Key audit matters disclosure: do they reveal construction firm’s risk of financial distress? Evidence from Ethiopia

Figures & data

Table 1. Sample selection procedure.

The sample: construction companies and company-year observations
Initial sample: all construction firms registered in EMUDC in 2017	3119
Less: construction firms not registered as grade one	(–) 2698)
Grade one construction firms	421
Less: construction firms with no required data of the consolidated annual statement (2017–2021)	(–) 334
Total construction firms of the sample: Firms with all consolidated annual statement data in ERCA (2017–2021)	87
Firm-year observations total (87*5)	435

Table 2. Key audit matters categorization.

Risk-level	Classification	Variable code	Variable description	Source
Account-specific KAMs (AKAM)	Liquidity	FLQY	Number of KAMs disclosed related to liquidity	Bellovary et al. (2007) and Camacho-Minano et al. (2023)
	Solvency	FSLY	Number of KAMs disclosed related to solvency	Bellovary et al. (2007) and Camacho-Minano et al. (2023)
	Profitability	FPRY	Number of KAMs disclosed related to profitability	Bellovary et al. (2007) and Camacho-Minano et al. (2023)
Company-wide KAMs (CKAM)	Going concern	GOCN	Number of KAMs disclosed related to going concern	Camacho-Minano et al. (2023)
	Other than going concern	OCWR	Number of KAMs disclosed other than going concern	Camacho-Minano et al. (2023)

Table 3. Descriptive statistics of sampled company-year observations.

Panel A. Company-year observation distribution in the year and industry category
Construction industry category (CINC)	2017	2018	2019	2020	2021	Total	%
General construction (GLC)	24	34	42	25	25	150	34.5
Building construction (BDC)	61	53	41	59	56	270	62.1
Road construction (RDC)	2	0	4	3	6	15	3.4
Total	87	87	87	87	87	435	100
Panel B. Summary of KAMs reported in the year
KAMs reported (NKAM)	2017	2018	2019	2020	2021	Means
Mean no. of KAMs	3.14	2.86	2.74	3.00	2.94	2.94
Std. dev. no. of KAMs	1.36	1.43	1.43	1.32	1.27	1.36
Min. no. of KAMs	1	1	1	1	1	1
Max. no. of KAMs	5	5	5	5	5	5
Panel C. Number of KAMs distribution by risk level and classification in year
KAMs classification		2017	2018	2019	2020	2021	Total	%
AKAM	FLQY	39	30	31	38	30	168	13.2
	FSLY	84	83	70	87	81	405	31.7
	FPRY	57	48	55	45	57	262	20.5
	Sub-total AKAM	180	161	156	170	168	835	65.4
	%	14.1	12.6	12.2	13.3	13.2	65.4
CKAM	GOCN	18	22	19	18	9	86	6.7
	OCWR	75	66	63	73	79	356	27.9
	Sub-total CKAM	93	88	82	91	88	442	34.6
	%	7.3	6.9	6.4	7.1	6.9	34.6
Total NKAMs		273	249	238	261	256	1277
%		21.4	19.5	18.6	20.4	20.0	100
Panel D. Summary of averaged audit fees (,000 ETB) in year
	2017	2018	2019	2020	2021	Total
Audit fees (ADFE)	12,019.083	12,776.551	12,948.375	12,119.339	12,203.943	62,067.291
Panel E. Summary of the nature of opinion issued in the year
Audit opinion (ADOP)	2017	2018	2019	2020	2021	Total	%
Unqualified and non-going concern	75	74	70	77	77	373	85.7
Qualified for going concern	12	13	17	10	10	62	14.3
Panel F. Summary of firms’ auditor change in the year
Auditor change (ADCH)	2017	2018	2019	2020	2021	Total	%
Not occurred	61	69	65	67	66	328	75.4
Occurred	26	18	22	20	21	107	24.6
Panel G. Distribution of firm size in the year
Construction firm size (CFSZ)	2017	2018	2019	2020	2021	Total	%
Small	15	15	14	12	11	67	15.4
Medium	49	38	31	52	51	221	50.8
Large	23	34	42	23	25	147	33.8
Panel H. Distribution of existence of restatement in year
Restatement (REST)	2017	2018	2019	2020	2021	Total	%
Not existed	64	63	60	64	57	308	70.8
Existed	23	24	27	23	30	127	29.2

Table 4. Descriptive statistics and univariate analysis of FIDT and NKAMs.

Panel A. Descriptive statistics
NKAM	Obs.	Mean FIDT	Std. dev. FIDT	Percentile 5	Percentile 95
1	85	13.145	1.266	11.832	15.254
2	89	10.936	.485	10.178	11.671
3	105	8.954	.656	7.996	10.055
4	81	6.898	.597	5.864	7.772
5	75	3.872	1.383	1.008	5.628
Total	435	8.919	3.217	3.187	13.633
Panel B. Univariate analysis
NKAM	Obs.	Mean FIDT	Std. dev. FIDT	p Value	t-test
> = 3	261	6.86	2.27	.000	−26.507***
< 3	174	12.02	1.46

The authors report a p-value with “***” indicating (two-tailed) statistical significance at the 1% level.

Table 5. Correlation matrix.

	FIDT	NKAM	AKAM	CKAM	FLQY	FSLY	FPRY	GOCN	OCWR	ADFE	ADOP	ADCH	CFSZ	REST
FIDT	1.000
NKAM	–0.955	1.000
AKAM	–0.922	0.087	1.000
CKAM	–0.448	0.622	0.155	1.000
FLQY	–0.426	0.384	0.449	0.056	1.000
FSLY	–0.464	0.460	0.494	0.136	–0.192	1.000
FPRY	–0.444	0.410	0.504	0.022	0.033	–0.268	1.000
GOCN	–0.372	0.486	0.257	0.567	0.093	0.143	0.128	1.000
OCWR	–0.203	0.309	–0.042	0.687	–0.016	0.036	–0.088	–0.210	1.000
ADFE	0.996	–0.094	–0.090	–0.472	–0.420	–0.451	–0.432	–0.350	–0.252	1.000
ADOP	0.589	–0.579	–0.347	–0.610	–0.179	–0.190	–0.134	–0.160	–0.583	0.641	1.000
ADCH	–0.061	0.051	0.008	0.089	0.032	–0.016	0.004	0.041	0.069	–0.067	–0.126	1.000
CFSZ	0.901	–0.089	–0.082	–0.496	–0.375	–0.407	–0.407	–0.416	–0.222	0.089	0.492	–0.139	1.000
REST	0.003	–0.012	0.029	–0.070	0.066	–0.035	0.028	–0.059	–0.031	0.008	0.080	0.057	0.016	1.000

Table 6. Pooled OLS regression model.

Model	Model 1	Model 2	Model 3
Dependent variable	FIDT	FIDT	FIDT
NKAM	–0.195*** (0.069)
AKAM		–0.347*** (0.121)
CKAM		–0.161*** (0.060)
FLQY			–0.329** (0.125)
FSLY			–0.330*** (0.117)
FPRY			–0.316** (0.128)
GOCN			–0.205*** (0.060)
OCWR			–0.05 (0.064)
Observations	435	435	435
R-squared	99.68	99.71	99.74
F-Statistics	12,384.01***	20,194.89***	1686.83***
Fixed effects (industry category and year) and controls	Yes	Yes	Yes
Model VIF	5.29	6.24	6.02

The authors report p-values with “**” and “***” indicating (two-tailed) statistical significance at the 5% and 1% levels, respectively.

Table 7. Two-step-system generalized method of moments (GMM), propensity score matching (PSM), and changes of the main independent variable model.

Model	Model 4	Model 5	Model 6	Model 7
Robustness tests	Two-step GMM	First stage PSM	Second stage PSM	Change specification model
Dependent variable	FIDT	TRMT	FIDT	FIDT
FIDT_ln	–0.063* (0.050)
NKAM	–0.323** (0.171)		TRMT −0.193*** (0 .064)
NKAM_g				–0.015** (0.008)
ADFE	0.022*** (0.007)	–0.005*** (0.001)	0.064*** (0.001)	0.065*** (0.001)
ADOP	–0.526*** (0.140)	0.225*** (0.050)	–0.684*** (0.052)	–0.721*** (0.047)
ADCH	–0.011 (0.033)	–0.034 (0.033)	0.088 (0.025)	0.013 (0.025)
CFSZ	0.110 (0.069)	0.164*** (0.041)	0.205** (0.082)	0.158** (0.073)
REST	–0.060 (0.048)	0.004 (0.028)	0.029 (0.033)	0.024 (0.035)
Observations	348	435	435	435
R-squared			99.65***	99.64***
Wald test	68.32***
F-Statistics				9698.28***
Fixed effects (industry category and year)	Yes	Yes	Yes	Yes
Model VIF	6.05		4.18	3.35
AR (1) (p value)	–2.07 (.038)
AR (2) (p value)	–1.45 (.209)
Hansen test (p value)	2.20 (.333)
Diff-Hansen test (p value)	4.35 (.226)

The authors report p-values with “*”, “**”, and “***”, indicating (two-tailed) statistical significance at the 10%, 5%, and 1% levels, respectively.

Dependent variables

In the main analysis
FIDT	Altman’s Z′′- Score of sampled grade 1 construction companies and calculated as: 3.25 + 6.56 × Z1 + 3.26 × Z2 + 6.72 × Z3 + 1.05 × Z4
	Z1	= (Current assets minus current liabilities) divided by total assets
	Z2	= Retained earnings divided by total assets
	Z3	= Earnings before interest and taxes divided by total assets
	Z4	= Book value of equity divided by total liabilities
In the test of robustness and endogeneity
FIDTzsv		Altman’s Z′′ -Score classification and coded as: 1 if score > =2.6 (safe zone) and 0 if score <2.6 (grey and distressed zone)
FIDTch		Charitou’s score of sampled grade-one construction companies was calculated as follows: 1/1 +EXP{-7.1786 + [12.3826 ×(TL/TA)] - [20.9691 ×(NI/TL)] – [3.0174 ×(OPCF/TL)]}
FIDTchv		Charitou’s Score classification and coded as follows: 1 if the score > =0.2 (non-distressed) and 0 if the score <0.2 (Distressed)
FIDT_ln		The lagged value of FIDT used for the endogeneity test

Independent variables

In the main analysis and test of endogeneity,
NKAM	The number of disclosed KAMs by an auditor
NKAM_g	Change of number of disclosed KAMs between period t and t−1
AKAM	Account-specific KAMs
CKAM	Company-wide KAMs
FLQY	KAMs on liquidity
FSLY	KAMs on solvency
FPRY	KAMs on profitability
GOCN	KAMs on going concern
OCWR	KAMs on other company-wide risks
ADFE	The amount of total audit fees
ADOP	Audit opinion coded as 1 if qualified for going concern, 0 otherwise)
ADCH	Auditor change coded as 1 if occurred, 0 not occurred)
CFSZ	Construction firm size is coded as 1 if small, 2 if medium, and 3 if large
REST	Restatement coded as 1 if existed, 0 not existed)

Bellovary JL, Giacomino DE, Akers MD. 2007. A review of bankruptcy prediction studies: 1930 to present. J Financ Educ. 33:1–42.

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Camacho-Minano M, Munoz-Izquierdo N, Pincus M, Wellmeyer P. 2023. Are key audit matter disclosures useful in assessing the financial distress level of a client firm? Br Account Rev. 101200. In press. doi: 10.1016/j.bar.2023.101200.

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Data availability statement

The data is available upon reasonable request.