Trade credit forecasting: empirical analysis using a ratio targeting approach
Mugova, Shame and Cucari, Nicola (2022) Trade credit forecasting: empirical analysis using a ratio targeting approach. Afro-Asian Journal of Finance and Accounting, 12 (4). pp. 413-426. ISSN 1751-6455
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Abstract
This study employs a panel data model that uses trade credit's own recent history to predict trade credit levels. A predictive model of trade credit is developed to predict the levels of trade payables and receivables. Previous forecasting techniques do not incorporate the targeting aspect and long period historical data. A target ratio should be set for trade payables and trade receivables to total assets. Trade credit is debt finance which is maintained at a certain ratio to total assets. In this paper, we make use of panel data from 230 non-financial South African listed firms from 2001 to 2013. Firms use trade credit targeting to pursue growth opportunities and their size affects their access to capital. Trade credit's recent history can be used to predict target trade credit levels. The paper makes an original contribution by developing a model to predict the level of trade credit.
| Item Type: | Article | ||||||
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| Identification Number: | https://doi.org/10.1504/AAJFA.2022.125064 | ||||||
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| Subjects: | CAH17 - business and management > CAH17-01 - business and management > CAH17-01-07 - finance | ||||||
| Divisions: | Faculty of Business, Law and Social Sciences > Birmingham City Business School > Centre for Accountancy Finance and Economics | ||||||
| Depositing User: | Shame Mugova | ||||||
| Date Deposited: | 08 Jan 2024 14:30 | ||||||
| Last Modified: | 08 Jan 2024 14:42 | ||||||
| URI: | https://www.open-access.bcu.ac.uk/id/eprint/15077 |
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