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Leveraging subjective expectations for production functions

Author

Listed:
  • Bond, Steve
  • Norris Keiller, Agnes
  • de Paula, Áureo
  • Van Reenen, John

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.

Suggested Citation

  • Bond, Steve & Norris Keiller, Agnes & de Paula, Áureo & Van Reenen, John, 2026. "Leveraging subjective expectations for production functions," LSE Research Online Documents on Economics 138667, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:138667
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    File URL: https://researchonline.lse.ac.uk/id/eprint/138667/
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    References listed on IDEAS

    as
    1. Agnes Norris Keiller & Áureo de Paula & John Van Reenen, 2024. "Production function estimation using subjective expectations data," IFS Working Papers WCWP15/24, Institute for Fiscal Studies.
    2. Norris Keiller, Agnes & De Paula Neto, Aureo & Van Reenen, John, 2024. "Production function estimation using subjective expectations data," LSE Research Online Documents on Economics 126812, London School of Economics and Political Science, LSE Library.
    3. Richard Blundell & Stephen Bond, 2000. "GMM Estimation with persistent panel data: an application to production functions," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 321-340.
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    More about this item

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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