Effect of Earnings Management on Earnings Quality and Sustainability: Evidence from Gulf Cooperation Council Distressed and Non-Distressed Companies
Abstract
:1. Introduction
2. Background
3. Literature Review and Hypotheses Development
3.1. EM Studies
3.2. EM and EQ
3.3. EM and ES
3.4. EM, EQ and ES, and Distressed and Non-Distressed Companies
3.5. EM, EQ, and ES across Industries
3.6. Conclusions
4. Research Methodology
4.1. Sample Selection
4.2. Empirical Models
β7(MJM*Distress)it + β8(EV*Distress)it + β8(ROA*Distress)it + β9(Firm Size*Distress)it + ε
β7(MJM*Distress)it + β8(ROA* Distress)it + β9(Firm Size*Distress)it + ε
EM Measurement
NIjt = net income before extraordinary items for firm j at time t; |
CFOjt = operating cash flows as from the statement of cash flows for firm j at time t. |
ΔREVt | = revenues in year t less revenues in year t − 1 scaled by total assets at t − 1; |
PPEt | = gross property, plant, and equipment in year t scaled by total assets at t − 1; |
At−1 | = total assets at t − 1; |
ΔRECt | = net receivables in year t less net receivables in year t − 1 scaled by total assets at t − 1 and all other variables as previously defined; |
α1, α2, α3 | = firm-specific parameters. |
TACCt | = total accruals scaled by lagged total assets; |
a1, a2, a3 | = the ordinary least squares estimates of α1, α2, and α3; |
γt | = measurement error in year t and all other variables as previously defined. |
TACCijp | = total accruals for estimation portfolio j for firm i in event year p; |
ΔREVijp | = change in revenue (total sales) for estimation portfolio j for firm i in event year p; |
PPEijp | = gross PP&E for estimation portfolio j for firm i in event year p; |
Aijp−1 | = total assets at beginning of period for estimation portfolio j for firm i in event year p; |
εijp | = measurement error for estimation portfolio j for firm i in event year p; |
i | = 1, …, N firm index; |
j | = 1, …, J estimation portfolio index; |
p | = 1, …, P year index. |
TACCip | = total accruals for firm i in event year p; |
DACCip | = discretionary accruals for firm i in event period p; |
NDACCip | = nondiscretionary accruals for firm i in event period p; |
i | = 1, …, N firm index; |
p | = 1, …, P year index. |
5. Empirical Findings
5.1. EQ and EM
5.2. ES and EM
5.3. EM across Industries
5.4. Endogeneity Tests
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A. Variable Definitions
EQ | Earnings quality, calculated as cash flow from operations (CFO) divided by operating profit. |
ES | Earnings sustainability, calculated as the standard deviation of the annual operating income growth rate for a firm over the period 2011–2022 on a rolling window basis. |
MJM | Discretionary accruals as a proxy for earnings management, calculated from the Modified Jones Model (Dechow et al. 1995). |
EV | Earnings volatility, calculated as the standard deviation of the change in earnings levels over a 2-year period. |
ROA | Return on assets, calculated as net income before extraordinary items divided by lagged total assets. |
Firm Size | Firm size measured as the natural logarithm of total assets. |
Industry Type | Industry dummies to control for industry fixed effects. |
Distress | An indicator variable that takes the value of 1 for firms with a debt ratio equal to or exceeding 62% and zero otherwise. |
Growth | Revenue growth rate, calculated as the percentage change in revenues. |
i | Firm subscript. |
t | Time subscript. |
1 | In terms of Stata functionality: industry and time dummies are included in the regressions by specifying the following operators, respectively: i.Industry and i.Year. |
2 | The Risk Management Association has conducted research on various companies across different industries. According to their findings, most companies tend to maintain an average debt ratio ranging between 57% and 67%. We have considered the average of this range (62%) as a benchmark to evaluate debt levels and ensure they are within acceptable limits. |
3 | These estimates represent the normal (expected) level of nondiscretionary accruals in the industry. |
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Panel A. Descriptive Statistics | ||||||||
Variables | Mean | Std. Dev. | Min | Max | 1st percentile | 99th percentile | ||
EQ | 0.949 | 6.347 | −35.567 | 31.130 | −35.567 | 31.034 | ||
EM | 0.000 | 0.087 | −0.330 | 0.393 | −0.273 | 0.348 | ||
EV | −19.009 | 361.630 | −2227.358 | 1606.701 | −2089.268 | 1594.212 | ||
ES | 4.689 | 1.526 | 1.372 | 9.038 | 1.539 | 9.038 | ||
Growth | 12.333 | 60.906 | −100.000 | 444.444 | −98.038 | 386.707 | ||
ROA | 0.044 | 0.086 | −0.303 | 0.306 | −0.298 | 0.306 | ||
Firm Size | 13.307 | 2.539 | 8.047 | 19.472 | 8.072 | 19.472 | ||
Distress | 0.464 | 0.499 | 0.000 | 1.000 | 0.000 | 1.000 | ||
Observations | 3621 | |||||||
Panel B. Correlation Matrix | ||||||||
Variable | EQ | ES | EM | EV | ROA | GROWTH | Firm Size | Distress |
EQ | 1.000 | |||||||
ES | −0.058 ** | 1.000 | ||||||
EM | −0.077 ** | −0.019 | 1.000 | |||||
EV | 0.013 | −0.030 | 0.125 ** | 1.000 | ||||
ROA | 0.055 ** | −0.309 ** | 0.367 ** | 0.171 ** | 1.000 | |||
Growth | −0.004 | 0.071 ** | 0.151 ** | 0.079 ** | 0.167 ** | 1.000 | ||
Firm Size | 0.030 | −0.062 ** | 0.010 | 0.046 * | 0.125 ** | 0.049 * | 1.000 | |
Distress | −0.007 | 0.133 ** | −0.071 ** | −0.052 * | −0.174 ** | 0.005 | 0.178 ** | 1.000 |
Dependent Variable | Earnings Quality (EQ) Modified Jones Model Discretionary Accruals (1) | Earnings Quality (EQ) Kothari et al. (2005) Performance-Matched Discretionary Accruals (2) |
---|---|---|
Variable | ||
Intercept | 0.637 ** | 0.675 ** |
(3.49) | (3.58) | |
Earnings management proxy | −5.583 ** | −4.557 ** |
(−15.80) | (−12.99) | |
Earnings volatility | −1.203 | −1.450 * |
(−1.93) | (−2.21) | |
Return on assets (ROA) | 0.004 ** | 0.002 ** |
(6.09) | (2.64) | |
Firm Size | −0.007 | −0.012 |
(−0.59) | (−1.09) | |
Distressed Firms | −0.565 | −0.587 |
(−1.67) | (−1.65) | |
EM*Distressed Firms | 0.469 | −0.395 |
(0.64) | (−0.53) | |
Earnings volatility * Distressed Firms | 0.714 | 0.857 |
(1.12) | (0.84) | |
ROA * Distressed Firms | 0.017 ** | 0.003 |
(2.60) | (0.39) | |
Firm Size * Distressed Firms | 0.027 | 0.035 |
(1.18) | (1.47) | |
Observations | 2459 | 2459 |
F-statistic | 14.71 ** | 10.93 ** |
Year dummies | Yes | Yes |
Industry dummies | Yes | Yes |
Dependent Variable | Earnings Sustainability (ES) Modified Jones Model Discretionary Accruals (3) | Earnings Sustainability (ES) Kothari et al. (2005) Performance-Matched Discretionary Accruals (4) |
---|---|---|
Variable | ||
Intercept | 5.281 ** | 5.211 ** |
(30.46) | (30.02) | |
Earnings management proxy | 1.895 ** | 2.164 ** |
(5.26) | (5.98) | |
Revenue growth rate | 0.003 ** | 0.003 ** |
(6.78) | (6.48) | |
Return on assets (ROA) | −6.257 ** | −5.171 ** |
(−18.80) | (−15.55) | |
Firm Size | −0.041 ** | −0.040 ** |
(−3.19) | (−3.14) | |
Distressed Firms | −0.630 | −0.639 |
(−1.70) | (−1.72) | |
EM * Distressed Firms | −0.442 | −0.600 |
(−0.62) | (−0.85) | |
ROA * Distressed Firms | 0.005 | 0.004 |
(0.64) | (0.58) | |
Firm Size * Distressed Firms | 0.070 ** | 0.070 ** |
(2.69) | (2.70) | |
Observations | 3621 | 3621 |
F-statistic | 10.957 ** | 10.949 ** |
Year dummies | Yes | Yes |
Industry dummies | Yes | Yes |
TRBC | Description | Frequency | % | Cumulative % | Firm-Year Observations |
---|---|---|---|---|---|
50 | Energy | 36 | 6.56 | 6.56 | 432 |
51 | Basic materials | 98 | 17.85 | 24.41 | 1176 |
52 | Industrials | 75 | 13.66 | 38.07 | 900 |
53 | Consumer cyclicals | 67 | 12.20 | 50.27 | 804 |
54 | Consumer non-cyclicals | 85 | 15.48 | 65.76 | 1020 |
56 | Healthcare | 26 | 4.74 | 70.49 | 312 |
57 | Technology | 39 | 7.10 | 77.60 | 468 |
59 | Utilities | 25 | 4.55 | 82.15 | 300 |
60 | Real estate | 86 | 15.66 | 97.81 | 1032 |
63 | Academic and educational services | 12 | 2.19 | 100.00 | 144 |
Total | 549 | 100.00 | 100.00 | 6588 |
Observations | Parametric (ANOVA) Test | Non-Parametric (Kruskal–Wallis) test | ||||
---|---|---|---|---|---|---|
TRBC | Industry | N | Mean | Std. Deviation | Rank Sum | Rank Mean |
50 | Energy | 284 | −0.0163 | 0.0611 | 504,612 | 1776.80 |
51 | Basic materials | 815 | −0.0004 | 0.0650 | 1,620,000 | 1987.09 |
52 | Industrials | 539 | 0.0020 | 0.1050 | 1,080,000 | 2004.19 |
53 | Consumer cyclicals | 464 | −0.0125 | 0.0936 | 860,603 | 1854.75 |
54 | Consumer non-cyclicals | 584 | 0.0058 | 0.0939 | 1,220,000 | 2088.88 |
56 | Healthcare | 173 | 0.0228 | 0.0768 | 415,277 | 2400.45 |
57 | Technology | 244 | −0.0423 | 0.1011 | 302,873 | 1241.28 |
59 | Utilities | 172 | −0.0049 | 0.0478 | 322,898 | 1877.31 |
60 | Real estate | 700 | 0.0184 | 0.0730 | 1,670,000 | 2390.72 |
63 | Academic and educational services | 52 | 0.0062 | 0.0424 | 110,969 | 2134.02 |
p-value | 0.0000 | 0.0001 |
Tests of Endogeneity and Over-Identifying Restrictions | Test Specification | |
---|---|---|
Durbin (score) chi2 | F = 2.27 | p-value = 0.1319 |
Wu–Hausman | F = 2.26 | p-value = 0.1327 |
Sargan (score) chi2 | X2 = 0.45 | p-value = 0.9288 |
Basmann (score) chi2 | X2 = 0.45 | p-value = 0.9294 |
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Aljifri, K.; Elrazaz, T. Effect of Earnings Management on Earnings Quality and Sustainability: Evidence from Gulf Cooperation Council Distressed and Non-Distressed Companies. J. Risk Financial Manag. 2024, 17, 348. https://doi.org/10.3390/jrfm17080348
Aljifri K, Elrazaz T. Effect of Earnings Management on Earnings Quality and Sustainability: Evidence from Gulf Cooperation Council Distressed and Non-Distressed Companies. Journal of Risk and Financial Management. 2024; 17(8):348. https://doi.org/10.3390/jrfm17080348
Chicago/Turabian StyleAljifri, Khaled, and Tariq Elrazaz. 2024. "Effect of Earnings Management on Earnings Quality and Sustainability: Evidence from Gulf Cooperation Council Distressed and Non-Distressed Companies" Journal of Risk and Financial Management 17, no. 8: 348. https://doi.org/10.3390/jrfm17080348