Eliwa, Y., Haslam, J. and Abraham, S. (2021) Earnings quality and analysts’ information environment: evidence from the EU market. Journal of International Accounting, Auditing and Taxation, 42. 100373. ISSN 1061-9518
Abstract
This study examines the relationship between earnings quality and analysts’ information environment as measured by analysts following, analysts’ forecasts dispersion, and analysts’ forecasts accuracy. Using a sample of all non-financial listed firms in the 15 European Union (EU) member states, we find that higher earnings quality leads to more analysts following, less dispersion of analysts’ forecasts, and more accurate forecasts from analysts. We also provide evidence of a positive link between the strength of this relationship and both International Financial Reporting Standards (IFRS) and the strength of enforcement regimes in EU countries. Further, we find that the innate component of earnings quality dominates the effect on analysts’ information environment proxies, whereas the discretionary component is likely to have a negligible impact. These findings shed light on the vital role of earnings quality in helping analysts and investors to make better financial investment decisions.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 Elsevier Inc. This is an author produced version of a paper subsequently published in Journal of International Accounting, Auditing and Taxation. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | earnings quality; analysts following; analysts’ forecasts dispersion; analysts’ forecasts accuracy; IFRS; Europe |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Management School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 05 Jan 2021 12:34 |
Last Modified: | 29 Dec 2022 01:13 |
Status: | Published |
Publisher: | Elsevier BV |
Refereed: | Yes |
Identification Number: | 10.1016/j.intaccaudtax.2020.100373 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:169557 |
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