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Title: | The prediction of future cash flow for UK private companies |
Authors: | Liu, S Skerratt, L |
Keywords: | prediction of future cash f low;financial reporting regulation;private companies |
Issue Date: | 5-Nov-2024 |
Publisher: | Routledge (Taylor & Francis Group) |
Citation: | Liu, S. and Skerratt, L. (2024) 'The prediction of future cash flow for UK private companies', Journal of Small Business Management, 0 (ahead of print), pp. 1 - 37. doi: 10.1080/00472778.2024.2416044. |
Abstract: | UK private companies follow less stringent reporting standards than public ones. Despite extensive research on public companies’ financial reporting, little has been done for private firms, especially in the UK. We conducted prediction error tests on about 1.5 million observations on UK private companies from 2006–2022, distinguishing between the different classes of private companies: micro, small, medium-sized, and large. We found that errors in predicting future cash flow one period ahead for micro and small companies were only slightly larger than those of public companies. For medium-sized and large private companies, the errors were more than double, suggesting less informative disclosures. These results are robust for predicting beyond the next period and for times when financial distress is high. The impact of regulatory revisions for private companies in 2016, based on International Financial Reporting Standards for Small and Medium-sized Companies, is minor. |
Description: | Data availability statement: Data is available upon request. |
URI: | https://bura.brunel.ac.uk/handle/2438/30202 |
DOI: | https://doi.org/10.1080/00472778.2024.2416044 |
ISSN: | 0047-2778 |
Other Identifiers: | ORCiD: Siming Liu https://orcid.org/0000-0001-6855-8391 ORCiD: Len Skerratt https://orcid.org/0000-0001-7167-9864 |
Appears in Collections: | Dept of Economics and Finance Research Papers |
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FullText.pdf | Copyright © 2024 The Author(s). Published with license by Taylor & Francis Group, LLC. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s)or with their consent. | 1.27 MB | Adobe PDF | View/Open |
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