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Relative Performance Goals and Management Earnings Guidance

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Abstract

We examine managers’ earnings forecasts for evidence of incentive alignment or subversion characteristics. We find that forecasts by managers compensated via relative performance (RP) goals are more likely to be pessimistic and less accurate than those by managers compensated via absolute performance (AP) goals. For firms not issuing earnings forecasts, disclosures in Form 10-Ks are more pessimistic for RP firms than for AP firms. Furthermore, we find that RP firms perform worse than AP firms in terms of future stock returns. Overall, our evidence is consistent with a proposition that, contrary to sound ethical business practices, RP managers make self-serving earnings disclosures to subvert the efforts of their peers to meet performance targets more easily.

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Notes

  1. RP managers may strategically influence the selection of peers for performance benchmarks and compensation benchmarks (see, e.g., Bizjak et al., 2008, 2011; Carter et al., 2009; Faulkender & Yang, 2010, 2013; Gong et al., 2011). In this study, we take peer selection as a given and focus instead on the potential for managers to influence the performance of peers.

  2. The subversion hypothesis is also called the sabotage hypothesis in the literature. Gibbons and Murphy (1990) note that paying workers based on RP goals can distort the worker’s incentives whenever the worker can influence the output of the reference group by taking the following actions: sabotage, collusion, choice of reference group, or production externalities.

  3. Our sample is limited to the years for which we have available data for management earnings guidance from IBES and performance goals data from Incentive Lab.

  4. As described later in the additional-test section, for a small sub-sample of firms for which appropriate data are available, we also perform a follow-up test and find that RP managers, on average, do meet their performance targets.

  5. Tournament theory suggests that managers are rewarded based on performance rankings within a reference group.

  6. As noted earlier, Gibbons and Murphy (1990) note that paying workers based on RP goals can distort the worker’s incentives whenever the worker can influence the output of the reference group by taking the following actions: sabotage, collusion, choice of reference group, and production externalities. The mechanism by which distortion occurs in our setting is sabotage. We do not expect CEOs with RP goals to collude with other CEOs because collusion among CEOs would constitute an antitrust violation and because collusion would require CEOs to communicate with each other, but as Gibbons and Murphy (1990) point out, “CEOs tend to have limited interaction with CEOs in the rival firms.” Sabotage is plausible in our setting because with public disclosures and the management earnings forecasts that we examine, there is no need for CEOs to interact with each other. Once a forecast is made, it becomes part of public information that everyone, including the competitors, can access and use.

  7. Consistent with the idea that firms’ decisions can be influenced by disclosures by their peers, Gong et al. (2019) show that RP firms intentionally delay earnings releases so they can observe peers’ earnings and conduct last minute earnings management.

  8. We use the OLS model because non-linear models such as Logit or Probit combined with fixed effects can yield inconsistent point estimates (Angrist and Pischke, 2009; Wooldridge, 2002).

  9. We use the average forecast pessimism rather than the pessimism for the most recent forecast for two related reasons. First, we focus on managers’ incentives to guide peer firms’ expectations and outputs (which are harder to be adjusted in a short time) rather than incentives to guide analyst forecasts (which are easier to be adjusted). Secondly, the sabotage hypothesis implies that managers may want to issue downward guidance early in the year for competitors to lower their expectations and efforts. Untabulated results show that using the first management earnings forecast issued after earnings announcement for the previous year does not change our inferences for earnings forecast properties.

  10. The inference remains the same using a logistic regression, where the coefficient on RP is positive and significant (p value < 0.05).

  11. To ensure the robustness of our results, we control for seven of the eight matching variables in the forecast properties regressions shown in Panel B of Table 4; we do not control for common risk because the literature does not consider it to be a variable related to forecast properties. However, untabulated results show that our regression results are qualitatively the same even if we control for common risk.

  12. We thank the referee for suggesting this analysis.

  13. Demerjian et al. (2012) use the managers’ efficiency in generating revenues as a measure of managerial talent. Conceptually, managers who can transform corporate resources to a higher level of revenue than their industry peers are considered to have higher talent.

  14. The financially negative words are developed by Loughran and McDonald (2011) based on actual usage frequency. These words are most likely associated with negative financial implications. They include some words from the Harvard-IV-4 TagNeg (H4N) list but also some other words not on the H4N list such as “litigation,” “restated,” “misstatement” that have clear negative implications in a financial context.

  15. Our result for Year T + 1 is qualitatively similar if we do not require the availability of stock returns for Year T + 2.

  16. Our results do not contradict the main findings in Tice (2020). Even though Tice (2020) finds that RP firms with high common risk exposure perform better than non-RP firms, she also finds that other groups of RP firms (e.g., firms with low common risk exposure) do not perform significantly better than non-RP firms.

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Authors and Affiliations

  1. Zicklin School of Business, Baruch College, New York City, NY, 10010, USA

    Yanrong Jia

  2. G. Brint Ryan College of Business, University of North Texas, Denton, TX, 76203-5017, USA

    Ananth Seetharaman

  3. Richard A. Chaifetz School of Business, Saint Louis University, St. Louis, MO, 63108, USA

    Yan Sun & Xu Wang

Authors
  1. Yanrong Jia
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  2. Ananth Seetharaman
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  3. Yan Sun
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  4. Xu Wang
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Correspondence to Yanrong Jia.

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We thank Scott Duellman, Sheila Killian (the editor), two anonymous referees, and conference participants at the 2018 Canadian Academic Accounting Association (CAAA) annual conference, the 2016 American Accounting Association (AAA) annual meeting, and the 2018 Financial Management Association (FMA) annual meeting for their useful comments and suggestions.

Appendices

Appendix 1: Variable Definitions

AD

Advertising expense scaled by average total assets

ADJRETURN

Market-adjusted annual stock return of the firm

BIG4

1if the auditor is one of the Big 4 auditors, and 0 otherwise

CAPEX

Firm capital expenditure on Property Plant and Equipment scaled by total sales revenue

CEO_Chair

1 if the CEO also chairs the board of directors, and 0 otherwise

CONCENTRATION

Sum of the squares of the market shares of the firms’ sales based on two-digit SIC industry

COMMON_RISK

The proportion of firm-specific stock returns variance explained by market-wide stock returns

DISPFOR

Standard deviation of analyst forecasts divided by absolute value of median forecast, based on the last-available analyst forecast information in IBES two days before the earnings announcement

EARNVOL

Standard deviation of quarterly earnings before extraordinary items for 12 quarters ending at the fourth quarter of the current fiscal year, divided by median assets over the 12 quarters

ErrMEF

The decile rank of the mean absolute value of management forecast bias scaled by price. Forecast bias is defined as point forecast or mid-point of a range forecast minus actual EPS

HORIZON

Average number of days between the forecast date and the fiscal period end date

INST

Percentage of common shares held by institutions at the previous fiscal year end

INVEST

1 if the sum of capital expenditure and R&D expense deflated by average total assets is greater than the sample median, and zero otherwise

LEV

Long-term debt divided by total assets at the beginning of the fiscal year

LITIGATE

1 if the firm belongs to the biotechnology (SIC codes 2833–2836), R&D services (8731–8734), programming (7370–7374), computers (3570–3577), electronics (3600–3674), or retailing (5200–5961) industry, and 0 otherwise

LMVAL

Natural log of the market value of a firm’s common equity (in $ millions) at the previous fiscal year end

LOGSALE

Natural log of the total sales revenue of the firm for the year

LOGSALE_SQ

The squared LOGSALE

LOSS

1 if the firm reported a loss for the previous year, and 0 otherwise

MBE

1 if the firm’s actual EPS for the previous year is equal to or higher than the consensus analyst forecast for that year and 0 otherwise

MKBK

Market value of equity divided by book value of equity at the previous fiscal year end

NUM_EST

Number of analysts following the firm, based on the last-available analyst forecast information in IBES two days before the earnings announcement

Pessimism

1 if average forecast bias for current-year annual earnings point or range forecasts issued during the year is negative and 0 otherwise. Forecast bias is defined as point forecast or mid-point of a range forecast minus actual EPS

PessTone

1 if financially negative words (Loughran & McDonald, 2011) as a percentage of all words in the 10-K is no less than the industry median, and 0 otherwise

RD

Research and development costs scaled by average total assets

RETURN

Annual stock return for the firm, defined as the buy-and-hold return during the previous fiscal year

RETVOL

Annual stock return volatility, defined as standard deviation of monthly stock return during the fiscal year

RP

1 if the CEO’s performance-based restricted stock plans are based on relative performance evaluation goals, and 0 if the plans are based on absolute goals. We require each sample observation’s performance-vested restricted stock component to be equal to or greater than the time-vested restricted stocks

SALE_GROWTH

Percentage change in sales from the previous year

SURPLUS

Operating cash flows minus depreciation/amortization plus R&D, divided by total assets at the beginning of the fiscal year

SURPRISE_MEF

Mean absolute value of the difference between management’s forecasted EPS and median analyst forecast, scaled by stock price at the beginning of the fiscal year

Appendix 2: Management Earnings Guidance for Firms with Small Versus Large Peer Groups in High-RP and Low-RP Industries

Panel A: pessimism of management earnings guidancea

 

Pessimism in high-RP industries

Pessimism in low-RP industries

RP_SmallPeerGroup

0.118**

0.002

 

(2.571)

(0.033)

RP_LargePeerGroup

0.056

0.059

 

(0.472)

(0.848)

All control variables

Yes

Yes

Industry and year fixed effects

Yes

Yes

Firm year clustered standard errors

Yes

Yes

Adjusted R2

12.39%

9.16%

N

569

1139

Panel B: accuracy of management earnings guidanceb

 

ErrMEF in high-RP industries

ErrMEF in low-RP industries

RP_SmallPeerGroup

0.897***

0.195

 

(2.910)

(0.976)

RP_LargePeerGroup

− 0.284

0.120

 

(− 0.553)

(0.474)

All control variables

Yes

Yes

Industry and year fixed effects

Yes

Yes

Firm year clustered standard errors

Yes

Yes

Adjusted R2

28.21%

37.58%

N

569

1139

  1. aThis table reports the estimation results of ordinary least squares regressions for pessimism of management earnings guidance on RP and control variables in high− versus low-RP industries. High-RP industries are industries where the percentage of RP firms is no less than the median percentage of all industries. Pessimism is an indicator variable that takes a value of 1 if the average forecast bias for earnings forecasts issued during the year for current-year annual EPS is negative and 0 otherwise. Forecast bias is defined as point forecast or mid-point of a range forecast minus actual EPS. RP_SmallPeerGroup takes a value of 1 if the CEO’s performance-based restricted stock plans are based on relative performance evaluation goals and the firm designates a small performance peer group that consists of specific peers or an industry specific index with fewer than 100 constituents, and 0 otherwise. RP_LargePeerGroup takes a value of 1 if the CEO’s performance-based restricted stock plans are based on relative performance evaluation goals and the firm designates a large performance peer group that consists of market-wide index or other indices with 100 or more constituents, and 0 otherwise. For brevity, intercepts, control variables, and industry and year indicators are included in the regressions but are not reported. T values in parentheses ( ) are based on two-tailed tests with standard errors clustered by firm and by year. ***, **, and * denote significance at the 0.01, 0.05, and 0.10 levels, respectively
  2. bThis table reports the estimation results of ordinary least squares regressions for the accuracy of management earnings guidance on RP and control variables in high- versus low-RP industries. High-RP industries are industries where the percentage of RP firms is no less than the median percentage of all industries. ErrMEF is the decile rank of the average absolute value of forecast bias for earnings forecasts issued during the year for current-year annual EPS, scaled by price at the beginning of the fiscal year. Forecast bias is defined as point forecast or mid-point of a range forecast minus actual EPS. RP_SmallPeerGroup takes a value of 1 if the CEO’s performance-based restricted stock plans are based on relative performance evaluation goals and the firm designates a small performance peer group that consists of specific peers or an industry specific index with fewer than 100 constituents, and 0 otherwise. RP_LargePeerGroup takes a value of 1 if the CEO’s performance-based restricted stock plans are based on relative performance evaluation goals and the firm designates a large performance peer group that consists of market-wide index or other indices with 100 or more constituents, and 0 otherwise. For brevity, intercepts, control variables, and industry and year indicators are included in the regressions but are not reported. T values in parentheses ( ) are based on two-tailed tests with standard errors clustered by firm and by year. ***, **, and * denote significance at the 0.01, 0.05, and 0.10 levels, respectively

Appendix 3: Pessimism of Management Earnings Guidance for CEOs with Low Talent and with Horizon Problems

 

Pessimism

RP

0.025

 

(0.653)

LTWHP

− 0.065

 

(− 1.489)

RP × LTWHP

0.138***

 

(2.687)

All control variables

Yes

Industry and year fixed effects

Yes

Firm year clustered standard errors

Yes

Adjusted R2

11.87%

N

1294

  1. This table reports the ordinary least squares regression results for the pessimism of management earnings guidance on the use of RP goals in CEO’s restrictive stock plans. Pessimism is an indicator variable that takes a value of 1 if the average forecast bias for earnings forecasts issued during the year for current-year annual EPS is negative and 0 otherwise. RP is an indicator variable that takes the value of 1 if the CEO’s performance-based restricted stock plans are based on relative performance evaluation goals, and 0 if the plans are based on absolute goals. LTWHP is 1 if CEO age is no less than median and managerial ability is no greater than median, and 0 otherwise. For brevity, intercepts, control variables, and industry and year indicators are included in the regressions but are not reported. T values in parentheses ( ) are based on two-tailed tests with standard errors clustered by firm and by year
  2. ***, **, and * denote significance at the 0.01, 0.05, and 0.10 levels, respectively

Appendix 4: Pessimistic Tone of Form 10-Ks for Forecasting Firms Using Relative (RP) Goals versus those Using Absolute (AP) Goals

 

PessTONE

RP

0.019

 

(0.500)

All control variables

Yes

Industry and year fixed effects

Yes

Firm year clustered standard errors

Yes

Adjusted R2

4.73%

N

1700

  1. This table reports estimation results for the ordinary least squares regression of the pessimistic tone in Form 10-K filings on RP and control variables, using the forecasting firm-years with available 10-K tone values. PessTONE is an indicator variable that takes a value of 1 if financially negative words as a percentage of all words in 10-K is no less than the industry median from 2006 to 2017, and 0 otherwise. RP is an indicator variable that takes a value of 1 if the CEO’s performance-based restricted stock plans are based on relative performance evaluation goals, and 0 if the plans are based on absolute goals. For brevity, intercepts, control variables, and industry and year indicators are included in the regressions but are not reported. T values in parentheses ( ) are based on two-tailed tests with standard errors clustered by firm and by year. ***, **, and * denote significance at the 0.01, 0.05, and 0.10 levels, respectively

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Jia, Y., Seetharaman, A., Sun, Y. et al. Relative Performance Goals and Management Earnings Guidance. J Bus Ethics 183, 1045–1071 (2023). https://doi.org/10.1007/s10551-022-05084-3

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