Ideología de género en juicios y argumentos

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the IFRS in 2012 fiscal year, and at this period, the NASB has not updated the Nigerian GAAP so that it provides a research setting to test whether IFRS makes impact in countries which adapt the old IAS as domestic accounting standards.

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variability in financial ratio grouping; hence, several ratios can belong to one group and a single ratio can belong to two or more groups; for example, the ratios of operating cash flow to total assets and working capital to total assets may go into capital turnover group of ratios, the liquidity group or even the solvency group. However, multiple ratios in a group can be a blessing and a curse; for example, analysts can evaluate a firm’s profitability using different financial ratios within the profitability group but when it comes to prediction the choice of which ratio to select in a group becomes an issue. Horrigan (1965) finds that financial ratios within a group are highly correlated, suggesting that a single representative ratio in a group is sufficient for the purpose of building a parsimonious model. Thus, analysts with the objective of predicting some phenomenon must embark on the selection of a surrogate financial ratio in each group.

A germane question is, ‘should refutation or the assumption be dismissed?’ This question is significant because the dominant finding in the literature is that the distributions of many financial ratios are non-normal (see, among others, Deakin, 1976; Bougen & Drury, 1980;

Frecka & Hopwood, 1983; Ezzamel, Mar-Molinero, Beecher, 1987; Buckmasters & Saniga, 1990; Akintola, 1998). If refutation is admitted, then it suggests that industry norm ratios cannot be established for performance evaluation. The idea beneath the assumption of normality in the distributions of financial ratios is that few firms in an industry perform below and above expectation due to some minor variability in capital intensity among the firms but majority of the firms should attain average expectation, which is an ideal description for performance of any family of living things (cf. Moore, 1995, p.21). Therefore, the normal distribution provides a theoretical orientation which cannot be dismissed, but it cannot be verified also because phenomena are the outcomes of context-specific mechanisms (Pawson &Tilley, 1997). What is

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logical to do is to ascribe non-normality in observed data to some black box that one can fiddle to achieve desired results. Transformation and winsorizing are suggested methods to restore normality but this would suggest that industry norms do not apply to all firms in an industry; for example, distress firms or highfliers but they belong to the family. The elimination of outliers to restore normality would have been a legitimate thing to do if ratio norms were to apply to different industries: pigs, pears, pipes, peas and prickets may be temporarily transformed to pounds sterling or the US dollar due to heterogeneity but this becomes illogical when the objects are of the same species. Thus, if the normative or positive use of financial ratios is a desired objective then management must order transactions to conform to normality rules, or standard setters must observe normality rules when formulating accounting standards.

Non-normality, and hence instability, in the distributions of financial ratios has been ascribed to differences in size of firms (Horrigan, 1965). The International Accounting Standards Board, or the IASB, develops separate accounting standards for small-medium and large firms in order to sustain the normality assumption. Moreover, differences in size of firms become constant when the relationship between two variables from financial statements is expressed in the form of a ratio, and this rules out ‘size’ as an explanatory factor for non-normality. Also, Horrigan proposes differences in accounting methods as a cause of non-normality but the application of accounting methods in an industry is a constant because custom and habit explain practices within an institution (Potts, 2007), suggesting that within an industry practices should become stable. Another explanatory factor for non-normality and instability is the presence of outliers in a financial ratio distribution (Deakin, 1976; Frecka & Hopwood, 1983; Martikainen, Perttunen, Yi-Olli & Gunasekaran, 1995). An outlier is a ratio either far below or above the industry norm,

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suggesting that it requires the existence of an industry norm to identify outliers. The standard practice is to establish the industry norm for a ratio using only healthy firms. Once this has been done, it becomes unjustifiable to spot some observations as outliers for they all belong to the family (that is the industry). The standardization of accounting practice which is driven by the IASB should help detect outliers and hence contributes to efficient functioning of capital market because an efficient market would reflect outliers in share market prices. Thus, industry ratio norms are required to improve capital market performance. A fourth explanatory factor for normality of a financial ratio is that the relationship between the components of a ratio is non-proportional (Barnes, 1982; Ezzamel, Mar-Molinero & Beecher, 1987). A ratio is a measure of some relationship between two components that are proportional; for example, the relationship between age and income can be expressed as a ratio provided age and income are proportionally related otherwise some other form must be estimated to express the relationship. Thus, the thesis is that when the relationship between the two components of a ratio is non-proportional, a cross-sectional distribution of the ratio would be non-normal. However, ratios calculated from financial statements do not violate the proportionality criterion because the accounting amounts constitute a system (cf. Most & Lewis, 1982, p. 31). To explain, age and income trail a pattern which constitutes a system, hence the relationship between age and income can be expressed as a ratio. Stated succinctly, when a pattern that constitutes a system exists, the proportionality assumption is not violated.

Based on the backcloth that the IASB standardises accounting practice among firms of similar sizes, it becomes important to establish whether financial ratio distributions differ under domestic accounting standards and the IFRS. The results would provide evidence to call for

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industry norms to improve capital market efficiency, and hence sustains the dogged pursuance of accounting change by the IASB. Industry norms help the market to fully reflect news about a company’s performance, and outliers quantify the magnitude of news effect (cf. Beaver, 1968;

O’Connor, 1973; Barnes, 1987), hence industry norm ratios are imperatives to sustain the IASB’s touted benefit of capital market efficiency arising from the adoption of IFRS. It requires an industry norm to detect outliers. Moreover, the results would have implications for the development of a surrogate financial ratio in each financial ratio group; for example, if the financial ratio distributions under IFRS are more temporally stable and this turns up in the form of group stability, then this would be ‘hard evidence’ to develop a representative ratio in each group for financial modelling.