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Estimating private information usage amongst analysts: evidence from UK earnings forecasts

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  • Svetlana Mira
  • Nicholas Taylor

Abstract

This paper introduces a methodology for estimating the likelihood of private information usage amongst earnings analysts. This is achieved by assuming that one group of analysts generate forecasts based on the underlying dynamics of earnings, while all other analysts are assumed to issue forecasts based on the prevailing consensus forecast. Given this behavioural dichotomy, we are able to derive (and estimate) a structural econometric model of forecast behaviour, which has implications regarding the determinants of analysts' private information endowments and forecast accuracy over the forecast horizon. Copyright (C) 2010 John Wiley & Sons, Ltd.

Suggested Citation

  • Svetlana Mira & Nicholas Taylor, 2011. "Estimating private information usage amongst analysts: evidence from UK earnings forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(8), pages 679-705, December.
    • Handle: RePEc:jof:jforec:v:30:y:2011:i:8:p:679-705
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    File URL: http://hdl.handle.net/10.1002/for.1189
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    Cited by:

    1. Young‐Soo Choi & Svetlana Mira & Nicholas Taylor, 2022. "Local versus foreign analysts' forecast accuracy: does herding matter?," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(S1), pages 1143-1188, April.
    2. Matthias Demmer & Paul Pronobis & Teri Lombardi Yohn, 2019. "Mandatory IFRS adoption and analyst forecast accuracy: the role of financial statement-based forecasts and analyst characteristics," Review of Accounting Studies, Springer, vol. 24(3), pages 1022-1065, September.

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