Informational content of key audit matters and financial analysts’ forecasts

Venturini, Lauren Dal Bem; Bianchi, Márcia; Machado, Vanessa Noguez; Paulo, Edilson

doi:10.1590/1808-057x202113080

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Original Article • Rev. contab. finanç. 33 (89) • May-Aug 2022 • https://doi.org/10.1590/1808-057x202113080 copy

Informational content of key audit matters and financial analysts’ forecasts^* * Paper presented at the 20th USP International Conference in Accounting, July of 2020

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

The aim of this article was to analyze the relationship between the informational content of the key audit matters (KAMs) reported in the Independent Audit Report (IAR) and financial analysts’ forecasts for the companies listed on the B3 S.A. - Brasil, Bolsa, Balcão (B3). The research that has investigated the relevance of KAMs has not analyzed the incremental information about the audited firm, from the independent auditor’s viewpoint, that can affect financial analysts’ forecasts. The findings of this research reveal that the KAMs reported present relevant informational content about the audited firm for financial analysts, thus improving the quality of their forecasts. In addition, it was observed in the quantile analysis that the KAMs contribute to the fine tuning of analysts’ forecasts. The debate on the auditor-analyst relationship is also widened, specifically regarding the utility of KAMs for financial analysts, in terms of them considering using this information in their projections for the analyzed companies, thus reinforcing the search for their improvement by the regulator. The analysis was conducted based on generalized least squares (GLS) and quantile regressions covering 137 non-financial companies, using data from (quarterly and annual) analysts’ forecasts available from Thomson Reuters Eikon^® and financial information from Economatica^®. In general, the quantity and content of the items reported as KAMs were revealed to be significant in relation to the analysts’ earnings per share forecasts and to their forecasting error, revealing a reduction in asymmetry. Thus, the higher the informational value of the KAMs, the better the quality of that information is, contributing to forming an earnings forecast consensus and minimizing the error in the financial analysts’ estimates. In addition, it was observed that the disclosure of KAMs has no immediate reflection in the earnings forecast in the quarter following their disclosure, with their informational content being diluted over the following financial period, impacting the annual earnings forecast.

Keywords:
audit report; key audit matters; financial analysts; informational asymmetry; informational value

Composition of the final sample	2016	2017	2018
1. Non-financial companies with reported KAMs	293	307	304
2. (-) Without analyst data in the Thomson database	(-156)	(-170)	(-134)
3. Final sample	n = 137		%
Cyclical consumption	43		31.39
Industrial goods	20		14.60
Public utility	22		16.06
Basic materials	12		8.76
Non-cyclical consumption	15		10.95
Health	13		9.49
Oil, gas, and biofuels	6		4.38
Information technology	3		2.19
Communications	3		2.19

	Description	Abbreviation	Metric	Theoretical support	Predicted sign
	Description	Abbreviation	Metric	Theoretical support	C	E	A
Dependent	Earnings per share forecast	EPSf	Consensus on the mean quarterly earnings expected per share according to data from the I/B/E/S Earnings Consensus Information	Behn et al. (2008Behn, B., Choi, J., & Kang, T. (2008). Audit quality and properties of analyst earnings forecasts. The Accounting Review, 83(1), 327-349.), Martinez (2004Martinez, A. L. (2004). Analisando os analistas: estudo empírico das projeções de lucros e das recomendações dos analistas de mercado de capitais para as empresas brasileiras de capital aberto [Doctoral Thesis]. Fundação Getulio Vargas., 2007Martinez, A. L. (2007). Otimismo e viés de seleção dos analistas. BBR - Brazilian Business Review, 4(2), 104-118.)	NA
	Forecast error	EEPSf	Difference between the actual earnings and the analysts’ forecasted earnings per share divided by actual earnings (modulus) [(EPS - EPSf)/│EPS│]	Dalmácio et al. (2013Dalmácio, F. Z., Lopes, A. B., Rezende, A. J., & Sarlo Neto, A. (2013). Uma análise da relação entre governança corporativa e acurácia das previsões dos analistas do mercado brasileiro. RAM - Revista Administração Mackenzie, 14(5), 104-139. ), Martinez (2004Martinez, A. L. (2004). Analisando os analistas: estudo empírico das projeções de lucros e das recomendações dos analistas de mercado de capitais para as empresas brasileiras de capital aberto [Doctoral Thesis]. Fundação Getulio Vargas., 2007Martinez, A. L. (2007). Otimismo e viés de seleção dos analistas. BBR - Brazilian Business Review, 4(2), 104-118.)	NA
	Accuracy of the forecast	AEPSf	Absolute difference (modulus) between the analysts’ forecast consensus and the actual earnings per share, weighted by the lagged share price (t-1). [│ (EPSf - EPS) │/ share price]	Behn et al. (2008Behn, B., Choi, J., & Kang, T. (2008). Audit quality and properties of analyst earnings forecasts. The Accounting Review, 83(1), 327-349.), Martinez (2004Martinez, A. L. (2004). Analisando os analistas: estudo empírico das projeções de lucros e das recomendações dos analistas de mercado de capitais para as empresas brasileiras de capital aberto [Doctoral Thesis]. Fundação Getulio Vargas., 2007Martinez, A. L. (2007). Otimismo e viés de seleção dos analistas. BBR - Brazilian Business Review, 4(2), 104-118.)	NA
Interest	Total number of KAMs reported	QKAM	Logarithm of the quantity of KAMs reported annually per company	Lennox et al. (2019Lennox, C. S., Schmidt, J. J., & Thompson, A. (2019). Is the expanded model of audit reporting informative to investors? Evidence from the UK [ Working Paper]. Social Science Research Network. https://ssrn.com/abstract=2619785 https://ssrn.com/abstract=2619785 ... ), Sierra-García et al. (2019Sierra-García, L., Gambetta, N., García-Benau, M. A., & Orta-Pérez, M. (2019). Understanding the determinants of the magnitude of entity-level risk and account-level risk key audit matters: The case of the United Kingdom. The British Accounting Review, 51(3), 227-240.)	+	-	+
	Matters reported	KAM	Quantity of matters reported per year and company categorized into six items:	ACCA (2018Association of Chartered Certified Accountants. (2018). Key audit matters: Unlocking the secrets of the audit. https://www.accaglobal.com/vn/en/professional-insights/global-profession/key-audit-matters.html https://www.accaglobal.com/vn/en/profess... )	+	-	+
			Sector-specific matters (SpMatt)
			Assets
			Impairments
			Liabilities
			Complex matters (CompMatt)
			Controls
Control	Company size	SIZE	Natural logarithm of total assets	Behn et al. (2008Behn, B., Choi, J., & Kang, T. (2008). Audit quality and properties of analyst earnings forecasts. The Accounting Review, 83(1), 327-349.), Sierra-García et al. (2019Sierra-García, L., Gambetta, N., García-Benau, M. A., & Orta-Pérez, M. (2019). Understanding the determinants of the magnitude of entity-level risk and account-level risk key audit matters: The case of the United Kingdom. The British Accounting Review, 51(3), 227-240.)	+	-	+
	Return on assets	ROA	Earnings before income tax divided by total assets	Behn et al. (2008Behn, B., Choi, J., & Kang, T. (2008). Audit quality and properties of analyst earnings forecasts. The Accounting Review, 83(1), 327-349.), Martinez (2004Martinez, A. L. (2004). Analisando os analistas: estudo empírico das projeções de lucros e das recomendações dos analistas de mercado de capitais para as empresas brasileiras de capital aberto [Doctoral Thesis]. Fundação Getulio Vargas.)	+	-	+
	Growth opportunity	MB	Market value divided by book value (price to book)	Behn et al. (2008Behn, B., Choi, J., & Kang, T. (2008). Audit quality and properties of analyst earnings forecasts. The Accounting Review, 83(1), 327-349.), Martinez (2004Martinez, A. L. (2004). Analisando os analistas: estudo empírico das projeções de lucros e das recomendações dos analistas de mercado de capitais para as empresas brasileiras de capital aberto [Doctoral Thesis]. Fundação Getulio Vargas.)	+	-	+
	Earnings for the period	Loss	Dummy taking the value 1 when the company presented a loss in the period and 0 otherwise (profit)	Chu et al. (2018Chu, L., Dai, J., & Zhang, P. (2018). Auditor tenure and quality of financial reporting. Journal of Accounting, Auditing & Finance, 33(4), 528-554.), Sierra-García et al. (2019Sierra-García, L., Gambetta, N., García-Benau, M. A., & Orta-Pérez, M. (2019). Understanding the determinants of the magnitude of entity-level risk and account-level risk key audit matters: The case of the United Kingdom. The British Accounting Review, 51(3), 227-240.)	-	+	-
	Earnings per share in the previous period	EPSp	Actual value of earnings per share for the company in the period prior to the analysis period	Behn et al. (2008Behn, B., Choi, J., & Kang, T. (2008). Audit quality and properties of analyst earnings forecasts. The Accounting Review, 83(1), 327-349.), Martinez (2004Martinez, A. L. (2004). Analisando os analistas: estudo empírico das projeções de lucros e das recomendações dos analistas de mercado de capitais para as empresas brasileiras de capital aberto [Doctoral Thesis]. Fundação Getulio Vargas.)	+	-	+
	Auditing firm	BIG	Dummy taking the value 1 if the company was audited by a Big Four firm and 0 otherwise	Behn et al. (2008Behn, B., Choi, J., & Kang, T. (2008). Audit quality and properties of analyst earnings forecasts. The Accounting Review, 83(1), 327-349.), Sierra-García et al. (2019Sierra-García, L., Gambetta, N., García-Benau, M. A., & Orta-Pérez, M. (2019). Understanding the determinants of the magnitude of entity-level risk and account-level risk key audit matters: The case of the United Kingdom. The British Accounting Review, 51(3), 227-240.)	+	-	+
	Age of the forecast	Age	Natural logarithm of the quantity of days between the date of the earnings per share forecast and the date of the actual earnings per share announcement	Behn et al. (2008Behn, B., Choi, J., & Kang, T. (2008). Audit quality and properties of analyst earnings forecasts. The Accounting Review, 83(1), 327-349.), Martinez (2004Martinez, A. L. (2004). Analisando os analistas: estudo empírico das projeções de lucros e das recomendações dos analistas de mercado de capitais para as empresas brasileiras de capital aberto [Doctoral Thesis]. Fundação Getulio Vargas.)	NA	+	-
	Analyst coverage	QAnalyst	Quantity of analysts who monitored the company in the period	Behn et al. (2008Behn, B., Choi, J., & Kang, T. (2008). Audit quality and properties of analyst earnings forecasts. The Accounting Review, 83(1), 327-349.), Martinez (2004Martinez, A. L. (2004). Analisando os analistas: estudo empírico das projeções de lucros e das recomendações dos analistas de mercado de capitais para as empresas brasileiras de capital aberto [Doctoral Thesis]. Fundação Getulio Vargas.)	+	-	+
	Forecast bias	DoTip	1 for optimistic forecast and 0 for pessimistic forecast	Martinez (2004Martinez, A. L. (2004). Analisando os analistas: estudo empírico das projeções de lucros e das recomendações dos analistas de mercado de capitais para as empresas brasileiras de capital aberto [Doctoral Thesis]. Fundação Getulio Vargas., 2007Martinez, A. L. (2007). Otimismo e viés de seleção dos analistas. BBR - Brazilian Business Review, 4(2), 104-118.)	+	-	+
	Operating sector	Sector	Sector where the company operates, according to the B3 website. Dummy for each sector, taking the communication sector as a reference	Sierra-García et al. (2019Sierra-García, L., Gambetta, N., García-Benau, M. A., & Orta-Pérez, M. (2019). Understanding the determinants of the magnitude of entity-level risk and account-level risk key audit matters: The case of the United Kingdom. The British Accounting Review, 51(3), 227-240.)	+	+	+
	Year the KAMs were reported	Year	Dummies for 2017 and 2018, based on the year 2016	Sierra-García et al. (2019Sierra-García, L., Gambetta, N., García-Benau, M. A., & Orta-Pérez, M. (2019). Understanding the determinants of the magnitude of entity-level risk and account-level risk key audit matters: The case of the United Kingdom. The British Accounting Review, 51(3), 227-240.)	+	-	+

IBRACON (2017Instituto dos Auditores Independentes do Brasil (Brazilian Institute of Independent Auditors). (2017). A experiência da aplicação do novo relatório do auditor 1º ano: principais assuntos de auditoria. http://www.ibracon.com.br/ibracon/Portugues/detDocumento.php?cod=100 http://www.ibracon.com.br/ibracon/Portug... , 2018Instituto dos Auditores Independentes do Brasil (Brazilian Institute of Independent Auditors). (2018). Principais assuntos de auditoria. http://www.ibracon.com.br/ibracon/Portugues/detNoticia. php?cod=5573&codregional=6 http://www.ibracon.com.br/ibracon/Portug... )	ACCA (2018Association of Chartered Certified Accountants. (2018). Key audit matters: Unlocking the secrets of the audit. https://www.accaglobal.com/vn/en/professional-insights/global-profession/key-audit-matters.html https://www.accaglobal.com/vn/en/profess... )	Lennox et al. (2019 Lennox, C. S., Schmidt, J. J., & Thompson, A. (2019). Is the expanded model of audit reporting informative to investors? Evidence from the UK [ Working Paper]. Social Science Research Network. https://ssrn.com/abstract=2619785 https://ssrn.com/abstract=2619785 ... ), Sierra-García et al. (2019Sierra-García, L., Gambetta, N., García-Benau, M. A., & Orta-Pérez, M. (2019). Understanding the determinants of the magnitude of entity-level risk and account-level risk key audit matters: The case of the United Kingdom. The British Accounting Review, 51(3), 227-240. )
Concession and sector-based assets and liabilities	Sector-specific matters	Account-level risk (RAccount)
Realization of the impact of deferred income	Assets
Investments
Stock
Property for investment
Biological assets
Fixed assets
Accounts receivable
Intangible assets
Assets available for sale/discontinued operations
Recoverable value of non-financial assets	Impairments
Reduction to recoverable value of financial assets	Impairments
Contingencies	Liabilities
Post-employment benefit
Other liabilities
Revenue	Complex matters
Financial instruments	Complex matters
Business combination	Complex matters	Entity-level risk (REntity)
Laws and regulations
Tax
Transaction with related parties	Controls
Assumption of operational continuity
Liquidity management
Internal controls - Information technology
Fiduciary statements

Test		Metric	EPSf	EESPf	AEPSf
Pooling vs. RE	Breusch-Pagan	Prob.	0.000	0.000	0.000
Pooling vs. RE	Breusch-Pagan	Effect	RE	RE	RE
FE vs. Pooling	Chow	Prob.	0.000	0.000	0.000
FE vs. Pooling	Chow	FE	FE	FE	FE
FE vs. RE	Hausmann	Prob.	-119.060	0.1243	0.000
FE vs. RE	Hausmann	Effect	RE	RE	FE
Most appropriate estimation		Effect	RE	RE	FE
Autocorrelation	Wooldridge	Prob.	0.000	0.000	0.001
Heteroscedasticity	Wald	Prob.	0.000	0.000	0.000
Multicollinearity	VIF		4.950	4.900	4.860

Analysis	Variable	Obs.	Mean	SD	Median	Min.	Max.
Consensus
	EPSf	1,368	1.179	0.876	1.010	-0.025	2.815
	QAnalyst	1,184	4.236	2.365	4.000	1.000	8.000
	EPSp	1,597	0.685	1.126	0.594	-1.127	2.696
	DoTip	1,368	0.915	-	-	0.000	1.000
Error and accuracy
	EEPSf	1,329	-0.822	1.179	-0.300	-3.459	0.278
	AEPSf	1,326	0.058	0.074	0.023	0.002	0.231
	Age	885	5.499	0.492	5.635	4.500	7.020
	QAnalyst	887	2.945	1.756	3.000	1.000	6.000
	EPSp	1,561	0.442	1.056	0.464	-1.421	2.206
	DoTip	1,355	0.855	-	-	0.000	1.000
Consensus, error, and accuracy
	QKAM	1,608	1.077	0.423	1.099	0.000	2.079
	SpMatt	1,644	0.100	0.338	0.000	0.000	2.000
	Assets	1,644	0.818	0.856	1.000	0.000	4.000
	Impairments	1,644	0.533	0.518	1.000	0.000	2.000
	Liabilities	1,644	0.526	0.637	0.000	0.000	3.000
	CompMatt	1,644	0.964	0.796	1.000	0.000	4.000
	Controls	1,644	0.180	0.432	0.000	0.000	2.000
	SIZE	1,632	15.769	1.402	15.719	12.285	20.573
	ROA	1,628	3.533	5.041	3.660	-4.745	11.624
	MB	1,576	2.084	1.578	1.452	0.470	5.432
	Loss	1,644	0.253	-	-	0.000	1.000
	BIG	1,624	0.909	-	-	0.000	1.000

	(1) EPSf	(2) QKAM	(3) SpMatt	(4) Assets	(5) Impairments	(6) Liabilities	(7) CompMatt	(8) Control	(9) SIZE	(10) ROA	(11) MB	(12) Loss	(13) EPSp	(14) BIG	(15) QAnalyst	(16) DoTip
(1)	1
(2)	-0.09^***	1
(3)	0.20^***	0.11^***	1
(4)	-0.12^***	0.43^***	-0.11^***	1
(5)	-0.12^***	0.21^***	-0.07^**	-0.21^***	1
(6)	0.02	0.35^***	-0.02	-0.10^***	-0.01	1
(7)	-0.02	0.38^***	-0.15^***	-0.06^*	-0.02	-0.16^***	1
(8)	-0.04	0.27^***	0.06^**	-0.02	-0.11^***	0.04	-0.11^***	1
(9)	0.16^***	0.23^***	0.19^***	-0.05	-0.02	0.26^{^***}	0.06^**	0.12^***	1
(10)	0.48^***	-0.25^***	0.05	-0.24^***	-0.02	0.01	-0.14^***	-0.05	-0.15^***	1
(11)	0.14^***	-0.07^**	-0.04	-0.13^***	0.04	-0.08^***	0.07^**	-0.05^*	-0.08^***	0.39^***	1
(12)	-0.41^***	0.18^***	-0.05^*	0.12^***	-0.03	0.05	0.13^***	0.08^**	0.02	-0.66^***	-0.29^***	1
(13)	0.75^***	-0.12^***	0.12^***	-0.12^***	-0.07^**	0.04	-0.09^***	-0.03	0.12^***	0.68^***	0.16^***	-0.58^***	1
(14)	0.21^***	-0.22^***	0.05	0.01	-0.14^***	-0.08^**	-0.16^***	-0.15^***	-0.16^***	0.21^***	0.16^***	-0.18^***	0.16^***	1
(15)	0.05^*	-0.02	-0.01	-0.04	-0.02	0.12^***	0	-0.06^*	0.33^***	0.06	0.22^***	-0.10^***	0.09^***	-0.03	1
(16)	0.42^***	-0.12^***	0.09^***	-0.14^***	0.09^***	-0.04	-0.07^**	-0.11^***	0.06^*	0.34^***	0.25^***	-0.47^***	0.38^***	0.17^***	0.11^***	1

EPSf	GLS panel data regression					Quantile regression
EPSf	t + 1	t + 2	t + 3	t + 4	x + 1	0.05	0.1	0.25	0.5	0.75	0.9	0.95
Constant	-0.64	-0.98	0.08	1.79	0.57	-1.46^**	-0.83	0.36	0.43	-0.41	-1.41^*	-1.25^*
QKAM	0.14	0.05	0.18	0.35	0.36^**	-0.50^**	-	-	-	-	0.42	0.60^**
SpMatt	-0.23	-0.02	-0.12	-0.22	-0.28	0.29^**	0.06	-0.06	-0.05	0.06	-0.10	-0.26^*
Assets	-0.13	-0.06	-0.04	-0.16^*	-0.16^***	0.19^**	0.01	-0.01	-0.02	-0.06^*	-0.20^*	-0.28^***
Impairments	-0.13	-0.14	-0.08	-0.20^*	-0.23^***	0.19^**	-0.02	-0.02	-0.04	-0.07	-0.20^*	-0.29^***
Liabilities	-0.08	-0.06	-0.07	-0.11	-0.18^***	0.12	-0.02	-0.06^*	-0.05^*	-0.04	-0.19	-0.24^**
CompMatt	0.00	-0.03	-0.03	-0.03	-0.15^**	0.22^**	0.06^*	0.09^***	0.05^**	0.13^***	0.00	-0.10
Controls	-0.01	-0.06	0.01	-0.07	-0.11	0.12	0.07	0.06	0.02	0.1267^*	0.05	-0.05
SIZE	0.05	0.07	0.00	-0.06	0.02	0.02	0.04	-0.03	-0.02	0.02	0.10^**	0.11^***
ROA	-0.02	000	0.00	-0.01	-0.01	0.01	0.00	0.00	-0.01	0.00	0.01	0.01
MB	0.08^**	0.03	0.00	0.03	0.04	-0.02	-0.01	0.02	0.01	0.01	0.02	0.04^*
Loss	0.28^**	0.29^**	0.30^**	0.05	0.17^**	0.10	0.07	0.14^**	0.42^***	0.61^***	0.32^**	0.15
EPSp	0.46^***	0.39^***	0.52^***	0.41^***	0.28^***	0.33^***	0.42^***	0.62^***	0.76^***	0.64^***	0.44^***	0.34^***
BIG	0.36^***	0.26^**	0.32^**	0.10	0.19^*	0.44^***	0.17^*	0.13^*	0.17^**	0.32^***	0.42^***	0.20
QAnalyst	-0.03	0.00	0.02	0.00	-0.01	0.01	0.01	0.0167^*	0.01	-0.01	-0.02	-0.03^*
DoTip	0.25	0.49^***	0.31^***	0.19	0.33^***	0.14	0.13	0.00	0.14^*	0.62^***	0.96^***	1.12^***
Year_2017	-0.12	-0.02	0.14	-0.18^**	-0.12^**	0.10	0.04	0.05	0.05	0.00	-0.08	-0.20^**
Year_2018	-0.05	0.00	0.17^**	-0.10^*	-0.03	0.11^*	0.08	0.07	0.05	-0.01	-0.11	-0.16^*
Observations	249	278	281	284	1092	1.092	1.099	1.099	1.099	1.099	1.092	1.092
R²/pseudo R²	0.2	0.18	0.35	0.37	0.22	0.32	0.39	0.43	0.46	0.47	0.44	0.36

	(1) EEPSf	(2) AEPSf	(3) QKAM	(4) SpMatt	(5) Assets	(6) Impairments	(7) Liabilities	(8) CompMatt	(9) Control	(10) SIZE	(11) ROA	(12) MB	(13) Loss	(14) EPSp	(15) BIG	(16) Age	(17) QAnalyst	(18) DoTip
(1)	1
(2)	-0.47^***	1
(3)	-0.09^***	0.15^***	1
(4)	-0.07^*	0.06^*	0.08^**	1
(5)	-0.08^**	0.11^***	0.46^***	-0.15^***	1
(6)	-0.06^*	0.05	0.25^***	-0.07^**	-0.19^***	1
(7)	0.04	0.04	0.37^***	-0.03	-0.04	-0.01	1
(8)	-0.04	-0.01	0.38^***	-0.17^***	-0.07^**	0.01	-0.14^***	1
(9)	0.01	0.1^***	0.25^***	0.03	0.03	-0.11^***	-0.01	-0.11^***	1
(10)	-0.03	0.13^***	0.23^***	0.18^***	-0.02	-0.01	0.29^***	0.06	0.08^**	1
(11)	0.45^***	-0.41^***	-0.31^***	0.07^**	-0.29^***	-0.03	0.00	-0.18^***	-0.06^*	-0.17^***	1
(12)	0.08^**	-0.46^***	-0.11^***	-0.03	-0.14^***	0.04	-0.07^**	0.06^*	-0.16^***	-0.12^***	0.41^***	1
(13)	-0.28^***	0.41^***	0.21^***	-0.08^**	0.15^***	0.01	0.04	0.14^***	0.1^***	0.05	-0.68^***	-0.32^***	1
(14)	0.53^***	-0.38^***	-0.14^***	0.1^***	-0.21^***	-0.1^***	-0.01	0.03	-0.07^**	0.05	0.65^***	0.23^***	-0.55^***	1
(15)	0.02	-0.23^***	-0.24^***	0.02^***	0.00	-0.14^***	-0.1^***	-0.12^***	-0.2^***	-0.13^***	0.22^***	0.21^***	-0.24^***	0.2^***	1
(16)	-0.12^***	0.14^***	0.00	-0.01	-0.03	0.05	0.01	0.01	-0.01	0.05	-0.03	-0.04	0.04	0.01	0.03	1
(17)	0.02	-0.11^***	-0.03	-0.01	-0.02	-0.01	0.1^***	-0.01	-0.11^***	0.27^***	0.05	0.19^***	-0.1^***	0.02	-0.04	-0.16^***	1
(18)	0.04	-0.28^*	-0.21^*	0.11^*	-0.20^*	0.04	-0.02	-0.07	-0.24^*	0.03	0.49^*	0.28^*	-0.65^*	0.49^*	0.17^***	-0.12^*	0.01	1

EEPSf	GLS panel data regression					Quantile regression
EEPSf	t + 1	t + 2	t + 3	t + 4	x + 1	0.05	0.1	0.25	0.5	0.75	0.9	0.95
Constant	2.79	-3.24	-3.25^*	-0.39	-0.40	-0.69	-3.33^**	-2.47	-0.09	1.15^***	1.55^***	1.77^***
QKAM	0.22	0.09	0.48	-0.26	0.21	2.25^***	-	-	-	-	0.22^*	0.31^**
SpMatt	-0.09	0.09	-0.56	0.11	-0.12	-1.36^***	-0.41^*	-0.45	0.19^**	0.01	-0.04	-0.07
Assets	0.05	0.04	-0.04	0.10	0.01	-0.79^***	0.11	0.06	0.02	0.01	-0.05	-0.11^**
Impairments	0.00	-0.04	-0.22	0.01	-0.06	-0.91^***	-0.06	-0.15	-0.08	-0.06	-0.12^**	-0.15^***
Liabilities	-0.10	-0.21	-0.28	-0.07	-0.19	-0.96^***	-0.10	-0.10	0.02	-0.01	-0.06	-0.14^**
CompMatt	0.05	0.06	0.00	-0.09	-0.01	-0.71^***	-0.02	0.06	0.00	-0.03	-0.14^***	-0.18^***
Controls	-0.03	0.22	-0.44	-0.24	-0.12	-0.99^***	-0.06	-0.31	-0.12^*	-0.05	-0.09	-0.13^**
SIZE	0.09	0.04	0.14^*	0.14	0.11	0.07	0.21^***	0.23^**	0.06^*	0.01	-0.02	-0.02
ROA	0.09^***	0.08^***	0.11^***	0.09^***	0.08^***	0.22^***	0.18^***	0.11^***	0.05^***	0.02^***	0.01^**	0.01^*
MB	0.05	-0.04	-0.02	-0.06	-0.05	-0.08	-0.01	-0.01	-0.02	-0.01	-0.02	-0.02^*
Loss	0.54	0.65^*	0.94^***	-0.70^*	0.27	0.70^**	0.77^***	0.30	-0.13	-0.44^***	-0.33^***	-0.27^***
EPSp	0.61^***	0.60^***	0.65^***	0.16	0.48^***	0.58^***	0.84^***	0.69^***	0.32^***	0.21^***	0.18^***	0.14^***
BIG	-0.72^***	-0.40	-0.17	0.00	-0.44^**	-0.24	0.25	-0.17	-0.20^**	-0.18^***	-0.20^***	-0.12^*
Age	-0.65	0.33	0.23	-0.04	-0.19^***	-0.15	-0.11	-0.15	-0.08	-0.10^***	-0.08^**	-0.07^**
QAnalyst	-0.10	0.05	0.02	-0.06	-0.01	0.00	-0.03	-0.10	-0.02	-0.03^*	-0.03^**	-0.03^**
DoTip	-1.59^***	-1.27^***	-1.69^***	-1.74^***	-1.53^***	-2.71^***	-3.11^***	-2.28^***	-1.09^***	-0.79^***	-0.56^***	-0.53^***
Year_2016	-0.40	0.32	-0.04	-0.17	0.05	-0.23	-0.29	-0.24	0.02	-0.08	0.00	-0.05
Year_2017	-0.20	0.05	-0.15	0.00	0.00	-0.16	-0.31^**	-0.12	0.01	0.01	0.04	0.01
Observations	172	211	220	230	833	833	837	837	837	837	833	833
R²/pseudo R²	0.22	0.31	0.41	0.38	0.23	0.24	0.31	0.24	0.17	0.12	0.10	0.05

AEPSf	GLS panel data regression					Quantile regression
AEPSf	t + 1	t + 2	t + 3	t + 4	x + 1	0.05	0.10	0.25	0.50	0.75	0.90	0.95
Constant	-0.07	0.05	0.11	0.08	0.08	-0.01	-0.01	0.00	0.16^***	0.22^***	0.24^***	0.28^*
QKAM	-0.04	0.01	-0.01	0.04^*	0.01	0.00	-	-	-	-	0.00	0.03
SpMatt	0.04^*	-0.02	0.00	-0.03^**	-0.01	0.00	0.00	0.00	0.00	0.00	0.00	-0.01
Assets	0.01	-0.01	0.00	-0.01	0.00	0.00	0.00	0.00	0.00	0.00	0.01	0.00
Impairments	0.01	0.00	0.01	-0.02	0.01	0.00	0.00	0.00	0.00	0.00	0.01	-0.01
Liabilities	0.01	0.00	0.00	-0.02^*	0.00	0.00	0.00	0.00	0.00	0.00	0.01	-0.01
CompMatt	0.01	0.00	0.01	-0.01	0.00	0.00	0.00	0.00	0.00	0.00	0.01	0.00
Controls	0.02	0.00	0.04^**	0.01	0.02	0.00	0.00	0.00	0.01	0.01^**	0.02^***	-0.01
SIZE	-0.01	0.00	-0.01	0.00	0.00	0.00	0.00	0.00	0.00	-0.01^**	-0.01^**	-0.01
ROA	-0.01^*	0.00	0.00	0.01^**	0.00	0.00	0.00	0.00	0.00	0.00	0.01^***	0.00
MB	0.00	-0.01^*	0.00	0.00	0.00	0.00	0.00	0.00	0.00	-0.01^***	-0.01^***	-0.01^**
Loss	0.02	0.03	0.04^**	0.07^***	0.03^*	0.01^**	0.01^***	0.02^***	0.04^***	0.08^***	0.12^***	0.13^***
EPSp	-0.03^***	-0.01	-0.02^***	-0.02^***	-0.02^***	-0.01^***	-0.01^**	-0.01^***	-0.01^***	-0.02^***	-0.02^***	-0.02^*
BIG	-0.02	-0.03	-0.04^**	-0.06^***	-0.02	0.00	0.00	0.00	-0.08^***	-0.07^***	-0.07^***	-0.08^***
Age	0.05^*	0.02	0.02	0.01^*	0.01^***	0.00	0.00	0.00	0.01	0.01	0.01^*	0.01
QAnalyst	0.00	0.00	0.00	-0.01^*	-0.01^*	0.00	0.00	0.00	0.00	-0.01^*	-0.01^**	-0.01
DoTip	-0.02	-0.02	0.00	0.04	0.02^**	0.01^**	0.01^***	0.01^**	0.00	-0.01	0.01	0.02
Year_2016	-0.02	-0.03^**	-0.03^**	-0.03^***	-0.02^***	0.00	0.00	-0.01	-0.01^*	-0.02^***	-0.03^***	-0.03
Year_2017	-0.05^**	-0.01	-0.03^***	-0.02^***	-0.02^***	0.00	0.00	0.00	-0.01	-0.01^**	-0.02^***	-0.01
Observations	172	211	220	230	833	833	837	837	837	837	833	833
R² / pseudo R²	0.36	0.13	0.1	0.12	0.08	0.01	0.03	0.09	0.24	0.45	0.54	0.46

Universidade de São Paulo, Faculdade de Economia, Administração e Contabilidade, Departamento de Contabilidade e Atuária Av. Prof. Luciano Gualberto, 908 - prédio 3 - sala 118, 05508 - 010 São Paulo - SP - Brasil, Tel.: (55 11) 2648-6320, Tel.: (55 11) 2648-6321, Fax: (55 11) 3813-0120 - São Paulo - SP - Brazil
E-mail: recont@usp.br

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Brasil

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Informational content of key audit matters and financial analysts’ forecasts* * Paper presented at the 20th USP International Conference in Accounting, July of 2020

Abstract

Informational content of key audit matters and financial analysts’ forecasts^* * Paper presented at the 20th USP International Conference in Accounting, July of 2020