Abstract
We investigate how boards incorporate private information about managerial performance in compensation and turnover decisions. Building from the literature documenting that loss firms’ publicly available valuation allowance (VA) disclosures contain value-relevant private information, we show that the decision of whether to record a VA also captures contract-relevant private information. We develop an approach to extract a private, firm-specific, time-varying signal of managerial performance by inferring a more positive (negative) private signal when the VA decision suggests the firm expects the loss to be transitory (persistent). Our empirical analyses rely on a joint test of whether the VA decision reflects a private signal of managerial performance and whether the board uses this private information in contracting. Confirming our hypothesis, we document significantly larger discretionary compensation for transitory loss-firm CEOs, relative to persistent loss-firms. We also show that the VA decision informs the weighting of earnings in determining CEO compensation. Additionally, we provide evidence that the likelihood of CEO turnover is lower in transitory loss-firm years, relative to persistent loss-firms. Overall, extracting private information from the VA decision provides an innovative way to extend understanding of how boards use discretion in contracting.
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Notes
We use the term “VA decision” throughout to refer to the manager’s assessment of whether there will be sufficient future taxable income to realize the tax benefit from the loss (i.e., whether they expect the current loss to be transitory or persistent), resulting in the recording (or nonrecording) of an associated VA.
Compensation payout decisions and the decision of whether to recognize a VA are made concurrently in the period just after fiscal year-end, further supporting the proposition both decisions are derived from related information.
While managers use discretion in establishing a VA, auditors evaluate the reasonableness of management’s assertions relating to the realizability of deferred tax assets. Although research finds mixed evidence that managerial discretion affects VA reporting (e.g., Frank and Rego 2006; Schrand and Wong 2003; Bauman et al. 2001; Miller and Skinner 1998; Visvanathan 1998), the findings of Dhaliwal et al. (2013) and Kumar and Visvanathan (2003) suggest that, even with the potential for managerial manipulation, the VA provides information about the anticipated loss persistence beyond that available from other publicly available information sources.
Using a sample of actual tax footnotes, Dhaliwal et al. (2013) validate that their methodology routinely classifies firm-years consistent with actual VA disclosures.
Since we modify the Dhaliwal et al. (2013) approach to address worldwide firm performance and worldwide income taxes, in sensitivity analyses reported in Sect. 5.3, we validate that this modification does not change our inferences about compensation or turnover. Further, because we limit our sample to Execucomp firms, we replicate the validation analyses of Dhaliwal et al. (2013) to establish that our modified loss-firm categories continue to predict actual loss persistence. We report an extensive set of validations tests in the online appendix.
Dhaliwal et al. (2013) similarly categorize loss observations into transitory and persistent (which they identify as “good news (GN)” and “bad news (BN)” respectively). They further partition the good news group to segregate those with positive taxable income (GN_TI), based on the sign of current year tax expense. If we omit the transitory loss observations without current period taxable income (GN_TI) (less than 2 percent of our sample), our inferences regarding the loss-firm categories in Tables 2 and 4 remain unchanged (untabulated). Alternatively, if we use the three Dhaliwal et al. (2013) categories we find that the coefficients on each group monotonically increases from the most persistent to the most transitory loss categories.
While the VA decision offers a succinct way to infer private signals of manager performance, other loss characteristics may provide information on boards’ private assessments of managers. In untabulated analyses, we verify that our two loss-firm categories contain significant variation in both above/below the line losses (i.e., Gaver and Gaver 1998) as well as in the level of financial distress (i.e., Chang et al. 2016), consistent with the loss-firm categories capturing a distinct aspect of boards’ private assessments of managers relevant for contracting.
This is a significantly lower loss-year frequency than in Dhaliwal et al. (2013). Our sample consists of Execucomp firms, which are larger and better performing, on average, than the Compustat universe and therefore less likely to experience frequent losses. Nevertheless, losses are common in our sample; 51.5 percent of Execucomp firms report a loss in at least one year over the sample period (untabulated).
In addition to the variance in stock returns, we expand the Graham et al. (2012) model to include the variance in ROA, as the weight on earnings in compensation decisions relates to its noise, commonly captured by the variance in the earnings measure (e.g., Hayes and Schaefer 2000; Lambert and Larcker 1987).
The model of Ghosh and Wang (2019) includes year and industry fixed effects. Although requiring firm fixed effects in our specification results in the loss of firms that do not have turnover during the sample period, in our main turnover analyses, we include firm- and year- fixed effects to be consistent with the compensation specifications in Eq. (1). In untabulated analyses, if we replace firm fixed effects with industry fixed effects, we can use the full sample of observations and find our primary inferences in Table 3 remain unchanged. The inclusion of firm fixed effects results in differences in the level of significance on several control variables from those of Ghosh and Wang (2019). However, when using an industry fixed effects specification, the level of significance on these control variables is consistent with that reported by Ghosh and Wang (2019).
The data on forced and voluntary turnovers is as described by Peters and Wagner (2014) and Jenter and Kanaan (2015) and has generously been provided by the authors. CEO turnover classifications follow the approach of Parrino (1997) in which turnovers are classified as forced based on a combination of information in press releases about the CEO departure and CEO age at the time of the turnover. For further details, see Peters and Wagner (2014) and Parrino (1997). Because CEO age is used to proxy for voluntary retirement decisions, we remove the retirement variable (Retire) from our analyses of the likelihood of forced and voluntary turnover.
See, for example, PwC guidance at https://www.pwc.com/us/en/cfodirect/multimedia/videos/valuation-allowance-deferred-tax-assets.html updated May 2020.
We note a significant difference in the proportions of equity compensation arising from restricted stock and options across our sample period in a manner consistent with a move away from the use of option compensation after FAS123R (untabulated). Pooling across our full sample period, we observe that options comprise the larger portion of equity compensation. Our inability to document significant differences in total equity compensation in Table 2 is likely driven by the larger proportion of stock options in the total equity grants. If, however, we partition our sample into pre/post FAS 123R periods, we document significant differences in total equity compensation paid to transitory and persistent loss-year managers in the post-FAS123R period, consistent with restricted stock dominating equity compensation in that period (untabulated).
Similar to the analyses in Table 2 Panel B, in untabulated analyses, we also test whether the weight on earnings and returns varies across transitory and persistent loss firm-years in granting restricted stock and option compensation. With the exception of a marginally significant increase in the weight on market returns in the granting of options between transitory and persistent loss years, we fail to document significant differences in the weight on underlying observable performance measures in separately determining equity grants across the transitory and persistent categories.
Because these tests use only loss-year observations, we include on a single indicator variable (TransitoryLoss) to test for differences in transitory and persistent loss-year compensation, as persistent-loss years are subsumed by the intercept.
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Acknowledgements
We thank our editor, Jennifer Blouin, and our anonymous referee. We also thank Mary Ellen Carter, Peter Demerjian, Feng Gao, Laura Li (MAS Discussant), Frank Moers, Kathleen Powers (ATA discussant), Steven Savoy, Stephanie Sikes, Xue Wang, participants at the 2017 Conference on Convergence of Financial and Managerial Accounting Research, the 2017 University of Illinois- Chicago Accounting Conference, the 2017 ATA Tax Mid-year meeting, the 2019 MAS Mid-year meeting, and the University of Illinois Tax and Managerial Readings Group, and workshop participants at Boston College and University of Wisconsin for their valuable suggestions.
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Appendices
Appendix A
Variable descriptions
Variable | Definition (compustat and CRSP mnemonics in parentheses) |
|---|---|
Loss-firm categories | |
Transitory Loss | Transitory loss-firm year observations. Modified measure from Dhaliwal et al. (2013), defined as a loss firm (IB < 0 and nonpositive PI) with negative total deferred tax expense (TXDI < 0) |
Persistent Loss | Persistent loss-firm year observations. Modified measure from Dhaliwal et al. (2013), defined as a loss firm (IB < 0 and nonpositive PI) with nonnegative total deferred tax expense (TXDI ≥ 0) |
Compensation variables | |
TotalComp | Natural log of (1 + TDC1) |
EquityComp | Natural log of (1 + option compensation + stock compensation), where option compensation is measured as either (OPTION_AWARDS_BLK_VALUE) in the pre-SFAS 123R period or (OPTION_AWARDS_FV) in the post-SFAS 123R period as reported in ExecuComp and stock compensation is measured as either (RSTKGRNT) in the pre-SFAS 123R period or (STOCK_AWARDS_FV) in the post-SFAS 123R period as reported in ExecuComp |
BonusComp | Natural log of (1 + (BONUS + NONEQ_INCENT)), following Cadman et al. (2010) |
RestrictedStockComp | Natural log of (1 + stock compensation), where stock compensation is measured as either (RSTKGRNT) in the pre-SFAS 123R period or (STOCK_AWARDS_FV) in the post-SFAS 123R period as reported in ExecuComp |
Option Comp | Natural log of (1 + option compensation), where option compensation is measured as either (OPTION_AWARDS_BLK_VALUE) in the pre-SFAS 123R period or (OPTION_AWARDS_FV) in the post-SFAS 123R period as reported in ExecuComp |
Pct_Bonus | The percentage of total compensation (TDC1) comprised of bonus compensation (BONUS + NONEQ_INCENT) |
Firm characteristics | |
TotalAssets | Natural log of total assets (AT) |
ROA | Net income (IB) divided by lagged total assets (AT) |
AnnRet | One-year buy-and-hold dividend reinvested return compounded from the CRSP monthly file |
MTB | Market-to-book ratio as measured as market value of equity (CSHO*PRCC_F) divided by book value of equity (CEQ) |
Var_Return | Standard deviation of monthly returns over the prior 12 months |
Var_ROA | Standard deviation of quarterly ROA over the prior five-year period |
MktAdj_AnnRet t | The difference in the raw buy and hold returns and value-weights CRSP market returns over the prior 12-month period ending with the current fiscal year-end |
MktAdj_AnnRet Interim | The difference in the raw buy-and-hold returns and value-weights CRSP market returns over the six-month period subsequent to the current fiscal year-end for nonturnover firms and between the current fiscal year-end and the CEO turnover date for turnover firms |
MVE | The market value of equity, defined as the outstanding common stock (CSHO) multiplied by the ending stock price (PRCC_F) |
HHI | The industry (two-digit SIC) level Herfindahl Index for the current fiscal year |
Growth | The sum of the market value of equity and book value of debt scaled by total assets as of the current fiscal year-end |
Restatement | An indicator variable taking the value of one if the firm has restated earnings during the current or prior period and zero otherwise |
Restructure | An indicator variable taking the value of one if the ratio of special items to total assets are less than or equal to -5% and zero otherwise |
Turnover | An indicator variable taking the value of one if the CEO leaves his or her position in the current period |
Forced Turnover | An indicator variable taking the value of one if the CEO was forced to leave his or her position as coded in the database provided by Florian Peters, Dirk Jenter, and Alexander Wagner from Peters and Wagner (2014), Jenter and Kanaan (2015); Peters and Wagner (2014) |
Voluntary Turnover | An indicator variable taking the value of one if the CEO left his or her position for some other event, not forced, as coded in the database provided by Florian Peters, Dirk Jenter, and Alexander Wagner from Peters and Wagner (2014) and Jenter and Kanaan (2015) |
HighInfo | An indicator variable taking the value of one if the firm’s cumulative three-year accounting income (IB) is less than zero but no valuation allowance was recorded (based on the Dhaliwal et al. 2013) or taking the value of one if the cumulative three-year accounting income (IB) is greater than zero and a valuation allowance was recorded (based on the Dhaliwal et al. 2013 algorithm) and zero otherwise |
LowInfo | An indicator variable taking the value of one if the firm’s cumulative three-year accounting income (IB) is less than zero and a valuation allowance has been recorded (based on the Dhaliwal et al. 2013 algorithm), or the firm’s cumulative three-year accounting (IB) is greater than zero and no valuation allowance has been recorded (based on the Dhaliwal et al. 2013 algorithm) and zero otherwise |
CEO characteristics | |
Tenure | The length of time the executive has been with the current firm. Measured as (DATADATE-JOINEDCO) |
Female_Ind | Indicator variable taking the value of one if the CEO is female |
CEO_COB | Indicator variable taking the value of one if the CEO is also the chair of the board during the current period (TITLEANN) |
FirmRelatedWealth | The value of the CEO’s stock and option portfolio. We use the CEO firm-related wealth data for each firm-year used by Daniel et al. (2020) and provided by the authors at https://sites.temple.edu/lnaveen/data/. To maximize our sample, we employ the following algorithms to evaluate this variable when needed. We replace missing values following each additional step if still missing: 1) with the average level of FirmRelatedWealth from the year prior and year after; 2) with the prior year level; 3) with the subsequent year level; 4) with the average level of FirmRelatedWealth for all remaining available firm-years |
Age | The age of the CEO (AGE) |
Retire | An indicator variable taking the value of one if the CEO is 60 or older and zero otherwise |
ROA_PI | Pre-tax income (PI) divided by lagged total assets (AT) |
Tax_Exp | Tax expense (TXT) scaled by lagged total assets (AT) |
Hist_Earn_Persist | The coefficient on a firm specific regression of current earnings (IB) on prior year’s earnings (IB) using rolling observations over a 10-year period |
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Drake, K.D., Engel, E. & Martin, M.A. Investigating discretion in executive contracting: extracting private information from valuation allowance decisions. Rev Account Stud 28, 533–569 (2023). https://doi.org/10.1007/s11142-021-09648-y
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DOI: https://doi.org/10.1007/s11142-021-09648-y
Keywords
- Executive compensation and turnover
- Private information
- Loss firms
- Loss persistence
- Valuation allowance
- Discretion in contracting