The Proportion of Non-Operating Income, and Analysts’ Forecasts

Andrew Ayimbila Anabila

Abstract


The US Senate Committee that investigated the Enron disaster assessed the role of analysts. At issue was whether analysts misled the public by ignoring warning signals that included a high proportion of non-operating income. Non-operating income derives from secondary activities like investments, but operating income is from the primary business activities like manufacturing. While the analysts admitted their limited ability to forecast Enron’s earnings, they denied any intentional deceit and claimed that they were misled by Enron. This study asks whether analysts’ ability to predict earnings is generally negatively associated with the proportion of non-operating income. The rationale is to determine whether the limited ability of analysts to predict earnings for Enron was an isolated incident or a pervasive one that applies to other firms. If pervasive, then another such disaster could occur without a warning from analysts. First, I examine the incentives for firms to resort more to non-operating income rather than focus on Operating income. Then I examine the association between analysts’ forecast attributes and the ratio of nonoperating to operating income. The results show that non-operating income and operating income are negatively associated, suggesting that firms use non-operating income to manage their operating results. Also, analysts’ forecast inaccuracy and dispersion are positively associated with the ratio of non-operating income to operating income. These results imply that analysts are generally inefficient in predicting earnings of firms with a high proportion of non-operating income.


Full Text: PDF DOI: 10.5539/ijef.v4n10p15

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This work is licensed under a Creative Commons Attribution 3.0 License.

International Journal of Economics and Finance  ISSN  1916-971X (Print) ISSN  1916-9728 (Online)

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