Ipotesi 2: L’utilizzo dei REM si incrementa successivamente all’entrata in
2.8 RISULTATI E CONCLUSION
Si riportano di seguito le conclusioni dedotte dai dati ottenuti applicando il modello discusso nel presente capitolo.
La tabella 6 esplicita i coefficienti ricavati dall’applicazione del modello
logit, discusso nel paragrafo 2.7, al campione di imprese determinato secondo le
modalità esplicitate nel paragrafo 2.4, nel periodo precedente all’entrata in vigore della SOX (1992 - 2002 non compreso). Dalla tabella si nota che sia il coefficiente di Ab_RoyPROD che di Ab_roa_jm sono statisticamente significativi, dunque sussiste una relazione tra la variabile dipendente Leverage e le variabili indipendenti citate, espressione rispettivamente delle politiche di Real ed Accruals
earnings management.
La tabella 7 invece, esplicita sempre i coefficienti stimati dall’applicazione del modello logit al campione di imprese ad oggetto ma, nel periodo successivo all’entrata in vigore della SOX (2002 non compreso - 2014). Dai dati emerge che il coefficiente Ab_RoyPROD rimane statisticamente significativo, al contrario di Ab_roa_jm. Inoltre Ab_RoyCFO, espressione, come dettagliatamente specificato nel paragrafo 2.5.1, delle politiche di Real earnings maangement, assume significatività statistica.
Si nota dunque, a conferma delle ipotesi presentate nel paragrafo 2.2, che nel periodo successivo all’entrata in vigore della SOX, si è assistito ad un incremento dell’utilizzo delle tecniche di REM a scapito delle tecniche di AEM. Rimano solido dunque l’impianto teorico alla base del presente studio, secondo cui l’applicazione della SOX non ha inciso sugli incentivi alla manipolazione del reddito, ma ne ha spinto la mutazione dalla forma degli AEM alla forma dei REM. Ulteriore convalida proviene dalle medie espresse nelle tabelle 8 e 9.
Si deduce che la diminuzione del coefficiente di Z-score, visibile dalle tabelle 6 e 7, nel passaggio dal periodo pre a quello post SOX, sia dovuta alla crisi finanziaria del 2007, la quale ha inciso sulla probabilità di fallimento delle imprese del campione. Nella stessa direzione i dati presentati nelle tabelle 8 e 9.
118
Tabella 6 - Coefficienti modelli pre - SOX
(5) (6) (7) (8)
VARIABLES LEV LEV LEV LEV
Ab_RoyPROD -247.3*** (40.55) Roa -0.00648 -0.00707 2.604*** -0.00654 (0.00468) (0.00488) (0.787) (0.00590) Size -2.211*** -2.212*** -2.389*** -1.985*** (0.0688) (0.0686) (0.216) (0.0569) Z_score - 0.000503*** - 0.000469*** -0.0123*** - 0.000378*** (0.000142) (0.000138) (0.00346) (0.000126) Ab_RoyCFO -0.893 (0.630) Ab_DISEXP 0.00322 (0.727) Ab_roa_jm -0.0874** (0.0436) Constant -16.55*** -16.51*** -17.28*** -15.20*** (0.499) (0.493) (1.558) (0.418) Observations 8,375 8,799 1,140 9,869
Industry FE YES YES YES YES
Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1
119
Tabella 7 - Coefficienti modelli post - SOX
(5) (6) (7) (8)
VARIABLES LEV LEV LEV LEV
Ab_RoyPROD -223.8*** (30.98) Roa -0.00253 -0.902*** -0.116*** -0.00131 (0.00177) (0.0544) (0.0434) (0.00150) Size -2.299*** -2.153*** -2.225*** -2.158*** (0.0401) (0.0302) (0.0830) (0.0336) Z_score -9.52e-06 -8.92e-
05***
-7.35e-05* -9.27e-07 (1.14e-05) (1.61e-05) (4.38e-05) (2.80e-06)
Ab_RoyCFO -1.197*** (0.289) Ab_DISEXP -0.360 (0.325) Ab_roa_jm 0.0145 (0.0194) Constant -17.15*** -16.09*** -16.43*** -16.31*** (0.296) (0.220) (0.608) (0.251) Observations 21,220 37,897 4,716 25,668
Industry FE YES YES YES YES
Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1
120
Tabella 8 - Statistiche descrittive pre - SOX
mean sd min max
Ab_RoyCFO .0081874 .1436894 -.5201985 .5591499 Ab_RoyPROD -.001067 .0055094 -.0166596 .0163706 Ab_DISEXP -.0109728 .2960217 -.8579603 .8702855 Ab_roa_jm .1619544 1.376394 -7.177557 6.835927 Roa -.3612724 4.527882 -147 .7666667 Size 4.837569 2.603194 -6.907755 11.16634 Z_score 222.7999 2084.375 -33599.98 38152.26
Tabella 9 - Statistiche descrittive post - SOX
mean sd min max
Ab_RoyCFO .0215536 .1308964 -.5274566 .6384959 Ab_RoyPROD -.0007298 .004491 -.0167516 .0199576 Ab_DISEXP -.0139621 .2675261 -.8719862 1.089703 Ab_roa_jm .0385177 1.843857 -7.177557 6.835927 Roa -.4303924 4.549011 -179.4737 6.676471 Size 5.578131 2.729714 -4.828314 12.57929 Z_score 738.0692 13311.52 -2282.131 749807.2
121
Tabella 10 - Tavola di correlazione
LEV Ab_ RoyCFO Ab_ RoyPROD Ab_ DISEXP Ab_ roa_jm Roa Size Z_score
LEV 1 Ab_ RoyCFO 0.229*** 1 Ab_ RoyPROD 0.0859*** -0.108*** 1 Ab_ DISEXP -0.164*** -0.431*** -0.234*** 1 Ab_roa _jm -0.0138 -0.0108 -0.0174 0.00690 1 Roa 0.0617*** 0.0529*** 0.0471*** -0.0528*** -0.0221 1 Size 0.708*** 0.265*** 0.158*** -0.149*** -0.0482*** 0.233*** 1 Z_score -0.0292* 0.00729 -0.0210 0.0230 -0.00545 0.0235 0.00505 1 * p < 0.05, ** p < 0.01, *** p < 0.001
122
INDICEDELLETABELLE
Tabella 1 - Abbreviazioni 17
Tabella 2 - Interessi e potere decisionale dei principali Stakeholder 25 Tabella 3 - Approccio ideale, ideologico e strumentale 33
Tabella 4 - Tecniche di REM 41
Tabella 5 – Dechow et al. (1996), sintesi dei risultati sugli incentivi agli EM 72 Tabella 6 - Coefficienti modelli pre - SOX 118 Tabella 7 - Coefficienti modelli post - SOX 119 Tabella 8 - Statistiche descrittive pre - SOX 120 Tabella 9 - Statistiche descrittive post - SOX 120
Tabella 10 - Tavola di correlazione 121
INDICEDELLEFIGURE
Figura 1 - La distinzione tra Fraud ed Earnings Management 12
Figura 2 - Asimmetrie informative 23
123
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