acc & ec

Two tales on nonprofit earnings management:

- accounting and (micro)economics- empirical analysis

Marc Jegers

Pag.2Navorsingsdag ES 2009

Acc & Ec

Focus on agency gap between board and management

(Steinberg 1986, Rand J. of Ec.)


Acc & Ec

Manipulations:– financial statement:

- real: bR

- accounting: bA

- cost accounting:- profit vs. nonprofit: Δip- program vs. adm.+fundr.: Δis

Agency: k (0: budget max.; 1: service max.)


Acc & Ec: real vs. accounting

earnings disclosed:

ΠM = Π + bA + bR – ½ αRbA² - ½ βRbR²

utility function:

S + F - ½ αPbA² - ½ βPbR² - k(½ αRbA² + ½ βRbR²)

Proposition 1: If subsidies and gifts are affected by the overall earnings disclosed by a nonprofit organization, a larger principal-agent gap will result in more important earnings manipulations.


Acc & Ec: taxable vs. non-taxable

earnings disclosed:

ΠM = Π + tΔipCI – γR| Δip|

utility function:

F + S + t ΔipCI – kγR|Δip| - ½ γP(Δip)²

Proposition 2: A deeper principal-agent gap results on average in more manipulations as to the allocation of indirect costs to taxable activities.

Acc & Ec


Acc & Ec: service vs. non-service

earnings disclosed:

ΠM = Π – δR|Δis|

utility function: F + S - kδR|Δis| – ½ δP(Δis)²

Proposition 3: A deeper principal-agent gap results on average in more manipulations as to the allocation of the mission related indirect costs to program activities.

Acc & Ec


Acc & Ec: risk aversion

after having introduced risk aversion, maximising certainty equivalent utility function:

Proposition 4: Both risk-neutral and risk-averse managers of nonprofit organizations will, on average, manipulate more the profits reported, the costs allocated to profit activities, and the costs allocated to program activities, the wider the gap between their objectives and the board’s objectives.


Empirical analysis

NOT direct test of previous hypotheses

Hypothesis 1 (zero profit hypothesis): Nonprofit organisations prefer to manage earnings in order to disclose zero profits.

Hypothesis 2: Under the zero profit hypothesis, unmanipulated earnings and manipulated earnings are negatively correlated.

Hypothesis 3: Nonprofit organisations receiving relatively more subsidies, will be more inclined to manipulate earnings than nonprofit organisations receiving relatively less subsidies.

Acc & Ec


Empirical analysis

Hypothesis 4: Nonprofit organisations characterised by a relatively deeper agency gap, will be more inclined to manipulate earnings than nonprofit organisations characterised by smaller agency gaps.

Hypothesis 5: There is a negative relationship between nonprofit organisations’ indebtedness and the level of earnings manipulations.

Hypothesis 5’: There is a positive relationship between nonprofit organisations’ indebtedness and the level of earnings manipulations.


Empirical analysis

Sample: 1,054 financial statements (2007)

Method: probit (yes/no), heteroscedastic-consistent OLS (amount)


Empirical analysis

Dependent: accruals (exc., fin.+exc., all)

Independent: earnings before ‘manipulation’, relative subsidies, agency gap, financial debt/TA, ln Assets, industry


Empirical analysis: before

-1e6 -800000 -600000 -400000 -200000 0 200000 400000 600000 800000 1e6

5

10

15

20

25

frequency

EBM


Empirical analysis: after

-1e6 -800000 -600000 -400000 -200000 0 200000 400000 600000 800000 1e6

5

10

15

20

25

30

35

40

45 frequency

EBEF


Empirical analysis

Table 3: Correlations between absolute values of manipulated and unmanipulated earnings

Variables correlated Pearson correlation (%) Observations absEBM-absME 63*** 844 absEBM-absME (≠ 0) 64*** 665 absEBEF-absMEFE 45*** 844 absEBEF-absMEFE (≠ 0) 62*** 250 absEBE-absMEE 43*** 844 absEBE-absMEE (≠ 0) 70*** 166

Note: *,**,*** : 10%, 5%, 1% significance levels respectively (one-sided)


Empirical analysis: one of the tables

Table 6: Absolute levels of manipulated earnings (Panel A: overall manipulated earnings (absME): total sample (n=844), restricted sample (n=665))

(14) (15) (16) (17) (18) (19) (20) (21) Constant (1,000) 1,081** 1,469** -3,169*** 1 4,320*** -17 -1,302*** -1,791*** RELSUB 5,286 2,917 13,049 5,110 15,699 2,427 AG 21,406** 31,553** 52,196*** -10,419 69,391*** -12,052 DEBT (1,000) 102 110 41 114 66 122 absEBM 0.15** 0.16** 0.17** 0.18** int:RELSUBabsEBM -0.09 -0.07 int:AGEabsBM 0.22*** 0.20** int:DEBTabsEBM 0.63** 0.62** absrEBM (1,000) 311 846** SIZE (1,000) 160** 212** 477*** 634*** 196*** 270*** industry dummies yes yes yes yes yes yes yes yes N 844 665 844 844 665 665 844 665 R² 46 53 22 41 26 43 45 46 Adj. R² 42 44 21 40 25 42 43 44


Empirical analysis

Conclusions:

Effect of size, agency gap, debt.

acc & ec

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