Predictive ability of accruals before and after IFRS in the Brazilian stock market

Boina, Terence Machado; Macedo, Marcelo Alvaro da Silva

doi:10.1590/1808-057x201806300

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Original Article • Rev. contab. finanç. 29 (78) • Sep-Dec 2018 • https://doi.org/10.1590/1808-057x201806300 copy

Predictive ability of accruals before and after IFRS in the Brazilian stock market

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

This study aimed to analyze and assess the predictive ability of discretionary accruals (DAs) and non-discretionary accruals (NDAs) for forecasting future cash flows before and after the convergence with International Financial Reporting Standards (IFRS) in Brazil. The study is warranted due to the scarcity of research in Brazil on the subject and is relevant because it aims to shed light on whether the changes occurring due to convergence with IFRS in Brazil have improved accounting quality. The accounting choices of managers and accountants in the Brazilian stock market, enabled by IFRS, contribute to an apparent improvement in accounting quality in terms of reliability, the faithful representation of entities’ equity and financial positions, and in particular, the predictive ability for forecasting future cash flows. The population was composed of publicly traded companies listed on the Bovespa and São Paulo Stock, Commodities, and Futures Exchange (BM&FBovespa) in 2004 to 2007 and 2010 to 2015. The non-probability convenience sample is composed of 715 enterprises, once companies from the “finance and insurance” and “funds” sectors and even those considered as “holding” were excluded. The data were pooled by year, as they contain different companies over the time series (unbalanced panel data). The DAs and NDAs produced prior to full convergence with IFRS are negative and statistically significant for predicting future cash flows in the Brazilian stock market, which indicated opportunistic/contractual earnings management. One of the possible explanations for this would be the influence of government tax authorities on Brazilian accounting norms, which could induce managers to manipulate accounting results with the aim of reducing earnings in order to pay fewer taxes, for example. The DAs and NDAs produced after IFRS are positive and statistically significant for predicting future cash flows in the Brazilian stock market, signaling the motivation of discretionary accounting choices under the informational aspect. Current DAs and NDAs add informational power compared to current aggregate accruals. It has also been observed that the current DAs and NDAs originating after IFRS in Brazil, compared to current aggregate accruals, have an informational gain in relation to those produced before.

Keywords
accounting quality; predictive ability; accruals; IFRS; cash flow

Reference	Summary of the Results
Finger (1994)Finger, C. A. (1994). The ability of earnings to predict future earnings and cash flow. Journal of Accounting Research, 32(2), 210-223.	Between 1935 and 1987, in the U.S. market, income or loss for the accounting period (NI) and operating cash flow (OCF) have a similar predictive ability for long term time horizons, but OCF is slightly superior to NI for short term time horizons.
Dechow et al. (1998)	Between 1963 and 1992, in the U.S. market, NI is a better predictor of future OCFs than current OCFs themselves, and companies with longer operational cycles better explain the supremacy of NI over OCF.
Barth et al. (2001)	Between 1987 and 1996, in the U.S. market, there was a significant improvement in the predictive ability of future OCFs with the disaggregation of total accruals (ACCs) into operational assets and liabilities and long term assets.
Kim and Kross (2005)Kim, M., & Kross, W. (2005). The ability of earnings to predict future operating cash flows has been increasing - not decreasing. Journal of Accounting Research, 43(5), 753-780.	Between 1973 and 2000, in the U.S. market, the role of current NI in predicting future OCFs improved over time for one year time horizons, however this relationship tends not to improve beyond one year time horizons.
Farshadfar, Ng, and Brimble (2008)Farshadfar, S., Ng, C., & Brimble, M. (2008). The relative ability of earnings and cash flow data in forecasting future cash flows: some Australian evidence. Pacific Accounting Review, 20(3), 254-268.	Between 1992 and 2004, in the Australian market, OCF has more predictive power than NI in forecasting future OCFs.
Ebaid (2011Ebaid, I. El-S. (2011). Accruals and the prediction of future cash flows: empirical evidence from an emerging market. Management Research Review, 34(7), 838-853.)	Better 1999 and 2007, in the Egyptian market, NI has a greater predictive ability than OCFs for estimating future OCFs and disaggregated ACCs improve the predictive ability of OCFs.
Malacrida, Yamamoto, Lima, and Lima (2008)	Between 1999 and 2005, in the Brazilian market, OCFs have a greater predictive ability than NI for estimating future OCFs, ACCs have a predictive ability additional to current OCF for estimating future OCFs, and OCF with disaggregated ACCs have a greater predictive ability for future OCFs than the aggregate ACCs model.
Costa and Afonso (2015)	Between 2005 and 2013, in Brazilian insurers, NI, ACCs, and OCF have the ability to predict future OCFs, and given the results of the adjusted R² and of the Akaike informational criteria, there are doubts about whether ACCs increase the ability to predict OCFs.
Boina et al. (2016a)	Between 2010 and 2014, in electrical energy providing companies, current OCF has a greater predictive ability than current NI for estimating OCFs for subsequent periods and current aggregate ACCs and some disaggregated ACCs increase the predictive ability of current OCFs for predicting the OCFs for subsequent periods.

Reference	Summary of the results
Tendeloo and Vanstraelen (2005Tendeloo, B. V., & Vanstraelen, A. (2005). Earnings management under German GAAP versus IFRS. European Accounting Review, 14(1), 155-180.)	Between 1999 and 2001, in the German market, there was greater earnings management after IFRS adoption, but to a lesser extent when the company was audited by a Big Four external auditing company.
Barth et al. (2008Barth, M. E., Landsman, W. R., & Lang, M. H. (2008). International accounting standards and accounting quality. Journal of Accounting Research, 46(3), 467-498.)	Between 1994 and 2003, in 21 countries, there was an increase in the quality of accounting information from an earnings management, conservatism, and value relevance point of view and a strong association between accounting information and share prices and returns after IFRS adoption.
Ahmed, Neel, and Wang (2013Ahmed, A. S., Neel, M., & Wang, D. (2013). Does mandatory adoption of IFRS improve accounting quality? Preliminary evidence. Contemporary Accounting Research, 30(4), 1344-1372.)	Between 2002 and 2007, in 20 countries, there was insufficient evidence that IFRS adoption produces improvements in accounting quality, from an earnings management and conservatism point of view.
Paulo, Girão, Carter, and Souza (2013Paulo, E., Girão, L. F. A. P., Carter, D., & Souza, R. (2013). The impact of the adoption of International Financial Reporting Standards about the quality of accounting information of the Brazilian and European public firms. Paper presented at the VII ANPCONT. Retrieved from http://congressos.anpcont.org.br/congressos-antigos/vii/images/engltrack_4bfc3.pdf?20150429112300 http://congressos.anpcont.org.br/congres... )	Between 2000 and 2011, in the Brazilian and European markets, the quality of accounting information did not significantly improve in relation to the period before IFRS, from a persistence, conservatism, earnings management, and errors in total accruals (ACCs) point of view.
Silva (2013Silva, R. L. M. (2013). Adoção completa das IFRS no Brasil: qualidade das demonstrações contábeis e o custo de capital próprio (Doctoral thesis, Accounting Sciences, University of São Paulo, São Paulo).)	Between 2000 and 2011, in the Brazilian market, there was a decrease in ACCs, an increase in conditional conservatism, an increase in the relevance and timeliness dimensions of the quality of accounting information, and a reduction in the cost of capital after the complete adoption of IFRS.
Machado et al. (2014Machado, M. A. V., Silva Filho, A. C. C., & Callado, A. L. C. (2014). O processo de convergência às IFRS e a capacidade do lucro e do fluxo de caixa em prever os fluxos de caixa futuro: evidências no mercado brasileiro. Revista de Contabilidade e Organizações, 21(2014), 4-13.)	Between 2006 and 2011, in the Brazilian market, there was an increase in the explanatory ability of NI and of operating cash flow (OCF) combined with ACCs in the period after convergence in Brazil and it was found that ACCs have additional informative power in predicting future OCFs.
Boina, Jesus, Soares, and Macedo (2016bBoina, T. M., Jesus, L. F., Soares, J. E. V. M., & Macedo, M. A. S. (2016b). Avaliação da capacidade preditiva do lucro líquido, do fluxo de caixa operacional e dos accruals antes e após a convergência às normas internacionais de contabilidade no Brasil. Trabalho apresentado no XVI Congresso USP de Controladoria e Contabilidade. Paper presented at the XVI USP Controlling and Accounting Congress. Retrieved from http://www.congressousp.fipecafi.org/anais/artigos162016/143.pdf http://www.congressousp.fipecafi.org/ana... )	Between 2005 and 2007 and 2010 and 2014, in the Brazilian market, there was a consolidation of the supremacy of the informational content of current OCF in relation to the income or loss for the current accounting period in predicting future OCFs and it was found aggregate ACCs and some disaggregated ACCs add informational content to current OCF for predicting future cash flows after IFRS adoption.

Variables	Period	Minimum	Maximum	Mean	Median	Standard deviation
OCF_t	2005-2007	0.00000	0.17819	0.013401	0.00000	0.021594
OCF_t	2012-2015	0.00000	0.33158	0.082599	0.069949	0.067003
OCF_t-1	2004-2006	0.00000	0.17019	0.0096173	0.00000	0.019693
OCF_t-1	2011-2014	0.00000	0.34589	0.088059	0.073715	0.069050
ACC_t-1	2004-2006	-0.070572	0.54004	0.072281	0.050306	0.076100
ACC_t-1	2011-2014	-0.28035	0.51241	-0.018972	-0.022159	0.074148
DA_t-1	2004-2006	-0.39443	0.29320	-0.049030	-0.044190	0.098408
DA_t-1	2011-2014	-0.41583	0.29517	-0.069143	-0.075340	0.087359
NDA_t-1	2004-2006	-0.17141	0.32386	0.12131	0.12458	0.087536
NDA_t-1	2011-2014	-0.18676	0.30392	0.050170	0.047364	0.049365

Variables	Period	Minimum	Maximum	Mean	Median	Standard deviation
OCF_t	2005-2007	0.00000	0.17819	0.014169	0.00000	0.022107
OCF_t	2012-2015	0.00000	0.33158	0.082703	0.070014	0.067071
OCF_t-1	2004-2006	0.00000	0.17019	0.010852	0.00000	0.020623
OCF_t-1	2011-2014	0.00000	0.34589	0.088321	0.073987	0.069312
ACC_t-1	2004-2006	-0.070572	0.51931	0.066840	0.047338	0.069920
ACC_t-1	2011-2014	-0.28035	0.45277	-0.019764	-0.022523	0.072719
DA_t-1	2004-2006	-0.36217	0.29019	-0.055855	-0.072137	0.12597
DA_t-1	2011-2014	-0.38395	0.28003	-0.051411	-0.052735	0.082458
NDA_t-1	2004-2006	-0.27436	0.37768	0.12269	0.13348	0.12423
NDA_t-1	2011-2014	-0.26365	0.37481	0.031647	0.033741	0.062865

	Kothari et al. (2005Kothari, S. P., Leone, A. J., & Wasley, C. E. (2005). Performance matched discretionary accrual measures. Journal of Accounting and Economics, 39(1), 163-197. ) model				Dechow et al. (2012Dechow, P. M., Hutton, A. P., Kim, J. H., & Sloan, R. G. (2012). Detecting earnings management: a new approach. Journal of Accounting Research, 50(2), 275-334. ) model
	Before IFRS		After IFRS		Before IFRS		After IFRS
Variables	Coefficient	p-value	Coefficient	p-value	Coefficient	p-value	Coefficient	p-value
Intercept	0.0163*	0.0000	-0.0306*	0.0000	0,0231*	0,0000	-0,0125*	0,0000
∆Rev_t - ∆AC_t	0.0745*	0.0002	-0.0552**	0.0149	0,0841*	0,0000	-0,0427**	0,0173
FA_t	0.0203*	0.0033	-0.0024	0.6502	0,0205*	0,0014	-0,0052	0,2454
ROA_t-1	0.5540*	0.0000	0.0877*	0.0033
ACC_t-1					0,4987*	0,0000	0,4395*	0,0000
Adjusted R²	0.309281		0.010058		0.309187		0.213634
F test (p-value)	0.0000		0.002795		0.0000		0.0000
Schwarz	-3,353.065		-4,933.472		-3,489.374		-5,364.704
Akaike	-3,373.163		-4,955.314		-3,509.501		-5,386.541
Observations (n)	1,124		1,738		1,132		1,736

	Model 1 - Kothari et al. (2005Kothari, S. P., Leone, A. J., & Wasley, C. E. (2005). Performance matched discretionary accrual measures. Journal of Accounting and Economics, 39(1), 163-197.)		Model 1 - Dechow et al. (2012Dechow, P. M., Hutton, A. P., Kim, J. H., & Sloan, R. G. (2012). Detecting earnings management: a new approach. Journal of Accounting Research, 50(2), 275-334.)		Model 2
Variables	Coefficient	p-value	Coefficient	p-value	Coefficient	p-value
Intercept	0.0197*	0.0000	0.0209*	0,0000	0,0233*	0,0000
OCF_t-1	0.7119*	0.0000	0.7005*	0,0000	0,6271*	0,0000
ACC_t-1					-0,1017*	0,0000
DA_t-1	0.0254	0.1277	0.0447**	0,0194
NDA_t-1	-0.0314***	0.0563	-0.0270	0,1450
Adjusted R²	0.554044		0.546093		0.512158
F test (p-value)	0.0000		0.0000		0.0000
Schwarz	-9,504.781		-9,002.424		-10,993.75
Akaike	-9,528.509		-9,025.973		-11,012.05
Observations (n)	2,785		2,663		3,287

	Model 3 - Kothari et al. (2005Kothari, S. P., Leone, A. J., & Wasley, C. E. (2005). Performance matched discretionary accrual measures. Journal of Accounting and Economics, 39(1), 163-197.)		Model 3 - Dechow et al. (2012Dechow, P. M., Hutton, A. P., Kim, J. H., & Sloan, R. G. (2012). Detecting earnings management: a new approach. Journal of Accounting Research, 50(2), 275-334.)		Model 4
Variables	Coefficient	p-value	Coefficient	p-value	Coefficient	p-value
Intercept	0.0193*	0.0000	0.0219*	0.0000	0.0236*	0.0000
OCF_t-1	0.6855*	0.0000	0.5981*	0.0000	0.4558*	0.0000
OCF_t-1 × IFRS	0.0257	0.5701	0.1191*	0.0027	0.1746*	0.0000
DA_t-1	-0.0223**	0.0152	-0.0489*	0.0000
DA_t-1 × IFRS	0.0948*	0.0005	0.1489*	0.0000
NDA_t-1	-0.0769*	0.0000	-0.0912*	0.0000
NDA_t-1 × IFRS	0.1530*	0.0000	0.1063*	0.0003
ACC_t-1					-0.0910*	0.0065
ACC_t-1 × IFRS					-0.0072	0.7797
Adjusted R²	0.559589		0.551132		0.513395
F test (p-value)	0.000000		0.000000		0.000000
Schwarz	-9,518.841		-9,011.496		-10,987.90
Akaike	-9,560.365		-9,052.707		-11,018.39
Observations (n)	2,785		2,663		3,287

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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[1] Correspondence address: Terence Machado Boina. Universidade Federal do Rio de Janeiro, Faculdade de Administração e Ciências Contábeis, Programa de Pós-Graduação em Ciências Contábeis. Avenida Pasteur, 250 - CEP 22290-902 Urca - Rio de Janeiro - RJ - Brazil