities with earlier estimators.
NPR provides valuable insights into productivity without needing input demand proxies.

Abstract

Norris Keiller, de Paula, and Van Reenen (2024) (NPR) propose estimating production functions using firms' subjective expectations of future output and inputs, data which are becoming increasingly available in surveys. This note compares their proposed estimator to traditional dynamic panel data (e.g., Blundell and Bond 2000) and proxy variable methods (e.g., Olley and Pakes 1996). While NPR allows for nonlinear productivity processes, we discuss commonalities with the former when those processes are linear. We note that NPR may be more robust to oligopolistic competition than the latter since it does not employ input demand relations to proxy for productivity.

اسأل الذكاء الاصطناعي

Bookmark