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The role of operating efficiency and asset productivity in relative performance evaluation and CEO compensation in Indian firms

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Abstract

The use of relative performance evaluation (RPE) to determine compensation improves contracting efficiency, reduces moral hazard, and provides effort incentive. This study investigates how RPE usage in CEO compensation in Indian private sector firms is associated with a firm’s operating efficiency and asset productivity. It documents that firms with lower operating efficiency and asset productivity use more RPE by placing a more negative weight on their peer’s performance. Further, this study documents that more RPE usage is associated with lower asset productivity in both business group-affiliated firms as well as independent firms. In contrast, more RPE usage is associated with lower operating efficiency only in independent firms. This indicates that a firm’s ownership structure too plays a role in the RPE usage in Indian private sector firms.

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Notes

  1. The terms compensation and pay are used synonymously in this study.

  2. The evidence of RPE usage in China is mixed. On the one hand, Lee et al. (2012) found RPE use only in large Chinese SOE (state-owned enterprises), but not in non-SOE firms during 2001–2006. On the other, Chen D et al. (2012) find no evidence of RPE usage in China during 1999–2009.

  3. Ghosh (2006), Jaiswall and Bhattacharyya (2016), Jaiswall and Firth (2009), and Parthasarathy et al. (2006) have documented a positive association between profitability and CEO compensation in Indian firms. Net profit by total assets is also the measure of firm performance employed in RPE usage (Jaiswal et al. 2015). In contrast, stock returns do not to play a role in CEO pay in Indian firms. Jaiswal et al. (2015) show that stock returns are not used in RPE in India, whereas Jaiswall and Firth (2009) document a statistically insignificant association between stock return and CEO pay.

  4. Bertrand and Mullainathan (2001) find that CEOs are rewarded for luck and more so under weak monitoring. Powerful CEOs can influence their firm’s board to extract rent (Bebchuk and Fried 2003). It is plausible that powerful Indian CEOs capture the compensation setting process. They may sway the board away from RPE usage in order to exert lower effort and enjoy greater pay for luck. However, it is less likely to be pervasive in India given the recent evidence of efficient CEO compensation contracting documented in Jaiswall and Bhattacharyya (2016).

  5. Dikolli et al. (2012) show that an implicit test correctly identifies the lack of RPE usage when CEO compensation is not based on RPE, but it may underestimate the RPE usage when CEO compensation is based on RPE. As a result, our ability to reject the null is abated. Therefore, the use of implicit test approach does not work in favor of our hypotheses.

  6. Similarly, the first-order derivative of the Eq. (1) with respect to OwnPerf it gives the weight placed on own performance in CEO compensation.

  7. The transformation of accounting ratios into scaled ranks may result in a loss of information. Poorer information content of scaled ranks may potentially affect the quality of the results in linear regressions. Kane and Mead (1998) suggest that despite some loss of information, scaled ranks have better distributional properties that facilitate their use in linear regression and statistical inference.

  8. While a number of proxies for growth opportunities have been used in accounting and finance literature, we choose market-to-book value of assets ratio because prior studies have documented its superiority over other proxies. Kallapur and Trombley (2001) report that prior emprical studies have used the following types of proxies for growth opportunities: price-based (such as Tobin’s Q and its reciprocal book-to-market value of assets), investment-based (such as R&D intensity and capital expenditure to firm value ratio), variance-based (such as variance of stock returns and asset betas), and composite measures obtained using factor analysis. The authors document that market-to-book value of assets ratio is significantly correlated with realized growth in future, and therefore a valid proxy for a firm’s growth options. Further, Adam and Goyal (2008) show that relative to other constructs, market-to-book value of assets ratio is the most informative about a firm’s growth opportunities.

  9. We include CEO fixed effects and do not check for random effects because the evidence in Graham et al. (2012) suggests that unobserved CEO talent is correlated with both CEO pay as well as several firm attributes such as profitability, size, growth opportunities, etc. Not using CEO fixed effects induces omitted variable bias. Therefore, it more appropriate to use CEO fixed effects, rather than random effects.

  10. When industry fixed effects are added, the results are qualitatively similar to those in Jaiswal et al. (2015).

  11. Since all continuous variables have been standardized to zero mean and unit standard deviation, their standardized value is negative when the underlying construct has a value below mean. For example, the asset turnover ratio rank, ATOR, has a mean of 0.50 before the standardization and zero after the standardization. All asset turnovers below mean have a negative ATOR after the standardization. Before the standardization, asset turnover rank has a standard deviation of 0.289. When the asset turnover rank is one standard deviation below the mean, it has a value of 0.500 − 0.289 = 0.211. After the standardization, this value is negative one.

  12. 1.99 = (−0.320 − 0.317) ÷ (−0.320); 1.51 = (−0.320 − 0.162) ÷ (−0.320).

  13. We include the interaction of BGF with lower-order terms so that the expanded specification does not violate the principle of marginality, following Fox (2008).

  14. Equation (1) uses lagged values of operating margin and asset turnover ratios so that they are exogenous to the model. As a result, RPE usage in a given year does not affect the previous year’s operating margin and asset turnover ratios. This avoids the concern about the joint determination of these ratios and RPE usage. Further, Fairfield and Yohn (2001) document that changes in ROA is not associated with a prior year’s operating margin and asset turnover ratios.

  15. 7.5 % = 0.150 (coefficient of Unsys_ROA) × 1.16 (standard deviation of PayT) ÷ 2.31 (average of PayT). Since the average Total CEO Pay is Rs. 23.5 million, 7.5 % of Total CEO Pay is about Rs. 1.8 million.

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Acknowledgments

We are grateful to the chief editor, anonymous reviewer, and Manju Jaiswall for their constructive comments.

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Authors and Affiliations

  1. University of Calcutta and Guest Faculty, Finance and Control Group, Indian Institute of Management Calcutta, Kolkata, India

    Sudhir Kumar Jaiswal

  2. School of Corporate Governance and Public Policy, Indian Institute of Corporate Affairs, Manesar, Gurgaon, Haryana, India

    Asish Kumar Bhattacharyya

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  1. Sudhir Kumar Jaiswal
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Correspondence to Sudhir Kumar Jaiswal.

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Jaiswal, S.K., Bhattacharyya, A.K. The role of operating efficiency and asset productivity in relative performance evaluation and CEO compensation in Indian firms. Decision 43, 201–221 (2016). https://doi.org/10.1007/s40622-016-0128-2

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