The effect of consistency in book-tax differences on analysts’ earnings forecasts: Evidence from forecast accuracy and informativeness
Journal of Accounting and Public Policy, ISSN: 0278-4254, Vol: 39, Issue: 3, Page: 106740
2020
- 10Citations
- 40Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
This study examines the relationship between the consistency of book-tax differences and the quality of analysts’ earnings forecasts. We find that the consistency of book-tax differences is associated with more accurate and informative forecasts. This suggests that the information embedded in the consistency of book-tax differences plays an important role in elevating the quality of analysts’ forecasts. Furthermore, the effect of consistency in book-tax differences on analyst forecast quality is greater for firms with noisier information environment. Finally, we find that the relation between consistency in book-tax differences and improvements in forecast accuracy and informativeness is stronger after the implementation of Regulation Fair Disclosure, which increased the role of public information in analysts’ forecasts.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0278425418302758; http://dx.doi.org/10.1016/j.jaccpubpol.2020.106740; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85144894430&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0278425418302758; https://dx.doi.org/10.1016/j.jaccpubpol.2020.106740
Elsevier BV
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