ISSN 0798 1015

Vol. 40 (Number 35) Year 2019. Page 19

Social inequality and poverty as a challenge to the development of human potential of the national economy

Desigualdad social y pobreza como un desafío para el desarrollo del potencial humano de la economía nacional

KORMISHKINA, Ludmila A. 1; KORMISHKIN, Evgenii D. 2; KOLOSKOV, Dmitrii A 3.; IVANOVA, Irina A. 4 & KORMISHKIN, Aleksander E. 5

Received: 30/07/2019 • Approved: 07/10/2019 • Published 14/10/2019

Contents

1. Introduction

2. Method

3. Results

4. Discussion

5. Conclusion

Acknowledgments

Bibliographic references

1. Introduction

1.1. Introducing the problem

A distinctive feature of modern economics is the awareness that it is necessary to replace the current economic paradigm, which was formed in the 18th–20th centuries, with a new one that does not place “economic wealth as such” in the center of the socioeconomic system (Stein, 1874) but the human, with the whole range of his abilities and needs, including the need for self-fulfillment; human potential, its fullest possible development and effective use; and human capital that can bring profit to its owner (Brown & Lauder, 2000; Bulanov, 2014; Senchagov, 2015; Ilyin, 2017). This has determined the need for a deep social reorientation of economic priorities and, therefore, a transition from “the human in the economy” to a “human-oriented economy” in which human development is both the ultimate goal of social production and a condition for its sustainable development (Human Development Report 2010, 2010). This conclusion fully complies with the well-known statement in Karl Marx’s Economic Manuscripts (1857–1859): “the society itself, that is, the person himself in his social relations, is the end result of the process of social production ... the immediate process of reproduction is in this case only an element” (Marx, 1968).

It should be noted that a “human-oriented economy” functions according to the well-known principles of humanistic development and an inclusive society in which everyone has access to all social benefits, including education, health care, vocational training, fast transport, and an ecologically clean environment (Kormishkina et al., 2018). In addition to this, the leading countries of the European Union are actively exploring the idea of ​​an inclusive society that complies with the nature, functions, and role of social capital.

However, until recently, studying the reproductive role of people in the economy, researchers mainly focused on labor potential, that is, the physiological and psychological capabilities, innate abilities and acquired knowledge and skills that people use or can use in social production at the current stage of civilization development (Lvov, 1999). However, labor potential is only one of the components of human potential and is determined by its functioning. At present moment researchers define human potential as the accumulated stock of physical and moral health, universal cultural and professional competencies, creative, entrepreneurial, and civic activities implemented in various fields, as well as in the level and structure of human needs (Bulanov, 2011, 2014; Senchagov, 2015).

We believe that such a definition of human potential emphasizes not its quantitative value, but the assessment of the quality of life and real economic conditions required for creating and using human potential in labor or other socially important activities. Human potential can be properly realized only under appropriate conditions, acting as a source not only of income for its owner, but also as a tool for ensuring economic growth and social development of the whole society.

Therefore, in the 21st century the increasing social inequality and growing multidimensional poverty not only in the underdeveloped, but also in the leading countries are among the main challenges to the development of human potential and its effective use. It is no coincidence that the indicators reflecting trends and patterns in the poverty level and profile are among key indicators used to analyze and evaluate the well-being achieved at different phases of economic development, the effectiveness of the implemented social policy for households with a low economic potential, deprivation and social isolation of individuals and/or a group of individuals from a certain set of goods, services of socially important needs, the absence of which in any country nowadays is considered unacceptable (Sachs, 2011; Diržytė et al., 2017; Balynskaya & Ponomarev, 2018).

1.2. The importance of the problem

In all countries, including Russia, the 21st century was marked by growing social inequality, which is not limited to the material aspect, but manifests itself in access to education and medical care, good jobs, housing conditions, opportunities for children, etc. Nowadays the enormous disparity is accompanied, on the one hand, with the concentration of capital and national wealth in the hands of an increasingly narrow group of people (Piketty, 2015), and on the other, with the steadily high number of poor people. For instance, according to the estimates of the Credit Suisse Bank experts, currently 1% of the population owns half of the planet’s entire wealth (Grigoriev, 2016). According to the WID data (World Inequality Database, n.d.), in 2016 the share of the income of the richest 10% estimated: in the USA—76%, in China—66%, and in France—53%. In the Russian Federation, 10% of the richest people own 87% of the total national wealth (Ilyin, 2017). At the same time, in 1990–2016 the income of this category of Russians grew at an average annual rate of 15% and was much higher than the average Russian value of this indicator that equaled 1.3%. The main indicator of inequality, the Gini coefficient, increased over this period from 0.31 to 0.56 and significantly exceeded the maximum permissible value for this indicator accepted in the world (30—40%) (Novokmet et al., 2017).

These data suggest that in modern Russia inequality is not only high, but excessive, which explains why so many people remain poor. According to the World Bank, in Russia, the share of the population with cash income below the subsistence minimum in 2017 was 13.3% (in the world, the adopted threshold value for this poverty indicator should not exceed 7%). According to the European poverty line (60% of the median income), the level of poverty for the whole population reached 21.3%, and for families with children—26.5% (in comparison, in the EU countries, the share of the poor according to this criterion in 2017 estimated 16.9%).

Such a situation leads to the so-called “poverty trap”, in which people lose motivation to economic activity, including labor, they become more dependent and inert; the quality of human reproduction decreases, and its transformation into human capital is hindered (Stiglitz, 2015, 2016; Sviridov & Grabova, 2015).

Considering the above, overcoming excessive social inequality and poverty that limit human development and its effective use, as well as entail a threat to socio-political stability in the country, undoubtedly, should be among the main priorities of Russia’s national development as a real welfare state: the Constitution of the Russian Federation (Article 7, paragraph 1) reads that “The Russian Federation is a social state whose policy is aimed at creating conditions for a worthy life and free development of man”. It is no coincidence that, in the Strategy of the Economic Security of the Russian Federation for the period until 2030, approved by Decree of the President of the Russian Federation No. 208 of May 13, 2017, the reduction of poverty and wealth disparity is identified as one of the main objectives of the state policy in human development aimed at ensuring national economic security and strengthening the power of the state.

Thus, the problem of inequality and poverty that became the main topic of public debates about human development and economic growth in a 2006 World Bank report on world development (World Bank, 2006) was and remains relevant for all countries, including Post-Soviet Russia.

1.3. Literature review

It is not a coincidence that over the past fifteen–twenty years the global scientific community has been focused on the issues related to the emergence of a new economic paradigm that would be able to reverse negative social trends (primarily, increasing income disparity and gap in the society; the concentration of capital and wealth in the hands of narrower groups; large-scale poverty and destitution, etc.). These were observed not only in the so-called periphery, but also in industrialized economies and are conditioned by the neoliberal concept of socio-economic development. In this context, nowadays international economists actively study and discuss the works of Sachs (2011), Piketty (2015), Stiglitz (2015, 2016), and Krugman (2014) that present other interpretations (different from the original) of the hypothetical Kuznets curve (1955), using the so-called formula of the “fundamental law” by Piketty (2015), the diagnosis of “systemic and staged regression” by Krugman (2014), etc. These papers form the theoretical and methodological basis for further study of the most acute of the global problems—the phenomenon of poverty.

Talking about social inequality and poverty as a challenge to the development of human potential of the national economy, we believe that in modern economics the emphasis should be placed not on the concept of absolute poverty (“by income”), but the deprivation theory (poverty “by deprivations”). The deprivation approach, to a large extent created by Townsend (1979), implies that the poor population is identified according to a set of deprivations an individual experiences that prevent him from maintaining a lifestyle that is considered minimally acceptable at this stage of social development (Slobodenyuk & Tikhonova, 2011).

Thus, the analysis of economic papers shows that when studying the effect of inequality on human potential, one should consider the multidimensionality of poverty, which can currently manifest itself, among other things, in a person’s perception of the severity of different types of social inequality, for instance, income inequality, access to health care and education, good jobs, housing conditions and property ownership (Ilyin, 2017).

In addition, the essence of and the correlation among the concepts such as “human capital,” “human potential,” and “labor potential” (Bulanov, 2014, p. 81) are of fundamental importance within the study context. The authors of this article support the interpretation of human capital proposed by Fischer et al. (2001, p. 303), who define it as “a measure of the person’s ability to generate income. Human capital includes innate abilities and talent, as well as education and acquired qualifications”. This definition of human capital, in our opinion, is more accurate than the well-known definition formulated by Becker (2003), since it reflects the essence of the category “capital.” Therefore, if a person’s knowledge, skills, and motivation do not generate income, they are not treated as human capital and should be interpreted as a consumer good, or human (but not labor) potential that, under certain conditions, can be demanded and used as human capital.

1.4. The research hypothesis

2. Method

The authors tested the hypothesis on the impact of excessive inequality and multidimensional, large-scale poverty on the development of human potential and its transformation into human capital using the methods described below.

2.1. Database development

Database creation commenced with building a representative sample of statistical aggregates and collecting necessary statistical information. This was followed by registering the values of factors and indicators within a model of various temporal and spatial intervals of the relevant phenomena, including:

- Time series (GDP per capita at purchasing power parity; number of people employed in the economy; the share of the population with income below the subsistence minimum, etc.), according to the statistical data of the Russian Federation for the period from 1992 to 2016;

- Panel data of regional statistics pertaining to the Russian Federation for the period from 2013 to 2017 (380 observations, 24 factors) characterizing the dynamics and level of economic development; ecological sustainability; social well-being; and development of education and health care in the regions of the Russian Federation;

- Spatial data characterizing the indicators of human development in various countries in 2018.

2.2. Intelligent data analysis

Intelligent data analysis, or data mining, was carried out using Statistica software and included:

- Model specification to identify the composition of endogenous and exogenous variables;

- Establishing initial premises and limitations of econometric models;

- Performing correlation analysis to identify possible multicollinearity of factors and adjusting them if necessary;

- Determining the nature, strength and direction of the relationship between endogenous and exogenous variables;

- Identification modeling that includes linear and non-linear (polynomial) regression analysis performed using the usual and generalized least squares methods;

- Factor analysis of data for subsequent grouping, the construction of the main components (integral indices) characterizing the indicators of economic development, environmental sustainability, social well-being, educational development and health care;

- Modeling the main components as linear combinations of normalized exogenous variables reflecting the latent core characteristics of each group;

- Building a multiple linear regression equation on the main components using a step-by-step analysis algorithm to identify data structures and relationships between variables (their classification and reduction), as well as decreasing the correlation between explanatory variables and reducing the risk of omitting factors that are found to be statistically insignificant by performing the t-test;

- Verification of the models constructed in the study using the adjusted coefficient of determination, testing hypotheses about the statistical reliability of the regression by the F-test and t-test.

The study used data from the Federal State Statistics Service of the Russian Federation (n.d.), as well as various international databases (CEDLAS and World Bank, 2018; CRED EM-DAT, 2018; Eurostat, 2018; Internal Displacement Monitoring Centre, 2018; International Monetary Fund, 2018).

3. Results

As noted above, increasing requirements to a person is a characteristic feature of the modern stage of social development. This can be explained by a qualitative change in the role of individual members of society in reproduction process. At the same time, the competitiveness of national economies is to a larger extent determined by factors such as capacity for innovation and technological advances. The ability to benefit from these developments depends on the workforce quality, and the motivation and responsibility of workers, among other factors—in other words, the country’s human potential.

As a part of the present investigation, the authors established that, in 2017, the quality of human potential, which is typically assessed for statistical reasons using the human development index (HDI), was high the Russian Federation and estimated 0.816 (with the values for this cluster ranging from 0.0 to 1). To estimate the dependence of HDI (Y) on its main components—life expectancy index ranking 49th out of 59 countries, as indicated by the HDI value of (X1), education level index (X2), GDP index per capita (in US dollars at purchasing power parity (PPP) of national currencies, X3)—we constructed several polynomial regression models, as shown in Figures 1−3).

Figure 1
Polynomial Regression Model of the Dependence of the Human
Development Index on the Life Expectancy Index (X1)

Source: Compiled by the authors

The analysis of the data depicted in Figure 1 suggests that human development in the countries characterized by high HDI values is strongly dependent on life expectancy. The correlation ratio was η = 0.84. The actual value of the F-test was F = 68.92, Fcr(α = 0.1; f1 = 2; f2 = 56) = 5.01. The actual value of the t-test was tа1 = –1.68; tа2 = 1.94, tcr(α = 0.1; f2 = 56) = 1.67.

In terms of life expectancy (71.2 years), the Russian Federation is only the 58th out of 59 and is quite significantly behind the leading countries regarding this indicator (Hong Kong, China (SAR)—84.1 years; Japan—83.9; Switzerland—83.5; the average life expectancy exceeds 80 years in 33 countries).

Figure 2
Polynomial Regression Model of the Dependence of the Human
Development Index on the Average Duration of Training (X2)

Source: Compiled by the authors

Having analyzed the data in Figure 2, we could conclude that human development in the countries of this cluster greatly depends on the average period of training. The correlation ratio was η=0.63. The actual value of the F-test was F=18.09 (Fcr(α=0.01; f1=2; f2=56)=5.01), and the actual value of the t-test was tа1= -0.95; tа2 = -1.41 (tcr(α=0.2; f2=57)=1.3)). Regression parameters are not statistically significant at a significance level of 0.1. Consequently, it can be concluded that the influence of the average duration of training on the human development index is not significant enough for the countries of this cluster compared to the countries with low human development indices.

Regarding the duration of training (12 years), the Russian Federation, along with Hong Kong, ranks the 30th out of 59 countries in this cluster; the leaders according to this indicator are Germany (14.1), Switzerland and the USA (13.4), Canada (13.3), and others. On average, people study less than 10 years in these 10 states with a high HDI: Argentina (9.9), Spain (9.8), Qatar (9.8), Saudi Arabia (9.5), Oman (9.5), Bahrain (9.4), Portugal (9.2), Brunei Darussalam (9.1), Uruguay (8.7), and Kuwait (7.3).

Figure 3
Regression Model of the Dependence of the Human Development Index on the Gross
National Income per Capita at the Purchasing Power Parity (PPP) of National Currencies (X3)

Source: Compiled by the authors

According to the data presented in Figure 3, it can be concluded that human development in the countries of the analyzed cluster is strongly connected with the gross national income per capita at the PPP of national currencies. The correlation ratio was η=0.72. The actual value of the F-test was F=29.92 (Fcr(α=0.01; f1=2; f2=56)=5.01), and the actual value of the t-test was tа1=7.05; tа2= -5.92 (tcr(α =0.01; f2=57)=2.66)).

Regarding this factor variable, in this cluster the Russian Federation (USD 24,648) ranks the 48th out of 59, with the following countries taking the leading positions: France (USD 116,818), Slovakia (USD 97,336), Japan (USD 82,503). This figure exceeds USD 25,000 per capita in 47 countries with a high HDI, and is less than USD 20,000 in six countries (Bahrain (USD 19,930), Spain (USD 18,740), Italy (USD 18,461), Argentina (USD 16,779), Saudi Arabia (USD 16,323), and Uruguay (USD 15,743).

As we can see from the above, the gap between countries connected with the levels of human development reflects the inequality in the access to education, health care, good jobs, property ownership, which may be due to the inequality in income, place of residence, etc. If the problem of social inequality in the country is not properly addressed; if “social elevators” stop working and individuals cannot easily and effectively improve their material and social status, inequality may become a destructive factor in the development of human potential.

This necessitated the introduction of the human development index due to inequality (HDII) in 2010. It is now used for scientific and statistical reasons. Considering the inequality of the global HDI for 2017, it decreased from 0.728 to 0.582, which means an average decrease in the global HDI caused by inequality by ≈20 pp. The volume of the reduction ranges from 3.6 pp in Japan to 45.3 pp on the Comoros.

It should be mentioned that the losses due inequality are smaller for the countries with a very high level of human development than for the countries with lower HDIs (Figure 4).

Figure 4
Reduction in HDII Values due to Inequality, by Groups of
Countries with Different Levels of Human Development, 2017

In the course of the study, we discovered a kind of paradox: Russia, with a very high HDI value by human development, at the same time is a “rich country with poor population” (Tikhonova, 2013). The dynamics of the volume and level of poverty in Russia for 2000–2016 due to different types of inequality and their perception (Sen, 1992, 1997) is shown in Figure 5.

It should be noted that the current situation with poverty in the Russian Federation is no longer connected with the overall economic situation in the country, but directly with the behavior of the poor (long-term unemployment, alcohol or drug addiction), various kinds of problems (severe illness, disability) or family problems (death of the income earner, fire, etc.) which were not properly compensated through the state social policy.

Figure 5
Poverty in Russia: Dynamics of
the Volume and Level of Poverty

Source: Compiled with the data of the Federal State
Statistics Service of the Russian Federation, n.d.

Within the working scientific hypothesis of this study (Section 1.4.), we concluded that labor potential plays a crucial role in the current human potential of the Russian economy.

When demanded and applied, human potential is transformed into human capital, which brings income to its owner. According to this logic, involvement in economic activities and poverty, in our opinion, can be considered factors affecting income inequality.

To determine the nature, strength and direction of the relationship between the resultant indicator Y1 (Russia’s GDP per capita at the purchasing power parity, USD) and the factor attributes X4 (employed in the economy, thousand people) and X5 (the share of the population with income below the subsistence minimum, %), we conducted multiple correlation analysis (Table 1).

Table 1
Matrix of Paired Correlation Coefficients

Source: Compiled by the authors

After analyzing the data in Table 1, we could conclude that there is a strong direct relationship between Y1 and X4, a strong reverse relationship between Y1 and X5, and a noticeable reverse relationship between factors X4 and X5.

Next, we applied a sequential connection method to build a multiple regression model of the dependence of the Russian GDP per capita at PPP (Y1) on the number of people employed in the economy (X4) and the share of the population whose income is below the subsistence minimum (X5) (1). Constructing this model, we used statistical information presented in the form of time series from 1992 to 2016.

Thus, the constructed model (1) can be used for research and forecasting. After analyzing this econometric model and economic interpretation of its parameters, we could draw the following conclusions:

1. An increase in the number of people employed in the Russian economy by 1000 will drive a growth in the GDP per capita at PPP by USD 0.83 as long as other factors remain at a constant average level;

2. An increase in the share of the population with incomes below the subsistence minimum by 1% will lead to a decrease in the GDP at PPP by USD 736.20 per capita as long as other factors remain at a constant average level.

The previously constructed polynomial regression model of the dependence of human development on the life expectancy index demonstrated that regarding this indicator Russia significantly lags behind other countries in the group with a very high HDI.

At the same time, it is known that life expectancy at birth is the most important indicator of the quality of life. It is determined, apart from other things, by different types of inequality and reflects the life potential of the population. The latter is estimated as the number of people taking into account the lived or cumulative time (Lvov, 1999). The number of people can go down, while the number of years they have lived, and therefore, the possible activity may increase. Long life and long-term health of the majority of the population is a historically new phenomenon. It is clear that in the context of the slowdown and then the cessation of growth of the Russian population special attention should be paid to the problem of preserving and increasing the life potential of the population.

The protracted stagnation in the health care and life protection of Russians means a huge loss of the population’s life potential. Such losses affect all the main components: the cumulative years of working life and the cumulative lifetime of economically active and economically inactive people.

4. Discussion

There is no doubt, that to overcome the current situation in Russia connected with growing social inequality, which goes far beyond material well-being, and large-scale poverty manifesting itself in various forms, the government should deal with many factors. However, we believe the economic policy conducted by the state plays the crucial role. This means that the indicators of GDP, GRP (gross regional product), population income, the system of stimulating economic activity and social protection of the poor and socially vulnerable groups should be considered when solving such a complex strategic task of the national economy as improving the quality of life and human development. The latter embraces various social issues (health care, education, development of fundamental science, culture, etc.). Regarding the current practice of the leading countries implementing the UN Development Program (UNDP), actively implemented for more than 20 years, the existing achievements of scientists in the economic theory of human capital and human potential, as well as a high degree of social inequality and specifics of Russia’s poverty profile, we firmly believe that the effective socio-economic policy of the Russian Federation should be formed according to the principle of “active industrial policy—progressive taxation—targeted social support of the poor and vulnerable groups” (Kormishkina et al., 2018).

Talking about Russia’s current situation, an active industrial policy would mean the speeded-up neo-industrial modernization of the economy—digital, high-tech, and technotronic. Its qualitative measure is a progressive change in the nature of labor and employment, accompanied by a reduction in the share of physical labor and an increase in the share of mental labor.  Intellectual labor should become widespread and dominant, and it should be measured as the share of automated, digitized jobs in the national economy (primarily in material production) ensuring the growth of labor productivity and decent pay for it (Gubanov, 2014, 2017; Bulanov, 2014). In such a context, neo-industrial modernization is of fundamental importance not only for reversing such a negative trend as increasing economic inactivity and dependency of the working-age population due to poor motivation to work. Thus, it contributes to improving the quality of human potential and its transformation into human capital.

It should be noted that a progressive taxation scale is generally seen as the main condition for successful functioning of national income distribution systems aimed at increasing social justice and reducing poverty. However, in 2001, Russia abandoned this approach and, as is known, has a flat tax rate on personal income of 13%. We share the opinion of the experts who see the flat tax rate as a kind of a multiplier of excessive social inequality: the income of the poor goes down, whereas that of the rich increases (Voeykov & Anisimov, 2018).

When high incomes are subject to progressive taxation and tax revenues are used not for direct transfers to the poor but to raise low wages, then even with excessive inequality, adopting this policy, the country can increase the overall productivity of the economy and ensure the development of the human potential (Kormishkina & Koroleva, 2016).

This conceptual approach to building an effective economic policy includes two main directions.

The first is connected with a labor market policy that should contribute to: a) a situation when a significant part of the employed population ceases to be poor, which is achieved through providing additional training and professional retraining according to the requirements of the neo-industrial economic modernization; b) creating conditions for those economically inactive people who are currently unemployed but are ready to and can work.

The second direction of social policy should include various targeted social support programs for the poorest people and groups with high risks of poverty. These programs should comply with family life cycles and combine self-reliance incentives and cash benefits. Talking about modern Russia, these can be regional programs to increase the self-sufficiency of families, for instance, a “social contract”, paying a monthly poverty allowance from the unused maternity capital, etc., which deploys the system of state social protection of poor families with children.

5. Conclusion

At present moment, reducing excessive social inequality and large-scale poverty that are accompanied with various social challenges and risks is one of the most important tasks of state policy for any country (a developed or periphery one) since this can maintain human potential and ensure its effective use for sustainable socio-economic development. However, even today, when the world understands the critical importance of social and demographic problems caused by excessive inequality and multidimensional poverty and is taking greater efforts to solve them, Russian state policy in this area is still chaotic and irregular, has no clear directions and is not seen as a top priority (Glazyev, 2017). This has a highly negative impact on the economic growth and demographic dynamics, as well as on the quality of human potential. Within the current approach to solving the problem of excessive social inequality and large-scale poverty, this problem, under certain conditions, can lead to social and political tension and instability.

Acknowledgments

The article was written with the financial support of the Russian Fund for Fundamental Research (RFBR), project No. 18-010-00756 “Development of the theory and methodology of research into the phenomenon of social and economic inequality in the context of the neo-industrial paradigm”.

Bibliographic references

Balynskaya, N. R., and Ponomarev, А. V. (2018). Current issues in the development of modern political and economic processes in Russia and Europe. Economics and Politics, 2(12), 5-7.

Becker, G. S. (2003). Human Behavior: An Economic Approach: Selected Works on Economic Theory. Moscow: Higher School of Economics Publishing House.

Brown, Ph., and Lauder, H. (2000). Human capital, social capital and collective intelligence. In S. Baron, J. Field, and T. Schuller (eds.), Social Capital. Critical Perspectives (pp. 226-249). Oxford: Oxford University Press.

Bulanov, V. S. (2011). Modernization of the Russian economy and human development. Society and Economy, 11-12, 20-34.

Bulanov, V. S. (2014). Fundamentals of Socio-Economic Theory of Human Development. Moscow: Prospekt.

CEDLAS and World Bank. (2018). Socio-Economic Database for Latin America and Caribbean. Retrieved from www.cedlas.econo.unlp.edu.ar/wp/en/estadisticas/sedlac/estadisticas/

CRED EM-DAT. (2018). The International Disaster Database. Retrieved from www.emdat.be

Diržytė, A., Rakauskienė, O. G., and Servetkienė, V. (2017). Evaluation of resilience impact on socio-economic inequality. Entrepreneurship and Sustainability Issues, 4(4), 489-501.

Eurostat. (2018). European Union Statistics on Income and Living Conditions. Retrieved from http://ec/europa.eu/eurostat/web/microdata/european-union-statistics-onincome-and-livingconditions

Federal State Statistics Service of the Russian Federation. (n.d.). Retrieved from http://www.gks.ru/

Fischer, S., Dornbusch, R., and Schmalensee, R. (2001). Economy. Moscow: Delo.

Glazyev, S. Yu. (2017). Why is the Russian economy not growing? Retrieved from http://www.glazev.ru/articles/6-jekonomika/54326-pochemu-ne-rastet-rossiskaja-jekonomika

Grigoriev, I. (2016). “Capital” by T. Piketty and “capital” by K. Marx. The Economist, 6, 25-34.

Gubanov, S. S. (2014). New industrialization and the recycling sector. The Economist, 12, 3-11.

Gubanov, S. S. (2017). Neo-industrial development paradigm: A brief summary. The Economist, 11, 22-39.

Human Development Report 2010. (2010). The Real Wealth of Nations: Pathways to Human Development. New York, NY: United Nations Development Programme. Retrieved from http://hdr.undp.org/sites/default/files/reports/270/hdr_2010_en_complete_reprint.pdf

Ilyin, V. A. (2017). “Crony capitalism”— a source of social inequality in modern Russia. Economic and Social Changes: Facts, Trends, Forecast, 10(6), 9-23.

Internal Displacement Monitoring Centre. (2018). Global Internal Displacement Database. Retrieved from www.internal-displacement.org/database

International Monetary Fund. (2018). World Economic Outlook Database. Retrieved from www.imf.org/en/Data

Kormishkina, L. A., and Koroleva, L. P. (2016). Taxation of wealth: A view in the context of ensuring neo-industrial development and inclusive economic growth. Taxes and Taxation, 1, 28-43.

Kormishkina, L. A., Kormishkin, E. D., Koloskov, D. A., and Ivanova, I. A. (2018). Subsistence minimum as a criterion of poverty (measurement, facts and politics). Journal of Applied Economic Sciences, 13(5), 1214-1225.

Krugman, P. (2014). Why we are in a new gilded age. The New York Review on Books, 61(8). Retrieved from https://www.nybooks.com/articles/2014/05/08/thomas-piketty-new-gilded-age/

Kuznets, S. (1955). Economic growth and income inequality. The American Economic Review, 45(1), 1-28.

Lvov, D. S. (1999). Path to the 21st Century: Strategic Problems and Prospects of the Russian Economy. Moscow: Publishing House “Economy“.

Marx, K. (1968). Economic Manuscripts (1857-1859). In K. Marx, and F. Engels, Complete Works, 2nd ed. In 50 Volumes, Vol. 46, Part 2. Moscow: Politizdat.

Novokmet, F., Piketty, T., and Zucman, G. (2017). From Soviets to Oligarchs Inequality and Property in Russia, 1905-2016. Cambridge: National Bureau of Economic Research.

Piketty, T. (2015). Capital in the 21st Century. Moscow: Ad Marginem Press.

Sachs, J. D. (2011). The End of Poverty. Economic Opportunities of Our Time. Moscow: Gaidar Institute Publishing House.

Sen, A. K. (1992). Inequality Re-Examined. Oxford: Clarendon Press.

Sen, A. K. (1997). On Economic Inequality. Enlarged Edition with a Substantial Annex “On Economic Inequality after a Quarter of Century“. Oxford: Clarendon Press.

Senchagov, V. K. (2015). Economic Security of Russia. Moscow: Binom. Knowledge Laboratory.

Slobodenyuk, E. D., and Tikhonova, N. E. (2011). Heuristic capabilities of absolute and relative approaches to the study of poverty in the Russian conditions. Sociology: Methodology, Methods, Mathematical Modeling, 33, 5-27.

Stein, L. (1874). Management Doctrine and Management Law with the Comparison of Papers and Legislation of France, England and Germany. St. Petersburg: A. S. Gieroglifov.

Stiglitz, J. (2015). The Price of Inequality: How Today’s Divided Society Endangers Our Future? Moscow: Eksmo.

Stiglitz, J. (2016). The Great Divide: Social Inequality, Or What Can the Remaining 99% Do? Moscow: Eksmo.

Sviridov, N., and Grabova, O. (2015). Poverty trap: Trends and transformations. The Economist, 9, 39-48.

Tikhonova, N. E. (2013). The Phenomenon of Poverty in Modern Russia. Moscow: Higher School of Economics.

Townsend, P. (1979). Poverty in the United Kingdom. A Survey of Household Resources and Standards of Living. New York: Penguin Books.

Voeykov, M. I., and Anisimov, G. V. (2018). Political Economy of Inequality. Moscow: Lenand.

World Bank. (2006). Equity and Development: World Development Report. New York: The World and Oxford University Press.

World Inequality Database. (n.d.). Retrieved from https://wid.world

1. Department of Economics. Ogarev Mordovia State University, Saransk, Russia

2. Department of Economics. Ogarev Mordovia State University, Saransk, Russia

3. Department of Economics. Ogarev Mordovia State University, Saransk, Russia. Email: koloskovdmitriy@yandex.ru

4. Department of Economics. Ogarev Mordovia State University, Saransk, Russia

5. Medical Institute. Ogarev Mordovia State University, Saransk, Russia.