Role of earnings management and capital structure in signalling early stage of financial distress: a firm life cycle perspective

Figures & data

Table 1. Classification of firms on the basis of life cycle descriptors

Life cycle stages	Life cycle descriptors
	Dividend payout	Sales growth	Age
Growth	Low	High	Young
Mature	Medium	Medium	Adult
Stagnant	High	Low	Old

Table 2. Descriptive statistics of life cycle descriptors by stages in the firm life cycle

S. no.	Variables	Year	Growth	Mature	Decline
1	% Change in sales mean (median)	t	29.12	18.57	15.66
			21.73	15.00	13.62
		t + 1	19.76	14.44	16.89
			18.61	14.57	12.14
		t + 2	13.99	12.82	11.44
			15.52	10.07	5.71
		t + 3	23.41	17.91	26.36
			2.27	18.88	15.66
		t + 4	23.54	14.07	10.94
			21.10	14.21	13.30
		t + 5	13.15	6.76	6.09
			13.74	7.57	4.94
2	Dividend payout (%) mean (median)	t	17.12	25.71	50.03
			15.48	24.47	32.52
		t + 1	25.06	29.54	39.54
			15.40	24.73	34.16
		t + 2	18.93	78.55	36.41
			14.62	23.24	31.56
		t + 3	19.73	23.59	36.90
			15.25	23.37	33.26
		t + 4	16.32	21.53	31.32
			16.35	24.39	32.92
		t + 5	16.70	28.79	56.65
			16.52	21.00	34.81

Note: Cells with grey color represent the mean values. White color cells represent median values.

Firm life cycle stage was determined using Anthony and Ramesh’s (1992) model. Life cycle descriptors are dividend payout, sales growth and age.

Table 3. Transition analysis

S. no.	Initial stage	Stage in future	t + 1	t + 2	t + 3	t + 4	t + 5
1	Growth (G)	Growth (G)	84.82	76.79	65.18	60.71	57.14
		Growth/mature	12.5	17.86	26.79	26.79	24.11
		Mature	2.68	4.46	7.14	8.93	14.29
		Mature/ stagnant		0.89	0.89	3.57	3.57
		Stagnant					0.89
2	Growth/mature	Growth (G)	9.78	16.3	18.48	19.57	21.74
		Growth/mature	66.3	53.26	42.39	36.96	27.17
		Mature	20.65	22.83	28.26	32.61	29.35
		Mature/ stagnant	3.26	6.52	9.78	8.7	14.13
		Stagnant		1.09	1.09	2.17	7.61
3	Mature (M)	Growth (G)	2.75	5.5	6.42	11.01	11.01
		Growth/mature	11.93	18.35	25.69	24.77	28.44
		Mature	71.56	55.96	44.95	34.86	28.44
		Mature/ stagnant	13.76	16.51	17.43	22.02	20.18
		Stagnant		3.67	5.5	7.34	11.93
4	Mature/ stagnant	Growth (G)	0.99	1.98	1.98	4.95	6.93
		Growth/mature	2.97	5.94	10.89	10.89	11.88
		Mature	17.82	21.78	23.76	24.75	23.76
		Mature/ stagnant	66.34	52.48	38.61	33.66	32.67
		Stagnant	11.88	17.82	24.75	25.74	24.75
5	Stagnant	Growth (G)					0.96
		Growth/mature		0.96	0.96		3.85
		Mature	2.88	3.85	8.65	13.46	16.35
		Mature/ stagnant	10.58	15.38	18.27	26.92	26.92
		Stagnant	86.54	79.81	72.12	59.62	51.92

Note: Firm lifecycle was measured using Anthony and Ramesh’s (1992) model with dividend payout, sales growth and age as life cycle descriptor.

Table 4. Descriptive statistics

Variables	Mean	Std. dev.	Minimum	Median	Maximum
AQ	0.0326	0.0236	0.0022	0.0268	0.267
DIS_AQ	0	0.0233	−0.0549	−0.0053	0.235
Debt	0.2312	0.1863	0	0.2311	0.8019
Z_Score	1.0212	0.74	−0.0365	0.8876	11.0632
Firm Size	3.8247	0.8121	1.281	3.7729	6.4702
Firm Performance	8.2584	7.1744	−43.69	6.82	60.77

Note: AQ = accruals quality measured using Equation (1)(1) $\mathrm{T}\mathrm{C}{\mathrm{A}}_{\mathrm{i}}{,}_{\mathrm{t}}={\beta }_{0,\mathrm{t}}+{\beta }_{1,\mathrm{t}}\mathrm{C}\mathrm{F}{\mathrm{O}}_{\mathrm{i},\mathrm{t}-1}+{\beta }_2\mathrm{C}\mathrm{F}{\mathrm{O}}_{\mathrm{i},\mathrm{t}}+{\beta }_{3,\mathrm{t}}\mathrm{C}\mathrm{F}{\mathrm{O}}_{\mathrm{i},\mathrm{t}+1}+{\beta }_{4,\mathrm{t}}\mathrm{\Delta }\mathrm{R}\mathrm{E}{\mathrm{V}}_{\mathrm{i},\mathrm{t}}+{\beta }_{5,\mathrm{t}}\mathrm{P}\mathrm{P}{\mathrm{E}}_{\mathrm{i},\mathrm{t}}+{\epsilon }_{\mathrm{i},\mathrm{t}}$(1) ; DIS_AQ = discretionary component of accruals quality measured using Equation (5)(5) $A{Q}_{i,t}=b_{i,0}+b_{1}SIZ{E}_{i,t}+b_2\sigma CF{O}_{i,t}+b_3\sigma SALE{S}_{i,t}+b_{4}NEGEAR{N}_{i,t}+e_{i,t}$(5) ; Debt = ratio of total debt to total assets; Z-Score = financial distress score; Firm Size =log of total assets; Firm Performance = return on assets.

Table 5. Panel data analysis results of discretionary accruals quality and firm life cycle

Discretionary accruals quality	Fixed effects		Random effects
Variables	Coefficient	t-statistic	Coefficient	z-statistic
Constant	−0.0322	−3.58	−0.0056	−1.48
	(0.000)*		(0.138)
FLC_DM_1	−0.0006	−0.49	−0.0008	−0.08
	(0.622)		(0.940)
FLC_DM_2
FLC_DM_3	−0.0028	−2.34	−0.0039	−3.68
	(0.020)**		(0.000)
Firm Size	0.0085	3.65	0.0013	1.35
	(0.000)*		(0.177)
Firm Performance	0.0001	2.00	0.0003	4.66
	(0.046)**		(0.000)
F (4,2068)/ Wald chi^2	5.7100		40.0200
Prob.>F	0.0001		0.0000
R^2 overall	0.0028		0.0605
Sigma_u	0.0210		0.1799
sigma_e	0.0129		0.0129
Hausman chi^2	66.55
Hausman prob>chi^2	0.0000

Note: Accruals are estimated as the standard deviation of the residuals obtained from Equation (1)(1) $\mathrm{T}\mathrm{C}{\mathrm{A}}_{\mathrm{i}}{,}_{\mathrm{t}}={\beta }_{0,\mathrm{t}}+{\beta }_{1,\mathrm{t}}\mathrm{C}\mathrm{F}{\mathrm{O}}_{\mathrm{i},\mathrm{t}-1}+{\beta }_2\mathrm{C}\mathrm{F}{\mathrm{O}}_{\mathrm{i},\mathrm{t}}+{\beta }_{3,\mathrm{t}}\mathrm{C}\mathrm{F}{\mathrm{O}}_{\mathrm{i},\mathrm{t}+1}+{\beta }_{4,\mathrm{t}}\mathrm{\Delta }\mathrm{R}\mathrm{E}{\mathrm{V}}_{\mathrm{i},\mathrm{t}}+{\beta }_{5,\mathrm{t}}\mathrm{P}\mathrm{P}{\mathrm{E}}_{\mathrm{i},\mathrm{t}}+{\epsilon }_{\mathrm{i},\mathrm{t}}$(1) using 5-year period from t-4 to t. Accruals are further decomposed into innate and discretionary to give the discretionary accruals quality. The model includes two dummy variables for the three life cycle stages, namely, growth, mature and decline. FLC_DM_1 is the dummy variable, which takes the value 1 for the growth firms and zero otherwise. FLC_DM_3 is the second dummy variable, which takes the value 1 for the firms classified as the declining firms and zero otherwise. Firm Size is the logarithmic transformation of the total assets of the firm. Firm Performance is return on assets estimated as profit after tax (net of prior period and extraordinary items) as % of assets.

* Significant at the level of 0.1 (p-value<0.10); ** significant at the level of 0.05 (p-value<0.05); *** significant at the level of 0.01 level (p-value<0.01)

Table 6. Panel data analysis results of financial distress, discretionary accruals quality and debt

	Model 1				Model 2
Z_Score	Fixed effects		Random effects		Fixed effects				Random effects
Variables	Coefficient	t-statistic	Coefficient	z-statistic	Coefficient		t-statistic	Coefficient		z-statistic
Constant	1.5101	8.4000	1.6386	13.3500	1.4254		7.8700	1.6015		13.2100
	(0.000)		(0.000)		(0.000)			(0.0000)
DIS_AQ	−2.9469	−6.8100	−2.5969***	−6.2000
	(0.0000)		(0.000)
Debt	−0.1048	−1.2400	−0.0942	−1.2100
	(0.216)		(0.228)
Growth Dummy	0.0102	0.4600	0.0082	0.3800
	(0.644)		(0.701)
Mature
Decline Dummy	−0.0215	−0.9600	−0.0224	−1.0300
	(0.340)		(0.305)
DIS_AQ X FLC_DM_1					0.1595		0.2500	0.0103		0.0200
					(0.799)			(0.987)
DIS_AQ X FLC_DM_3					−3.5313		−5.6700	−2.9617		−4.8500
					(0.000)***			(0.000)
Debt X FLC_DM_1					0.0796		1.3300	0.0741		1.2900
					(0.183)			(0.198)
Debt X FLC_DM_3					−0.0628		−0.9900	−0.0618		−1.0000
					(0.322)			(0.319)
Firm Size	−0.1220	−2.6600	−0.1571	−5.2100	−0.1119		−2.4000	−0.1580		−5.2300
			(0.000)***		(0.016)**			(0.000)
Firm Performance	0.0038	2.8900	0.0039	3.0600	0.0049		3.7500	0.0047		3.7400
			(0.002)***		(0.000)***			(0.0000)
F (4,2068)/ Wald chi2	11.7000		83.8300		9.5400			70.2400
Prob.>F	0.0000		0.0000		0.0000			0.0000
R2	0.0252		0.0324		0.0217			0.0316
Sigma_u	0.7098		0.6952		0.7110			0.6865
sigma_e	0.2316		0.2316		0.2324			0.2324
Hausman chi^2	12.51				35.26
Hausman prob>chi^2	0.0514				0.0000

* Significant at the level of 0.1 (p-value<0.10); ** significant at the level of 0.05 (p-value<0.05); *** significant at the level of 0.01 level (p-value<0.01).

Note: Z_Score measures the financial distress using the Modified Altman Z-score model. Accruals are estimated as the standard deviation of the residuals obtained from Equation (1)(1) $\mathrm{T}\mathrm{C}{\mathrm{A}}_{\mathrm{i}}{,}_{\mathrm{t}}={\beta }_{0,\mathrm{t}}+{\beta }_{1,\mathrm{t}}\mathrm{C}\mathrm{F}{\mathrm{O}}_{\mathrm{i},\mathrm{t}-1}+{\beta }_2\mathrm{C}\mathrm{F}{\mathrm{O}}_{\mathrm{i},\mathrm{t}}+{\beta }_{3,\mathrm{t}}\mathrm{C}\mathrm{F}{\mathrm{O}}_{\mathrm{i},\mathrm{t}+1}+{\beta }_{4,\mathrm{t}}\mathrm{\Delta }\mathrm{R}\mathrm{E}{\mathrm{V}}_{\mathrm{i},\mathrm{t}}+{\beta }_{5,\mathrm{t}}\mathrm{P}\mathrm{P}{\mathrm{E}}_{\mathrm{i},\mathrm{t}}+{\epsilon }_{\mathrm{i},\mathrm{t}}$(1) using 5-year period from t-4 to t. Accruals are further decomposed into innate and discretionary to give the discretionary accruals quality (DIS_AQ). Debt is the ratio of the total debt (long term and short term) to total assets. DIS_AQ X FLC_DM_1 is the interaction term to assess the effect of discretionary accruals in predicting financial distress in growth firms. DIS_AQ X FLC_DM_3 is the interaction term to assess the effect of discretionary accruals in predicting financial distress in declining firms. Debt X FLC_DM_1 is the interaction term to assess the effect of debt on the financial distress prediction in growth firms. Debt X FLC_DM_3 is the interaction term to assess the effect of debt on the financial distress prediction in declining firms. Firm Size is the logarithmic transformation of the total assets of the firm. Firm Performance is return on assets estimated as profit after tax (net of prior period and extraordinary items) as % of total assets.

* Significant at the level of 0.1 (p-value<0.10); ** significant at the level of 0.05 (p-value<0.05); *** significant at the level of 0.01 level (p-value<0.01).

Anthony, J. H., & Ramesh, K. (1992). Association between accounting performance measures and stock prices: A test of the life cycle hypothesis. Journal of Accounting and Economics, 15(2–3), 203–227. https://doi.org/10.1016/0165-4101(92)90018-W

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