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Purpose of paper

Earnings Management and Overinvestment: Accrual-Based versus Real Activities Daniel A. Cohen and Paul Zarowin New York University November, 2009. Purpose of paper. examine how both real and accrual-based earnings management activities affect firms’ investment activities. Motivation.

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Purpose of paper

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  1. Earnings Management and Overinvestment: Accrual-Based versus Real ActivitiesDaniel A. Cohen and Paul ZarowinNew York UniversityNovember, 2009

  2. Purpose of paper • examine how both real and accrual-based earnings management activities affect firms’ investment activities

  3. Motivation • dearth of evidence on how EM affects firms’ real activities • Research on the consequences of EM has concentrated largely on announcement and post event stock market returns

  4. Motivation, continued • earnings management may affect resource allocation by causing firms to make suboptimal investment decisions • returns studies can only determine whether securities are mispriced, which causes redistribution (between different groups of shareholders), but cannot assess affects on real firm decisions • Because they affect the size of the pie, and not just its distribution, real decisions are likely more costly than share price effects.

  5. 2 recent papers • Kedia and Philippon, 2008 • McNichols and Stubben, 2008 • Study real effects of EM

  6. Kedia and Philippon, 2008 • SEC mandated restatement sample • overinvested (excess capexp) and over hired during the EM period • subsequently underinvested and shed employment • Their hypothesis: manipulating firms invest and hire excessively to pool with better performing firms, in order to avoid detection

  7. McNichols and Stubben 2008 • 3 groups of firms that overstated earnings • investigated by the SEC for accounting • sued by their shareholders for accounting • restated their financial statements • Overinvested (excess capexp) during the misreporting period • underinvested during post-event period • Their hypothesis: overinvestment is caused by the misleading signals that the misstated information sends to both internal decision makers and external suppliers of capital.

  8. 2 recent papers, continued • Both studies focus exclusively on accrual-based earnings management • Small, event-based samples • Extreme cases of earnings management

  9. Our contribution • First study to examine economic consequences of real EM • Large sample, not event-based, not extreme earnings management: results can be generalized to wide population of firms

  10. Our findings • Both real and accrual EM firms overinvest in the years up to and including the period of high EM, and then underinvest • Indicates that EM is associated with significant real effects • Real EM firms overinvest more than accrual EM firms • first evidence that real EM has important economic effects

  11. Increased interest in real EM • Recent increased interest in EM thru real activities manipulation • Gunny 2006 • Roychowdhury 2006 • Zang 2006

  12. Increased interest in real EM, continued • Graham et al. (2005): managers prefer real earnings management activities compared to accrual-based earnings management. • Real management activities can be indistinguishable from optimal business decisions. • More difficult to detect.

  13. Increased interest in real EM, continued • Cohen et al. (2008): managers have shifted away from accrual to real earnings management in the post SOX period. • Perhaps because of the need to avoid detection following highly publicized accounting scandals.

  14. Related Literature – consequences of EM • focus on stock price effects related to EM • EM around specific corporate events: IPOs, SEOs, management buyouts, stock repurchases, stock for stock acquisitions • how ex-ante EM relates to observed post event abnormal stock returns • Rangan (1998) and Teoh et al. for SEO’s • Teoh, Wong, and Rao (1998) for IPOs

  15. Related Literature – consequences of EM, cont’d • short-term capital market reactions around announcements of fraudulent reporting • Foster (1979), Dechow, Sloan, and Sweeny (1996), Beneish (1997), and Palmrose, Richardson, and Scholz (2004) • market reaction to disclosure of manipulation is on average negative, implying that investors were surprised and interpret these as negative news

  16. Related literature: Studies of real earnings management • Graham et al.’s survey (2005) - managers prefer real activities manipulation, over accruals manipulation, as a way to manage earnings. • Several features of real earnings management: • Involve current or future cash flows • Cannot be made after the end of the fiscal period • Tougher to be challenged by auditors • Managers may favor real EM strategies • Less regulatory scrutiny • Earlier actions to safeguard against future potential accrual shortfalls

  17. Real earnings management, cont’d • Roychowdhury (2006) - firms try to avoid losses 3 ways: • (1) boosting sales through accelerating timing and/or generating additional unsustainable sales through increased price discounts or more lenient credit terms • (2) overproducing and allocating more overhead to inventory and less to cost of goods sold • (3) reducing aggregate discretionary expenses (R&D + advertising+ SG&A) to improve margins.

  18. Real earnings management, cont’d • Zang (2006) - analyzes the tradeoffs between accrual manipulations and real earnings management. • shows that real manipulation is positively correlated with the costs of accrual manipulation • accrual and real manipulations are negatively correlated • Conclusion: managers treat the two strategies as substitutes.

  19. Empirical methodology – Data and Initial Sample • COMPUSTAT from 1987 to 2006, to use SFAS No. 95 SCF to estimate accruals, (Collins and Hribar, 2002) • all nonfinancial firms with available data necessary to calculate the discretionary accruals metrics and real EM proxies for our analysis • ≥ 8 observations in each 2-digit SIC grouping per year • 82,039 firm-year observations

  20. SUSPECT Firms • Focus on SUSPECT firms – firms likely to have managed earnings • firms with annual earnings before extraordinary items (scaled by total assets) between 0 and 0.005 • 3,831 firm-year observations (Table 2, Panel B - 4.67% of initial sample)

  21. Accrual-based Earnings Management Metric • modified cross-sectional Jones model (Jones 1991) as described in Dechow et al. (1995). • (1)

  22. Accrual model, cont’d • where, for fiscal year t and firm i, TA represents total accruals: • TA it = EBXI it – CFO it, • EBXI is earnings before extraordinary items and disc. operations (annual Compustat 123) • CFO is operating cash flows (from continuing operations) taken from the statement of cash flows (Compustat 308 – Compustat 124), • Assetit-1 is total assets (Compustat 6), • REVit is change in revenues (Compustat 12), and • PPEit is the gross value of property, plant and equipment (Compustat 7).

  23. Accrual model, cont’d • cross-sectional model of discretionary accruals • for each year we estimate the model for every 2-digit SIC code • control for industry-wide changes in economic conditions that affect total accruals • allows coefficients to vary across time

  24. Accrual model, cont’d • coefficient estimates from equation (1) are used to estimate the firm-specific normal accruals (NA it) for our sample firms: • (2) • discretionary accruals is the difference between total accruals and the fitted normal accruals, defined as: • DAit = (TA it / Assetit-1) – NAit. • Accrual based earnings managers: top 10% of firm-year DA observations each year (8,204 firm-year observations)

  25. Real Earnings Management Metrics • Based on Roychowdhury (2006), Zang (2006) and Gunny (2006) • 3 metrics as proxies for real earnings management - abnormal levels of: • CFO • discretionary expenses • production costs

  26. 3 real manipulation methods • 1. Accelerate timing of sales by increased price discounts or more lenient credit terms. • 2. Reporting of lower cost of goods sold through increased production. • 3. Decreased discretionary expenses, such as advertising, R&D, and SG&A expenses.

  27. Calculation of 3 metrics • 1. ∆sales > 0 and ∆CFO < 0 • INCR_SALES&DECR_CFO • 2. ∆COGS < 0 and ∆inventory > 0 • COGS_CUT&∆INV>0 • 3. 0 < EBDISXt < DISXt-1 • can show profits by cutting discretionary expenditures below last year’s amount

  28. Table 1- Panel ASample statistics • comparison of SUSPECT vs non-SUSPECT firms • SUSPECT firms are: • smaller (in terms of assets, sales, MV) • less profitable • Invest more (cap and non-cap exp, %TA) • greater growth in assets and employees. • high growth -consistent with Kedia and Philippon and McNichols and Stubben.

  29. Table 1, Panel A: Comparison of Investment Activities and Earnings Management Strategies among Different Group of Firms: SUSPECT vs. NON-SUSPECT Firms

  30. Table 1 - Panel B sample distribution • Firms using real earnings management: • 2,000 – 2,600 observations (2.5% - 3.2% of initial sample)

  31. Focus: 4 subgroups • intersection of SUSPECT and earnings management • firms likely to have managed earnings • we can identify the method of earnings management • Thus, we can calculate the relation between the method and the extent of over- or under investment.

  32. 4 subgroups, cont’d • All 4 subgroups have similar number of observations (0.8% - 1.0% of sample) • This gives us confidence that all four subgroups have comparable degrees of earnings management

  33. Panel B: Sample Distribution

  34. Table 2 - Investment behavior of SUSPECT firms • investment for years t-3 thru t+3 • Investment relative to control groups of firms ranked by size and industry • Results for total investment and its components, capital expenditures, and non-capital expenditures

  35. Table 2, cont’d • column 1: total investment • SUSPECT firms with overinvest during the period of upward management, and then subsequently underinvest • Year 0: SUSPECT firms invest 1.9% more than comparable firms, as a % of TA • year +1: invest 2.8% less • relative investment decline of 4.7% (of TA) • Columns 2, 3, and 4 (CAPEXP, non-CAPEXP, Employment) • Consistent with Kedia and Philippon and McNichols and Stubben

  36. Table 2:Investments Activities partitioned by Alternative Earnings Management Strategies throughout Time among SUSPECT Firms

  37. Table 3 - Investment behavior for different EM strategies • investment for years t-3 thru t+3 • Investment relative to control groups of firms ranked by size and industry • Results for total investment and its components, capital expenditures, and non-capital expenditures

  38. Table 3, cont’d • All strategies: overinvestment in the period up to and including EM year; subsequent underinvestment • Panel A – high DA firms overinvest during the period upto and including the EM year, and then subsequently underinvest • Panels B – D: same for real EM firms • real EM firms have even greater over- and underinvestment than high DA firms

  39. Table 3:Investment Activities for Different EM strategies

  40. Table 4 - Control for investment opportunities • investment is a function of investment opportunities and liquidity • Omitted factors may be correlated with measures of earnings management • relation between investment and EM may be due to omitted factors • i.e., excess investment might really be optimal given the firm’s opportunity set

  41. Investment as a function of fundamentals and earnings management • Insert equation (10) here • Model based on Biddle, Hilary, and Verdi (2008) • Augmented by SUSPECT, EM, and SUSPECT*EM

  42. Investment model • dependent variable: INVEST, CAPEX, or NONCAPEX, scaled by total assets (TA) • LOG_ASSET is the log of total assets • MKT_BK is MV of equity/BV of TA • LEVERAGE is long term debt/MV of equity • SLACK is cash/PPE • AGE is current year - first year on CRSP • OP_CYCLE is ln(AR/sales+inv/CGS)* 360 • LOSS = 1 if NI before extra.items is negative and zero otherwise; • TANGIBLE is PPE/TA • DIVIDEND = 1 if the firm paid dividends and zero otherwise.

  43. Table 4, Panel AResults of equation (10) • Overall, the coefficients on the fundamentals are consistent with expectations, and equation (10) explains about 25% of the cross-firm variation in investment.

  44. Focus on SUSPECT*EM • focus on firms most likely to have managed earnings, but by different means • coefficients on SUSPECT*EM capture the overinvestment for suspect firms differentiated by strategy • enable us to compare the effects of different earnings management strategies on excess investment.

  45. Results for SUSPECT*EM • Table 4, Panel A • coefficients on all of the interaction terms are significantly positive • shows that firms managing earnings by any of the strategies overinvest • the coefficients on the real earnings management interactions are two to four times as great as the coefficient on the accrual interaction

  46. Table 4, Panel A, cont’d • Firms increasing production to cut COGS have the greatest overinvestment: 14.2% of TA • followed by firms cutting discretionary expenditures: 8.1% • High DA firms - overinvestment of 3.1%

  47. Table 4:Relation between Investments and Alternative Earnings Management Strategies Panel A: Dependent variable is INVEST

  48. Table 4, Panels B and C • Results due mainly to CAPEXP (Panel B) • Little variation in NONCAPEXP (Panel C)

  49. Panel B: Dependent variable is CAPEX

  50. Panel C: Dependent variable is NONCAPEX 50

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