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Uncertainty, imperfect information, and expectation formation over the firm’s life cycle

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  • Chen, Cheng
  • Senga, Tatsuro
  • Sun, Chang
  • Zhang, Hongyong

Abstract

Using a long panel data set on Japanese firms, we find that firms make more precise forecasts and less autocorrelated forecast errors as they gain more experience. Then, we build a firm dynamics model where firms gradually learn about their demand by using a noisy signal. Using expectations data over time, we cleanly isolate the learning mechanism from other mechanisms and find that it accounts for 20%–40% of the overall decline in forecast errors over the life cycle. Productivity gains from removing information frictions range from 3% to 12%, with firm entry and exit playing prominent roles.

Suggested Citation

  • Chen, Cheng & Senga, Tatsuro & Sun, Chang & Zhang, Hongyong, 2023. "Uncertainty, imperfect information, and expectation formation over the firm’s life cycle," Journal of Monetary Economics, Elsevier, vol. 140(C), pages 60-77.
    • Handle: RePEc:eee:moneco:v:140:y:2023:i:c:p:60-77
    DOI: 10.1016/j.jmoneco.2023.08.001
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    Keywords

    Firm expectations; Forecast errors; Learning; Life cycles; Productivity;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity
    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • F23 - International Economics - - International Factor Movements and International Business - - - Multinational Firms; International Business
    • L2 - Industrial Organization - - Firm Objectives, Organization, and Behavior

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