This document summarizes a research paper that investigates whether stronger investor protections in Latin American countries are associated with less earnings management by publicly traded companies. The paper uses statistical models to estimate discretionary accruals and examines their relationship with country-level measures of investor protection. It finds evidence that higher investor protections are linked to lower earnings management. The paper contributes to understanding how institutional environments influence financial reporting practices across emerging markets.

1. Earnings Management and the Institutional Environment: A Study in Latin America
Daniel Monfort de Alencastro Guimarães
Escola de Economia de São Paulo (EESP)
Fundação Getúlio Vargas
Hsia Hua Sheng (夏华声)
Professor of Finance, Department of Accounting,
Finance and Control
Vice-coordinator of the International Business
Research Forum (IBRF)
Fundação Getulio Vargas FGV - EAESP and
EESP
ABSTRACT
This paper investigates whether the institutional environment, related to the level of
investor protection in Latin American countries, contributes to reducing earnings management
by firms. We use four models to detect earnings management (the Jones Model, Modified Jones
Model, Modified Jones Model with ROA and the Kang & Sivaramakrishna Model). Our
sample comprises 313 publicly held companies listed in the stock exchanges in Argentina,
Brazil, Chile, Colombia, Mexico and Peru, during the period from 2006 to 2010, a total of
9,986 statistics company-year. The discretionary accruals were estimated using a two-stage
regression, firstly with panel data models and then with the model residuals as the dependent
variable and the level of investor protection as the independent variable. The score for each
country, published in the Latin American Venture Capital Association (LAVCA) Scorecard, is
used as a proxy for the level of investor protection. There is evidence in line with the theory
that a better institutional environment contributes to reducing not only earnings management,
but also the variability in earnings management. These findings reveal that investor protection
is an important factor in the development of countries in Latin America. Countries with
systems that provide incentives for private investment, with better tax treatment, creditor
protection, corporate governance and a standardized accounting system, present companies
with a lower level of earnings management.
Keywords: Earnings management, Investor protection, Institutional environment, Latin America,
Institutional investors, corporate governance
JEL classification: G24, G30, K20, M41

2. 1. Introduction
The financial statements prepared by a firm are its means of communication to the
market and a way of reducing asymmetrical information between insiders (executives and
controllers) and outsiders (minority shareholders, creditors, government and suppliers).
Accordingly, managers are expected to use the discretionary accruals permitted by accounting
rules to reflect the company`s economic environment more fairly. Using as a basis, corporate
finance theories addressing corporate governance, agency and economic theories and self-
regulatory markets, this study seeks to determine the importance of investor protection in
earnings management. The first important question is whether companies practice earnings
management. Authors such as Jones (1991), Dechow et al (1995), and Healy et al (1998),
sought to comprehend, as well as to detect earnings management. As a result of these studies
econometric models were created and used to study other aspects of the earnings management
theory.
In the existing literature, the most addressed topic is how to detect earnings
management. Other studies analyze empirically which incentives encourage managers to
engage in earnings management, including the influence of external factors, such as the sector
in which the firm operates as well as the institutional environment. Leuz et al (2003), who
studied the relationship between earnings management and investor protection across 31
countries, concluded that there is evidence that earnings management is influenced by the level
of investor protection. According to La Porta et al (2000), investor protection is an important
factor for understanding corporate finance standards in different countries and to protect
minority shareholders and creditors from expropriation by controlling shareholders and
executives. Investor protection aids the development of capital markets, the reduction of private
control benefits (corporate ownership structure) and the allocation of investments, which are
important factors for the development of Latin American countries.
Contrary to the US, whose capital market is fully developed and where there is a debt
market and companies with dispersed capital, in which the majority shareholder holds less than
51% of capital and which are managed by professionals rather than by the partners, the capital
markets in Latin America are still maturing with a private debt market which has a strong
concentration of banks and government entities and concentrated share ownership. Although
these countries are often regarded as alike, since they have similar macro characteristics, i.e.
they are emerging countries with the same democratic systems, the same legal system origins
(Civil Law) and their corporate executives have the same incentives, nevertheless their
investors are treated differently. The countries also differ in the maturity of their capital
markets, capital concentration, legal enforcement and tax incentives for investors. These
differences produce different earnings management levels in each country and as a result the
standardization of accounting practices (migration to International Financial Reporting
Standards - IFRS) alone will not be sufficient to resolve these differences. Further, not all the
countries comprising this study are converging to IFRS. Only Argentina, with compulsory
adoption as from 2011, Brazil, with compulsory adoption in 2010 and Mexico, with
compulsory adoption as from 2012, have pledged to adopt IFRS for listed companies.
This article investigates the influence of the institutional environment on earnings
management, based on a sample of Latin American countries which includes Argentina, Brazil,
Chile, Colombia, Mexico and Peru for 2006 to 2010. We will contribute to the study of the
theory of earnings management by bringing the research analyzing Brazilian companies up to
date, comparing the results to those of other Latam countries and determining whether the
investor protection environment reduces earnings management by firms, decreasing private

3. control benefits and improving agency costs. This study also makes a valuable contribution by
studying earnings management specifically in Latin America, a market which previously
because of its prolonged period of inflation and largely inexpressive capital market, had an
insufficient amount of data available for analysis.
2. Literature Review
Prior to commenting on the models and methods used to detect earnings management,
this paper will address the incentives for executives to engage in some form of earnings
management. The study presented by Dichev et al (1997) on US companies suggests that 8%
to 12% of firms that would have reported a slight downturn in earnings use discretionary
accruals to present an increase in income. And 30% to 44% of firms that would have presented
a slight loss use discretionary freedom to report positive earnings. To explain the results of their
study, Dichev et al present two theories. The first is that managers avoid reporting a downturn
in earnings and income loss as a means of decreasing the cost of the firm`s transactions with its
shareholders and the second is based on the prospect theory.
According to Healy et al (1998), earnings management occurs when executives use
judgment in financial reporting and in structuring transactions to alter financial reports either to
inform incorrectly the company`s true economic performance to outside stakeholders, or to
adjust to contractual clauses that depend on accounting indices, and this judgment may be of an
economic nature, in predicting future events, liabilities such as employee benefits and the
allowance for doubtful accounts, or of an accounting nature, such as depreciation, cost of
inventories and working capital requirements.
According to Yaping (2005), earnings management has five different characteristics:
(1) earnings are manipulated by managers not by accountants; (2) earnings are manipulated
knowingly and intentionally; (3) the measures taken for earnings management include both
operational and accounting decisions; (4) both accounting numbers and operating data are
manipulated; (5) the level of earnings management is that intended by the mangers. Healy et al
(1998) highlighted the following as incentives for the practice of earnings management: (i)
capital market expectations and valuation; (ii) contracts that have clauses based on accounting
indices; (iii) anti-trust government regulation.
According to McNichols et al (2008), earnings management also leads companies to
make suboptimal investment decisions, bringing further consequences to investors, managers
and regulators.
Jones (1991) studied whether import companies use earnings management during
periods in which they are under investigation by the regulatory agency to avoid sanctions. In
his study, Jones describes a new approach for detecting earnings management and addresses a
situation where there are no incentives for external stakeholders to perfectly monitor the
internal stakeholders.
The Jones model has been studied in its original and modified forms. The Healy
Model, the DeAngelo Model and the Industry Model were subject to comparative analysis by
Dechow et al (1995), which concluded that the Modified Jones Model provides the best tests
for earnings management. Martinez (2008) analyzed the Healy, Jones, Modified Jones and KS
Models and their application in the case of Brazil and concluded that the KS Model is that
which presents the best results and the most robust statistics for the country. The difference
between the Jones, Modified Jones and Modified Jones with ROA models, is that the second
includes the difference between Net Revenue and Accounts Receivable, assuming that the
changes in Accounts Receivable represent earnings management, since its is easier to manage

4. installment sales than cash sales, and the third includes the ROA variable as a means of
adjusting company performance. The difference between the Jones and KS Model is that the
former operates with the variation in the profit and loss accounts between two periods, which
could pose a problem for countries which present bouts of high inflation, while the latter
operates with balance sheet accounts in a specific accounting year and accordingly, does not
compare amounts in different periods and uses instrumental variables as a means of correcting
problems with variable correlations.
The following articles, found in related literature, use the models selected by this
paper to detect earnings.
Tabel 1
The following table presents a number of articles found in literature and which use the same models as those used in this paper to detect
earnings management.
Model Author Topic
Jones Model and KS Model Baber and Kang (2001) Stock Price Reactions to On-target Earnings Announcements
Jones Model and Modified Jones
Model
Prevost et al (2008) Earnings Management and the Cost of Debt
Modified Jones Model Chen et al (2008) On the Use of Accounting vs. Real Earnings Management to Meet
Earnings Expectations – A Market Analysis
Modified Jones and Modified Jones
with ROA
Gavious (2007) Market Reaction to Earnings Management: The Incremental
Contribution of Analysts
Various studies explain the relationship between the practice of earnings management
and the institutional environment. The study by Leuz et al (2003) compared the differences in
earnings management and investor protection across 31 countries, excluding Latin America,
and found that the investor protection environment exerts an influence on earnings
management. Leuz et al (2003) estimated the average use of earnings management for each
country, based on four commonly used models in literature and then carried out a second
regression using as independent variables the level of investor protection, legal enforcement, as
defined by La Porta et al, and the private benefits of control, as defined by Dyck et al (2002).
Chung et al (2001) revealed that the presence of institutional investors with a significant
ownership interest in companies in the US and with the resources and incentives to monitor and
influence the decisions of executives, effectively contributed to reducing earnings management.
The study estimated the level earnings management based on the Jones Model and then used a
second regression using as the main independent variable a dummy which has a value of one, if
the percentage ownership interest held by the institutional investors in the company, is greater
than the panel data mean for the year under analysis.
In Brazil, the article written by Gioielli and Carvalho (2008) revealed that companies
that had carried out initial public offerings (IPO) and which had institutional investors prior to
going public, in this case private equity funds, contributed to a lower level of earnings
management. Tukamoto et al also studied, in the case of Brazilian companies, whether the
issuance of securities in other stock exchanges, more specifically ADRs in the New York Stock
Exchange (NYSE), contributed to reducing earnings management, considering the additional
information which companies are obliged to disclose in compliance with SEC rules. The study
addressed whether earnings management was practiced to a lesser extent in companies whose
shares were listed in a more developed market, providing greater protection to investors, than in
companies whose shares were listed in BM&FBovespa only, however, the study presented no
evidence to confirm this.

5. 3. Methodology
The theory of Earnings Management proposes that the practice occurs as a result of the
freedom that managers have to establish the criteria used to determine the amounts of certain
balance sheet and statement of income accounts. Since these two statements are prepared
differently, the economic result differs from the cash result. The accounts which equalize the
company’s economic earnings to its cash earnings will be called total accruals (TA) and those
which depend on the decision of executives will be called discretionary accruals (DA) and
those which do not depend on management decisions will be called non-discretionary accruals
(NDA). By definition: TA = DA-NDA. In general, the different models define total accruals as
being the variation in working capital between two periods.
This study seeks to compare the level of earnings management in different Latin
American countries and to reveal whether the institutional environment of these countries
contributes to a reduction in earnings management. We estimate the existence of earnings
management based on four predictive models and seek the best method of molding the
institutional environment based on the treatment available in each country for protecting
investors. The protection given to contracts as well as to economic continuity and stability and
the incentives for entrepreneurship and capital market development were deemed decisive
factors in inhibiting earnings management by executives and/or controlling shareholders.
This paper uses four models for detecting earnings management, i.e. the Jones Model,
with two modifications (the Modified Jones Model and the Modified Jones Model with ROA)
and the Kang & Sivaramakrishnan Model1
. These models, except for the KS model, were
studied in the article “Detecting Earnings Management” by Dechow et al (1995) which sought
to compare the existing models used to detect earnings management and concluded that the
Jones Model and its modifications are those which present the best results. The KS model
estimates the adjustment portion based on the percentage of total assets of the balance sheet
account for the period, and is more appropriate for countries which present a higher inflation
level. Earnings managed through a company`s balance sheet accounts is possible as a result of
the freedom given to managers to choose certain accounting methods and determination criteria
for the purpose of providing the means for best reflecting a company`s current economic
position. For example, the Allowance for Doubtful Accounts (PDD), which based on a
definition by the regulatory agencies, permits the pre or post payment of amounts as defined by
the mangers and their modification during a specific period. In general, accrual accounts which
will not affect the company`s cash are used.
Subsequent to the application of the models to detect earnings management, a
regression will be used to identify whether the investor protection environment contributes to
reducing earnings management. The model uses as the dependent variable the average
discretionary accruals of the models calculated for each country-year and, as the independent
variable, the overall score published by LAVCA for each country-year. The same model will
also be used with a standard deviation as the dependent variable to explain the decrease in
earnings management.
Where:
= Average discretionary accruals of country i for period t.
= Overall score published by LAVCA for country i for period t.
1
The Kang and Sivaramakrishnan model will be referred to hereinafter as the KS Model for easier reading.

6. Considering the lack of available data on Latam countries, only six countries were
included in the study and panel data was used for the above model. The average discretionary
accruals for each country were extracted for 2006 to 2010¸ comprising a total of 30
observations.
Since it was not practicable to establish what qualifies as merely a change in criteria
and what qualifies as earnings management, it is difficult to conclude whether the company is
effectively managing its earnings.
4. Sample: selection and descriptive statistics
To analyze the existence of earnings management in Latam companies, publicly traded
companies will be used as a proxy. Data was gathered from the balance sheet and statement of
profit and loss using Economática® software. The database comprises the following Latam
countries in alphabetical order: Argentina, Brazil, Chile, Colombia, Mexico and Peru. To form
a larger sample, quarterly information of the listed companies in each country was used for the
period from December 1999 to March 2010, a total of 42 quarters. Each company could present
a maximum of 42 quarters and a minimum of four quarters. Companies in the financial and real
estate sectors were excluded since their balance sheet preparation method differs from the
others and could influence the results. Moreover, holding companies were also excluded since
they have no operating activities. Subsequent to applying this filter, the sample was comprised
as follows: 923 companies-years for Argentina, 3,853 companies-years for Brazil, 1,931
companies-years for Chile, 736 companies-years for Colombia, 1,973 companies-years for
Mexico and 570 companies-years for Peru. Panel A of Table 2 presents the descriptive statistics
for the companies of each country comprising the study. The importance of Brazil and Chile is
revealed by their greater average total assets, as well as Chile which appears in third place.
Table 2 – Panel A
The information on publicly traded companies available in the Economática® software database was used to prepare the sample of companies
in each country. A filter was applied as presented in the following table:

7. Panel B
The table below presents a description of the Economática® software accounts used to extract the amounts of each company necessary for the
models.
Variable Description Economatica Compusat
REV Net Sales Revenue Receita liquida operac 12
AR Receivables, excluding tax refunds Clientes CP 2-161
INV Inventory Estoques 3
OCA Other current assets than cash, receivables, and invetory Creditos Diversos 4-1-2-3
Outros Ativos CP
CL Current liabilities excluding taxes and current maturities of long-term debt Finaciamento CP 5-71-44
Outros Passivos CP
EXP Operating Expenses (cost of goods sold, selling and administrative expenses
before depreciation)
Despesas operac proprias dez/13
DEP Depreciation and amortization Deprec, amortize e exaust 14
Deprec, amort e exaust
GPPE Gross Property plant and equipement Permanente 7
Panel C
Data extracted from Economática® software on the balance sheet and statement of profit and loss accounts of publicly traded companies in the
following countries: Argentina, Brazil, Chile, Colombia, Mexico and Peru which presented at least 4 consecutive quarters of data for the period
from 12/1999 to 03/2010. Companies in the financial and real estate sectors, as well as holding companies were excluded.
Country Firms Firms-year
Mean Total Assets
(USD)
Mean Net Revenues
– Quarter (USD)
Mean Net Earnings
– Quarter (USD)
Mean ROA
Argentina 23 923 1.076.432 175.534 19.677 0,93%
Brazil 137 3.853 5.216.883 785.946 82.555 2,45%
Chile 54 1.931 2.404.344 338.540 22.895 2,71%
Colombia 21 736 1.249.853 165.268 24.735 3,07%
Mexico 52 1.973 3.849.290 725.332 63.837 3,43%
Peru 26 570 819.477 123.184 18.287 5,10%
In analyzing the institutional environment, the treatment given to local and foreign investors in
each country is observed. Whether there are incentives for corporate investment, favorable
legal and tax systems, the presence of local institutional investors (pension funds) and also
whether the country provides incentives for entrepreneurship and protects innovation. As a
proxy for the institutional environment and how each country adopts its investor protection
mechanisms, the score presented in the LAVCA scorecard is used. LAVCA is an association
founded in 2002 with support from the Multilateral Investment Fund (MIF) of the Inter-
American Development Bank, from the National Venture Capital Association (NVCA) and the
Development Capital Networks (DCN), for the purpose of stimulating regional economic
growth based on the increase in venture capital and private equity investments through research
programs, networking efforts, investor education, the promotion of best investment practices
and the defense of public policy. The countries were organized based on their score for items
which consider the legal, institutional, tax and business environments, as well as the percentage
of private equity and venture capital investments in relation to the Gross Domestic Product
(GDP). This research also takes into account emerging countries, other than those comprising
the study. Table 3 presents the overall score of each country, comprising the study, from 2006
to 2010. The Doing Business index, extracted from the study carried out by the World Bank,
was also used as a proxy for investor protection however, as a result of the low variability of
the index during the period under analysis the result presented was not significant.

8. Table 3
LAVCA Scorecard 2010 results. Scores range from 0 to 100, with 100 as the best/most favorable environment for investment. To prepare the
overall score, LAVCA analyzes the following criteria with a score from 0 to 4: Laws on VC/PE fund formation and operation; Tax treatment
of VC/PE funds & investments; Protection of minority shareholders rights; Restrictions on institutional investors (pension funds, insurance
firms) investing in VC/PE; Protection of intellectual property rights; Bankruptcy procedures/creditors’ rights/partner liability in cases of an
invested company bankruptcy; Capital Markets development and feasibility of exits (i.e., local IPOs); Registration/reserve requirements on
inward investments; Corporate governance requirements; Strength of the judicial system; Perceived corruption; Quality of local accounting
industry/use of international standards.
As well as the countries comprising this study, the following countries are also presented in the report with their corresponding scores for
2010 in brackets: UK (93), Israel (81), Spain (76), Taiwan (61), Uruguay (57), Trinidad & Tobago (56), Costa Rica (54), Panama (49), El
Salvador (43) and Dominican Republic (38).
Year Argentina Brazil Chile Colombia Mexico Peru
2006 41.2 58.8 76.5 42.6 54.4 47.1
2007 43 65 74 47 60 41
2008 50 75 78 53 58 49
2009 46 75 76 57 58 50
2010 43 75 76 60 63 51
5. Hypotheses
Based on the above and the research carried out by La Porta et al (2000) and Leuz et
al (2003) three hypotheses were constructed:
H1: a better level of investor protection decreases earnings management in Latin
American countries.
H2: a better level of investor protection decreases the standard deviation of earnings
management in Latin American countries.
The second hypothesis is formulated considering that, since the detection of earnings
management could be difficult to ascertain, the standard deviation is the method used to
measure the quality of the total accrual. Since when there are clearer rules, an active legal
system and penalization for non-compliance with rules, the investor has the necessary tools to
resolve potential conflicts of interest in addition to monitoring executive-team practices. As
well as analyzing the average discretionary accruals, the standard deviation will also be
analyzed and it is expected that the level of investor protection will contribute to decreasing the
variability in earnings management.
Additionally, this study seeks to verify whether, considering the limits established by
accounting rules, the discretionary power of the managers is also limited and accordingly, in
the long term, the discretionary accrual will be annulled. The third hypothesis is written as
follows:
H3: considering that the discretionary power of the managers is limited and will be
reversed in n subsequent periods, the average DAC will be greater for a 5-year period as
compared to a 10-year period.
6. Results
In the first part of the analysis, four models were used (the Jones Model, Modified
Jones Model, Modified Jones Model with ROA and the KS Model) to predict earnings
management in the countries comprising the study from 2000 to 2010. The estimated result,
given as the average percentage in relation to the company’s total assets, is not explained by the
models. The results are presented in Table 4, where it is noted that the level of earnings
management is greater in Colombia and lower in Mexico and Peru. It should be stressed that
the incentives for earnings management may lead managers to increase (positive sign) or
decrease (negative sign) earnings, and the absolute value of the results is under analysis. Brazil,

9. Colombia, Mexico and Peru present a negative sign, evidencing the practice of earnings
management to decrease income, while Argentina and Chile present a positive sign, improving
income. Since each model uses different criteria to estimate earnings management, the results
are not expected to be identical however the expected sign of the variable should be the same,
indicating the direction of the earnings management practiced by the manager. This result was
found in all countries-years, except for: Argentina in 2009; Brazil in 2009; Chile in 2008 and
2009, Colombia in 2009, Mexico in 2006 and 2009 and Peru in 2006 and 2007. This paper
contributes to related literature by analyzing, based on data for longer periods of time, the
occurrence of earnings management in Latin American countries, considering that the existing
database was insufficient for conducting analyses, mainly because these countries had
experienced prolonged periods of inflation and their economies were not yet fully developed.
Table 4
In this table, we present the average amount of the discretionary accruals (DAC), i.e. the average amount of the regression residuals using the
Jones Model, Modified Jones Model, Modified Jones Model with ROA and KS Model¸ as a proxy for the practice of earnings management.
This amount should be interpreted as a percentage, in relation to the company’s total assets, of the level of earnings management, which is
positive for practices which seek to improve earnings and negative for practices which seek to decrease earnings.
Period
Country Model 2000Q1-
2010Q1
2000Q1 -
2005Q4
2006Q1 -
2009Q4
2006 2007 2008 2009
Argentina
Jones Model 0.22% 0.07% 0.36% 0.68% 0.42% 0.55% -0.23%
Modified Jones 0.34% 0.19% 0.48% 0.85% 0.63% 0.59% -0.15%
Modified Jones with ROA n/a n/a n/a n/a n/a n/a n/a
KS Model 0.00% -1.181% 1.428% 1.190% 1.613% 1.798% 1.101%
Model Averages 0.188% -0.307% 0.755% 0.909% 0.890% 0.979% 0.241%
Brazil
Jones Model -1.42% -4.54% 1.19% 4.98% 6.25% -4.41% -0.75%
Modified Jones 0.95% -2.15% 3.31% 7.32% 7.00% -1.68% 1.93%
Modified Jones with ROA -1.58% -4.67% 0.79% 5.15% 4.69% -4.37% -0.84%
KS Model 0.00% -0.121% 0.060% 1.882% -0.141% -0.221% -0.779%
Model Averages -0.511% -2.869% 1.336% 4.833% 4.448% -2.668% -0.108%
Chile
Jones Model 0.12% 0.14% 0.36% 1.10% 0.31% 0.11% -0.02%
Modified Jones 0.17% 0.18% 0.40% 1.14% 0.38% 0.12% 0.02%
Modified Jones with ROA 0.05% 0.11% 0.20% 0.93% 0.06% -0.02% -0.12%
KS Model 0.00% -0.411% 0.624% 0.563% 0.587% -0.001% 1.416%
Model Averages 0.085% 0.005% 0.397% 0.936% 0.332% 0.054% 0.321%
Colombia
Jones Model -1.16% -1.74% -1.06% -0.77% -2.69% -0.14% -0.74%
Modified Jones -1.20% -2.33% -1.21% -1.08% -3.02% -0.43% -0.43%
Modified Jones with ROA -0.84% -2.16% -0.59% -0.21% -2.35% -0.15% 0.26%
KS Model -1.01% -0.04% -2.22% -3.13% -4.89% 0.66% -2.09%
Model Averages -1.052% -1.568% -1.268% -1.298% -3.240% -0.015% -0.751%
Mexico
Jones Model -0.01% -0.14% 0.10% 0.13% 0.73% -0.50% 0.06%
Modified Jones -0.03% -0.15% 0.10% 0.15% 0.79% -0.52% 0.00%
Modified Jones with ROA -0.20% -0.27% -0.14% -0.14% 0.50% -0.74% -0.15%
KS Model 0.00% -0.358% 0.386% 1.031% 0.953% -0.265% -0.115%
Model Averages -0.058% -0.226% 0.113% 0.292% 0.744% -0.506% -0.051%
Peru
Jones Model -0.06% -0.26% 0.27% 0.50% -0.06% 1.30% -0.66%
Modified Jones -0.04% -0.25% 0.30% 0.53% -0.02% 1.28% -0.56%
Modified Jones with ROA -0.13% -0.29% 0.14% 0.25% -0.20% 1.14% -0.62%
KS Model 0.00% -0.246% 0.226% -0.179% 0.796% 1.030% -0.639%
Model Averages -0.058% -0.260% 0.235% 0.276% 0.131% 1.188% -0.619%

10. Table 5
In this table, we present the standard deviation of the discretionary accruals (DAC), i.e. the standard deviation of the regression residuals using
the Jones Model, Modified Jones Model, Modified Jones Model with ROA and KS Model¸ as a proxy for the quality of the accruals.
Period
Country Model 2000Q1-
2010Q1
2000Q1 -
2005Q4
2006Q1 -
2009Q4
2006 2007 2008 2009
Argentina
Jones Model 7,50% 8,72% 5,61% 6,91% 4,96% 5,72% 4,65%
Modified Jones 7,56% 8,75% 5,74% 6,84% 5,14% 5,88% 4,97%
Modified Jones with ROA n/a n/a n/a n/a n/a n/a n/a
KS Model 11,23% 13,148% 7,917% 9,224% 7,619% 8,263% 6,479%
Model Average 8,767% 10,205% 6,425% 7,658% 5,907% 6,619% 5,366%
Brazil
Jones Model 50,06% 33,45% 60,40% 99,00% 76,93% 23,21% 28,81%
Modified Jones 49,54% 32,33% 61,56% 99,55% 75,20% 23,26% 29,36%
Modified Jones with ROA 49,68% 32,71% 61,60% 99,40% 75,46% 23,18% 29,39%
KS Model 10,84% 9,948% 11,653% 17,409% 11,066% 8,938% 8,981%
Model Average 40,031% 27,108% 48,802% 78,842% 59,664% 19,650% 24,133%
Chile
Jones Model 6,66% 6,37% 6,86% 7,04% 5,75% 6,24% 8,13%
Modified Jones 6,65% 6,35% 6,88% 7,02% 5,78% 6,31% 8,14%
Modified Jones with ROA 6,61% 6,30% 6,85% 6,87% 5,74% 6,14% 8,29%
KS Model 9,08% 7,926% 8,313% 7,028% 8,151% 8,816% 9,107%
Model Average 7,250% 6,736% 7,228% 6,991% 6,355% 6,878% 8,419%
Colombia
Jones Model 39,07% 5,26% 13,94% 4,72% 19,46% 5,26% 18,30%
Modified Jones 40,35% 5,76% 14,07% 4,86% 19,50% 5,32% 18,57%
Modified Jones with ROA 40,33% 6,11% 14,19% 5,03% 19,67% 5,36% 18,69%
KS Model 17,11% 10,83% 22,54% 10,16% 31,44% 11,36% 28,25%
Model Average 34,217% 6,992% 16,187% 6,192% 22,515% 6,826% 20,954%
México
Jones Model 5,27% 4,82% 5,91% 4,41% 6,69% 6,96% 5,08%
Modified Jones 5,24% 4,80% 5,87% 4,29% 6,54% 7,07% 5,03%
Modified Jones with ROA 5,21% 4,81% 5,80% 4,28% 6,51% 6,90% 5,02%
KS Model 8,09% 7,846% 8,439% 7,083% 9,695% 9,217% 7,393%
Model Average 5,954% 5,567% 6,504% 5,015% 7,360% 7,540% 5,632%
Peru
Jones Model 6,87% 7,50% 6,11% 6,17% 4,96% 7,54% 5,35%
Modified Jones 6,83% 7,37% 6,22% 6,18% 5,11% 7,62% 5,60%
Modified Jones with ROA 6,76% 7,19% 6,33% 6,23% 5,17% 7,79% 5,75%
KS Model 9,88% 8,738% 11,304% 10,450% 8,486% 14,086% 11,195%
Model Average 7,587% 7,700% 7,491% 7,257% 5,931% 9,260% 6,977%
It can be observed, in Table 6, that the sign presented by the LAVCA variable, when the
average discretionary accrual for each country-year is used as the dependent variable, is
negative for the model, in line with expectations and the theory, however, it presents a
coefficient very close to zero, suggesting that while the variable is important, there are other
factors, which despite investor control, affect earnings management. A possible explanation is
that, in countries with a high tax burden and a high concentration of share capital, incentives
are greater for earnings management directed to decreasing income and consequently the
amount of tax payable. It is assumed that the investor protection level is an exogenous
variable, since on the contrary there would be a risk of a biased result. The model R² was
between 0.31 and 0.42 for the four models, evidencing that the variable is representative for
explaining the model and in line with the findings of Leuz et al (2003), where the model
presents an R² value of 0.38 and a negative sign for the investor protection level variable. A
second matter for analysis is the quality of the accruals, measured by the standard deviation of
the regression residuals, presented in Table 4. Analyzing as the dependent variable the
standard deviation determined by each model for each country-year, the results present an R²
of 0.78 and as the independent variable LAVCA presents a negative sign and a value of -.02,

11. confirming the second hypothesis and demonstrating that investor protection is important for
controlling the quality of the discretionary accruals used by managers.
Table 6
The table below presents the results of the cross-section panel regression model for testing whether the level of investor protection influences
earnings management. The average level of earnings management of country i during period t, was used as the dependent variable, calculated
based on the Jones Model, the Modified Jones Model, the Modified Jones Model with ROA and the KS Model, with the results presented in
Table 3 and the overall score published annually by LAVCA for 2006 to 2009 was used as the independent variable, with the results presented
in Table 2. We corrected the model for problems with correlated variables using cross-section fixed effects, subsequent to applying the
Hausman test. (Table 6)
Dependent
Variable
Model Constant LAVCA R² Observations
DAC - Average
Jones 0.128132
(2.426)**
-0.002191
(-2.384)**
0.3577 24
Modified Jones 0.113091
(2.387)**
-0.001865
(-2.263)**
0.42 24
Modified Jones – ROA 0.117146
(2.402)**
-0.002022
(-2.38)
0.31 24
KS Model 0.006
(0.182)
-3.28E-25
(-0.057)
0.23 24
Standard
Deviation
Jones 1.2386
(3.50)***
-0.0189
(-3.072)***
0.78 24
Modified Jones 1.230
(3,49)***
-0,0187
(-3,0629)***
0.78 24
Modified Jones – ROA 1.420
(-0,02)***
-0.0208
(-3.016)***
0.78 20
KS Model 0.102
(0.723)
0.000
(0.069)
0.49 24
* Significance level of 10%; ** Significance level of 5%; *** Significance level of 1%
T-statistics in brackets
Table 7
Hausman test to compare the use of fixed or random effects for panel data. The null hypothesis means that the model coefficients and the
random effects are orthogonal. The rejection of the null hypothesis indicates that the best choice is the fixed effects model.
Correlated Random Effects - Hausman Test
Equation: Untitled
Test cross-section random effects
Test Summary
Chi-Sq.
Statistic Chi-Sq. d.f. Prob.
Cross-section random 7.713276 1 0.0055
** WARNING: estimated cross-section random effects variance is zero.
Cross-section random effects test comparisons:
Variable Fixed Random Var(Diff.) Prob.
LAVCA -0.001901 -0.000059 0.000000 0.0055
The main differences in countries with a better institutional environment for
investors are those related to the protection of minority shareholders, the restrictions imposed
on institutional investors (pension funds), strong capital market development and sound
corporate governance and with less importance the adoption of international financial reporting
standards (IFRS). These differences enable a country from the Latam block to stand out from
the rest and attract a greater investment flow, providing the capital required to boost its
economy.
Since accounting rules establish limits, it is expected that directional earnings
management will be null in the long term and accordingly the study presents the averages
determined for two periods: one comprising the first five years (1st
Quarter of 2000 to 4th
Quarter of 2005) and the other comprising the last four years (1st
Quarter 2006 to 4th
Quarter

12. 2009). It can be noted that all of the countries, except Chile and Colombia, present different
signs in each of the two periods. Table 2 aids the test of the third hypothesis. Earnings
management may be used by executives to increase or decrease their firm’s income. It can be
presumed that in countries with a high tax burden such as Brazil, and with a high concentration
of company capital in the hands of the controlling shareholders, earnings management is
directed to decreasing income and as a result reducing the amount of tax payable. This is
contrary to manager incentives and investor objectives but in line with majority shareholder
interests. Moreover, prior studies which analyzed the relationship between earnings
management and the cross-listing of company shares in a country which is not that of its
headquarters, did not present conclusive results regarding a decrease in earnings management.
And further, the number of companies in Latin American with cross-listings is too small to
enable a comparison between Argentina, Brazil, Chile, Colombia, Mexico and Peru.
7. Final Considerations
This paper sought to evidence that a better institutional environment is related to less
engagement in earnings management, complementing the literature and articles already
published by Leuz et Al (2003), addressing the influence of investor protection in 31 countries,
by Gioielli and Carvalho (2008), on the influence of private equity managers on companies
that have gone public in Brazil and by Chung et al (2002) who studied the influence exerted by
institutional investors, all of which concluded that the investor contributes to reducing earnings
management and increasing control over executives.
The results are in line with the hypotheses formulated and the theory revealing that
earnings management is negatively associated with the level of investor protection in Latin
American countries and present a high rate of explanation for the discretionary accrual. It is
important to stress that the results for the countries in Latin America reveal that the level of
investor protection is more influential in decreasing earnings management variability than
decreasing the actual level of earnings management, evidencing that there are even greater
incentives for maintaining a particular level of earnings management, such as for example, the
decrease in the tax payable on company income.
There is evidence that the practice of directional earnings management is not
sustainable in the long term, because of the limits established by accounting rules, since they
require double entry accounting and the accruals defined by the managers are limited to the
total amount of the book balance. When we divide the period under analysis into two, the signs
presented by the discretionary accrual for each period are different, increasing or decreasing
income, confirming that, in the long term, managed earnings are unsustainable.
Considering that it was not possible to obtain data from various periods for the
countries under analysis, cross-sectional panel data techniques were used for applying the
models used to detect earnings management. The study is limited by the lack of available data
on these countries, by the non-representative percentage of publicly traded companies in
relation to the total market and the lack of historical investor protection indexes which would
have permitted observation over a longer period of time.

13. 8. References
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Implications for Earnings Management. Working Paper – September 2001
BURGSTAHLER, D., Dichev, I., - Earnings management to avoid earnings decreases and
losses – Journal of Accounting & Economics – Vol. 24, p 99-126 – 1997
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CHUNG, R., Firth, M., Kim, J., - Institutional monitoring and opportunistic earnings
management. Journal of Corporate Finance 8 – p. 29-48 (2002)
DECHOW, P., Sloan, R., Sweeney, A. – Detecting Earnings Management. The Accounting
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GIOIELLI, S., Carvalho, A. – The Dynamics of Earnings Management in IPOs and the Role of
Venture Capital – Working Paper – April 2008.
HEALY, P., Wahlen, J., - A review of the earnings management literature and its implications
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JONES, J., - Earnings Management During Import Relief Investigations. Journal of Accounting
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KANG, S., Sivaramakrishnan, K., - Issues in Testing Earnings Management and an
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367 (Autumn, 1995)
KOTHARI, S.P., Leone, A., Wasley, C. – Performance matched discretionary accrual measures
– Journal of Accounting and Economics 39, p 163-197, 2005
LA PORTA, R., Lopez-de-Silanes, F., Shleifer, A., Vishny, R., - Investor protection and
corporate governance – Journal of Financial Economics, 58, pp 3-27 (2000)
LAVCA Report - Latin American Venture Capital Association Scorecard 2006, 2007, 2008,
2009 and 2010
LEUZ, C., Nanda, D., Wysocki, P.,- Earnings management and investor protection: an
international comparison. Journal of Financial Economics 69 – p. 505-527 – (2003)
McNICHOLS, M., Stubben, S., - Does Earnings Management Affect Firms’ Investment
Decisions? – The Accounting Review Vol. 83, No. 6, p 1571-1603 – 2008
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approaches. Journal of Accounting and Public Policy 19 – p.347 -376 - (2000)
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ADR – Working paper

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– Vol.1. No. 3, pp 32-38 (2005)
9. Appendix:
A- Earnings Management Models
The Jones Model
When:
And:
Then:
And:
Where:
= Total accruals
= Non-discretionary accruals
= Discretionary accruals
= net revenue for year t less net revenue for year t-1 divided by total assets for year t-1
= permanent assets for year t divided by total assets for year t-1
= total assets for year t-1
For the Modified Jones model, the Accounts Receivable variable was included to eliminate the
tendency of the Jones Model to measure discretionary accruals with error, when the
discretionary adjustment is made in Revenue, as described by DECHOW et al., (1995), and the
model was re-written as follows:
Where:
= net accounts receivable for year t less net accounts receivable for year t-1 divided by total
assets for year t-1.
For the Modified Jones with ROA model, the return on assets variable was included, as per KOTHARI
et al. (2005), and the model is described by the following equation:
Where:

15. = return on assets in t.
Although the Jones Model is frequently used to estimate engagement in earnings management, an
omitted variables error could occur if other variables which could be manipulated are not included, for
example, variations in expense and simultaneousness, considering that the dependent variable and the
independent variables are determined in conjunction and manipulation is restricted by accounting
practices.
The Kang & Silvaramakrishnan model uses the difference in the level of the balance sheet accounts
rather than the variation between two periods, since it presents a better result for countries with high
inflation levels. Further, the KS model uses instrumental variables to eliminate the problem of
correlation between variables.
KS Model
Where:
= Total accruals.
= Accounts receivable of company i for the period t-1.
= Inventories for company i for the period t-1.
= Other short-term assets, excluding cash, accounts receivable and inventories, of company i for
the period t-1.
= Short-term debts, excluding taxes and long-term loan installments recorded in Current liabilities
of company i for the period t-1.
= Depreciation and amortization of company i for the period t-1.
= Net revenue of company i for period t.
= Expenses and Operating Cost (CMV, DGA) of company i for period t.
= Permanent assets of company i for period t.
= net revenue for year t less net revenue for year t-1 divided by total assets for year t-1
= permanent assets for year t divided by total assets for year t-1.
= total assets for year t-1.