ACCOUNTING RESTATEMENTS: MALFEASANCE AND/OR OPTIMAL INCOMPETENCE? - PowerPoint PPT Presentation

ACCOUNTING RESTATEMENTS: MALFEASANCE AND/OR OPTIMAL INCOMPETENCE? JACQUELYN GILLETTE, SUDARSHAN JAYARAMAN, JEROLD ZIMMERMAN (2016)

RESEARCH QUESTION  Is the level of earnings quality driven by managers’ optimal investment in accounting resources, absent managerial malfeasance?

MOTIVATION  Large number of studies on the determinants of earnings quality (EQ) (Dechow et al., 2010).  Recognize that EQ is driven by innate and discretionary factors (e.g., Dechow and Dichev, 2002; Francis et al., 2005).  Innate factors (e.g., firm size) capture the difficulty of estimating accruals in uncertain operating environments.

CONTRIBUTION  Build on prior studies to suggest another mechanism for why innate factors are correlated with EQ through firms’ investment in accounting resources.  Investment in accounting resources : Long-term investments in accounting hardware, software, and human capital.  Ceteris paribus , smaller investments in accounting resources will lead to:  1 . Less accurate accrual estimates  2 . More mistakes  3 . Higher incentives to misrepresent firm performance

OBJECTIVES  Theoretical Framework :  Develop a framework where restatements (proxy for EQ) are a function of both:  ( 1 ) Optimal investment in accounting resources  “Optimal incompetence”  ( 2 ) Incentives to intentionally misrepresent the firm’s financial performance  “Malfeasance”

OBJECTIVES  Empirical Measures :  Provide two measures for investment in accounting resources:  (1) 10K Filing Timeliness  (2) 10K Spelling Errors  Test whether investment in accounting resources determines EQ (predicts restatements).

MAIN FINDINGS  The firm’s investment in accounting resources determines earnings quality (EQ).  ( 1 ) Measures of accounting resources are significantly correlated with innate factors (e.g., firm size and profitability).  ( 2 ) Accounting resources are negatively associated with the likelihood of a restatement in the subsequent year.  Additional Analyses:  Accounting resources better predict future restatements during booms in the business cycle.  Robust to controlling for endogeneity using an IV design that exploits changes in firms’ filing deadlines.

MODEL INTUITION  Smaller, financially weaker firms will optimally invest less in accounting resources.  Why? Accounting resources are long-run investments that provide benefits over a long period of time.  Smaller, less profitable firms have shorter horizons and receive smaller benefits to these investments.  (1) More likely to be acquired  (2) More likely to file for bankruptcy (abandonment option)  Investing less in accounting resources will lead to lower EQ ( ex post ):  More spelling mistakes  Less timely 10-K filings  More accounting restatements

EMPIRICAL DESIGN  =  = α + β + β + β + β + β Pr RESTATE 1 ACC _ RES ROA RET NCAP LEV   + i t , 1 0 1 i t , 2 i t , 3 i t , 4 i t , 5 i t , ∑ + β + β + β + β + SGR RETVOL SIZE SIZE _ SQ Ind (14) 6 i t , 7 i t , 8 i t , 9 i t , i i ∑ + + ε Year + t i t . 1 t

TABLE 1: DATA & SAMPLE SELECTION

TABLE 2: DESCRIPTIVE STATISTICS

TABLE 4: RESTATEMENT PREDICTION MODEL WITH ACCOUNTING RESOURCES

TABLE 5: RULING OUT AUDIT VERIFICATION EFFECTS

TABLE 6: ADDRESSING ENDOGENEITY OF ACCOUNTING RESOURCES

TABLE 7: FILING TIMELINESS & RESTATEMENTS ACROSS THE BUSINESS CYCLE

TABLE 7: FILING TIMELINESS & RESTATEMENTS ACROSS THE BUSINESS CYCLE

TABLE 8: ACCOUNTING RESOURCES BY RESTATEMENT TYPE

CONCLUSION  We provide a theoretical and empirical model where the investment in accounting resources depends on size and profitability.  Introduce two novel measures for accounting resources (10K filing timeliness and spelling errors).  Accounting resources predicts future restatements.  Firms optimally invest in accounting resources, and the level of this investment drives earnings quality (EQ).

THANK YOU. JGILLETT@MIT.EDU

APPENDIX

RESTATEMENT MODEL R t = v 0 + v 1 SIZE t-1 + v 2 ROA t-1 + v 3 MTB t-1 + v 4 LEV t-1 + v 5 NCAP t-1 + v 6 GROW t-1 + v 7 INCENT t-1 (1) R t = e 0 + e 1 ACC_RES t-1 + e 2 INCENT t-1 (6) ACC_RES t = a 0 + a 1 SIZE t + a 2 ROA t + a 3 CMPLX t + a 4 GROW t (2) INCENT t = d 0 + d 1 ACC_RES t + d 2 ROA + d 3 NCAP t + d 4 LEV t + d 5 MTB t + d 6 GROW t (5)

RESTATEMENT MODEL FILE_TIME t = b 0 + b 1 ACC_RES t (3) SPELL_ERR t = c 0 + c 1 ACC_RES t (4) R t+1 = g 0 + g 1 FILE_TIME t + g 2 SPELL_ERR t + g 3 ROA t + g 4 NCAP t + g 5 LEV t + g 6 MTB t + g 7 GROW t (13)  FILE_TIME : The difference between the firm’s filing deadline date and the date the firm filed its 10K.  SPELL_ERR : The number of spelling errors in the 10K.