The value-added statement: An appeal for standardisation

Owing to the absence of accounting standards for the preparation of a value-added statement (VAS), a large variety of methods are used in financial statements. In this study the published value-added statements (PVAS) of companies listed on the JSE Securities Exchange during the period 1976-2005 have been standardised by the Graduate School of Business of the University of Stellenbosch (USB) in order to quantify the differences between the standardised VAS (SVAS) and the PVAS. These differences consist of the inclusion of items that do not belong in the VAS, items that are erroneously allocated among the distribution to stakeholders, and interpretation differences in whether a certain item forms part of the calculation of value added or the distribution thereof. The greatest difference quantified was the overstatement of the distribution to government that amounted to 54.4% of total differences. For users, including government, to properly calculate and compare the value added of different business entities, a standard for the preparation and presentation of VAS ought to be published. In the South African context the need of a precise measurement of each business entity's contribution to the growth of the national economy is relevant, and this need should also be addressed.Value added, Gross Domestic Product, South Africa, financial statements

The value-added statement: An appeal for standardisation

Owing to the absence of accounting standards for the preparation of a value-added statement (VAS), a large variety of methods are used in financial statements. In this study the published value-added statements (PVAS) of companies listed on the JSE Securities Exchange during the period 1976-2005 have been standardised by the Graduate School of Business of the University of Stellenbosch (USB) in order to quantify the differences between the standardised VAS (SVAS) and the PVAS. These differences consist of the inclusion of items that do not belong in the VAS, items that are erroneously allocated among the distribution to stakeholders, and interpretation differences in whether a certain item forms part of the calculation of value added or the distribution thereof. The greatest difference quantified was the overstatement of the distribution to government that amounted to 54.4% of total differences. For users, including government, to properly calculate and compare the value added of different business entities, a standard for the preparation and presentation of VAS ought to be published. In the South African context the need of a precise measurement of each business entity's contribution to the growth of the national economy is relevant, and this need should also be addressed

Wat is die bester manier om maatskappye se finansiële nood te voorspel

University of Stellenbosch Business SchoolThe original publication is available at http://thoughtprint.usb.ac.za/Pages/Agenda.aspxENGLISH ABSTRACT: Predicting distress is essential for investors or lending institutions who wish to protect their financial investments. Which predictive techniques work best?AFRIKAANSE OPSOMMING: Dit is noodsaaklik vir beleggers en leningsinstellings wat hul finansiële beleggings wil beskerm om finansiële nood te kan voorspel. Watter voorspellingstegnieke werk die beste?Publishers' versio

Predicting financial distress of companies listed on the JSE : a comparison of techniques

CITATION: Muller, G. H., Steyn-Bruwer, B. W. & Hamman, W. D. 2009. Predicting financial distress of companies listed on the JSE : a comparison of techniques. South African Journal of Business Management, 40(1):a532, doi:10.4102/sajbm.v40i1.532.The original publication is available at https://sajbm.orgIn 2006, Steyn-Bruwer and Hamman highlighted several deficiencies in previous research which investigated the prediction of corporate failure (or financial distress) of companies. In their research, Steyn-Bruwer and Hamman made use of the population of companies for the period under review and not only a sample of bankrupt versus successful companies. Here the sample of bankrupt versus successful companies is considered as two extremes on the continuum of financial condition, while the population is considered as the entire continuum of financial condition. The main objective of this research, which was based on the above-mentioned authors' work, was to test whether some modelling techniques would in fact provide better prediction accuracies than other modelling techniques. The different modelling techniques considered were: Multiple discriminant analysis (MDA), Recursive partitioning (RP), Logit analysis (LA) and Neural networks (NN). From the literature survey it was evident that existing literature did not readily consider the number of Type I and Type II errors made. As such, this study introduces a novel concept (not seen in other research) called the "Normalised Cost of Failure" (NCF) which takes cognisance of the fact that a Type I error typically costs 20 to 38 times that of a Type II error. In terms of the main research objective, the results show that different analysis techniques definitely produce different predictive accuracies. Here, the MDA and RP techniques correctly predict the most "failed" companies, and consequently have the lowest NCF; while the LA and NN techniques provide the best overall predictive accuracy.https://sajbm.org/index.php/sajbm/article/view/532Publisher's versio

Share repurchases : which number of shares should be used by JSE-listed companies when publishing market capitalisation in annual reports?

CITATION: Bester, P. G. et al. 2008. Share repurchases : which number of shares should be used by JSE-listed companies when publishing market capitalisation in annual reports? South African Journal of Business Management, 39(4):a571, doi:10.4102/sajbm.v39i4.571.The original publication is available at https://sajbm.orgThe legalisation of share repurchases in South Africa since July 1999 introduced additional complexity to financial reporting. The repurchasing of shares by subsidiaries or share trusts has led to a new concept: the number of company shares differs from the number of group shares. Ratios like earnings per share and headline earnings per share are governed by accounting standards and circulars, and prescribe the use of the (weighted) number of group shares. No guidance exists on the calculation of market capitalisation. This article aims to determine the methods used by companies listed on the JSE Securities Exchange South Africa (JSE) to calculate their number of shares when publishing market capitalisation. It was found that only about 25% of companies participating in share repurchases and publishing market capitalisation in their annual reports calculated market capitalisation based on the number of group shares. About 75% of the companies did not calculate their market capitalisation based on the number of group shares (i.e. they omitted to deduct subsidiary repurchases and/or trust consolidations in their calculation of the number of shares). It was also found that the JSE, when compiling the Top 40 index, calculates market capitalisation based on the number of company shares (i.e. ignoring subsidiary repurchases and trust consolidations). Accounting guidance is needed on the reporting of market capitalisation to ensure that this aspect is not overstated by the reporting entities.https://sajbm.org/index.php/sajbm/article/view/571Publisher's versio

The ASOS Surgical Risk Calculator: development and validation of a tool for identifying African surgical patients at risk of severe postoperative complications

Background: The African Surgical Outcomes Study (ASOS) showed that surgical patients in Africa have a mortality twice the global average. Existing risk assessment tools are not valid for use in this population because the pattern of risk for poor outcomes differs from high-income countries. The objective of this study was to derive and validate a simple, preoperative risk stratification tool to identify African surgical patients at risk for in-hospital postoperative mortality and severe complications. Methods: ASOS was a 7-day prospective cohort study of adult patients undergoing surgery in Africa. The ASOS Surgical Risk Calculator was constructed with a multivariable logistic regression model for the outcome of in-hospital mortality and severe postoperative complications. The following preoperative risk factors were entered into the model; age, sex, smoking status, ASA physical status, preoperative chronic comorbid conditions, indication for surgery, urgency, severity, and type of surgery. Results: The model was derived from 8799 patients from 168 African hospitals. The composite outcome of severe postoperative complications and death occurred in 423/8799 (4.8%) patients. The ASOS Surgical Risk Calculator includes the following risk factors: age, ASA physical status, indication for surgery, urgency, severity, and type of surgery. The model showed good discrimination with an area under the receiver operating characteristic curve of 0.805 and good calibration with c-statistic corrected for optimism of 0.784. Conclusions: This simple preoperative risk calculator could be used to identify high-risk surgical patients in African hospitals and facilitate increased postoperative surveillance. © 2018 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.Medical Research Council of South Africa gran

Maternal and neonatal outcomes after caesarean delivery in the African Surgical Outcomes Study: a 7-day prospective observational cohort study.

BACKGROUND: Maternal and neonatal mortality is high in Africa, but few large, prospective studies have been done to investigate the risk factors associated with these poor maternal and neonatal outcomes. METHODS: A 7-day, international, prospective, observational cohort study was done in patients having caesarean delivery in 183 hospitals across 22 countries in Africa. The inclusion criteria were all consecutive patients (aged ≥18 years) admitted to participating centres having elective and non-elective caesarean delivery during the 7-day study cohort period. To ensure a representative sample, each hospital had to provide data for 90% of the eligible patients during the recruitment week. The primary outcome was in-hospital maternal mortality and complications, which were assessed by local investigators. The study was registered on the South African National Health Research Database, number KZ_2015RP7_22, and on ClinicalTrials.gov, number NCT03044899. FINDINGS: Between February, 2016, and May, 2016, 3792 patients were recruited from hospitals across Africa. 3685 were included in the postoperative complications analysis (107 missing data) and 3684 were included in the maternal mortality analysis (108 missing data). These hospitals had a combined number of specialist surgeons, obstetricians, and anaesthetists totalling 0·7 per 100 000 population (IQR 0·2-2·0). Maternal mortality was 20 (0·5%) of 3684 patients (95% CI 0·3-0·8). Complications occurred in 633 (17·4%) of 3636 mothers (16·2-18·6), which were predominantly severe intraoperative and postoperative bleeding (136 [3·8%] of 3612 mothers). Maternal mortality was independently associated with a preoperative presentation of placenta praevia, placental abruption, ruptured uterus, antepartum haemorrhage (odds ratio 4·47 [95% CI 1·46-13·65]), and perioperative severe obstetric haemorrhage (5·87 [1·99-17·34]) or anaesthesia complications (11·47 (1·20-109·20]). Neonatal mortality was 153 (4·4%) of 3506 infants (95% CI 3·7-5·0). INTERPRETATION: Maternal mortality after caesarean delivery in Africa is 50 times higher than that of high-income countries and is driven by peripartum haemorrhage and anaesthesia complications. Neonatal mortality is double the global average. Early identification and appropriate management of mothers at risk of peripartum haemorrhage might improve maternal and neonatal outcomes in Africa. FUNDING: Medical Research Council of South Africa.Medical Research Council of South Africa