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Review of Accounting Studies

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18-06-2018

Accounting comparability and relative performance evaluation in CEO compensation

Authors: Gerald J. Lobo, Michael Neel, Adrienne Rhodes

Published in: Review of Accounting Studies | Issue 3/2018

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Abstract

We investigate whether accounting comparability is associated with the likelihood that CEO compensation is tied to relative accounting performance (e.g., return on assets). We predict that higher accounting comparability increases the risk-sharing benefit of accounting-based RPE because peer firm performance better controls for common risk in RPE firm performance. Thus, firms that have higher accounting comparability with potential performance peers will be more likely to include accounting-based RPE as a component of the total CEO compensation contract. We find support for this prediction using (1) an explicit test design that relies on the ex ante terms of CEO compensation contracts obtained from proxy disclosures, and (2) an implicit design that relies on the actual realizations of CEO compensation. To provide further evidence, we examine the association between accounting comparability and the selection of performance peers when the CEO compensation contract includes an accounting-based RPE component. We find that higher comparability between the RPE firm and a potential peer firm increases (decreases) the potential peer firm’s likelihood of being selected into (dropped from) the peer group. Cross-sectional analyses show that this association is less pronounced, or not present, when the relative performance measure is price-based (as opposed to accounting-based), indicating that these results do not merely reflect a more general role of comparability in all RPE contracts.

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We use the term “accounting-based RPE” to describe a compensation contract that awards any component of pay based on accounting performance relative to a peer group. This is likely to be in conjunction with pay components based on other performance measures (i.e., stock price), or evaluated on a non-relative basis.

Possible performance targets extend beyond price-based and accounting-based metrics. For example, the balanced scorecard incorporates non-financial performance metrics such as customer satisfaction, production quality, efficiency, etc. (Kaplan and Norton 1996). However, we follow prior literature by focusing on accounting- and price-based performance as the two primary performance benchmarks.

While Sloan (1993) focuses on the noise-filtering role of earnings, his result that CEO compensation is associated with the component of earnings that is orthogonal to firm-specific returns suggests that earnings is incrementally informative about managers’ actions (Lambert 1993). This result is also consistent with earnings signaling an aspect of CEO effort that is not also reflected in price.

Accounting-based RPE contracts contain at least one grant with an accounting-based target specified relative to the performance of a peer group. The performance-based grants can be either cash or equity-based.

We transform the comparability measures into annual deciles that range from 0 to 9 and divide by 9. Our inferences are unchanged if we use the raw variables in place of the decile ranks.

Cash compensation is measured as the sum of salary, bonus, and long-term incentive payouts prior to 2006 and the sum of salary, bonus, and non-equity incentives post 2006.

Prior research shows that restricted stock is the primary component of equity pay using RPE (Gong et al. 2011; Bettis et al. 2014). Additionally, less than 1% of option grants in the ISS Incentive Lab database are tied to accounting-based RPE. Therefore, we exclude option compensation.

These observations are for six firms: Berkshire Hathaway, Carlisle Companies, General Electric, Leucadia National Corp., Teleflex, and Textron. We delete these firms because we are unable to make reasonable industry matches for them.

We report correlations in Table 2.

We first compute the average comparability rank for each industry. For example, the average comparability rank for Banking is (0.597 + 0.634 + 0.764) / 3 = 0.665. Second, we compute the group average using each industry’s average rank.

On the other hand, it raises the possibility that some other industry characteristic results in both higher comparability and greater use of accounting-based RPE. We address this possibility by including both industry fixed effects and controls for within-industry economic similarity in our model. Additionally, we complement our main analyses with an instrumental variable specification.

Although the coefficient signs on the control variables are consistent with Gong et al. (2011) and Bettis et al. (2014), these coefficients are generally not significant. Untabulated analysis indicates that this is due to the inclusion of industry fixed effects in our model. Omitting the fixed effects increases the significance of the control variables substantially, but does not affect our inferences.

Throughout the paper, we use the term significant (marginally significant) to denote a five (ten) percent significance level under a one-sided alternative when we have a directional hypothesis, and under a two-sided alternative otherwise.

The “odds” of using accounting-based RPE equals the probability of using accounting-based RPE divided by the probability of not using accounting-based RPE. To compute the increase in odds, we exponentiate the coefficient on the ranked accounting comparability measure (range 0 to 1). For example, the coefficient on COMPFAC_I is 1.336, resulting in e^1.336 = 3.80.

We adjust standard errors for firm clusters in the second-stage regressions. We are unable to adjust the second-stage standard errors for both firm and year clusters because the estimated covariance matrix of moment conditions is not full rank. As an alternative, we partial out the model constant and all exogenous regressors and estimate the coefficient for COMPFAC_IHAT. This permits us to adjust the resulting standard error for firm and year clusters. Our inferences are unchanged. We also use an over-identifying restrictions test in the 2SLS specification to formally confirm that the two instruments satisfy the exclusion restriction. The test-statistic (χ²(1) = 1.34; p-value = 0.247) indicates that the instruments and error term from the second-stage model are uncorrelated (Sargan 1958; Basmann 1960).

We do not investigate the source of this positive association between industry-size matched ROA and compensation, instead leaving that to future research.

In untabulated tests our results hold when we also estimate Eq. (3) using a comparability-industry-size matched measure of PEER RET. Additionally, we also estimate Eq. (3) including both industry-size and comparability-industry-size matched measures of PEER ROA and PEER RET together. We continue to find evidence of RPE in ROA for cash compensation based on the comparability-industry-size matched measure of peer ROA but not the industry-size matched measure of peer ROA.

Our inferences are unchanged when we match selected and unselected peers based on three-digit SIC code industries or the 48 Fama-French industries. Additionally, our inferences are unchanged when we use unselected peers that are matched to the RPE firm (as opposed to the selected peer firm) based on size and two-digit SIC industry.

The odds ratio is equal to 1.98 (e^0.684).

We omit the industry and year fixed effects when using the ranked variables to facilitate our subsequent calculations of predicted comparability. Our inferences are unchanged when we include these fixed effects.

The results hold when we match firm-pairs on three-digit or four-digit SIC in the rank regressions.

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Title: Accounting comparability and relative performance evaluation in CEO compensation
Authors: Gerald J. Lobo
Michael Neel
Adrienne Rhodes
Publication date: 18-06-2018
Publisher: Springer US
Published in: Review of Accounting Studies / Issue 3/2018
Print ISSN: 1380-6653
Electronic ISSN: 1573-7136
DOI: https://doi.org/10.1007/s11142-018-9447-1

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