We study how professional forecasters form equity market expectations based on a new micro-level dataset which includes rich cross-sectional information about individual characteristics. We focus on testing whether agents rely on the beliefs of others, i.e., consensus expectations, when forming their own forecast. We find strong evidence that the average of all forecasters' beliefs influences an individual's own forecast. This effect is stronger for young and less experienced forecasters as well as forecasters whose pay depends more on performance relative to a benchmark. Further tests indicate that neither information extraction to incorporate dispersed private information, nor herding for reputational reasons can fully explain these results, leaving Keynes' beauty contest argument as a potential candidate for explaining forecaster behavior.
Rangvid, J., Schmeling, M., & Schrimpf, A. (2013). What do Professional Forecasters' Stock Market Expectations Tell Us about Herding, Information Extraction and Beauty Contests? Journal of Empirical Finance, 20(1), 109-129. https://doi.org/10.1016/j.jempfin.2012.11.004