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Risk Pooling, Supply Chain Hierarchy, and Analysts’ Forecasts

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  • Nan Hu
  • Jian‐Yu (Fisher) Ke
  • Ling Liu
  • Yue Zhang

Abstract

We investigate whether a firm's risk pooling affects its analysts’ forecasts, specifically in terms of forecast accuracy and their use of public vs. private information, and how risk pooling interacts with a firm's position in the supply chain to affect analysts’ forecasts. We use a social network analysis method to operationalize risk pooling and supply chain hierarchy, and find that risk pooling significantly reduces analysts’ forecast errors and increases (decreases) their use of public (private) information. We also find that the positive (negative) relationships between risk pooling and analyst forecast accuracy and analysts’ use of public (private) information are more pronounced upstream than downstream in a supply chain.

Suggested Citation

  • Nan Hu & Jian‐Yu (Fisher) Ke & Ling Liu & Yue Zhang, 2019. "Risk Pooling, Supply Chain Hierarchy, and Analysts’ Forecasts," Production and Operations Management, Production and Operations Management Society, vol. 28(2), pages 276-291, February.
    • Handle: RePEc:bla:popmgt:v:28:y:2019:i:2:p:276-291
    DOI: 10.1111/poms.12904
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    Cited by:

    1. Ruirui Fang & Nan Hu & Peng Liang & Ling Liu, 2023. "Cross‐market information transmission along the supply chain network," Production and Operations Management, Production and Operations Management Society, vol. 32(7), pages 2227-2244, July.
    2. Peng Liang & Hasan Cavusoglu & Nan Hu, 2023. "Customers’ managerial expectations and suppliers’ asymmetric cost management," Production and Operations Management, Production and Operations Management Society, vol. 32(6), pages 1975-1993, June.
    3. Hu, Nan & Liang, Peng & Liu, Ling & Zhu, Lu, 2022. "The bullwhip effect and credit default swap market: A study based on firm-specific bullwhip effect measure," International Review of Financial Analysis, Elsevier, vol. 84(C).

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