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The Relationship between Managers' Compensation and Market Value Added (MVA) in Iranian Listed Firms: Panel Data Technique

Author

Listed:
  • Meysam Doaei

    () (Faculty of Management and Human Resource Development, Universiti Teknologi Malaysia)

  • Mohammad Hossein Vadiee

    () (Faculty of Economics and Administrative Sciences, Ferdowsi University of Mashhad)

  • Hasan Bari

    () (Board of Director Iranian Accounting Association in Khorasan Razavi Province)

Abstract

Nowadays, manager compensation is considered as one of the motivation factors in many communities. Other researchers have been done in scientific and professional associations about what variable should be the subject of compensation. Many firms and economic organizations determine the manager compensation based on profitability rates; however, it has been criticized due to formulating some failures on modification and computation of it. So, this research has intended to investigate the relationship between manager¡¯s compensation and market value added (MVA). In this paper, it is applied panel data technique for 46 listed firms in five years. Finally, it is concluded that there is a relationship between manager¡¯s compensation and market value added in Tehran Stock Exchange (TSE) and the 47% of fluctuations is explained by the defined regression model.

Suggested Citation

  • Meysam Doaei & Mohammad Hossein Vadiee & Hasan Bari, 2012. "The Relationship between Managers' Compensation and Market Value Added (MVA) in Iranian Listed Firms: Panel Data Technique," Review of Economics & Finance, Better Advances Press, Canada, vol. 2, pages 37-42, November.
  • Handle: RePEc:bap:journl:120404
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    More about this item

    Keywords

    Compensation; Market value added; Panel data technique; Tehran Stock Exchange;

    JEL classification:

    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs
    • G3 - Financial Economics - - Corporate Finance and Governance
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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