The effect of production diversification on the investment attractiveness of Russian companies

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ПЕРМСКИЙ ФИЛИАЛ ФЕДЕРАЛЬНОГО ГОСУДАРСТВЕННОГО АВТОНОМНОГО ОБРАЗОВАТЕЛЬНОГО УЧРЕЖДЕНИЯ
ВЫСШЕГО ОБРАЗОВАНИЯ

«НАЦИОНАЛЬНЫЙ ИССЛЕДОВАТЕЛЬСКИЙ УНИВЕРСИТЕТ

«ВЫСШАЯ ШКОЛА ЭКОНОМИКИ»

Факультет экономики, менеджмента и бизнес-информатики

Выпускная квалификационная работа

Влияние диверсификации на инвестиционную привлекательность российских компаний

(The Effect of Production Diversification on the Investment Attractiveness of Russian Companies)

Рецензент

Барахас Алонсо Анхель Антонио

Руководитель

М.А. Шелунцова

Пермь 2016



Outline

Introduction

1. Theoretical background

1.1 The concept of investment attractiveness

1.2 The concept of production diversification

1.3 The determinants of the investment attractiveness

2. Research Design

3. Methodology

3.1 Preliminary data analysis

3.2 Econometric Model

4. Empirical Results

Conclusion

References

Appendix



Introduction

The investment attractiveness in terms of modern business stands for one of the most essential features of the company's performance due to the fact that it has an apparent influence on the prospects of a firm for further development, competitive abilities, and financial stability. The adequate investment policy of the company gives opportunities to raise funds, direct the money appropriately and to reinforce the financial position. To retain its status and to reach the leadership an enterprise needs to permanently cope with up-to-date technologies and broaden the sphere of activity. Under these conditions, a moment occurs when the further extension is unfeasible without an extra flow of investments. The involvement of supplies of money gives a company competitive advantage and often becomes a significant tool for growth.

At the same time, every external investor faces the problem of choice which company to invest in. For making up the mind he needs to get and compare the estimations regarding the investment attractiveness of the potential organizations. In this case, the investment attractiveness is not only a matter to manage but also a criteria or evaluation for making the decision from the investors' point of view.

One of the possible alternatives for a firm to increase its investment attractiveness is the information disclosure, both financial and nonfinancial. The higher is the degree of disclosure, the more transparent the company seems for investors. This transparency is somehow referred to the guarantee of the investment's' safety. If there is more information about the enterprise, investors tend to be more confident.

Nowadays many companies provide a huge amount of information, which is not always easy to interpret and understand. The companies' diversification, the existence of different financial and nonfinancial components claim for solid and comprehensive approach for making investment decisions. In this situation, the investment attractiveness is put to the forefront. With the rash evolution of the financial sector, the attractiveness of the enterprises has become determined by different components. However, their influence is not similar across various markets or countries. In foreign researches, mainly firms' financial ratios are considered, whereas in Russia the attractiveness of regions is of substantial interest. Besides, the effect of diversification was poorly studied for Russian enterprises and the researches of foreign markets were conducted much time ago. What is more, the theory claims that diversification implies value-enhancing as well as value-reducing effect.

Thus, it is relevant to explore, if production diversification increases the firms' investment attractiveness taking into account several control variables, which will be introduced further.

The understanding of the impact of the factors, which designate the investors' potential benefits, gives a deeper knowledge of this economic phenomenon and a chance to manage the investment attractiveness of the company in a more efficient way.

The purpose of this paper is to assess the relative importance of the production diversification and other factors determining the investment attractiveness of a company.

The goal is not just to develop a kind of theory, rather than to see why these determinants are so considerable or not.

In this paper, the following issues are examined:

a) Examination of the investment attractiveness and diversification's concepts

b) Formulating initial hypotheses

c) Description of the given data set

d) Model parametrization and specification

e) Model identification and verification

f) Economic interpretation

The study is based on the econometric estimation of the panel data. The data comprises the 174 Russian companies for the period from 2012 to 2014, which was collected from the Thomson database as well as from the financial reports of the companies in question.

The paper consists of two sections: theoretical and practical. The former includes the definition of the investment attractiveness, the methods of its evaluation, the explanation of the diversification concept and preceding findings in this sphere. The latter concerns the analysis of production diversification and other possible factors for Russian companies, model specification, identification, and testing the initial hypotheses. After that the economic interpretation is given.



1. Theoretical background

Economic transformations and alterations has changed the existing system of economic relationships of the society in Russia during the last 20 years. In terms of current developing Russian market economy, the companies seek for steady flow of investments, which is directed to firms' development, expansion and modernization of production and also to technological and product innovations. The involvement of the investments in a proper dimension is a consequence of smooth firm's work on advancement of investment attractiveness.

The recent research bears upon the systematical study of a wide range of literature. As the definition of investment attractiveness is highly complicated and versatile, it is worthwhile to narrow it. Consequently, we provide the sufficient explanation for the following approaches of the investment attractiveness explanation and assessment.

1.1 The concept of investment attractiveness

The investigation of the “investment attractiveness” definition has become prevailing in the framework of free trade development. However, there is no common approach to determine, what it means exactly. Basically the investment attractiveness can be designated either as a group various factors, as a ratio of risk and return, or as investor's main goals. According to the first approach, the investment attractiveness is:

a) The aggregate characteristic of advantages and disadvantages of investing

b) The set of quantitative and qualitative factors, which explain the demand for investments

c) The conditions for investing, which affect the investor's preferences

d) The feasibility to invest, which is influenced by a number of factors, defining firm's performance

The second approach implies that the investment attractiveness is:

a) A presence of economic effect (i.e. earnings) after investing with a low risk

b) Making the highest profit with the given risk

c) The feasibility to invest, which is based on the coordination of investor's and company's concerns and opportunities

From the investor's consideration, the investment attractiveness is:

a) A guaranteed goals' achievement, based on the company's financial performance

b) A set of economic and psychological determinants of company's performance, which define the area of preferable investment behavior

In current research the investment attractiveness implicates market-to-book ratio, which is taken as a proxy variable, the explanation for this will be given further.

Generally, the organizations apply different tools to raise funds. The most widely spread are: bank loans, bond issue, and attraction of investors. The first one is the most simple, though the most expensive. Besides, the terms of the loan are determined by the bank relying on its credit policy. Calling in the investments on the stock market and a search for investors need public accounting, control over cash flows, business transparency. The more investment attractive the company is, the more is the likelihood to get investments.

While analyzing the investment attractiveness of company investors generally consider:

a) The reasons for successful performance of a firm in the past and perspectives for the future earnings

b) Alteration trends (growth, stability or slump) of profitability, returns on sales and equity

c) Current financial state of affairs and possible factors, which can influence it

d) The structure of a capital, risks and benefits from the investor's point of view

e) Enterprise's position in the framework of corresponding industry

f) The forecast of stock prices

The analysis of the investment attractiveness is a process of studying financial information in order to:

a) Assess reasonably the state-of-the-art level of the investment attractiveness and financial conditions of a company, their alterations in response to various factors

b) Make a decision from the investors' side to finance projects given specific limitations

c) Improve financial conditions of the company, its financial stability and investment attractiveness

Due to these objectives of the estimation of the investment attractiveness, the following aims can be derived:

a) The analysis of the structure, volume and effectiveness of application of company's property

b) The analysis of sufficiency of debt and equity capital

c) The evaluation of firms' financial independence, paying responsibility, liquidity and diversification

d) The analysis of sufficiency of capital assets, inventories and goods in process to ensure competitive advantage and profitability

e) The estimation of the influence of risks and ambiguity (including inflation and tax policy) on company's performance and investment attractiveness

Investors and potential investment project do not always come across each other due to complicated system of their interrelation. The process of investment is engrafted by several factors, which investors meet while making decisions. However, owing to huge amount of information and operating enterprises it might be difficult for an investor to make up his mind and to choose the most attractive company.

Yet every potential investor is in charge of his own decisions, that is why it is vital for him to estimate all the pros and cons, which are related to the investment process. To understand, whether the funds are going to be invested in a proper way, all the investors estimate the attractiveness of the company. In particular, the investment attractiveness. There are a number of particular approaches to assess it.

The first one is built on the market capitalization indexes and its variations. It was used by the investors of the developed countries in the 1960s for the first time. (Esipenko, 2010). The basic measurements for the investment attractiveness assessment here are:

a) Price to revenue ratio;

b) Price to equity ratio;

c) Price to net profit ratio;

d) Dividend payout.

Ratings, made up with the help of these ratios, are published routinely in the periodical business press, for example Financial Times, Business Week or Forbes and also on the internet.

The first three ratios seem quite obvious, as they are directly related to the business evaluation. The dividends though are not clearly seen as measure of the investment attractiveness, however there are a few reasons to do this.

Gordon and Linter in their “theory of dividend preferability” describe that every unit of income, which is given to the investors in a form of dividends, is worth more than the profit, reserved for the future, because the former contains less risk. Moreover, in the “signal theory” Ross, Kato and Levenstein claim that the payments of higher dividends is an indicator of firm's stability, its revenues and further perspectives. Thus, the dividend payment can be treated not just as a source of income for shareholders, but also plays a role of an indicator to judge about the performance of the company (Al-Malkawi et al., 2010).

Investors are more interested to understand the profitability of the firm, due to the fact that it defines the return on their investments. Moreover, potential investors have incomplete data in imperfect markets. There is a lack of information so whatever is available should be considered important by the investors. The announcement of dividend payments is a call for future growth of the organization. (Rehman, 2012).

However, for the Russian economy this proxy is not a good one, as a small amount of firms pay out the dividends on a regular basis.

Another approach to measure the investment attractiveness is to apply various financial ratios. The financial information of the firm assembles many important aspects of its performance. It gives a general idea about the resources opportunities and future returns through the identification of the ratios from the balance sheet, income statement and statement of cash flows. These estimations include several groups of indicators:

a) Indicators of liquidity, which stand for the ability of a company to repay short-term debt out of cash.

b) Indicators of financial stability, which define the degree of firm's independence from debt.

c) Indicators of profitability, which show company's performance and efficiency.

d) Indicators of business activity, which are related to the analysis of the turnover ratios.

This approach is clear, nevertheless, it presents company's activity only in terms of its financial conditions and does not take into account other possible determinants of investment attractiveness.

Another approach is the estimation of the security indexes. It incorporates operations on purchase and sales of securities. The supporters of this method claim that the required data is included in the exchange rates. However, it seems hard to analyze this type of information due to the lack of disposable information and it is not convenient for every kind of business.

The fourth method is a thorough evaluation. It can be described as a number of both psychological as well as economic drivers, under which we presuppose the preferences from the investors' point of view concerning various factors of company's activity. Thus, the investment decision is made under anticipation and waiting of a particular person or a group. The application of this method needs experts' opinion, which makes the assessment more precise, but complicated.

Anyway, the definition of the investment attractiveness is vital both for the investors as well as for managers, who try to understand the place of the firm on the market, firm's advantages and disadvantages. (Goncharuk A.G., Karavan S. 2013)

1.2 The concept of production diversification

The production diversification is a strategy of business development. Any firm can implement the production diversification through the modification of existing products or the introduction of the new products to the range. These approaches provide great opportunities to extend the business by higher sales to the customers or conquering new markets.

The definition of the diversification is quiet complicated. It order to understand this concept the diversification was defined as the entrance to new markets with new products (Ansoff, 1957). Eventually the definition was extended in several dimensions. It was identified as the pursuit of more than one earmarked market (Dundas, Richardson, 1980). After that the incentives for diversification were determined, in particular the firms want to diversify mainly due to financial incentive (Amit and Livnat, 1988). Later on, the several segment operation of business was explained as a wish to expand the organization, to achieve the economy of scale and to create the synergic effect of all productions. (Patrick, 2012)

Many firms today are involved in the production of several products, in this sense they are diversified or in other words horizontally integrated. So what are the main features of this kind of a company?

Firstly, we need to identify two groups of characteristics: managerial and financial. The managerial features of the diversified company include:

a) the presence of several activity dimensions, i.e. the operating in several segments, which can be either connected with each other or not;

b) the existence of a major center (or the leading company), which is responsible for investment decisions, financing, monitoring the other divisions and establishing the relationship with the government and clients;

c) The presence of the multilevel organizational structure and managerial hierarchy;

d) The availability of specific knowledge and skills of managers, which are required for the competitive advantage in particular lines of business and for controlling them;

e) The existence of high costs of coordination and control.

These features make a foundation for the financial characteristics, which are related to the capital formation and its distribution. The financial features imply:

a) The presence of the internal capital market, which means the specific mechanism of capital allocation among the divisions and the toolkit to control these lines. Thus, as a consequence of diversification the centralization of the financial decisions is brought to the corporate center.

b) The existence of the two-tiered agency model (Shamraeva, 2010).

The production diversification is referred to the cohesion of the company's products or to which extent firm's industries are linked. A number of theories have made an attempt to investigate the performance of diversification. However, they can hardly give a unanimous conclusion. The transaction cost theory for instance reveals that diversification enlarges the coordination and control of firm's activities costs, which in turn serve as a barrier for the performance improvement. On the other hand, diversification can distribute the costs of transportation, communication and allocation within the market, which declines the transaction costs and increases enterprise's performance. All in all, the transaction cost theory does not give a valid confirmation of a particular relationship between firm's diversification and its performance. (Shen, Wang, Su, 2011)

The advantages of diversification are:

a) The obtainment of market power. A company with several products can extract more from the potential customers than several firms operating noncooperatively would get. Yet many companies have negligible market shares, subsequently they seek for other incentives for diversification.

b) The elusion from risks. If there would be no risks of bankruptcy or liquidity any company would not have to diversify. However, because of incomplete insurance capabilities, avoiding risk might be important for many companies, which are considerably dependent on cash flows.

c) The access to funds. As the capital market is imperfect, the opportunity for investments may turn to the companies, which have funds to finance it, rather than to simply efficient producers. If the enterprise notices the opportunity in some segment and has funds, it will likely diversify in this production even if it is costlier than specialization. This idea is quite probable especially for large organizations, where the capital can be raised more quickly and easily.

d) The increase in product compatibility. A company has a chance to rise its profits and probably the customers' welfare by producing the product set jointly, when these items need to work together. This scheme can be applied even if there are no potential cost advantages. Besides, it can make a company integrate vertically to guarantee the optimal combination of inputs and to increase the worth of production chain.

e) Stabilization. Diversification can also help to build stability. If the company is concentrated too much on a single item, the risks of volatility in sales and resources increase because the demand is not constant. If the business varies across several segments or categories, it has more chances to predict the alterations in consumers' preferences.

f) Gaining of efficiency. With the help of multiproduct range, a company can increase the sales and achieve the economies of scale in promotion, advertising and the distribution of products. What is more the additional lines will call for extra workers, thus enlarging the labor market for them. (Boyan Jovanovic, 1993)

The disadvantages of diversification:

a) There is a probability that companies can have agency problems between shareholders and managers. It is quite difficult to check multiple operations for shareholders and this helps manager to get perquisites.

b) Some researches claim that the drawback of diversification is the cross-subsidizing of poor performing segments, which are inefficient when traded in the external market.

c) Another disadvantage is the misalignment among the central and divisional managers. If the latter is sure that some cash flow might be redirected to another division, he has less motivation to run his sector efficiently.

d) Besides the firms, which enter a new activity, seek for advantage over what they are now operating, however they do not pay attention on the absolute predominance over competitors.

e) The diversification of production causes the high costs of control and coordination. If these costs exceed the benefits, the company's value declines.

Thus the diversified companies are not always effective due to the information asymmetry, which complicates the monitoring process, the inefficiency of the motivation system, the problem of resources allocation, that interfere the goals of all the segments. (Diltz, 2002)

If the production diversification is used, the investments and costs should be spread among different lines, which prevents from directing enough money in cash-cow segments.

On the one hand, production diversification seems to be ineffective, because it contradicts one of the most fundamental ideas in economics that the specialization is productive. On the other hand, from theoretical point of view there exist potential advantages for diversifying firms.

1.3 The determinants of the investment attractiveness

In Russia the evaluation of the investment attractiveness is generally based on the financial ratios. Perzukhov (2007) examining 360 Russian firms from 1995 to 2005 assessed that liquidity, business activity, financial stability and profitability are positively related with the investment attractiveness. The results were obtained through regression models (both linear and nonlinear), in which the indicators with the largest load factor were included.

In many foreign countries, the assessment of the investment attractiveness of this or that company is built upon the market capitalization and its value. According to Sunityo-Shauki and Siregar (2007), companies' size and financial leverage play major role in determining success and failure of enterprise in terms of price to book ratio. The study also reveals that board performances, board size and the existence of audit committee need to be improved to strengthen the investment attractiveness.

These results correlate with the publication of Pandey (2005), who found a scientific support to the possible drivers, affecting the market-to-book ratio. In his paper, the author scrutinizes that leverage and risk increase shareholders value, while free cash flow-to-total assets ratio has a very weak dependence with M/B ratio.

Adam and Goyal (2007) elaborated the impact of ROA, leverage, value of reserves and resources on market-to-book ratio. They also focused on companies' diversification using Herfindahl index. However, for the sample of 90 mining companies the diversification was found to be insignificant in increasing the investment attractiveness.

Beckareva and Meltenisova (2009) offered another explanation for the investment attractiveness taking Tobin's Q as a proxy to measure it. The study analyses the significant effect of capital structure and liquidity indicators. A striking example can be found in research conducted by Kirianova (2014), who addressed the investment attractiveness issue by including profitability, liquidity, size, investments and riskiness to estimate the model. Return on assets and investment activity turned out to be the only significant for the study. Instead of attempting to discover the impact of financial indicators, Kuznecov (2012) convinced that transparency & disclosure indexes as proxies of corporate governance positively affect the investment attractiveness of the Russian energy sector companies, while Herfindahl index (as a measure of market concentration) indicated a negative influence.

Foreign scholars also considered the effects of firm size, liquidity and profitability of the company on Tobin's Q. Lin (2011) along with these drivers studied the board performance and realized that its size and inside directors positively correlate with firm performance. On the contrary, Shauki and Siregar (2007) found no support for the relevance of these factors for Indonesian listed companies.

The results obtained by Connolly (2005) suggest the positive effect of growth, advertising and R&D intensity on investment attractiveness, while risk had a negative effect.

However, our aim is to focus the attention on the product diversification and its effect on investment attractiveness. Theoretical arguments propose that diversification has its own pros and cons in respect to company's value. The benefits include better operating efficiency and debt capacity, the ability to approve projects with positive NPV, the reduction in taxes. The costs imply huge cross-subsidies from better performing segments to poor ones, the increase in additional resources and opposing incentives of managers from different lines. Thus, the overall effect of diversification is quite controversial. (Berger, Ofek, 1995)

Coming back to the assessment of diversification effect (measured in terms of Herfindahl index), the paper of Stulz (1993) should be mentioned, where he exploited various approaches to determine whether the companies, which operate in several segments, are more attractive for the potential shareholders than one-activity specified. The author manages to explain the negative effect of diversification on Tobin's Q, in conjunction with negative effect of unpaid dividends and size of company and positive effect of R&D expenditures.

Schoar (2002) identified two sources of value decrease in firms with diversification. Firstly, he explains the negative dynamic effect of operating in several lines. The productivity of the main plants declines while the new segments work more efficiently. However, the net effect is on average negative, which shows that the diversifying moves are not optimal. Secondly, the author provides the evidence that the companies with diversification pay higher wages and extra benefits than one line operating, which seems not advantageous from shareholders' view.

Montgomery (1994) in her research clearly shows that production diversification is not an assured way to success. She points out that firms, which diversify more, are on average less profitable than those with lower degree of diversification.

Polk and Lamont (2002) also proved the negative effect of diversification, which reduces the firm's market-to-book ratio. The study was conducted on the sample of 1987 firms for the period of 1980-1997.

The negative effect of diversification was also found in the works of Lins and Servaes (1999), Graham, Lemmon and Wolf (2002).

Yet Bae, Kwon and Lee (2008) found that for example in the emerging markets there is much space for the firms to increase their value through diversification due to the high level of information asymmetry and market imperfection. Firstly, multiline production firms might work effectively by coordination of several specialized divisions. Secondly, diversification may decline the problem of underinvestment through the allocation of assets in efficient way. Moreover, the cash flows can be stabilized as the earnings from different dimensions have low correlation.

All in all, studies on this concern have mixed results.



2. Research Design

From the theoretical point of view during the precise studying, the majority of modern theories in this booming sphere seem controversial. Moreover, while closer examination some of them fail to withstand criticism, especially within the framework suggested. In the current paper we don't want to doubt the treatment of western scientists, though we will try to concentrate on the practical part of the issue.

Thus, the abovementioned factors somehow refer to the value of any company, which consequently can be employed as an indicator of the investment attractiveness. Basically it pertains the quite modern concept of value-based management. It is believed, that the companies, which manage their value successfully seem more attractive for investing. Moreover, the indicators of the market value cover the financial performance as well as nonfinancial results.

However, it should be highlighted that we are not intending to explore the market value itself. The ratios, which give insights to the difference of the market value and the book value, give a better perception of the concept. This inequality represents the investors' attitude to the enterprise and can be explained through some factors, which give competitive advantage over the rivals.

As it was denoted above, the major ratios in the empirical studies, which address the value of the company, are Tobin's Q and market-to-book ratio. These proxies for the investment attractiveness lead to sufficient and precise estimates.

The Tobin's Q coefficient was first suggested by J.Tobin in 1969 as a measure of feasibility to invest. Generally, this ratio is estimated through the relation of the company's market value and replacement cost of assets. However, in practice the latter category can be hardly calculated, therefore the bulk of researchers equal the replacement costs to the book value of assets. In essence, this estimation is reconciled to the market-to-book ratio.

Market-to-book ratio is a fundamental one and it is determined as a relation between market capitalization of a company and the book value of its equity. This coefficient presupposes, how each item of assets is evaluated by the investors. It is one of the most accessible coefficients as it is rather easily calculated. Besides, the investors' attention is turned to the basic fundamental ratios, subsequently we will use market-to-book ratio as a proxy for the investment attractiveness.

The following determinants are used as variables for assessment of investment attractiveness:

a) The production diversification

b) Current ratio

c) Quick ratio

d) Debt-to-equity ratio

e) Return on equity

f) Return on assets

g) Size of a company

h) The life cycle stage

i) The relation to this or that industry

The diversification is measured through Herfindahl index, which in our case stands for the following estimation HHI=, where S is the percentage share of one product in total revenue of a company. The higher the Herfindahl index, the lower the diversification of the firm.

The estimation of the Herfindahl index was made with the following procedure. For the all the companies in the sample a careful analysis of the income statement was conducted. The financial reports for each of three years for every company were downloaded and there the parameter of revenue was found. For 174 companies the revenues turned out to be broken down into dimensions, which indicated the presence of multiproduction in these firms. This sample did not include the organizations without the division of the sales (the degree of diversification could not be estimated, even if a company indeed has several lines of production but does not want to disclose this information), so they were dropped out from the sample. Below we present the example of a firm with low and high level of production diversification.

Table 1 Examples of low and high levels of production diversification

The Likhachov Plant (example)	VSMPO-AVISMA (example)
Revenue (in thousands of roubles)	Revenue (in thousands of roubles)
Sales of electricity	682757	The production of titan	50844539
Sales of heat	45161	Other production	3931829
Leasing of the property	334900	-	-
Sales of goods	66896	-	-
The services of residence	53846	-	-
Other production	59155	-	-
Total	1242715	Total	54776368

Hypothesis: more product diversified (with lower Herfindahl index) company is less attractive for potential investors.

The control variables include:

a) Return on assets (ROA), which is equal to EBIT divided by total assets. It shows the amount of net profit, which each item of assets brings. The higher the ratio, the more properly the company exploits its assets. It is a signal for the potential investors, whether the enterprise is profitable or not.

b) Debt-to-equity, which is equal to total liabilities divided by the shareholders' equity. The ratio assesses the ratio of debt and equity, which are used to finance the company's assets. It can be also treated as a factor of risk, because the higher proportion displays that a firm is likely to go bankrupt as it starts to be dependent on the external funds.

c) Current ratio and quick ratio, which test the liquidity through looking at the available current assets to cover the current liabilities. The higher the ratios, the more likely that a firm has funds to cover the obligations and not to borrow extra money. Liquidity is helpful for investors as it assists to avoid the enterprises that are getting in trouble and to purchase or vend shares when there is a need for that.

d) Size of a firm, where we use a proxy variable in a form of total assets. Usually, larger firms are more attractive than small ones, due to the fact that the former meet less constraints and are more safe and stable. In this research the logarithm of assets is considered to estimate the percentage change and its effect on M/B value.

e) The life cycle stage of the firm has a significant influence on its performance. During the various stages the organizational characteristics of the enterprises change and consequently different methods of management are needed. The organizational specifity of a company develops the opportunities to get the benefits from running several lines and determines the financial relationships within diversified firms and serves as an self-contained factor of the investment attractiveness. Therefore, it is crucial for every investor to determine the current stage of the company. Researchers define various life cycle stages, which stand for a particular phase of the firm's existence. Birth, growth and maturity are the basic phases, which are related practically to every company. The following stage is a turning stage. This phase indicates the future of an enterprise: whether it will shift to a new cycle of development or its performance will decline with subsequent dying.Dickinson (2007) and W. Bruwer with W. Hamman (2008) suggested that each phase of the firm's life cycle is defined by a particular correspondence of cash flows from operating, financing and investing activities of organization. This relationship alters while conversion to the next stage.

To avoid multicollinearity problem, one of these stages (maturity) is excluded from the model to compare the results regarding this variable.

f) Return on equity (ROE), which is equal to EAT divided by equity. It indicates how much profit is earned per rouble, which was invested in the company by the owners. To put it differently, it shows how efficiently the invested capital is used. If return on equity is high then a company makes high profit with the application of invested capital.

g) The relation to this or that industry is crucial for the investors. They assess which segments are undervalued and have potential for future growth. Thus, we include the dummy variables, which represent the correspondence of the firm to the particular industries.



3. Methodology

In this part of the research we aim to explain the methods used in carrying out the study, giving emphasis to the obtained results.

The goal of the research will be achieved by the deployment of the statistical method, particularly the regression analysis of the panel data is going to be conducted. To hold a research it is necessary to analyze the data. The initial sample will comprise around 522 observations. They include 174 Russian companies from the energy sector, oil and gas production, metallurgy, machinery construction and chemical industries for the period from 2012 to 2014 (The names of the companies are presented in Appendix, Application 5). The panel data was collected from Thompson database. The results of companies' performance are going to be used in the research, that is why the indexes of profitability, liquidity, life cycle stage and other financial and non-financial ratios were extracted from financial reports. The Herfindahl index was calculated to estimate the production diversification effect.

3.1 Preliminary data analysis

In order to check the influence and significance of the abovementioned determinants we apply an econometric approach. It is used as the information can be analyzed with the computer software through the regression models. No need to mention, that a research can not be conducted without the analysis of the necessary data. This step is vital as it gives a possibility to understand the nature of the material and to adjust the sample if it is essential.

There is a probability that some of the observations are not suitable for our model and can be identified as outliers. Consequently, we need to introduce some constraints in the model.

What is more, the descriptive statistics can not be analyzed without the identification of the outliers. So, we build the boxplots for all the variables (before excluding the outliers). They are presented in the application 2.

The boxplots indicate all the descriptive statistics for the variables (mean, median, max, min). These graphs show the outliers for all variables. Consequently, given the presented statistics and the analysis of the boxplots, the constraints were introduced.

After these procedure the number of firms to be analyzed declined by forty six. The boxplots after excluding the outliers are given in Appendix. (Application 2)

The results for descriptive statistics after deleting outliers are given in the tables 2 and 3:

Table 2 Descriptive statistics after excluding outliers

	Current ratio	D/E	Herfindahl	ROA	log(assets)	ROE	Quick ratio	M/B
Mean	148.11	89.33	73.98	4.55	16.86	9.88	104.67	102.84
Median	120.00	51.45	76.03	3.08	16.36	8.56	91.00	64.50
Maximum	566.00	820.86	100.00	68.55	23.44	172.41	482.00	994.00
Minimum	5.00	0.00	23.42	-18.43	12.89	-41.33	3.00	1.00
Std. Dev.	90.91	117.80	22.50	7.91	2.22	19.55	78.12	113.36
Skewness	2.02	2.71	-0.31	1.80	0.57	2.73	2.46	3.43
Kurtosis	8.34	12.34	1.68	14.74	2.68	24.18	10.51	20.82
Jarque-Bera	717.38	1864.93	34.26	2411.68	22.51	7655.21	1289.09	5832.15
Probability	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00
Observations	384	384	384	384	384	384	384	384

The descriptive statistics analysis presents:

a) The mean and median of all the variables are not equal so the distribution is not symmetric, which means that the number of companies with different values of variables is not identical.

b) Current ratio, quick ratio, debt-to-equity, log(assets), roa, roe, market-to-book ratio and practically all dummy variables are positively skewed (the number of firms with smaller values in these variables is greater), whereas the dummy for the turning life cycle stage and Herfindahl index are negatively skewed (the number of firms with higher values in these variables is greater).

c) All the variables have leptokurtic distribution (which indicates the strong scattered nature of the ratios), except for Herfindahl index, log(assets) and dummies for the second and third industries, which distribution is platykurtic (it indicates the high accumulation of the ratios near the mean).

The descriptive statistics also allow to test the homogeneity and normality. To test homogeneity econometricians use the variation coefficient (standard deviation divided by mean of the variable). The variation coefficients for the variables are:

Table 4 The variation coefficients

Variable	Variation coefficient	Sample
current ratio	61%	heterogeneous sample
Debt-to-equity	132%	heterogeneous sample
herfindahl index	30%	homogeneous sample
ROA	174%	heterogeneous sample
log(assets)	13%	homogeneous sample
quick ratio	75%	heterogeneous sample
ROE	198%	heterogeneous sample
market-to-book ratio	110%	heterogeneous sample
Industry 1	275%	heterogeneous sample
Industry 2	131%	heterogeneous sample
Industry 3	163%	heterogeneous sample
Industry 4	240%	heterogeneous sample
Industry 5	311%	heterogeneous sample
Birth	480%	heterogeneous sample
Growth	1960%	heterogeneous sample
Mature	452%	heterogeneous sample
Turning	36%	heterogeneous sample
Recession	686%	heterogeneous sample

The results observe a strong variation in the total population for the majority of the variables in respect to the mean value.

The normality is tested with the Jarque-Bera coefficient. The figures for all variables are higher than the critical value of 9,21 at 1% significance level, which means they are not normally distributed. All the preliminary data analysis shows that the firms in the sample are nonidentical and dissimilar across the variables in question, which is a limitation of the research.

The latter is warranted by the quantile-quantile graphs and histograms. They present that not all the observations are situated along the quantile of normal distribution. (Application 3)

3.2 Econometric Model

After running the technical assessments, preliminary data analysis, the review of descriptive statistics, testing homogeneity and normality the model can be parametrized and specified.

Firstly, it is crucial to make the correlation matrix, to reveal, whether the multicollinearity problem occurs.

The correlation matrix shows, that the correlation coefficients for the majority of the pairs are not high, which presents weak linear relationship. However, there exist a strong one between current ratio and quick ratio, therefore we exclude quick ratio from the estimation to avoid the multicollinearity problem. The same is done for ROA coefficient as it has a noticeable relationship with ROE (this can be explained through Dupont model ROE=ROA*(1+D/E)). As for the dummy variables, the stage of maturity and ind5 are excluded to avoid multicollinearity.

Before the estimation, the model must be parametrized and specified. The multiple regression model looks as follows:

M/b = b0+b1*HERF + b3*CURRENT_RATIO + b4*D/E + b5*ROE + b6*birth + b7*GROWTH + b8*TURNING + b9*RECESSION + b10*LOGASSETS + b11*IND1 + b12*IND2 + b13*IND3 + b14*IND4 + vit



Where: M/B - market-to-book ratio

HERF - herfindahl index

CURRENT_RATIO - current ratio

D/E - Debt-to-equity

ROE - return on equity

birth - stage of birth

GROWTH - stage of growth

TURNING - turning stage

RECESSION - stage of recession

LOGASSETS - logarithm of assets

IND1 -manufacturing industry

IND2 - energy sector

IND3 - oil and gas sector

IND4 - metallurgical industry

vit - error term (vit=ui+eit)

The description of variables is presented in Appendix (Application 4).

As the collected data comprises the observations for 3 years and represents the panel form of information, the model will be tested in several directions. Firstly, the pooled regression will be estimated, further the random and fixed effects models will be identified. With the help of several tests the most appropriate functional form is going to be chosen.

Pooled regression is the most restricted due to the fact that it doesn't take into consideration the panel structure of the data.

Due to the peculiarities of the given dataset the fact, that the problem of endogeneity might occur, is probable during the regression analysis. The most common explanation of the endogeneity implies the correlation between the regressors and the error. It leads to the bias and inconsistency of the estimates and incorrect interpretation of the results. There exist several sources of the endogeneity. Firstly, the omitted variables, which can correlate with the explanatory variables in the model. Secondly, the simultaneity which takes place when two variables can be dependent for each other. Finally, the presence of the error while using the proxy variables. The most relevant approach to eliminate the endogeneity problem in our case is to apply fixed and random effects models.

Unlike pooled regression, fixed effect model enables to capture the item's individual heterogeneity. It allows to account for the effect of missing and unobservable variables, which characterize the individual non-time-changing features.

Random effects model is a compromise, as it is less limited than pooled regression and as it gives more statistically significant coefficients than the fixed effects model. In this type of estimation the individual heterogeneity is considered (not in the equation itself, but in the covariance matrix). Random effects model is calculated by the deployment of generalized least squares method.

The results of the regression assessments are presented in the table:

Table 7 Model estimation

	Pooled regression	Fixed effects	Random effects
Herfindahl	0.533*** (0.198)	0. 425* (0. 230)	0. 580** (0. 266)
Current ratio	-0.035 (0.045)	-0. 060 (0. 055)	-0.028 (0.048)
Debt-to-equity	0.507*** (0.083)	0. 334** (0. 153)	0. 476*** (0. 115)
ROE	1.698*** (0.547)	0. 135 (0. 353)	0. 860** (0.404)
Birth stage	-3.128* (41.887)	7.069 (29.653)	4.199 (29.680)
Growth stage	-125.666*** (40.425)	-40.603** (19.658)	-71.935*** (20.214)
Turning stage	-37.193 (25.477)	6.634 (15.707)	-16.833 (22.636)
Recession stage	44.999 (29.489)	38.179** (15.460)	40.615** (19.263)
Log(assets)	1.963 (1.921)	-38.432** (18.473)	-0.069 (2.911)
Industry1	-55.783** (21.590)	-	-63.867* (33.047)
Industry2	-42.672** (11.725)	-	-45.592 (29.026)
Industry3	-27.410 (17.494)	-	-27.470 (29.020)
Industry4	-16.596 (19.879)	-	-18.837 (31.337)
Const	38.050 (41.071)	690.127 (308.232)	62.782 (56.209)
Adjusted R2	0.470	0.104	0.452
Number of observations	384	384	384

Notes: *** significant at 1%. ** significant at 5%. *significant at 10%. Robust standard errors in parentheses.

All three types of models are compared with each other to choose the most appropriate for this research.

a) The fixed effect model and the pooled regression are compared with the Wald test, where the null hypothesis is the equality of all individual effects to zero.

b) Random effects model and the pooled regression are compared with the Breusch-Pagan test, where the null hypothesis is the presence of random individual effect.

c) Fixed and random effects models are compared with the Hausman test, where the null hypothesis is that the residuals can be taken as random effects.

Table 8 Choosing the most appropriate model

	H0	t-statistics	(Prob > t- statistics)
Wald test	u =0	F(127, 247) = 4.88	0,0000
Breusch-Pagan test	var(u) = 0	chibar2(01) = 77.10	0,0000

The Wald test indicated that the null hypothesis is rejected at all the significance levels, consequently the fixed effects model is better than pooled regression, as the presence of individual effects is observable.

The Breusch-Pagan test revealed the rejection of the null hypothesis at all the significance levels, therefore the random effects model is more preferable than pooled regression. investment attractiveness competitiveness diversification

Comparing random and fixed effects models the Hausman test should be applied. The unpleasant limitation of fixed effects type of regression is the inability to identify the coefficients, which are related to the time-constant dummy variables. The Hausman test is accomplished only with the estimates which are used both in fixed and random effects models. This means that the time-invariant variables are not considered at all. The test is based on the difference between the fixed effects and random effect estimates. The fixed effect evaluation is consistent both for null and alternative hypothesis, and the random effect is consistent only for the null hypothesis.

However, after the estimation of the models with robust standard errors this test can not be run with the Stata software. Consequently, the choice of the model to be interpreted will be explained further.

To avoid the drawback of the fixed effect model (the inability to use time-constant variables) at least to a small degree another approach of estimation was applied. The Hausman-Taylor model serves as an alternative to estimate both time-constant and time-varying parameters. It uses the within and between variation of the exogenous variables as the instruments. Particularly the individual characteristics of the exogenous parameters are treated as the instruments for the variables, which are correlated with the individual effects. The main issue here is the determination of exogenous and endogenous independent variables. This approach gives consistent coefficients for time-invariant regressors and more efficient estimates of the other parameter than in fixed effects model.

Here the dummies for industry are treated as time invariant exogenous, as they do not depend on the organization and particular decisions of the top managers. The financial coefficients (Herfindahl index, current ratio, debt-to-equity, roe and log(assets)) are time varying endogenous variables, because they are related to the managers' decisions. The dummy variables for the life cycle stage are treated as time varying exogenous.

The estimation of the Hausman-Taylor model is presented in table 9.

Table 9 Hausman-Taylor model

...

Variable	Coefficient	Standard error
Time varying endogenous

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