Earnings

Earnings are the net benefits of a corporation's operation.[1] Earnings is also the amount on which corporate tax is due. For an analysis of specific aspects of corporate operations several more specific terms are used as EBIT (earnings before interest and taxes) and EBITDA (earnings before interest, taxes, depreciation, and amortization).

Many alternative terms for earnings are in common use, such as income and profit. These terms in turn have a variety of definitions, depending on their context and the objectives of the authors. For instance, the IRS uses the term profit to describe earnings, whereas for the corporation the profit it reports is the amount left after taxes are taken out. Many economic discussions use principles derived from Karl Marx[2] and Adam Smith.[3] However, the rise of the importance of intellectual capital[4] affects such analyses.

Routine earnings

Routine earnings or commodity-based earnings are those that can be achieved by application of assets that are those that can be achieved by any business that employs sufficient capital and manpower. These conditions are commonly assumed in economic analyses of profit.

Non-routine earnings

The use of intellectual property generates non-routine profits. Those are often an order-of-magnitude greater than routine earnings.[5] Non-routine profits are essential to warrant the high investments needed for high-technology industries.

Earnings manipulation

Some statistical models (e.g. based on Benford's law or Beneish M-score) are used in order to detect possible earnings manipulations (fraud).

Citations

  1. Robert G. Eccles, Robert H. Herz, E. Mary Keegan, David M. H. Phillips: The Value Reporting Revolution: Moving Beyond the Earnings Game; Price-Waterhouse-Coopers, 2001.
  2. Karl Marx: Das Kapital, Kritik der Politischen Oekonmie; 1967.
  3. Adam Smith: The Wealth of Nations; 1876.
  4. Gordon Smith and Russell Parr: Intellectual Property, 4th edition; Wiley 2005.
  5. John Hand and Baruch Lev (editors): Intangible Assets, Values, Measures. and Risks; Oxford University Press, 2003.
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