Critical Review O Ball and Brown

Critical Review of Ball, R. & Brown, P. (1968), "An Empirical Evaluation of Accounting Income Numbers", Journal of Accounting Research, 6(2), 159-178

Modern accounting scientific theory developments of important ways are innovative accounting research methods. The empirical accounting research methods began from the United Stated in 1960s. Since then, some significant progress can be discovered in this field. Professor Ray Ball and Philip Brown (1968) conducted a study "An Empirical Evaluation of Accounting Income Numbers" which is recognized as the first literature used empirical research method of accounting problems. This classical document aimed to evaluate the information content of accounting income numbers, the relationship between earnings and share prices. Traditionally, serviceability of the accounting income numbers or the accounting practices was measured by the normative accounting analytical models. It implied that the income numbers couldn't be intrinsically defined because they are only the accumulation of different parts. However, Ball and Brown (1968) insisted that, without the empirical evaluation, it was improper to say the income numbers are doubtful. To the extent that this study tried to prove the utility of the income numbers by observation of earnings and share price. This positive study appears to be more important in accounting research though there are several limitations should be considered when analyzing the findings.

The context of this paper can be summarized that, Ball and Brown examines the utility of the accounting income numbers by providing empirical evaluation.

The first part provided a general overview of the analytical models agreed by the accounting theorists and their limitations. Meanwhile, Ball and Brown came up with the empirical evaluation to test the value of the accounting income numbers. Considering that the investors interested in the net income and earnings per share, they choose these two variables as the income figures.

This article first introduced the capital market efficiency hypothesis to check the information content of accounting income numbers. The capital market is semi-strong efficient and appears unbiasedly : if the information is useful to affect the share prices, capital market will react quickly to the new information in order to prevent the chance to get much more abnormal returns. Actually, related evidences revealed that, the stock prices adjust promptly by the market information which can be reflected by the accounting income numbers. Be connecting the accounting income with the share price to carry on research, the key is to distinguish the specific information and the system information.

The second part indicates that how the information content of accounting income can be verified by the constructed models. It shows that the earnings per share (EPS) are related to the economy wide effects. (Ball & Brown, 1968) However, the system factors partly affect all the firms' income; a firm's accounting income change can be reasonably expected for the next year through some stable contact with other firms. Then, the difference between the expected changes of income and the actual changes of income can be estimated as the forecast error. Meanwhile, the authors define the differences as the information content of current income.

To estimate the forecast error, the authors firstly put to use the Ordinary Least Squares (OLS) to calculate the linear regression coefficient and its intercept by the sample firm's annual income change and other firms' average income change. Once more, adopting the market average income change as the independent variable to factor into the regression model and finally get the expected income change figure. As has been said, the forecast error is the actual income changes minus the expected income changes. Remarkably, apply the regression model to estimate the forecast error which shows that the authors remove the market wide effects instead considering the specific factor.

Identically, the share prices (rate of return) are also influenced by the market wide factors. For this reason, the authors firstly employ the CAPM to separate the systematic factor and unsystematic factor. Secondly, use the similar linear regression model again to calculate the deviation degree of expected and actual stock yield for abnormal return. Therefore, the residual is the difference between the realized return and expected return. Since the capital market is semi-strong efficient, the firm' share price will adjust quickly and effectively to the new information, so the residual can be used to represent the impact of the new information on the rate of return in shares. Meanwhile, to inspect the usefulness of statistics, the authors take the naïve model as a substitution. Although it seems to be good, the share return model has violated some assumed conditions. In the authors' view, on the basis of other educated opinions, the impact of industry effects only accounts for 10% of one firm's variation in the share's average returns. Moreover, the industry effects on the influence of regression coefficients are not significant compared to overall.

At the end of the study, in order to proceed a better examine the information relation contained in the unexpected accounting income change and the share return residual, this study defined the negative forecast error as the bad news, vice are good news. In case, the relation exists, when the unexpected accounting income change is negative, then the share return residual should be also negative, vice verse. Under the empirical evaluation, the assumptions are verified observably by the abnormal performance index (API) with the annual report declared date. Ball and Brown (1968) argued that, if the expected income differs from the actual income, the market will react in the same direction, and then the information content of income is useful.

It can't be denied that the data had been gathered has its own merits, such as the period from 1957 to 1965, the gap between the accounting year end date and the announcement

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