Readability as a measure of textual complexity: determinants and evidence in Brazilian companies

Souza, João Antônio Salvador de; Borba, José Alonso

doi:10.1590/1808-057x202114180

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Brasil

Revista Contabilidade & Finanças

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Original Article • Rev. contab. finanç. 33 (88) • Jan-Apr 2022 • https://doi.org/10.1590/1808-057x202114180 copy

Readability as a measure of textual complexity: determinants and evidence in Brazilian companies

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

The aim of this article was to evaluate the effect of company earnings and of harmonization with IFRS on the readability of Management Reports in the Brazilian stock market. There is a gap to be filled both in the elaboration and adaptation of readability measures to the context studied, as the studies tend to replicate the original formulas, and in identifying the determinants of the readability of Brazilian company reports, as the research in this field remains in its infancy and the results are inconclusive. The results provide indications for investors to identify complex textual information and may help public policymakers to establish a simple writing manual, along the lines of the SEC’s 1998 Plain English Handbook. The modified metrics and the one developed overcome the criticisms regarding the use of readability formulas in accounting research and could be used in substitution of the original metrics in future studies. An econometric model was used that presents the determinants of readability. Readability was calculated for the Results Analysis section of the Management Report. The resulting construct is understood via three attributes: persistence, current performance, and the reference benchmark. Harmonization with IFRS is a dummy variable, which delimits the pre- and post-IFRS periods. The hypotheses were tested in a sample of Brazilian companies made up of 714 company-year observations covering the period from 2006 to 2019. The descriptive results show that there is an apparent improvement in the readability of the reports in the pre- and post-IFRS period comparison. The econometric evidence shows that, in general, companies with persistent and positive earnings present less complex reports and are more likely to have highly readable reports, because managers publish reports with better readability to signal positive results to the market.

Keywords:
textual complexity; readability; reference benchmark; earnings persistence

	Companies	Companies-year
All companies with data in the Economática® database between 2006 and 2019	600	8,400
Minus: companies belonging to the “financial sector” and “others”	111	1,554
Minus: companies with insufficient data to calculate the variables	298	4,172
Minus: companies with a stock market liquidity index < 0.0001	140	1,960
	51	714

Main independent variables
Measures of the earnings construct
Persistence	Estimate of the coefficient of inclination β_1i based on the model presented in equation 4. This is the first-order autoregressive model (AR1) estimated for every company-year using 7-year windows. ${E a r n i n g s p e r s h a r e}_{i t} = β_{0} + β_{1 i} {E a r n i n g s p e r s h a r e}_{i t - 1} + µ_{i t}$ (4)
Concept: A positive relationship is expected between the Persistence measure and the readability variables. Earnings per share is understood as the values of profit or loss per share. The interpretation of eq. 4 is that the higher β_1i values indicate high persistence and values close to 0 indicate transitory performance or low persistence. Note that the choice of analysis window follows the research of Francis et al. (2004Francis, J., LaFond, R., Olsson, P. M., & Schipper, K. (2004). Costs of equity and earnings attributes. The Accounting Review, 79(4), 967-1010. https://doi.org/10.2308/accr.2004.79.4.967 https://doi.org/10.2308/accr.2004.79.4.9... ), who opted to employ a 10-year window. In this research, a 7-year window is preferred, because we chose to employ a balanced data panel. Thus, by choosing a bigger window of years, the final sample is substantially reduced, as was observed in unreported tests, which would hinder the statistical inferences. The procedure for calculating persistence by estimating an autoregressive model followed the studies of Barton, Hansen, and Pownall (2010Barton, J., Hansen, T. B., & Pownall, G. (2010). Which performance measures do investors around the world value the most-and why? The Accounting Review, 85(3), 753-789. https://doi.org/10.2308/accr.2010.85.3.753 https://doi.org/10.2308/accr.2010.85.3.7... ) and Francis et al. (2004Francis, J., LaFond, R., Olsson, P. M., & Schipper, K. (2004). Costs of equity and earnings attributes. The Accounting Review, 79(4), 967-1010. https://doi.org/10.2308/accr.2004.79.4.967 https://doi.org/10.2308/accr.2004.79.4.9... ). Unlike the present study, which employs Earnings per share, Barton et al. (2010Barton, J., Hansen, T. B., & Pownall, G. (2010). Which performance measures do investors around the world value the most-and why? The Accounting Review, 85(3), 753-789. https://doi.org/10.2308/accr.2010.85.3.753 https://doi.org/10.2308/accr.2010.85.3.7... ) use a composite earnings variable and Francis et al. (2004Francis, J., LaFond, R., Olsson, P. M., & Schipper, K. (2004). Costs of equity and earnings attributes. The Accounting Review, 79(4), 967-1010. https://doi.org/10.2308/accr.2004.79.4.967 https://doi.org/10.2308/accr.2004.79.4.9... ) employ a measure of net income before extraordinary items. To identify possible econometric problems, the augmented Dickey-Fuller test was applied (Said & Dickey, 1984Said, S. E., & Dickey, D. A. (1984). Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, 71(3), 599-607. https://doi.org/10.1093/biomet/71.3.599 https://doi.org/10.1093/biomet/71.3.599... ). The procedure was carried out with the test equation with trend, with drift, and with a 1-period lag, as discussed by Gujarati and Porter (2011Gujarati, D. N., & Porter, D. C. (2011). Econometria básica (5a ed.). Editora AMGH.). Initially, the test was conducted by company for all the data windows, from 2000 to 2019. At this stage it was not possible to reject H₀ for 12 companies, that is, 12 companies presented a non-stationary data series. To test the effect of this violation of the property of a series, the observations were excluded from the sample and the parameters of model (1) were re-estimated. As there were no discrepancies in relation to the original values, we chose to maintain the observations in the database. Subsequently, the augmented Dickey-Fuller test was conducted by company-year using 7-year windows, which resulted in 14 statistics for the test by company. As before, the companies that presented a non-stationary data series were excluded from the sample of companies and the parameters of model (1) were re-estimated. As no significant changes occurred in the estimate of the parameters, the companies were maintained in the sample.
Performance	= EBIT / Total assets
Concept: The Performance proxy captures accounting performance. A positive relationship is expected between the Performance measure and readability. The operationalization of the variable is in accordance with Li (2008Li, F. (2008). Annual report readability, current earnings, and earnings persistence. Journal of Accounting and Economics, 45(2-3), 221-247. https://doi.org/10.1016/j.jacceco.2008.02.003 https://doi.org/10.1016/j.jacceco.2008.0... ) and Lo et al. (2017Lo, K., Ramos, F., & Rogo, R. (2017). Earnings management and annual report readability. Journal of Accounting and Economics, 63(1), 1-25. https://doi.org/10.1016/j.jacceco.2016.09.002 https://doi.org/10.1016/j.jacceco.2016.0... ).
Benchmark	= 1 if the variable for Performance from year ₊₁ to year t₁ is negative, or 0 otherwise.
Concept: a negative relationship is expected with the readability measures, indicating that companies that did not achieve the reference benchmark in relation to the previous year tend to disclose more complex reports. This variable is in accordance with the one presented by Li (2008Li, F. (2008). Annual report readability, current earnings, and earnings persistence. Journal of Accounting and Economics, 45(2-3), 221-247. https://doi.org/10.1016/j.jacceco.2008.02.003 https://doi.org/10.1016/j.jacceco.2008.0... ) and Lo et al. (2017Lo, K., Ramos, F., & Rogo, R. (2017). Earnings management and annual report readability. Journal of Accounting and Economics, 63(1), 1-25. https://doi.org/10.1016/j.jacceco.2016.09.002 https://doi.org/10.1016/j.jacceco.2016.0... ).
Measure of harmonization with IFRS
IFRS	= 1 if the observation belongs to the post-IFRS period (≥ 2010), or 0 otherwise
Concept: In Brazil, the main milestone of the IFRS convergence process was the enactment of Law n. 11,638/2007Lei 11.638, de 28 de setembro de 2007. (2007). Altera e revoga dispositivos da Lei n. 6.404, de 15 de dezembro de 1976, e da Lei n. 6.385, de 7 de dezembro de 1976, e estende às sociedades de grande porte disposições relativas à elaboração e divulgação de demo. http://www.planalto.gov.br/ccivil_03/_ato2007-2010/2007/lei/l11638.htm http://www.planalto.gov.br/ccivil_03/_at... . The approach of distinguishing harmonization with IFRS is in accordance with the studies of Boubaker et al. (2019Boubaker, S., Gounopoulos, D., & Rjiba, H. (2019). Annual report readability and stock liquidity. Financial Markets, Institutions and Instruments, 28(2), 159-186. https://doi.org/10.1111/fmii.12110 https://doi.org/10.1111/fmii.12110... ) and of Cheung and Lau (2016Cheung, E., & Lau, J. (2016). Readability of notes to the financial statements and the adoption of IFRS. Australian Accounting Review, 26(2), 162-176. https://doi.org/10.1111/auar.12087 https://doi.org/10.1111/auar.12087... ). A positive result is expected for the variable, because harmonization with IFRS can add an incremental improvement in the informational environment.
*Control variables*
Liquidity	$= 100 * \frac{p}{P} * \sqrt{(\frac{n}{N} * \frac{v}{V})}$	Where: p = number of days on which there was at least one trade with the share within the chosen period P = total number of days of the chosen period n = number of trades with the share within the chosen period N = number of trades with all the shares within the chosen period v = financial volume with the share within the chosen period V = financial volume with all the shares within the chosen period
Concept: Bloomfield and Wilks (2000Bloomfield, R. J., & Wilks, T. J. (2000). Disclosure effects in the laboratory: liquidity, depth, and the cost of capital. The Accounting Review, 75(1), 13-41. https://www.jstor.org/stable/248631 https://www.jstor.org/stable/248631... ) and Heflin, Shaw, and Wild (2005Heflin, F. L., Shaw, K. W., & Wild, J. J. (2005). Disclosure policy and market liquidity: impact of depth quotes and order sizes. Contemporary Accounting Research, 22(4), 829-865. https://doi.org/10.1506/eetm-falm-4kdd-9dt9 https://doi.org/10.1506/eetm-falm-4kdd-9... ) argue that an improvement in disclosure increases the demand for shares, with a resulting increase in their liquidity. Boubaker et al. (2019Boubaker, S., Gounopoulos, D., & Rjiba, H. (2019). Annual report readability and stock liquidity. Financial Markets, Institutions and Instruments, 28(2), 159-186. https://doi.org/10.1111/fmii.12110 https://doi.org/10.1111/fmii.12110... ) and Lang and Stice-Lawrence (2015Lang, M., & Stice-Lawrence, L. (2015). Textual analysis and international financial reporting: large sample evidence. Journal of Accounting and Economics, 60(2-3), 110-135. https://doi.org/10.1016/j.jacceco.2015.09.002 https://doi.org/10.1016/j.jacceco.2015.0... ) are examples of studies that empirically test this relationship. And a positive sign is expected of the liquidity proxy when related to readability.
Size	= ln of Total assets
Concept: Bigger companies tend to be more complex, both operationally and geographically (Dempsey et al., 2012Dempsey, S. J., Harrison, D. M., Luchtenberg, K. F., & Seiler, M. J. (2012). Financial opacity and firm performance: the readability of REIT annual reports. Journal of Real Estate Finance and Economics, 45(2), 450-470. https://doi.org/10.1007/s11146-010-9263-2 https://doi.org/10.1007/s11146-010-9263-... ). Such complexity may be reflected in the readability of their reports, because bigger companies issue more complex reports (Ajina et al., 2016Ajina, A., Laouiti, M., & Msolli, B. (2016). Guiding through the Fog: does annual report readability reveal earnings management? Research in International Business and Finance, 38, 509-516. https://doi.org/10.1016/j.ribaf.2016.07.021 https://doi.org/10.1016/j.ribaf.2016.07.... ; Dempsey et al., 2012Dempsey, S. J., Harrison, D. M., Luchtenberg, K. F., & Seiler, M. J. (2012). Financial opacity and firm performance: the readability of REIT annual reports. Journal of Real Estate Finance and Economics, 45(2), 450-470. https://doi.org/10.1007/s11146-010-9263-2 https://doi.org/10.1007/s11146-010-9263-... ; Li, 2008Li, F. (2008). Annual report readability, current earnings, and earnings persistence. Journal of Accounting and Economics, 45(2-3), 221-247. https://doi.org/10.1016/j.jacceco.2008.02.003 https://doi.org/10.1016/j.jacceco.2008.0... ; Lo et al., 2017Lo, K., Ramos, F., & Rogo, R. (2017). Earnings management and annual report readability. Journal of Accounting and Economics, 63(1), 1-25. https://doi.org/10.1016/j.jacceco.2016.09.002 https://doi.org/10.1016/j.jacceco.2016.0... ). The sign expected for the size variable is negative.
Volatility	= Standard deviation of the Performance variable (EBIT / Total assets) for a 5-year window.
Concept: It is assumed that, in more volatile business environments, corporate communication is more complex (Li, 2008Li, F. (2008). Annual report readability, current earnings, and earnings persistence. Journal of Accounting and Economics, 45(2-3), 221-247. https://doi.org/10.1016/j.jacceco.2008.02.003 https://doi.org/10.1016/j.jacceco.2008.0... ). Thus, a negative sign is expected for this variable. Cheung and Lau (2016Cheung, E., & Lau, J. (2016). Readability of notes to the financial statements and the adoption of IFRS. Australian Accounting Review, 26(2), 162-176. https://doi.org/10.1111/auar.12087 https://doi.org/10.1111/auar.12087... ), Li (2008Li, F. (2008). Annual report readability, current earnings, and earnings persistence. Journal of Accounting and Economics, 45(2-3), 221-247. https://doi.org/10.1016/j.jacceco.2008.02.003 https://doi.org/10.1016/j.jacceco.2008.0... ), and Lo et al. (2017Lo, K., Ramos, F., & Rogo, R. (2017). Earnings management and annual report readability. Journal of Accounting and Economics, 63(1), 1-25. https://doi.org/10.1016/j.jacceco.2016.09.002 https://doi.org/10.1016/j.jacceco.2016.0... ) are examples of studies that use this variable.
Indebtedness	= (Current liabilities + Non-current liabilities) / Total assets
Concept: Companies with a high level of debts may publish more complex reports, with the aim of persuading capital providers (Dempsey et al., 2012Dempsey, S. J., Harrison, D. M., Luchtenberg, K. F., & Seiler, M. J. (2012). Financial opacity and firm performance: the readability of REIT annual reports. Journal of Real Estate Finance and Economics, 45(2), 450-470. https://doi.org/10.1007/s11146-010-9263-2 https://doi.org/10.1007/s11146-010-9263-... ). A negative relationship is expected between indebtedness and readability as in Ajina et al. (2016Ajina, A., Laouiti, M., & Msolli, B. (2016). Guiding through the Fog: does annual report readability reveal earnings management? Research in International Business and Finance, 38, 509-516. https://doi.org/10.1016/j.ribaf.2016.07.021 https://doi.org/10.1016/j.ribaf.2016.07.... ) and Dempsey et al. (2012Dempsey, S. J., Harrison, D. M., Luchtenberg, K. F., & Seiler, M. J. (2012). Financial opacity and firm performance: the readability of REIT annual reports. Journal of Real Estate Finance and Economics, 45(2), 450-470. https://doi.org/10.1007/s11146-010-9263-2 https://doi.org/10.1007/s11146-010-9263-... ).
Age	= ln of the difference, in days, from the date the company was founded to the closing date of the financial statements
Concept: Companies in operation for longer may present less complex reports due to the greater asymmetry and uncertainty in their information (Li, 2008Li, F. (2008). Annual report readability, current earnings, and earnings persistence. Journal of Accounting and Economics, 45(2-3), 221-247. https://doi.org/10.1016/j.jacceco.2008.02.003 https://doi.org/10.1016/j.jacceco.2008.0... ). This variable was used by Li (2008Li, F. (2008). Annual report readability, current earnings, and earnings persistence. Journal of Accounting and Economics, 45(2-3), 221-247. https://doi.org/10.1016/j.jacceco.2008.02.003 https://doi.org/10.1016/j.jacceco.2008.0... ) and Lo et al. (2017Lo, K., Ramos, F., & Rogo, R. (2017). Earnings management and annual report readability. Journal of Accounting and Economics, 63(1), 1-25. https://doi.org/10.1016/j.jacceco.2016.09.002 https://doi.org/10.1016/j.jacceco.2016.0... ).
*Variables used in the additional tests*
Low Persistence	Observations found in the first two quintiles (Q_2/5) of the Persistence variable
High Persistence	Observations found in the last two quintiles (Q_4/5) of the Persistence variable
Low Performance	Observations found in the first two quintiles (Q_2/5) of the Performance variable
High Performance	Observations found in the last two quintiles (Q_4/5) of the Performance variable
Ranking	The Ranking variable takes the value of 1 if the company belongs to the last two quintiles (Q_4/5) of the readability ranking and 0 if it belongs to the first two quintiles (Q_2/5).	The readability ranking is captured after multiplying the percentages of shared variance, obtained from the factor loadings of the textual characteristics ModFlesch, ModFog, and Simple Writing.

Panel A. Descriptive statistics for the main interest and control variables
Readability measures	n	Mean	Median	SD	Min		Max		Q _1/4		Q _3/4
ModFlesch	714	5.00	5.00	0.04	4.87		5.07		4.97		5.03
Original Flesch	714	3.46	3.53	0.32	2.30		3.91		3.33		3.66
ModFog	714	-10.29	-10.02	2.11	-16.31		-6.52		-11.47		-8.81
Original Fog	714	-10.83	-10.56	2.12	-16.87		-7.04		-12.01		-9.34
Simple Writing	714	-10.38	-6.19	12.13	-57.87		-1.26		-10.83		-3.63
Earnings measures
Persistence	714	0.22	0.25	0.45	-0.67		0.88		-0.16		0.62
Performance	714	0.08	0.08	0.07	-0.09		0.24		0.04		0.12
Control variables
Liquidity	714	0.54	0.23	0.75	0.0002		3.33		0.01		0.75
Size	714	15.69	15.67	1.73	12.81		19.49		14.11		17.07
Volatility	714	0.03	0.02	0.04	0.001		0.19		0.01		0.04
Indebtedness	714	0.63	0.58	0.30	0.26		1.90		0.45		0.70
Age	714	9.67	9.89	0.70	8.02		10.64		9.41		10.17
Panel B. Occurrence of the main interest variables by reference benchmark type
	Negative Benchmark (A)			Positive Benchmark (B)			Difference (A - B)
	n	sum	mean	n	sum	mean	n		sum		mean
ModFlesch	366	1,828.08	4.99	348	1,740.16	5.00	18		87.92		-0.01
ModFog	366	-3,817.90	-10.43	348	-3,525.60	-10.13	18		-292.29		-0.30
Simple Writing	366	-3,832.78	-10.47	348	-3,579.38	-10.29	18		-253.39		-0.19
Persistence	366	89.17	0.24	348	64.61	0.19	18		24.56		0.06
Performance	366	24.32	0.07	348	32.88	0.09	18		-8.56		-0.03
Panel C. Descriptive statistics of the main interest variables in relation to harmonization with IFRS
	Pre-IFRS (A)			Post-IFRS (B)			Difference of means and medians
	n	Mean	Med	n	Mean	Med	Mean B-A		Student t test		Mann-Whitney test
ModFlesch	204	4.99	5.00	510	5.00	5.00	0.01		^*-1.810		-0.990
ModFog	204	-10.49	-10.00	510	-10.20	-10.02	0.29		^*-1.651		-0.797
Simples Writing	204	-12.24	-6.37	510	-9.64	-6.12	2.61		^***-2.604		-1.060
Persistence	204	0.32	0.36	510	0.17	0.18	-0.15		^***4.081		^***4.068
Performance	204	0.10	0.10	510	0.07	0.07	-0.03		^***3.347		^***4.582
Panel D - Pearson’s correlation
		(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)
ModFlesch	(1)
ModFlesch
ModFog	(2)	0.94
ModFog		(0.00)
Simple Writing	(3)	0.41	0.34
Simple Writing		(0.00)	(0.00)
Persistence	(4)	0.17	0.14	0.24
Persistence		(0.00)	(0.00)	(0.00)
Performance	(5)	0.11	0.11	0.25	0.31
Performance		(0.00)	(0.00)	(0.00)	(0.00)
Benchmark	(6)	-0.07	-0.07	-0.01	0.06	-0.20
Benchmark		(0.08)	(0.06)	(0.84)	(0.08)	(0.00)
IFRS	(7)	0.07	0.06	0.10	-0.15	-0.18	-0.02
IFRS		(0.07)	(0.10)	(0.01)	(0.00)	(0.00)	(0.57)
Liquidity	(8)	0.02	-0.04	0.22	0.14	0.11	0.05	-0.003
Liquidity		(0.51)	(0.26)	(0.00)	(0.00)	(0.00)	(0.17)	(0.95)
Size	(9)	-0.05	-0.10	0.30	0.04	0.09	0.04	0.17	0.72
Size		(0.20)	(0.01)	(0.00)	(0.35)	(0.01)	(0.27)	(0.00)	(0.00)
Volatility	(10)	-0.10	-0.09	-0.21	-0.14	-0.14	-0.09	-0.02	-0.09	-0.21
Volatility		(0.01)	(0.01)	(0.00)	(0.00)	(0.00)	(0.02)	(0.57)	(0.02)	(0.00)
Indebtedness	(11)	0.04	0.02	-0.11	-0.16	-0.17	-0.03	0.06	-0.11	-0.20	0.19
Indebtedness		(0.30)	(0.61)	(0.00)	(0.00)	(0.00)	(0.36)	(0.13)	(0.00)	(0.00)	(0.00)
Age	(12)	0.13	0.10	-0.03	-0.04	-0.19	-0.02	0.13	-0.06	-0.31	0.08	0.23
Age		(0.00)	(0.01)	(0.46)	(0.26)	(0.00)	(0.57)	(0.00)	(0.10)	(0.00)	(0.02)	(0.00)

	ModFlesch			ModFog			Simple Writing
	(I)			(II)			(III)
	Coef.	Error	t	Coef.	Error	t	Coef.	Error	z
Persistence	^***0.011	(0.003)	3.25	^**0.393	(0.173)	2.27	^***50.417	(12.007)	4.20
Performance	^***0.078	(0.025)	3.17	^***3.696	(1.279)	2.89	-25.978	(37.827)	-0.69
Benchmark	^*-0.005	(0.003)	-1.75	^*-0.288	(0.148)	-1.94	^*-4.100	(2.250)	-1.82
IFRS	^**0.018	(0.008)	2.36	^*0.668	(0.399)	1.68	5.844	(4.268)	1.37
Liquidity	^**-0.007	(0.003)	-2.21	-0.27	(0.164)	-1.65	^***-7.753	(2.190)	-3.54
Size	^**0.004	(0.002)	2.50	0.047	(0.082)	0.57	^***4.527	(0.948)	4.77
Volatility	-0.043	(0.046)	-0.93	-2.363	(2.488)	-0.95	-8.367	(21.586)	-0.39
Indebtedness	0.006	(0.005)	1.08	0.148	(0.300)	0.49	2.632	(2.981)	0.88
Age	0.001	(0.003)	0.39	-0.017	(0.148)	-0.12	2.435	(1.616)	1.51
Constant	^***4.941	(0.043)	115.74	^***-10.299	(2.245)	-4.59	^***-128.120	(26.365)	-4.86
Observations		714			714			714
R²		0.36			0.26			-
Year/sector fixed effect		Included			Included			Included
Model specification tests
Variance Inflation Factor (VIF)	Min	Max	Mean	Min	Max	Mean	Min	Max	Mean
Variance Inflation Factor (VIF)	1.18	6.29	2.03	1.18	6.29	2.03	1.18	6.29	2.03
Autocorrelation: Durbin-Watson (DW)		1.897			1.844			1.952
Endogeneity: Durbin-Hu-Watson (DHW)
Persistence/ Performance Variable	0.627 / 1.171			1.373 / 0.647			^*76.465 / ^*10.854
Breusch-Pagan Lagrangian multiplier (BP)	^***1,046			^***646			^***344
F Chow	^***15.57			^***10.74			^***7.54
Hausman	^*15.16			^**17.34			^***29.46
Sargan-Hansen (SH)	^**20.93			^**20.52			^***36.45

Ranking dep. var.	(I)	(II)	(III)	(IV)	(V)	(VI)
Persistence	^***0.948
Persistence	(3.83)
Low persistence		0.182
Low persistence		(0.28)
High persistence			^***2.925
High persistence			(2.85)
Performance				^***4.521
Performance				(2.75)
Low performance					2.310
Low performance					(0.76)
High performance						-1.255
High performance						(-0.33)
∑Control variables	Included	Included	Included	Included	Included	Included
Constant	Included	Included	Included	Included	Included	Included
Observations	572	240	221	572	235	224
Pseudo R²	0.26	0.11	0.17	0.25	0.05	0.14
Year fixed effect	Included	Included	Included	Included	Included	Included
Sector fixed effect	Included	No	No	Included	No	No
Quality tests of the model’s fit
Hosmer-Lemeshow	7.64 (0.47)	4.18 (0.84)	9.71 (0.29)	6.66 (0.57)	7.36 (0.50)	18.11 (0.02)
Sensitivity	75.17%	40.00%	83.72%	78.67%	36.63%	73.60%
Specificity	72.73%	84.83%	54.35%	71.33%	81.34%	52.53%
Correct classification	73.95%	67.08%	71.49%	75.00%	62.13%	64.29%
ROC	0.823	0.709	0.755	0.817	0.643	0.732

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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: joaosalvador@id.uff.br