Transition between firm life cycle stages and earnings management strategies

Ribeiro, João Paulo Machado; Paulo, Edilson; Magro, Cristian Baú Dal

doi:10.1590/1808-057x20231954.en

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Original Article • Rev. contab. finanç. 35 (96) • 2024 • https://doi.org/10.1590/1808-057x20231954.en linkcopy

Transition between firm life cycle stages and earnings management strategies

Authorship SCIMAGO INSTITUTIONS RANKINGS

This study analyzed the effects of firm life cycle stages (LCS) and their changes on the level of adoption of earnings management strategies. Gaps were identified regarding the effects of the transition between various life cycle stages and the propensity for accrual-based earnings management (AEM) and real activities earnings management (REM), as well as the impacts on the trade-off or complementarity relationship between them. The findings reinforce the need for auditors, financial analysts, investors, and regulators to consider company context and specific characteristics, such as firm cycle stage, when analyzing earnings management. The results suggest a greater propensity for all earnings management strategies, in order to hide financial difficulties, at the beginning of the decline stage. A total of 185 companies listed on the Brazilian capital market were analyzed for the period from 2011 to 2022, with data collected from Refinitiv^®. Park and Chen’s (2006) model has been adopted to classify firm life cycle stages, and the models were estimated by the system generalized method of moments (system GMM). Growth stage firms use overproduction and avoid discretionary expense cuts as REM strategies. However, when transitioning from the growth stage to the mature stage, they are more likely to cut discretionary expenses as an REM strategy. The use of AEM is more prevalent in the decline stage, when compared to mature stage companies. The findings add evidence to the literature that the trade-off or complementarity relationship between AEM and REM is influenced by firm LCS and their transitions.

Keywords:
earnings management; firm life cycle; discretionary accruals; earnings quality

Variables	Code	Proxies
Capital Expenditures	CEV	Capex_it / Book value_it ^* 100
Sales Growth	SG	(Net Sales_it - Net Sales_it-1)/ Net Sales_it-1 ^* 100
Dividend Payout	DP	Dividends Paid_it / Net Profit_it ^* 100
Firm Age	AGE	Current Year - Year of Foundation

Panel A - Scoring Criteria
Quintiles		Variables
Quintiles		DP	SG	CEV	AGE
1º quintile	0% - 20%	5(1)	1	1	5
2º quintile	20% - 40%	4(2)	2	2	4
3º quintile	40% - 60%	3	3	3	3
4º quintile	60% - 80%	3	4	4	2
5º quintile	80% - 100%	3	5	5	1
Panel B - Classification of company life cycle stages
Life Cycle Stage			Index Score Range
Growth			16-20
Mature			9-15
Decline			4-8

Variables	Description	Metric	Theoretical basis
Dependent variables
REM	Earnings management proxy under analysis: REM, ADISX, or APROD	Residuals from Roychowdhury’s (2006) model	Pae (2005), Paulo and Mota (2019), Roychowdhury (2006), and Zang (2012)
AEM	Proxy for earnings management via AEM	Residuals from Pae’s (2005) model	Pae (2005) and Paulo and Mota (2019)
Independent variables
Growth	Growth stage at t and t-1	Park and Chen’s (2006) model	Lima et al. (2015) and Park and Chen (2006)
Decline	Decline stage at t and t-1		Lima et al. (2015) and Park and Chen (2006)
Growth-Mature	Transition from growth stage at t-1 to mature at t		Bhattacharya et al. (2020), Can (2020), and Hansen et al. (2018)
Mature-Decline	Transition from mature stage at t-1 to decline at t
Mature-Growth	Transition from the decline stage at t-1 to mature at t
Decline-Mature	Transition from the decline stage at t-1 to mature at t
Control variables
Size	Company size	Natural logarithm of total assets at t	Azevedo et al. (2022), Du and Shen (2018), Khuong et al. (2022), and Qi et al. (2018)
ROA	Return on assets	Net income divided by total assets in t	Du and Shen (2018), and Paulo and Mota (2019)
Lev	Financial leverage	Ratio between onerous liabilities and total assets in t	L. Chen et al. (2018), Paulo and Mota (2019), Qi et al. (2018), and Roma et al. (2021)
SG	Sales growth	Percentage variation in sales	Azevedo et al. (2022), Li (2019), and Rocha et al. (2022)
CFO	Cash flows from operations	Cash flows from operations divided by total assets in t	Khuong et al. (2022), Li (2019), and Roma et al. (2021)
Vol(CFO)	Volatility of cash flow from operations	Standard deviation of CFO over a 5-year window	L. Chen et al. (2018) and Du and Shen (2018)
Big4	Audit firm	Dummy for a Big four audit firm	Azevedo et al. (2022), Xie et al. (2022), and L. Chen et al. (2018)
Loss	Loss	Dummy for income negative at t	Azevedo et al. (2022), Qi et al. (2018), and Roma et al. (2021)
Covid	COVID-19	Dummy for the COVID-19 period (2020 and 2021)	Azevedo et al. (2022)
REM	Earnings management through operational decisions	Equation 5	Li, (2019), Paulo and Mota (2019), Rocha et al. (2022), and Zang (2012)

Variables	Mean	Standard deviation	Minimum	Perc 25	Median	Perc 75	Maximum
Panel A - Total Sample (1,223 observations)
AEM	0.006	0.047	-0.513	-0.014	0.004	0.026	0.22
REM	-0.018	0.186	-1.239	-0.073	0.002	0.064	1.765
ADISX	-0.001	0.099	-0.545	-0.027	0.007	0.03	1.805
APROD	-0.017	0.109	-0.772	-0.065	-0.008	0.044	0.476
Size	22.439	1.587	17.101	21.354	22.395	23.469	26.936
ROA	0.06	0.075	-0.93	0.025	0.052	0.083	1.077
Lev	0.296	0.170	0.000	0.170	0.298	0.411	0.768
SG	0.474	10.897	-0.983	0.016	0.107	0.225	365.157
CFO	0.083	0.106	-1.153	0.042	0.087	0.135	0.508
Vol(CFO)	0.067	0.209	0.003	0.029	0.045	0.07	5.85
Panel B - Growth (169 observations)
AEM	-0.001	0.046	-0.25	-0.022	0.000	0.022	0.193
REM	-0.031	0.199	-0.822	-0.076	0.019	0.08	0.372
ADISX	-0.014	0.096	-0.432	-0.042	0.013	0.03	0.228
APROD	-0.017	0.122	-0.39	-0.069	0.004	0.056	0.217
Size	22.700	1.532	18.505	21.627	22.779	23.895	25.637
ROA	0.047	0.057	-0.105	0.014	0.037	0.073	0.327
Lev	0.385	0.184	0.000	0.248	0.387	0.524	0.768
SG	0.363	0.533	-0.71	0.138	0.233	0.399	5.049
CFO	0.081	0.097	-0.287	0.028	0.085	0.142	0.385
Vol(CFO)	0.103	0.452	0.007	0.03	0.046	0.074	5.850
Panel C - Mature (848 observations)
AEM	0.007	0.048	-0.513	-0.013	0.005	0.025	0.220
REM	-0.02	0.178	-1.239	-0.075	-0.002	0.059	0.583
ADISX	-0.001	0.082	-0.545	-0.024	0.008	0.030	0.29
APROD	-0.019	0.110	-0.772	-0.067	-0.010	0.037	0.476
Size	22.499	1.523	17.819	21.491	22.451	23.413	26.936
ROA	0.062	0.078	-0.930	0.028	0.053	0.083	1.077
Lev	0.289	0.162	0.000	0.170	0.294	0.399	0.768
SG	0.557	12.538	-0.983	0.016	0.103	0.204	365.157
CFO	0.085	0.110	-1.153	0.044	0.091	0.136	0.508
Vol(CFO)	0.058	0.048	0.003	0.028	0.044	0.069	0.517
Panel D - Decline (106 observations)
AEM	0.015	0.046	-0.072	-0.01	0.007	0.035	0.204
REM	0.021	0.216	-0.48	-0.06	0.005	0.070	1.765
ADISX	0.020	0.185	-0.208	-0.03	0.003	0.027	1.805
APROD	0.002	0.084	-0.297	-0.037	0.000	0.048	0.262
Size	21.534	1.870	17.101	20.178	21.312	22.815	26.840
ROA	0.061	0.069	-0.189	0.022	0.053	0.085	0.376
Lev	0.208	0.150	0.000	0.069	0.200	0.321	0.629
SG	-0.016	0.184	-0.882	-0.087	-0.006	0.067	0.636
CFO	0.076	0.079	-0.216	0.034	0.075	0.111	0.356
Vol(CFO)	0.085	0.342	0.007	0.030	0.042	0.068	3.560

Variables	(1)	(2)	(3)	(4)
Variables	AEM	REM	ADISX	APROD
Growth	-0.009^***	-0.026^***	-0.055^***	0.037^***
Decl	0.065^***	-0.054^***	-0.049^***	-0.003
Growth-Mature	0.000	0.026^***	0.021^***	0.001
Mature-Decline	0.027^***	0.106^***	0.010^***	0.092^***
Mature-Growth	-0.013^***	0.003	-0.014^***	0.011^***
Decline-Mature	-0.009^***	0.085^***	0.021^***	0.062^***
Size	0.013^***	-0.044^***	-0.014^***	-0.031^***
ROA	0.276^***	-0.506^***	-0.165^***	-0.355^***
Lev	0.042^***	-0.165^***	0.034^***	-0.185^***
SG	0.003^***	-0.008^***	-0.001	-0.004^***
CFO	0.005^*	-0.179^***	0.052^***	-0.228^***
Vol(CFO)	-0.014^***	0.020^***	0.013^***	0.006^***
Big4	-0.007^**	0.015^***	-0.062^***	0.067^***
Loss	0.001	0.020^***	-0.029^***	0.055^***
Covid	-0.007^***	0.037^***	0.010^***	0.031^***
REM	0.111^***
Intercept	-0.327^***	0.980^***	0.335^***	0.659^***
Dummies for Industry and Year	Yes	Yes	Yes	Yes
Observations	1,223	1,223	1,223	1,223
Maximum VIF	3.10	3.10	3.10	3.10
Wald chi² (p value)	0.000	0.000	0.000	0.000
Arellano-Bond Test - AR1 (p value)	0.000	0.000	0.001	0.000
Arellano-Bond Test - AR2 (p value)	0.745	0.263	0.198	0.236
Hansen test (p value)	0.866	0.534	0.520	0.453

Variables	(1)
Variables	AEM
Growth	-0.006^*
Decline	0.074^***
Growth-Mature	0.001
Mature-Decline	0.021^***
Mature-Growth	-0.012^***
Decline-Mature	-0.024^***
REM	0.157^***
Growth ^ REM*	-0.222^***
Decline ^ REM*	-0.371^***
Growth-Mature ^ REM*	0.049^***
Mature-Decline ^ REM*	0.158^***
Mature-Growth ^ REM*	0.027^**
Decline-Mature ^ REM*	-0.281^***
Control variables	Yes
Dummies for Industry and Year	Yes
Observations	1,223
Maximum VIF	3.13
Wald chi² (p value)	0.000
Arellano-Bond Test - AR1 (p value)	0.000
Arellano-Bond Test - AR2 (p value)	0.547
Hansen test (p value)	0.858

Variables	(1)	(2)	(3)	(4)
Variables	AEM	REM	ADISX	APROD
Initial stages	-0.002^***	0.004^***	-0.013^***	0.020^***
Final stages	0.014^***	0.032^***	-0.007^***	0.030^***
Initial stages-Mature	0.010^***	0.003^**	-0.005^***	0.009^***
Mature-Final stages	0.047^***	0.090^***	0.008^***	0.075^***
Mature-Initial stages	-0.006^***	-0.011^***	-0.023^***	0.015^***
Final stages-Mature	0.005^***	-0.016^***	-0.024^***	0.007^***
Control variables	Yes	Yes	Yes	Yes
Dummies for Industry and Year	Yes	Yes	Yes	Yes
Number of companies	185	185	185	185
Observations	1,223	1,223	1,223	1,223
Wald chi² (p value)	0.000	0.000	0.000	0.000
Arellano-Bond Test - AR1 (p value)	0.000	0.000	0.002	0.000
Arellano-Bond Test - AR2 (p value)	0.958	0.320	0.591	0.706
Hansen test (p value)	0.795	0.648	0.838	0.689

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[TFN1] Source: Adapted from Park and Chen (2006 ).