Learning and incentive: A study on analyst response to pension underfunding
Xuanjuan Chen,
Tong Yao,
Tong Yu and
Ting Zhang
Journal of Banking & Finance, 2014, vol. 45, issue C, 26-42
Abstract:
There is a long-standing debate on whether sell-side analysts learn from their experience to improve earnings forecast skills. This study shows that incentive is an important factor for understanding the “learning by doing” effect by analysts. We examine analysts’ response to a complex type of information – corporate pension underfunding. Pension underfunding negatively impacts future earnings and analysts on average underreact to such information in their earnings forecasts. More importantly, when there is a strong incentive for analysts to deliver accurate forecasts, analyst learning effectively reduces their underreaction to pension underfunding information. On the other hand, when such an incentive is absent, the analyst learning effect is not discernible in the data. Further evidence suggests that analyst learning and incentive jointly reduce stock market mispricing associated with corporate pension underfunding.
Keywords: Analyst learning; Incentive; Pension underfunding; Earnings forecast error (search for similar items in EconPapers)
JEL-codes: G14 G23 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378426614001277
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:45:y:2014:i:c:p:26-42
DOI: 10.1016/j.jbankfin.2014.04.001
Access Statistics for this article
Journal of Banking & Finance is currently edited by Ike Mathur
More articles in Journal of Banking & Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().