The Impact of Tax Risk Indicators on the Company's Market Capitalization

Journal of Environmental Treatment Techniques

2019, Special Issue on Environment, Management and Economy, Pages: 1082-1088

J. Environ. Treat. Tech.

ISSN: 2309-1185

Journal web link: http://www.jett.dormaj.com

The Impact of Tax Risk Indicators on the

Company's Market Capitalization

Regina V. Nagumanova, Tatyana V. Erina, Aigul I. Sabirova

Kazan Federal University, Institute of Management, Economics and Finance, Kazan, Russia

Received: 13/09/2019

Accepted: 22/11/2019

Published: 20/12/2019

Abstract

To date, empirical research is one of the reliable methods of scientific knowledge. It is aimed at collecting and analyzing data on

the object of study. Its purpose is to identify and establish certain dependencies and patterns. All empirical studies are based on a

clear scientific base and a rigorous organization process. In this regard, the organization’s tax risk management system, as one of the

components of the financial management system, also serves as an indicator of the effectiveness of the corporate tax management

system itself. Financial management is a complex process, which consists in the effective use of all available financial resources in

the organization. In order for the company or enterprise to be stable, and its market value to increase over time, it is necessary to

combine the efforts of all structural divisions of the company. These units should work as a single, well-coordinated mechanism, and

only then the goals of the organization will be fully achieved.

Keywords: tax risk, tax planning, risk management, company capitalization, risk factors, financial management.

much is its chaotic and unpredictable fluctuation (1, 2, 4, 6,

Introduction

10). The analysis showed that an increase in the tax burden

Given the continuity of the activities of many enterprises,

leads to a decrease in the production activity of economic

entities both in the industrial sphere and in the Russian

economy as a whole.

it is important to eliminate the imbalance of interests of

process participants, in other words, to harmonize the

organization’s financial management system, and as a result,

tax burden management. Harmonizing this system is not

necessary at one time, but systematically, comparing the

results of the process with its main goals, setting priorities

and comparing them with key indicators, monitoring and

controlling the taxation management process of the company,

in order to increase the efficiency of company management

2 Methodology

In most of the works that we examined, the indicators of

tax burden act as an effective sign during the regression

analysis, and as a factor variable - performance of the

enterprise, presented in Figure 1. According to the results of

an empirical study, there is a linear relationship between the

indicators presented in Figure 1. In addition, for the purposes

of tax planning, it is proposed to conduct a regression

analysis, where the indicator of the tax burden acts as the

effective sign, and the indicators included in the denominator

of the tax burden indicator act as the factor indicator (Figure

2). The conducted studies examine the impact of the tax

burden on the volume of production in the regions of the

Russian Federation, which is characterized by various natural

resource potentials: rich mineral resources, or knowledge-

intensive production. In other words, the authors considered

the influence of the tax burden on the main factor stimulating

economic growth in a particular region. In their opinion,

different industries and industries are not at all in the same

position in terms of fiscal pressure exerted on them (3, 5, 7, 8,

(

11, 12, 13, 14).

A business is a complex investment product, the

consumer usefulness of which is expressed in the ability to

generate net cash flows, while ensuring the growth of well-

being of owners. The system of internal corporate taxation

influences all processes of the organization, the ultimate goal

of this management is to increase the efficiency of the

enterprise as a whole.

In scientific studies, in addition to the influence of the

total tax burden as the main factor of tax risk on the economic

growth of a business entity, the influence of the very fact of

its quick and sharp change is considered, since, according to

many experts, not only (and not so much) has a detrimental

effect on the economy the magnitude of the tax burden, how

9).

Corresponding Author: Aigul I. Sabirova, Kazan Federal

University, Institute of Management, Economics and

Finance, Kazan, Russia. Email: aigylkinyes@mail.ru.

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Journal of Environmental Treatment Techniques

2019, Special Issue on Environment, Management and Economy, Pages: 1082-1088

Fig. 1: Effective and factor signs in the construction of a regression model

Fig. 2: Effective and factor signs in the construction of a regression model

Among foreign studies, one can also find works devoted

taxation, which will be disclosed in more detail in the next

to studying the effects of corporate tax planning on the

market value of a company.

paragraph of the study.

In the framework of this study, we formulated the

following hypothesis: “tax risk factors have a significant

impact on the company's market capitalization, expressed

through the indicator of economic value added”. In practice,

serious, key decisions are never taken without taking into

account tax consequences, since they, being a powerful tool

of economic regulation, in some cases are capable of forcing

enterprises to radically change the tactics of their actions. The

absence of effective tax risk management tools at the

enterprise can lead not only to heavy financial losses, but also

to the inability of the organization to continue to exist,

because due to significant tax burden (in the absence of an

effective tax planning system), the business entity is in a

much weaker competitive position market in comparison with

participants using tax optimization tools of their activities,

and directs their efforts not at achieved the final goal, and for

the payment of all necessary taxes, respectively, due to the

satisfaction of customers' needs, the market value of such an

entity is lower. The main factor of tax risk is the fluctuation

Results

The main goal of our study is to determine the impact of

corporate tax risk indicators on the company's market

capitalization. Financial management has the main goal of

ensuring the well-being of shareholders, respectively, tax

risk, as an object of financial management, can also affect the

indicator of market capitalization. Our task is to correctly

determine the main factors of tax risk and conduct a study of

their impact on market capitalization. Moreover, as the main

indicator that characterizes the market efficiency of the

company, we will choose the indicator of economic value

added or its derivatives (15, 16, 17, 18, 19, 20).

Thus, the main objective of the study is to study the

nature, direction and degree of interconnection of indicators

of corporate risk management and indicators that determine

the effectiveness of the organization. As independent

variables, we selected several indicators of corporate

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Journal of Environmental Treatment Techniques

2019, Special Issue on Environment, Management and Economy, Pages: 1082-1088

of the tax burden of the company by more than 10%. In this

regard, as the main indicator in the model, we will use the tax

and its individual divisions. EVA reflects various categories

of organization activity (Fig. 3).

burden indicator (X

current legislation, which were able to be calculated using the

SPARK database, we included other indicators, such as:

) of the organization. According to the

EVA is an indicator of the quality of management

decisions: a constant positive value of this indicator indicates

an increase in the value of the company, while a negative

value indicates its decrease. The calculation of the dependent

variable is performed according to the formula:

The ratio of income and expenses of the company (X );

Fluctuation in the amount of VAT deductions (HZ);

Fluctuation of the indicator of profitability of sales by

);

net profit (X

EVA = (NOPAT – IC) * WACC

(2)

At the same time, to improve the quality of the model, we

used the following variables:

Financial leverage (X

Absolute liquidity ratio (X

Asset mobility ratio (X ).

);

EVA = (ROIC - WACC) * IC

(3)

Thus, the inclusion of these factors in the overall system

of factor sampling is considered logical. Table 1 lists all the

variables used to test the hypothesis. To improve the quality

of the model and bring it to the form of a linear function,

absolute indicators are logarithmized. Therefore, the desired

function in general form will look as follows:

where EVA is economic value added; IC is invested capital;

NOPAT is net operating profit after taxes; WACC is

weighted average cost of capital; and ROIC is return on

invested capital. We calculated the dependent variable

according to formula 3; the quantitative data necessary for

this were taken from the SPARK database. To calculate the

tax burden, the study uses a technique developed by the

Ministry of Finance of the Russian Federation. According to

this methodology, the company's tax burden represents the

share of all tax payments paid in revenue from the sale of

goods (work, services) for the reporting period, including

income from other income:

1 2 3 4 5 6 7

LnY(t) = [LnX (t), X (t), LnX (t), X (t), X (t), X (t), X (t)], (1)

where LnY (t) is the natural logarithm of the economic value

added of the company; LnX (t) is the natural logarithm of

the relative tax burden; X (t) is the ratio of income and

expenses of the company; LnX (t) is value of VAT

deductions; X (t) is financial leverage; X (t) is net profit

margin; X (t) is absolute liquidity ratio; X (t) is asset

mobility ratio; and t is the time period (year).

ONN = [NP / (V + VD)] * 100%,

(4)

where ONN is relative tax burden; NP is the sum of all taxes

paid by the enterprise; In is revenue from sales; and VD is

revenue from other sales. Indicators of the tax burden by type

of economic activity were taken from the Appendix to the

Order of the Federal Tax Service “On Approving the Concept

of a Planning System for Field Tax Audits” dated 05.30.2007

No. MM-3-06 / 333.

As a dependent variable, an indicator of a company's

market performance, is an indicator of economic value added

(

EVA). EVA shows the excess of the company's net

operating profit after taxes and capital expenditures; and

combines the simplicity of calculation and the ability to

evaluate the effectiveness of both the enterprise as a whole

Table 1: List of variables used to build a regression model

No.

Variables

Economic Value Added (L )

Relative tax burden

The ratio of income and expenses of the company

VAT deduction (L

)

Financial leverage

Net profit margin

Absolute liquidity ratio

Asset mobility ratio

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Journal of Environmental Treatment Techniques

2019, Special Issue on Environment, Management and Economy, Pages: 1082-1088

Fig. 3: The relationship between economic value added and other characteristics of the company

The company's income and expense indicators, as well as

VAT deductions, were taken from the financial statements of

the studied companies. Financial leverage is defined as the

ratio of the total liabilities of the organization (both long-term

and short-term) to the amount of equity:

According to Figure 4, 36% of the sample (9

organizations) were enterprises engaged in the field of oil and

gas production and oil refining, 20% (or 5 organizations) in

the field of electricity; 16% (4 organizations) - in the

transport and communications industry; 4% (1 organization) -

in the field of transportation of petroleum products; 8% (2

organizations) - in the chemical industry; 4% (1 organization)

O = (DO + KO) / SK

(5)

in the engineering industry; 12% (or 3 organizations) are

where: O is financial leverage; TO is long-term obligations of

the organization; KO is short-term obligations of the

organization; and SK is the amount of equity capital of the

enterprise. Net profit margin is calculated as follows:

employed in other services. The activities of enterprises were

analyzed for 2015-2018. The sample is incredible - when

selecting enterprises, certain conditions were met, such as: (a)

legal form (public joint stock company) and (b) the presence

of financial statements compiled in accordance with Russian

accounting standards for the period under review. The sample

we have formed can be considered representative of joint-

stock commercial enterprises of Russia, since: each unit of

the general population has an equal probability of falling into

the sample; the selection of variables was made regardless of

the trait we are studying; the number of units in the sample is

large enough; the sample is relatively uniform. As a result of

the Correlation program, we calculated a matrix of paired

correlation coefficients, which is presented in the Table 2.

Based on the analysis of the matrix of pair correlation

coefficients, we can draw the following conclusion: none of

the variables forms significant relationships with others,

which means that we can continue the study and build a

regression model. The results of the regression analysis for

the first hypothesis are presented in the Table 3.

ROS = PE / V

(6)

where ROS is net profit margin; PE is the net profit of the

organization; and In is revenue. The absolute liquidity ratio is

calculated as follows:

Kabl = (DS + KFV) / TO

(7)

where: Kabl is absolute liquidity ratio; DS is cash; KFV is

short-term financial investments; and THAT is current

liabilities. The value of this indicator can also be found in the

SPARK database. Asset mobility ratio was calculated:

KMobak = (DS + KFV) / OA

(8)

where Kmobak is asset mobility ratio; DS is cash; KFV is

short-term financial investments; and OA is the value of

current assets. In addition to the financial statements of the

companies, the study also used industry-specific non-

diversified risk ratios (leveraged beta) from the website of

Asfat Damodaran. 25 Russian enterprises were selected as the

empirical base, most of which are employed in the industrial

sector of the economy. The industry sample structure is

shown in Figure 4.

As is known, in order to obtain the best results from least-

squares analysis, it is necessary to fulfill the following basic

assumptions: homoskedasticity (constant variance of

deviations) and the absence of autocorrelation. The analysis

showed that in the model under consideration there is no

autocorrelation of residuals and variances of deviations of

significant variables are constant. Testing for the absence of

multicollinearity of factors using the method of inflation

factors showed that multicollinearity is absent in the model.

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Journal of Environmental Treatment Techniques

2019, Special Issue on Environment, Management and Economy, Pages: 1082-1088

Fig. 4: Sectoral structure of the sample, in percent

Table 2: Matrix of paired correlation coefficients

0,2769

0,3637

0,3508

0,313

0,1692

0,373

-0,2182

0,0032

-0,1519

-0,1223

0,4014

0,0165

-0,0502

-0,162

0,0049

-0,3837

0,0519

-0,2134

-0,1286

-0,0349

-0,3122

0,2507

0,0822

-0,1692

-0,0445

0,2023

0,136

0,2769

0,3637

0,313

-0,2182

0,4014

-0,3837

0,2507

0,3508

0,1692

0,0032

0,0165

0,0519

0,0822

0,373

-0,1519

-0,0502

-0,2134

-0,1692

-0,1223

-0,162

-0,1286

-0,0445

0,0049

-0,0349

0,2023

-0,3122

0,136

0,1945

Source: compiled by the author

In general, the results of the analysis are at a fairly high

level of significance. The multiple correlation coefficient is

determination, which also indicates a good specification of

the regression equation. The assessment showed that the

model is statistically significant at significance levels of 90%.

The significance of individual parameters is estimated using

Student's t-test. According to the results of the study, it turned

out that the empirical free coefficient and all the coefficients

considered by us for independent variables are statistically

significant at significance levels of 90%. The regression

equation takes the following form:

0.75. It shows the tightness of the combined influence of

factors on a productive trait. In our case, the multiple

correlation coefficient indicates a close relationship between

the indicator of economic value added and the independent

variables included in the model. The value of the coefficient

of determination is 66%, which confirms a sufficient degree

of conditionality of the variation of the result by variation of

factors, in other words, a fairly close relationship of factors

with the result. The adjusted coefficient of determination is

1 2 З 4 5

Y=-0,65+0,4*Х +0,04*Х +0,01*Х -0,02*Х +0,02*Х -

64%. In magnitude, it is close to the coefficient of

0,06*Х +0,65*Х

(9)

086

Journal of Environmental Treatment Techniques

2019, Special Issue on Environment, Management and Economy, Pages: 1082-1088

value of VAT deductions; X

is financial leverage; X is net

where Y is economic value added; X

is relative tax burden;

profit margin; X

mobility ratio.

is absolute liquidity ratio; and X is asset

is ratio of income and expenses of the company; X

Table 3: Checking the significance of the coefficients of the regression equation

Determination

t - statistics

F- statistics (Fcr =

2,745)

Factors

Coefficients

coefficient

Relevance

tcr = 2,605)

-0,652167

0,397116

-4,67

3,761

3,416

3,673

-4,646

5,365

-5,256

6,395

Significant

0,0359225

0,0129198

-0,0234624

0,0234530

-0,0606797

0,646146

,66

311,3

Source: compiled by the author

The regression analysis revealed certain relationships

between the tax risk indicators and the market capitalization

of the companies included in our sample, thereby confirming

the main hypothesis posed in the study.

For the total sample of enterprises, indicators of corporate

tax risk correlate with company value at an average level

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