Dechow et al., (1996) provides evidence that the modified Jones model is the most powerful to detect earnings management among the alternative models to measure discretionary accruals. Thus we used a modified version of the Jones model to obtain discretionary accruals from regressions of total accruals on changes in sales and on property, plant, and equipment within industries. Jones model attempts to control for the effects of changes in a firm's economic circumstances on nondiscretionary accruals. The Jones Model for nondiscretionary accruals in the event year is: Where: NDAt is the nondiscretionary accruals in year t scaled by lagged total assets; ∆REVt is revenues in year t less revenues in year t−1, where ∆RECt is net receivables in year t less net receivables in year t−1, PPEt is gross property plant and equipment at the end of year t; At−1 is total assets at the end of year t−1; and β1, β2, β3 are industry-specific parameters for each country. Estimates of the industry-specific parameters, β1, β2 and β3, are obtained by using the following model in the estimation period for each country: Where: β1, β2 and β3, denote the country-industry specific OLS parameters, and TAt is total accruals in year t, εt is the residual, which represents the discretionary portion of total accruals. 3.1. Regression Models In order to get discretionary part of accruals we estimated 32 different regressions (8 country x 4 industry group) and obtained residuals. We used ICB general codes to classify industries. Table 2 shows the sectors which used to estimate discretionary accruals by using Modified Jones Model within industries. We haven’t used SIC two digit sector specific classification because there weren’t adequate observations for some countries to use Modified Jones Model. In our analysis three models have been used to test hypothesis. First two models have been tested for whole sample (8 countries, 1507 observations) the third model has been tested for each 8 countries separately. Absolute value of Discretionary Accruals is dependent variable at all three models as a proxy of earnings management. Auditor dummy (BIG) and Rule of Law index are independent variables for the first model, auditor dummy and Control of Corruption index are independent variables for the second model, only Auditor dummy (BIG) independent variable for the third model.



Consistent with the literature we have used auditor dummy is a proxy for audit quality. To measure legal system quality and effectiveness we have used a Rule of Law and Control of Corruption index which comes from the Worldwide Governance Indicators project. These two indices are made by Kaufmann et al. (2010) in order to construct an aggregate Worldwide Governance Indicator. Basically, rule of Law index indicates perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence. And control of corruption index reflects perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as "capture" of the state by elites and private interests (Kaufmann et al., 2010:4). In order to control variety in earnings management incentives based on firm characteristics which are associated with accruals, we added following variables as control variables. As a proxy for the size of a company, we used the natural logarithm of total assets (SIZE), which is expected to lower earnings management incentives because of company’s prestige and the potential government scrutiny which increases as firms are larger and more profitable (Dechow and Dichev 2002). Another control variable is leverage variable (LEV), which is calculated as a ratio of total liabilities to total assets. Firms’ leverage degree may have an impact on earnings management two different ways. While highly leveraged firms could be expected to engage more in upward earnings management to avoid debt covenant violations, alternatively, high leverage may induce income-decreasing earnings management in financially distressed firms in view of contractual renegotiations (Tandeloo and Vanstraelen, 2008). Hribar and Nichols (2007) show that controlling for differences across companies in the natural volatility of their accruals mitigates the potential bias arising from the use of the absolute value of discretionary accruals. Thus, in order to control poor performance for the previous year, we include Lagged ROA of firms which have disclosed loss at 2008. Finally, we added to model Tobin Q ratio as a control variable, with the purpose of take account of market reaction, investment opportunities and intellectual capital of company. As a result, to test the hypothesis following three regression equations has been estimated. Model 1 (For Whole Sample) Model 2 (For Whole Sample) Model 3 (For Each Country) where: DA = Absolute value of discretionary portion of total accruals BIG = Audit Quality Dummy Variable ( If company works with Big 4 auditor = 1, otherwise = 0 ) SIZE = Natural logarithm of total assets in year t LEV = Ratio of total liabilities to total assets in year t DROA = ROA of the year 2008 for the firms which have negative ROA’s at 2008, otherwise (positive ROA) = 0 TOBQ = (Total Debt + Market value) / Total Assets

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ROL = Rule of Law Index COR = Corruption Index 3.2. Results Table 3 presents the descriptive statistics for the accruals and other company characteristics, where ALL columns presents the results for the full sample, other columns represent countries. For the 1,507 company-year observations included in the sample, average discretionary accruals is 8.1 percent. Respectively higher accruals estimated for Russian, Brazilian and Israelite companies, while Mexican has lower. Tobin q ratio varies a lot between countries. While Brazilian companies have 2.8 Tobin Q average Polish companies have 0.37 average Tobin Q ratio. Rule of Law index is 0.0375 for whole sample and control of corruption index is 0.046. These two indices may range approximately from -2.5 to 2.5 and lower values points inefficient judicial system and more corruption, positive and higher values vice versa.

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Conclusion. In this paper we have investigated the relationship between earnings management-audit quality and earnings management-legal system quality by using 1507 firms’ observations from the listed companies in private firms across different 8 emerging countries. Consistent with the previous research, we have proposed; first: differentiation between Big 4 and non-Big 4 audit firms which represent audit quality effects earnings management incentives, second: national legal environment determines earnings manipulations’ degree. According to our results, only for Brazilian and Mexican companies, there are significant relationship between the discretionary accruals and audit quality. For the other countries there is not significant relationship. Furthermore efficiency of the judicial system helps decrease earnings management incentives. The results of our study are relevant to the current discussion on the international comparison of legal environments and enforcements on earnings management incentives. Along with results, the big four auditors do not constrain the earnings management incentives in every emerging country but judicial system does. In other words, whether international big audit firms provide high quality services or not, audit environment, which affected directly by legal environment and effectiveness of legal system, is more important than audit quality.
Словарь основных терминов.

Audit Quality - Аудит качества

Discretionary charges - Дискреционные сборы

Earnings Management - Управление доходами

Economic dependence - Экономическая зависимость

Financial statements - Финансовые отчеты

Indirect indicators - Косвенные показатели

International comparative studies - Международные сравнительные исследования

Income - Доход

Legal Enforcement - Правоприменение

Monitoring mechanism - Механизм мониторинга

Net cash flow - Чистый денежный поток

Interest Rates - Процентные ставки

Bank–balance - Банковский баланс

Neo-Fisherian effect - Эффект неофишера

Equation - Уравнение

Monetary policy credibility - Доверие к денежно-кредитной политике

Behavior of inflation -

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Поведение инфляции

Aggregate demand - Совокупный спрос

5. 
   Резюме (CV)
   

Let me introduce myself. My name is Valeria Schelkunova. I am twenty-four. I am a student in the university . At the moment I am in magistrature. As of my traits of character, I am purposeful, easy-going, cheerful and responsive. I love my family and friends and I am always eager to help them and divide their joy and sorrows. I like to spend much time with my nearest and dearest. I adore outdoor activities, drawing and travelling. I really like my job, because I get new knowledge at work. Besides, I am a very versatile person. I am fond of fashion, music, English. In my free time I can spend hours out in the open air indulging in my hobby. Twice a week I go to the gym where I practice fitness. I have a dog and cat. I love so much them. My dog is small, but very harmful. I took the cat home from the street.

I want to tell about my job. I work in bulding company. I am engeneer. A civil engineer must know everything about materials and building technologies. He should know about design and geodesy regulations, building standards and safety of workers in the workplace. we are building a hospital. it’s a very difficult and long process, but it's a great experience. I’m not afraid of the fact that their job is often dangerous and they have to spend a lot of time outside rain or shine. Every profession has its disadvantages but when you do what you love and it benefits the society then you can overcome everything.

5. 
   Motivation Letter
   

With this letter, I would like to express my interest in obtaining a master's degree in finance. I am interested in starting a career in economics in construction, and I am sure that this degree will help me realize myself both professionally and personally.

I am currently studying for a Master's degree in Finance, where I have spent a lot of time and effort studying accounting, studying economics in construction. While studying in high school, I also attended additional classes in mathematics, which clearly reflects my preferences and interests.

My current goal is to start my career in finance in the construction industry. After doing some research, I realized that a master's degree in finance is the best choice for me for a number of reasons.

First of all, this program covers a number of topics that interest me the most, such as construction economics, microeconomics, information activities, etc. As a future economist, I should be an expert in these areas. I am sure that numerous internships and seminars in which I will take part during my studies will help me acquire the necessary knowledge and skills.

Secondly, studying at the university will significantly improve my knowledge of English. Being one of the most important languages in the world, English will help me establish new connections and expand my social network to a global level.

Finally, a master's degree in finance from the University will help me develop myself as a team player. In addition, I am attracted by the possibility of an internship during my studies. This great opportunity will give me valuable professional experience necessary to build a successful career in today's competitive environment.

In general, I believe that I will be able to make the most of the knowledge and experience gained during the training program at the university. I hope to bring my talents and efforts to your university and become a worthy member of the team.

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