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

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

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

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.

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.

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:

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.

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,

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%

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,

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 4

th

Quarter of 2005) and the other comprising the last four years (1st Quarter 2006 to 4

th Quarter

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.

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

CHI, J., Gupta, M. – Overvaluation and earnings management – Working Paper – March. 2009.

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

Review, Vol. 70, No. 2 – p. 193-225 – April 1995

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

for standard setting. – Working Paper - November 1998

JONES, J., - Earnings Management During Import Relief Investigations. Journal of Accounting

Research, Vol. 29, No.2 – p. 193 – 228 – Autumn 1991.

KANG, S., Sivaramakrishnan, K., - Issues in Testing Earnings Management and an

Instrumental Variable Approach. Journal of Accounting Research, Vol. 33, No. 2 – p .353 –

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

THOMAS, J., Zhang, X,. – Identifying unexpected accruals: a comparison of current

approaches. Journal of Accounting and Public Policy 19 – p.347 -376 - (2000)

TUKAMOTO, Y,. Lopes, A. – Contribuição ao estudo do gerenciamento de resultados: uma

comparação entre as companhias abertas brasileiras emissoras de ADR e não emissoras de

ADR – Working paper

YAPING, N., - The theoretical framework of earnings management – Canadian Social Science

– 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:

= 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.