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PR - Pretesting The Suitability Of The Income Valuation Framework On The Agricultural Companies Within The Visegrad Group

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  • Ruzickova, Kamila

Abstract

The income valuation framework presents high-powered, complex and math-intensive process. Therefore, any pretesting of valuation objects can be beneficial and time saving for the individual professional appraisers. Since the income valuation approach is based on the estimation of the income value of the company on an ongoing-concern basis, if this basic assumption is not met by the valuation object, the other approaches need to be employed. This paper closely examines theoretical and practical aspects for the initial stage for the application of the income valuation methods on the agricultural companies within the member countries of the Visegrad Group. Firstly, the applicability of the income valuation methods is verified via the indicator of value spread, as a difference between the return on equity and costs of equity and secondly, the conclusions are drawn properly. This paper finds that only a part of the sample is suitable for income valuation, for the majority of companies the income valuation methods are rather non-applicable, due the fact that some of the basic requirements are not met. Based on empirical tests, it was shown that there is a slightly positive dependence between the value spread indicator and the country of origin of the agricultural company.

Suggested Citation

  • Ruzickova, Kamila, 2013. "PR - Pretesting The Suitability Of The Income Valuation Framework On The Agricultural Companies Within The Visegrad Group," 19th Congress, Warsaw, Poland, 2013 345693, International Farm Management Association.
  • Handle: RePEc:ags:ifma13:345693
    DOI: 10.22004/ag.econ.345693
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    References listed on IDEAS

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    1. Plenborg, Thomas, 2002. "Firm valuation: comparing the residual income and discounted cash flow approaches," Scandinavian Journal of Management, Elsevier, vol. 18(3), pages 303-318, September.
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    Keywords

    Agricultural and Food Policy;

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