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The uneven distribution of welfare not only hinders social fairness but also affects the optimal allocation of resources for rural residential land. Recourse to traditional welfare theory or Amartya Sen's function and ability welfare theory is inappropriate in this situation as neither is focused on the influence of welfare differences. Therefore, this study aims to provide a new focus for welfare economics in integrating the concept of the internal group welfare gap into overall welfare evaluation. Fuzzy mathematics is applied to calculate welfare and the concept of the Gini coefficient is used to evaluate the welfare gap. The resulting model is applied to the cities of Guangzhou, Chongqing, and Wuxi before and after rural residential land circulation (RRLC) to determine their resulting changes in welfare and welfare gap. From this, it is found that, after RRLC, the farmers' overall welfare increased by 17.5%, 15.1%, and 23.5% respectively, while the welfare gap of Guangzhou and Wuxi was improved, and Chongqing was decreased. This means the welfare gap widened in Guangzhou and Wuxi, while narrowed in Chongqing. Concluding remarks call for increased government attention to the fair distribution of welfare between different groups of farmers by increased social security and a more detailed consideration of the groups involved.

We construct unanticipated government spending shocks for 103 developing countries from 1990 to 2015 and study their effects on income distribution. We find that unanticipated fiscal consolidations lead to a long-lasting increase in income inequality, while fiscal expansions lower inequality. The results are robust to several measures of income distribution and size of the fiscal shocks, to an alternative identification strategy, across expansions and recessions and across country groups (low-income countries versus emerging markets). An additional contribution of the paper is the computation of the medium-term inequality multiplier. This is on average about 1 in our sample, meaning that a cumulative decrease in government spending of 1 percent of GDP over 5 years is associated with a cumulative increase in the Gini coefficient over the same period of about 1 percentage point. The multiplier is larger for total government expenditure than for public investment and consumption (with the former having larger effect), likely due to the redistributive role of transfers. Finally, we find that (unanticipated) fiscal consolidations lead to an increase in poverty.

Carbon emission allowances (CEAs) are critical to regional economic growth against the background of tackling global climate change, and CEA misallocation may be detrimental to productivity and carbon emission performance. However, whether Chinese provincial CEAs are misallocated over the past decades has not yet been thoroughly investigated. For this purpose, this study first defines CEA misallocation based on the concept of provincial CEA marginal outputs; then we develop a distortion index to measure CEA misallocation by extending the conventional Gini coefficient method. Finally, an empirical analysis of Chinese provincial CEA misallocation throughout 2000–2017 is presented. The results indicate the existence of Chinese provincial CEA misallocation, as the distortion index increases from 0.229 to 0.279 over 2000–2017, implying that Chinese provincial CEA misallocation is aggravated. At the regional level, we find that the CEA misallocation of the western area is relatively the most serious, while that of the central area is not obvious. The CEA misallocation in the western area aggravates the CEA misallocation of the entire nation. We further discuss how to alleviate CEA misallocation by investigating the distortion index in different carbon emission reduction scenarios. We find that the distortion index of 2017 can be reduced to 0.272 compared with 0.279 in the actual scenario if the provinces with CEA marginal outputs lower than the national level reduce their emissions by 3%. The results indicate that controlling the emissions of the provinces with lower CEA marginal outputs may be an effective way to alleviate CEA misallocation.

Esports is often described as a growing industry ripe with financial opportunities for young professional, competitive gamers. However, these claims rarely consider how income is distributed amongst players. This study uses prize earnings data from 2005 to 2019 to examine labor market inequality and related social inequalities and social stratifications. Lorenz curves and Gini coefficients show that inequality has increased in the labor market overall and the labor markets for the five top games based on total prizes awarded ( Dota 2, Counter-Strike: Global Offensive, Fortnite, League of Legends, StarCraft II). Competitors can expect to earn more today than in 2005, but median incomes have shown sporadic and inconsistent growth compared with top incomes. Moreover, most competitors earn less than the US poverty threshold. Comparing the earnings of the top female players to the whole labor market shows that gender inequalities exist in median incomes and the likelihood of earning more than the poverty threshold. The esports labor market is an engine of inequality that provides opportunities for a few (primarily male) competitors while building a growing class of lowly paid players who support the interests of game designers and event organizers.

Tax and social expenditure policies have a crucial role in income distribution. This study explores the potential role of taxation and social expenditure policies in income redistribution in South Asia. For this purpose, empirical analysis is conducted by Fixed Effect (FE) and Instrumental Variable (IV) FE models. The analysis suggests that both taxation and social expenditures policies effectively reduce income inequality in South Asia. These findings indicate that social spending and taxation can be used as a policy tool to redistribute income in developing countries. The results also indicate that higher social spending, increased direct taxes, and more reliance on foreign debts can ameliorate the income distribution. Based on the results, it can be suggested that for this region, with the low level of taxes, direct taxes, a large informal economy, and other weak features of tax administration, more reliance on direct taxes and social expenditure policies should be the primary tool for income redistribution.JEL Classification: H2, H5, I3How to Cite:Khan, S., & Padda, I. U. H. (2021). The Impact of Tax and Social Expenditure Policies on Income Distribution: Evidence from South Asia. Etikonomi, 20(2), xx – xx. https://doi.org/10.15408/etk.v20i2.18121.

Replacement rates have gained acceptance as a useful metric for assessing the conditions of retirees and households at point of retirement. Here we use data from the SHARE longitudinal database to investigate income dynamics within a comparative European context. Our analysis, centering on households as opposed to the individuals on whom international data commonly focus, reduces replacement rates to their components—pension, work income, etc.—and looks at the dynamics among household members in relation to work and pension income. Total replacement rates vary widely among the fourteen countries sampled: overall replacement rates are around the Bismarckian 70% across the entire sample, 80% in countries that have Social Democratic and Continental social-policy regimes, and 60% in countries that have East European and Middle Eastern regimes. Looking at the pension and wage components, however, the latter accounts for about 30% of household income—an important fact for decision-makers to consider. Couples tend to retire together, especially if close in age, and work income compensates amply for lower pension income. The Gini coefficients of our sample are compared before/after retirement to determine whether the social programs that underlie pensions mitigate income inequality after retirement. Finally, we examine the well-being and quality of life of retirees and their households. We find a positive correlation between replacement rate and indicators of retirees’ and their households’ quality of life, e.g., satisfaction with life, ability to consume healthcare services, and ability to cover unforeseen expenses.

Inequality in the distribution of income of the population has a certain impact on different aspects of the economic and socio-cultural development of countries and regions. This inequality arises due to a number of factors as the current nature of the production specialization, the availability of production and economic infrastructure, the achieved level of development of the social sphere, socio-cultural, demographic, and other factors. The main objective of this study is to assess the nature and extent of the impact of income inequality in the Russian regions for the subsequent justification of the directions of socio-economic development. We conducted an econometric analysis of the impact of intraregional income inequality (the Gini coefficient), fixed capital investment per capita, and average per capita consumer spending on one of the main indicators of regional economic growth (GRP) per capita was carried out. The model is based on panel data for the period 2012-2018 for 85 regions of the Russian Federation. The results of the study confirm two of three hypotheses. As prospects for further research, it is proposed to consider the impact of inequality in the distribution of household income on economic growth for different groups of regions, including resource-type regions and regions with a predominance of manufacturing industries, as well as for leading regions and regions with a relatively low level of socio-economic development.

The Gini coefficient features prominently in Amartya Sen’s 1973 and 1997 seminal work on income inequality and social welfare. We construct the Gini coefficient from social‐psychological building blocks, reformulating it as a ratio between a measure of social stress and aggregate income. We determine when as a consequence of an income gain by an individual, an increase in the social stress measure dominates a concurrent increase in the aggregate income, such that the magnitude of the Gini coefficient increases. By integrating our approach to the construction of the Gini coefficient with Sen’s social welfare function, we are able to endow the function with a social‐psychological underpinning, showing that this function, too, is a composite of a measure of social stress and aggregate income. We reveal a dual role played by aggregate income as a booster of social welfare in Sen’s social welfare function. Quite surprisingly, we find that a marginal increase of income for any individual, regardless of the position of the individual in the hierarchy of incomes, improves welfare as measured by Sen’s social welfare function.

By combining household survey data before and during the COVID-19 pandemic with detailed tax-benefit simulations, this paper quantifies the distributional effects of COVID-19 in Ecuador and the role of tax-benefit policies in mitigating the immediate impact of the economic shocks. Our results show a dramatic increase in income poverty and inequality between December 2019 and June 2020, the period when the economy was hit the hardest. The national poverty headcount increases from 25.7 to 58.2%, the extreme poverty headcount from 9.2 to 38.6%, and the Gini coefficient from 0.461 to 0.592. On average, household disposable income drops by 41%. The new Family Protection Grant provides income protection for the poorest income decile. However, overall tax-benefit policies do little to mitigate the losses in household incomes due to the pandemic. Informal workers, in particular, are left unprotected due to the lack of income support in the event of unemployment.The online version contains supplementary material available at 10.1057/s41287-021-00490-1.En combinant les données d'enquêtes auprès des ménages avant et pendant la pandémie de COVID-19 avec des simulations détaillées d’impôts et de prestations, cet article quantifie les effets distributifs de la COVID-19 en Équateur et le rôle que jouent les politiques d’impôts et des prestations pour atténuer l'impact immédiat des chocs économiques. Nos résultats montrent une hausse spectaculaire de la pauvreté monétaire et des inégalités entre décembre 2019 et juin 2020, période durant laquelle l'économie a été le plus durement touchée. Le taux national de pauvreté passe de 25,7% à 58,2%, le taux d'extrême pauvreté de 9,2% à 38,6% et le coefficient de Gini de 0,461 à 0,592. En moyenne, le revenu disponible des ménages baisse de 41%. La nouvelle allocation de protection familiale offre une assurance de protection des revenus aux 10% des ménages les plus pauvres. Cependant, de façon générale, les politiques d’impôts et des prestations en font peu pour atténuer les pertes de revenus des ménages en raison de la pandémie. Les travailleurs et travailleuses informel·le·s, en particulier, sont laissé·e·s sans protection en raison de l'absence d’allocation de revenu en cas de chômage.

The introduction discusses the importance of the study problem, study subject and object, the goal and objectives, the described research methodology and findings of the research. The innovations of the research are highlights. The research was conducted in Samtskhe-Javakheti region. At the beginning, the reasons of unequal distribution of income from the perspective of different scientists, the coefficients of the equal and unequal distributions are reported. For presenting global economic inequity we referred the study of Monetary Fund, according to it the global inequity index is 0.55-0.70. In 2018 Gini coefficient in Georgia reached to 0,37, while it is close to the critical range (0,41-0,46). Gini Coefficient are as follows according to the municipalities of Samtskhe-Javakheti -Akhaltsikhe - 0,41, Adigeni - 0,52, Aspindza - 0,52, Borjomi - 0,47, Akhalkalaki - 0,50, Ninotsminda - 0,56. According to the findings an average inequality index of the region is 0,49, or 0,09 higher than it is estimated by the Geostat for the region (0,40). We conducted a public attitude survey on starting up business and immigration. 60-80% of surveyed reported that they have no business as they cannot start it. 90-100% plans to immigrate. In order to develop an inclusive business, it is necessary to support skilled young people from the vulnerable families, include them in the business study and organizing business incubators. The study reports an explain establishment costs per one business incubator which should be covered by the local budget. Another problem referred is substitution of a proportional tax by introduction of progressive tax. All the promoted countries in the world apply the progressive tax system, what means that tax payer with higher income pays more compared to those who have less income. There is untaxed income as well. We developed the scale for progressive tax for Georgia and Samtskhe-Javakheti region in particular and defined the size for the non-taxable income as well (500GEL).

Research background:Intensive economic growth in Russian regions during recent decades has been associated with numerous environmental issues, particularly increasing CO2 emissions, as well as income inequality. To achieve sustainable development, it is necessary to resolve these issues. Purpose of the article: To shed light on the impact of income inequality on CO2 emissions based on Russian regional data covering the years 2004–2018. Methods: Gini index and decile dispersion ratio are used to measure income inequality. To study the impact of income inequality on CO2 emissions in the Russian regions, we estimate econometric models with fixed and random effects and apply GMM method. We test the hypothesis of the environmental Kuznets curve to determine the impact of economic growth on CO2 emissions. Findings & value added: The results show that CO2 emissions increase in tandem with growth in income inequality between 10% of people with the lowest income and 10% of people with the highest income. Simultaneously, CO2 emissions decrease with growth of Gini coefficient. The hypothesis of the Environmental Kuznets Curve was confirmed based on GMM method. Our findings underscore that the activities of the extraction and manufacturing sectors, as well as energy consumption, increase CO2 emissions. The chief significance of this paper is the finding that large income gap between extremely rich and extremely poor population cohorts increases CO2 emissions. This implies that economic policy aimed at reducing income inequality in Russian regions will also reduce CO2 emissions, especially if accompanied by increased use of environmentally friendly technologies. From the international perspective, our research can be extended to study other countries and regions. © Instytut Badań Gospodarczych. This research was supported by a grant from the Russian Science Foundation № 19-18-00262: “Empirical modelling of balanced technological and socioeconomic development in the Russian regions”.

Tourism’s relationship with income inequality is a hot spot in the academic community; however, few studies focus on how tourism shapes rural income inequality, despite its significant role in rural poverty alleviation. This article investigates the nonlinear effects of tourism on urban–rural income inequality and rural income inequality based on data from China’s provincial regions over the period 1995–2018, using the dynamic panel data approach. This study further examines the regional heterogeneity of such effects. The results demonstrate that for the national sample, there exists a significant cubic curve relationship between domestic tourism and rural income inequality. However, inbound tourism’s relationship with rural income inequality is not significant. Besides, there exists an N-shaped Kuznets curve between domestic or inbound tourism and urban–rural income inequality. The effects of tourism on rural income inequality and urban–rural income inequality vary significantly across the eastern, middle, and western regions. From east to middle to west, the significance of inbound tourism’s influence on income inequality decreases gradually. This study also highlights some critical theoretical and practical implications. Unlike prior studies, this article builds the first comprehensive research framework consisting of tourism, rural income inequality, and urban–rural income inequality.

Over the past four decades, the Egyptian economy has suffered from both income inequality and environmental degradation. This dual problem raises the question about the nature of the relationship between inequality and the environment in a developing country like Egypt. In this regard, the study aims to examine the impact of income inequality on carbon emissions during the period 1975–2017. The analysis considers the ability of the political economy approach compared to the Keynesian trade-off approach to explain the inequality-environment relationship in Egypt. To do this, the novel dynamic autoregressive distributed lags approach is employed to capture the short-run and long-run relationships and to overcome the complications associated with the structure of the widely used autoregressive distributive lags model. The findings show that the relationship between inequality and CO2 emissions is not a trade-off. Rather, inequality leads to environmental deterioration in the long run, but there is no significant effect in the short run. In the long run, a 1% rise in the Gini coefficient increases CO2 emissions by 2.28%. These results support the political economy approach in explaining the inequality-environment nexus. Hence, the economic development policies adopted in Egypt during the past four decades have led to a negative impact on the environment. The study advises economic policy makers in Egypt to adopt income redistribution policies to reduce the severity of income inequality. Improving income distribution has a positive effect on the environment in Egypt.

PURPOSE: The study aims to analyze the relationship between the pace of economic development expressed by the GDP index and the level of income inequalities measured by the Gini coefficient., DESIGN/METHODOLOGY/APPROACH: The research hypothesis assumes that the level of income inequalities influences GDP growth. I hypothesize that this relationship is negative – a lower level of income inequalities favor the economic growth. I use the GDP per capita (per adult) year-to-year index to measure the pace of economic development. GDP index is a dependent variable in all estimated models. The explanatory variables are, GINI index, net national saving, public goods spending, country's dummy variables, year dummy variables., FINDINGS: Using data from 43 countries covering the years 1990-2017, I prove that (1) higher income inequality is related to higher economic growth (but only on the level of the sample); (2) a level of savings affects the economic growth positively; (3) a higher level of spending on public goods affects GDP positively (on the level of the whole sample and in the group of more improve rished countries)., PRACTICAL IMPLICATIONS: The analysis confirms the positive relationship between income inequalities and the pace of economic development, but only at the whole sample level. Higher public spending positively affects economic growth. Savings accumulated by the citizens significantly affect economic growth, as a higher level of savings creates greater investment opportunities., ORIGINALITY/VALUE: Inequalities are an inherent part of society and the economy. It is often presumed that if the level of income inequality is too high, it negatively affects the economy by lowering the development pace. Although the previous findings are somewhat mixed, I pose the research hypothesis assuming a low level of income inequality is linked to higher GDP growth., The project is financed by the Ministry of Science and Higher Education in Poland under the programme "Regional Initiative of Excellence" 2019 - 2022 project number 015/RID/2018/19 total funding amount 10 721 040,00 PLN., peer-reviewed

The New Development Bank (NDB) and the BRICS Contingent Reserve Arrangement (CRA) were built by Brazil, Russia, India, China, and South Africa (the BRICS countries) in response to the ‘disappointing’ Bretton Woods Institutions, including the World Bank and the International Monetary Fund (IMF). The main difference between the Bretton Woods Institutions and the BRICS institutions is that the latter adopts an equal‐weight system instead of a weighted voting system in the NDB (all five BRICS countries have equal shares and voting weights regardless of the major differences in their economic weights) and uses consensus instead of majority voting rules to make decisions regarding critical issues in the CRA. In fact, both the equal‐weight system and consensus rule are unprecedented in the history of multilateral financial institutions. The World Bank, the IMF, the Asian Development Bank and even the Asian Infrastructure Investment Bank (AIIB) all adopt weighted voting systems and majority voting rules. We explain why the BRICS countries adopt these unprecedented designs through precise power measurements and carefully designed experiments. First, we measure the voting power of each member of the BRICS’ NDB and CRA under the current decision‐making systems, using this information as a control group. Then, we remeasure the voting power of each member of the NDB under the assumption that their shares and voting weights are allocated according to their economic weights; additionally, we remeasure the voting power of each country of the CRA under the assumption that majority rules are adopted when decisions are being made on critical issues. Moreover, we establish evaluation indices of power equality and power equity based on classic and variant Gini coefficients and Lorenz curves and use them to assess and compare the power structures of the BRICS’ NDB and CRA in the contexts of different voting weight reallocations and different voting rules redesigns. We use these indices to precisely analyse whether the power structures of the BRICS institutions become more equable or equitable in the examined contexts and to investigate the relationship between equality and equity in this setting.

Tourism has a significant impact on income inequality, which seems to be an academic consensus. However, there are still great differences in impact direction and intensity. This study uses the meta-analytic technique to reconcile the results of 12 econometrics studies derived from the Web of Science and Scopus databases examining the relationship between tourism and income inequality measured as the Gini coefficient. The results show that tourism increases income inequality significantly. Moreover, economic growth and trade openness positively moderate the effects of tourism on income inequality. Besides, the sample characteristics, including research period, midpoint of research period, sample size, destination type, and data type, significantly affect the relationship between tourism and income inequality as well. This study reaches a more reliable, robust and universal conclusion about the relationship between tourism and income inequality. Also, it gives theoretical and practical implications for future research and decision-makers.

This paper addresses the impact of productive government expenditure on income inequality using a dataset of 80 countries over the period of 1980–2015. It incorporates the conflicting predictions implied by alternative growth models on this issue. While the neoclassical model suggests that productive government expenditure will reduce long-run income inequality, the corresponding endogenous growth model suggests the opposite. We examine this proposition, by considering both the aggregate Gini coefficient, and the income shares of quintiles. The results obtained using the Gini coefficients provide compelling support for the contrasting impacts of government investment on income inequality, suggested by the underlying theoretical models. These findings are supported, albeit somewhat more weakly by the regressions employing the quintile data. Our general conclusion is that government investment has a mixed effect on income inequality, a conclusion consistent with previous studies.

This study probes the environmental consequences of income inequality (INQ) in G7 economies from 1971 to 2015. INQ is captured by four indicators comprising GINI coefficients, Palma ratio, Theil index, and Atkinson index on per capita carbon emission as a proxy for environmental degradation using both fully modified OLS (FM-OLS) and dynamic OLS (D-OLS). The empirical data are subjected to pre-test using cross-sectional dependence (CSD) test and panel unit root and panel cointegration tests. The following results are established. First, the absence of CSD and presence of cointegration is confirmed. Second, positive effects of INQ indices are reported for the panel analyses. Third, the results of country-specific analyses are divergent and mixed among the G7 economies. For instance, positive impacts are reported for Canada, Japan, and the USA and negative for France and Germany; and insignificant impacts are evident in the case of Italy and the UK. Fourth, the effects of other covariates emerge from two directions entailing both positive and negative. While per capita GDP (LGDPPC) and trade openness (OPN) are aligned with the former a prior, per energy use (PEU) and inflation (INF) satisfied the latter. Consequently, embarking on pro-poor programs such as social welfare funds, private initiative support fund, and state intervention aimed at checkmating the excesses of the capitalists is seen as sacrosanct to solving the INQ-pco2 nexus disharmony.

Objective To examine the distributional effects of the 2008 recession and subsequent recovery across generational cohorts. Methods Using data from the Survey of Consumer Finances (2007–2016), we constructed a measure of economic well-being accounting for income, household size, and annuitized value of assets. We examine trajectories of adjusted income and inequality, using Gini coefficients and income shares by decile, for the overall population and by cohort during the recession and recovery. Results Inequality declined temporarily during the recession, but reached new highs during the recovery. During recovery, population-level increases in economic resources were not reflected among below-median households, as the more concentrated financial assets rose while broader-based home equity and employment fell or remained stagnant. Inequality measures increased for cohorts in their primary working years (Generation-X and Baby Boomers), but not among the younger Millennials, who were at early stages of education, workforce entry, and household formation. Discussion The study illustrates an integrative approach to analyzing cumulative dis/advantage by considering interactions between historically consistent macrolevel events, such as economic shocks or policy choices affecting all cohorts, and the persistent life-course processes that tend to increase heterogeneity and inequality as cohorts age over time. Although recovery policies led to rapid recovery of financial asset values, they did not proportionately reach those below the median or their economic resource types. Results suggest that in a high-inequality environment, recovery policies from economic shocks may need tailoring to all levels of resources in order to achieve more equitable recovery outcomes and prevent exacerbating cohort inequality trajectories.

Punctuated Equilibrium Theory posits that policy-making is generally characterized by long periods of stability that are interrupted by short periods of fundamental policy change. The literature converged on the measure of kurtosis and L-kurtosis to assess these change patterns. In this letter, we critically discuss these measures and propose the Gini coefficient as a (1) comparable, but (2) more intuitive, and (3) more precise measure of “punctuated” change patterns.

The Taiwan Stock Exchange discloses data on daily trading volume across brokerage firms for each listed stock. Market practitioners suggest that the concentration of trading volume contains information on the trading behaviors of big players. We use the Gini Coefficient to measure the degree of concentration, upon which a trading strategy is proposed. We conduct an event study to examine whether such a strategy will yield abnormal returns. Our sample contains 375 listed companies with events identified during the sample period from February 2020 to August 2020. The empirical results show that the trading signal based on the Gini coefficient is informative and that most of the average abnormal returns after the event date are significantly positive with the cumulative average abnormal returns increasing almost monotonically up to the end day of the event window. Consistent with prior studies in which different measures of concentration are utilized, our findings provide additional evidence that the Gini Coefficient could help investors to develop profitable stock selection and market timing strategies.

This paper is an empirical study of per capita CO2 emissions divergence. Trade intensity reflects the strength of bilateral trade relations between China and the Belt and Road Initiative (BRI) countries. Using panel data covering 97 of the BRI countries from 2002 to 2017 and employing the dynamic panel system generalized method of moments (GMM) model with additional instrumental variables of remoteness and the Shapley value decomposition technique, this study has three main findings. First, the import intensity from China tends to restrain per capita CO2 emissions, but the export intensity to China tends to promote per capita CO2 emissions of BRI countries. Second, the Gini coefficient of per capita CO2 emissions continually decreases, representing a gradually weakened divergence. Third, from 2009 the impact of import intensity from China on the divergence changed from increasing CO2 emissions to restraining them. However, export intensity to China has continually promoted the divergence among the BRI countries, with the impact being largest in 2016. The results suggest that China should adjust the sources of its energy imports and the destinations of its exports, and develop green trade cooperation with the BRI countries to jointly tackle climate change.

Правильный выбор и корректная интерпретация методологии измерения неравенства важны для понимания особенностей и глубины экономического неравенства в России. В данной статье рассмотрены оценки для России основных показателей неравенства, используемых в международных исследованиях. В первой части статьи представлены оценки неравенства в России по официальным статистическим данным Росстата и проанализированы альтернативные оценки по расчетам международных организаций и отдельных групп ученых. Также исследуются показатели неравенства и ряд методологических аспектов измерения, которые необходимо учитывать при проведении расчетов. В рамках этого показано, как выбранные показатели и используемые данные влияют на оценку неравенства. Дана оценка неравенства россиян по накопленному богатству и описана специфика доходного неравенства российского населения, а именно наличие тяжелых хвостов распределений.Во второй части статьи на данных ОЭСР проведено сравнение неравенства по доходам населения России и других стран по различным показателям. Согласно результатам, по большинству показателей Россия относится к группе стран с умеренно высоким неравенством по доходам (выше среднего уровня ОЭСР), а с учетом дооценки доходов самого богатого верхнего дециля на основе данных по богатству и налоговой статистике она становится одним из мировых лидеров по неравенству (как по оценкам Credit Suisse, так и Т. Пикетти). Автор приходит к выводу, что для получения объективной картины неравенства необходимо его оценивание одновременно по нескольким измерениям. Помимо стандартных показателей дифференциации доходов (таких как коэффициент Джини и децильный коэффициент), важно учитывать и ряд других показателей, которые отражают специфику распределения доходов в России, в частности, наличие тяжелого хвоста. Особый интерес представляют показатели, учитывающие особенности распределения доходов россиян в концах распределений (коэффициент Пальма и др.) и чувствительные к изменению доходов среди бедных слоев населения (индекс Аткинсона, среднее логарифмическое отклонение).

The goal of article is to identify the characteristics of economic behavior of households based on the study of inequality and statistical analysis of their income and expenditure for the period of 2014–2019. The population differentiation according to the level of per capita equivalent income for 2019 was analyzed and Gini coefficient was calculated based on the methods of economic and mathematical statistics. The Lorentz concentration curve was constructed using the graphical-variational method. Based on the method of analysis and synthesis, the resources and expenditures of households in 2014–2019 were studied and conclusions were made about their economic behavior. The calculated Gini coefficient for Ukraine's economy in 2019 is 23.50% which means that there is a moderate level of inequality in the country. The analysis of household income and expenditure statis-tics provides information on low standards of living, as the main sources of household income are wages, pensions, scholarships, and social benefits; the most important item of expenditure is food expenditures. Economic behavior of households, resulting from the current standard of living, the structure of its resources and expenditures, is defined as passive and is characterized by adaptation, conformism and patience of the population to their living conditions, which hinders the active development of so-cio-economic system and the change of economic thinking. The Lorentz curve proves the low level of population differentiation in Ukraine, however, given the high proportion of the poor in the country, there is a need to improve the methodology for collecting and compiling statistical information. The scientific novelty is in the practical application of the method of calculating the Gini coef-ficient and construction of the Lorentz concentration curve on the basis of data from the State Statistics Service was developed. Based on the analysis of household income and expenditure, the type of their economic behavior was defined as passive. The practical significance is in the basis for the study of different types of economic human behavior in the system of social relations based on the analysis of socio-economic inequality was developed. Keywords: income inequality, economic behavior, welfare level, Gini coefficient, Lorentz curve. У статті виявлено особливості економічної поведінки домогосподарств на основі дослідження нерівності та статистич-ного аналізування їх доходів і витрат за період 2014–2019 років. На основі методів економіко-математичної статистики проаналізовано диференціацію населення за рівнем середньодушових еквівалентних доходів за 2019 рік, розраховано коефіцієнт Джині. За допомогою графічно-варіаційного методу побудована крива концентрації Лоренца. Розрахований коефіцієнт Джині для економіки України у 2019 році складає 23,50% та означає, що наявний помірний рівень нерівності в країні. Аналізування статистики доходів та витрат домогосподарств надає інформацію про низький рівень життя насе-лення, оскільки основними джерелами формування грошових доходів домогосподарств є оплата праці, пенсії, стипендії, соціальні допомоги, а найбільш вагомою статтею витрат залишаються витрати на продукти харчування. Економічна по-ведінка домогосподарств, що випливає з поточного рівня життя населення, структури його ресурсів і витрат, визначається як пасивна та характеризується пристосуванством, конформізмом та терплячістю населення до умов їх існування, що заважає активному розвитку соціально-економічної системи та зміни економічного мислення населення. Крива Лоренца підтверджує низький рівень диференціації населення в Україні, але зважаючи на високу долю бідного населення в країні є потреба удосконалення методики збору та формування статистичної інформації. Ключові слова: нерівність доходів, економічна поведінка, рівень добробуту, коефіцієнт Джині, крива Лоренца.

From 1992 to 2014, Brazil experienced a decline in income inequality along with a significant increase in schooling level, though the latter was more pronounced among women. Brazil also experienced a decline in returns to education, whereas an opposite trend was observed in several developed countries and China. In this paper, we evaluate the effects of educational, marital, and labor market factors on the income inequality of married couples. We also analyze how changes in educational assortative mating affect their income. Our findings suggest that changes in educational marital sorting parameters had a small but statistically significant effect on household income inequality. We show that growth in female labor force participation and a decrease in the gender wage gap explain part of the decline of the Gini coefficient. Educational factors also explain a part of that decline. Nevertheless, the main driver of the reduction in income inequality among couples appears to be the overall decrease in the educational wage gap.