ДИФЕРЕНЦІАЦІЯ ДОХОДІВ ДОМОГОСПОДАРСТВ УКРАЇНИ

Internationally a debate on the distributional impact of energy taxation has focused on the tax burden relative to income. The general conclusion is that taxes are regressive, but at a varying degree for different countries. This study examines the relationship between location, income, heating technology characteristics and the energy tax that households pay. The article aims at identifying general implications of energy taxes with respect to different impacts on population groups depending on location and income. Tax payments associated with energy use are considered relative to total disposable income of households grouped in income deciles and by other characteristics. The impact of environmental taxes depends on income levels in rural areas compared to income in urban areas. In Denmark, the income difference is found to be quite small, but energy consumption and, therefore, also the burden of energy taxation, is higher in rural areas. Furthermore, the low-income households in rural areas consume much more energy than low-income households in urban areas. Low-income households in rural areas are, therefore, a group that is specifically exposed to increased energy taxation. Households living in rural areas have the disadvantage of not having access to public heating grids and natural gas grids, which is adding to the risk of high welfare losses from higher taxes. Apart from higher energy costs, the rural households also pay considerably higher taxes on transport by private cars. This article documents that rural populations have higher energy bills also compared to income, but there is no income inequality between rural and urban areas in Denmark. In countries with higher inequality in income distribution and a higher proportion of low-income households in rural areas, the impact of energy and transport taxes might be more uneven. In such cases, the environmental tax structure should compensate the low-income rural households. For countries with a high proportion of low-income households living in urban areas and little income inequality, this issue might, as in the Danish case, not be a problem in the design of energy and environmental taxes.

Purpose: The unemployment rate as well as the labor force indicate the large number of people who must be included in the development process. This shows that the dynamics of the development process must be able to involve the entire work force, meaning that a large number of work force can become a burden for economic development. Apart from education, another aspect that influences the unemployment rate is the unequal distribution of income (gini ratio). Inequality in income distribution is a problem of differences in income between the richest and the poorest individuals. The greater the income gap, the greater the variation in income distribution. This study aims to obtain quantitative "evidence" regarding the effect of education and the gini ratio on the unemployment rate. Methodology: Based on the research objectives, this research is a quantitative research with the type of explanatory research, which will explain the causal relationship between the independent variables and the dependent variable through hypothesis testing. The type of data used in this study is secondary data. The secondary data used is in the form of a time series from 2013 to 2017. The data analysis used is multiple linear regression analysis. Results: Based on the research results it is known that (1) Education partially has a positive and significant effect on the unemployment rate in South Kalimantan. This means that education can reduce the number of unemployed in accordance with the theory of human capital, therefore education is one of the factors that needs to be improved so that the quality of human resources increases and has competitiveness; (2) The Gini ratio (income inequality) partially has a positive and significant effect on the unemployment rate in South Kalimantan. This means that when income inequality is high, the unemployment rate will also increase.

ІNCOMES AND EXPENSES OF THE RURAL POPULATION AND THEIR IMPACT ON THE STANDART OF LIVING

Inequality, segregation, and redistribution

The allocation and distribution of a country's income in the 4.0 era need to be given special attention so that it can be allocated efficiently by each individual. The efficiency of allocation and distribution of income in a capitalist economic system has an impact on income inequality in society which can lead to conflict and also creates poverty. But in achieving this prosperity, it is as if there is no government intervention. This study aims to explore how the allocation and distribution of state income are seen from an Islamic economic perspective and also to compare the capitalist distribution system with the Islamic distribution system in the 4.0 era. The research method used is library research which originates from books, journals, the internet, and other relevant sources. The results of the study show that the allocation and distribution of state income from an Islamic economic point of view is an economic concept that has the concept of equal distribution of wealth or income for the community, applicable in Indonesia, which will produce prosperity for the community. The comparison of the capitalist distribution system is based on absolute ownership of the factors of production so that the main goal is to make a profit. As much as possible appears to ignore moral and social values. The Islamic economic distribution system in the era of disruption upholds moral and social values because, in addition to achieving good profitability, Islam also teaches problems in economic activities. With Islamic economic equality, it is hoped that it can reduce the gap in economic inequality to realize prosperity. Therefore, sharia distribution can be carried out by prioritizing Islamic business ethics which is implemented through the concept of Rahmatan lil 'Alamin in the economy. Likewise, in Indonesia, where the majority of the population is Muslim, special attention is needed so that it can implement the allocation and distribution of state income through the concepts of Zakat, Infak, Shadaqah, and Wakaf adapted to the times.

Individual vulnerability and the nurturing state: The case of self-reported health and relative income

Analysis of the Gini index based on education level shows significant inequality in the distribution of education in society. Higher levels of education tend to be accessed by groups with higher incomes, while groups with lower incomes often face barriers to obtaining quality education. This is reflected in the Gini index, which shows that the gap between groups with good and limited access to education is widening. This inequality has an impact on economic opportunities and social mobility, suggesting that improvements in a more inclusive education system and equal access to education across all levels of society are essential to reducing inequality and achieving greater social justice. The secondary sector in Muaro Jambi also shows significant levels of inequality. In the manufacturing and processing industries, large companies that produce goods on a large scale often make substantial profits, while small and medium enterprises struggle to compete. Inequality is also reflected in the construction sector, where the income gap between skilled and unskilled construction workers, and between large and small contractors, is quite striking. This contributes to the high Gini index in this sector, reflecting income inequality among workers and employers. In the tertiary sector, which includes services, retail, finance, and insurance, income inequality tends to be higher. In the service sector, the difference in income between workers in customer service and managers or professionals is very large. In the finance and insurance sector, income inequality is also significant because wages in this sector are often very high compared to other sectors, creating a large gap between workers in these fields and those in lower-wage sectors. This unequal distribution of income leads to a high Gini index in the tertiary sector. The quaternary sector in Muaro Jambi, which includes technology, information, and research and development, shows high levels of inequality. This inequality is caused by the large differences in wages between technology professionals and workers in non-technology sectors, as well as between workers in large technology companies and small businesses. Specialized skills and high levels of education in this sector are often directly related to high incomes, while those in less skilled or educated positions earn much lower wages. This creates a clear inequality in the distribution of income in this sector.

Purpose of research . The relevance of the research topic is associated with the presence of a number of controversial issues arising in the statistical study of monetary incomes of the population of the country and regions. These issues include: comparability of monetary income in dynamics, assessment of differentiation of population by income and consumption, comprehensive assessment of regional differences in the income level. The aim of this work is to study the monetary income of the population of the Russian Federation as a universal characteristic of the living standard. Materials and methods . The information base of the study was the official statistical materials of the Federal State Statistics Service, including the materials published by ROSSTAT in the “Statistical review” in early 2019. Along with traditional statistical methods, the study also used the method of assessing structural differences, the method of index analysis of the differentiation of the population by monetary income at both the Federal and regional levels. Structural shifts in consumer spending between groups with different income levels were identified. Results . In Russia, from 2014 to 2017, the annual decline in real disposable income ranged from one to 3%, with an average annual growth rate of nominal income of 5%. In 2010–2018, more than 47% of income was concentrated in 20% of the population of the Russian Federation with the highest incomes. The 20% of the population with the lowest income accounted for less than 5.4% of the total. Inequality in the distribution of monetary income leads to the formation of consumer structures that differ in social groups with different levels of income. In the study, an integral coefficient of structural shifts of Gatev was used to estimate these differences. As a result of its calculation, significant structural differences between the groups of the population of Russia with the highest and lowest incomes were established. A study was conducted on the level of monetary income of the population of 14 regions of the Volga Federal District in 2018. For all regions of the Federal District, three local indices were calculated on three indicators: average per capita monetary income of the population, the average monthly nominal accrued wages of employees of organizations and the share of the population with incomes below the subsistence minimum. Their arithmetic mean value representing the index of monetary incomes of the population was determined. Conclusion . The results of the calculations allowed identifying three groups of entities in the district, which differ significantly in terms of cash income of the population. The problems of differentiation of monetary income in the Volga Federal District, identified in the study, are typical for many regions of Russia. In order to solve the problems, concerted actions of the regional government and the state, aimed at improving the living standard of the population of the country are necessary.

The livelihood diversification significantly contributes to the family income having effect on food varieties' consumption in rural families of different sizes. This study investigated the food intake differences among rural families considering different income levels and family sizes. Moreover, barriers faced by the rural families to increase the consumption of food varieties were also analysed. A total of 200 rural families were selected through multistage purposive and random sampling techniques in the Punjab province of Pakistan and were directly interviewed and categorized first into low and high livelihood diversified families. The food groups were derived by assigning individual food to conventional food group taxonomies, and two‐way ANOVA (4 (income groups) × 3 (family size groups) was separately conducted for low and high livelihood diversified families. The income instability, prices of food items, market distance and storage were perceived as barriers for increasing food consumption. The high livelihood diversified families significantly and regularly consumed more food items than low diversified families. The rural households both in low and high livelihood diversified family categories having low income and high family size consumed less expensive food items. The regular consumption of fruits, bakery products, and livestock and dairy items was greatly associated with high income and small family size. One of the most remarkable findings of the multivariate multiple regression model was the households belonging to the lowest income group were significantly lowering the consumption of livestock and dairy food items as the family size increased from small to large family size. The interaction effect was highly associated with per capita income because the consumption of food items increased with the rise in income irrespective of the family size. However, family size groups showed different patterns of food intakes with different income levels. Government agencies should assist rural households to diversify their income portfolios for better nutrition.

Are there income differences in the impact of a national reimbursement policy for smoking cessation treatment and accompanying media attention? Findings from the International Tobacco Control (ITC) Netherlands Survey

This study aims to examine the impact of the provision of credit by PD. BPR NTB Sumbawa on the welfare of debtor customers through per capita income indicators. This research is a comparative study to compare the income levels of customers before and after receiving working capital loans from PD. BPR NTB Sumbawa. The type of data used is quantitative data in the form of customer income before and after receiving working capital loans from PD. BPR NTB Sumbawa obtained directly from customers. The research subjects were customers who received working capital loans from PD. BPR NTB Sumbawa in 2022, totaling 37 people. Data collection was carried out through structured interviews using a list of questions that had been prepared by the researcher to obtain relevant data related to the research object. Data analysis techniques were carried out using the two-average difference test method, including calculating the difference in income, standard deviation, and one variable test. Based on the results of the research that has been done, it can be concluded that there are differences in the average income of respondents before and after receiving working capital loans from PD. BPR NTB Sumbawa. There was an increase in the income of customers who were used as respondents after receiving working capital loans from PD. BPR NTB Sumbawa of Rp. 81,432,081.04/month.

In countries that have developed under the current market economy, inequalities in income distribution tend to increase with three different trends, i.e., high (United States, United Kingdom, Japan), low (North Europe countries), and medium Gini coefficient levels. On the other hand, the relationship between income distribution and social welfare is generally a difficult problem to solve in economics. So, this paper discusses the impact of income distribution on the macroeconomy, limiting the scope to consistency with long-term economic growth. We attempt to answer these economic policy issues by simulation using an agent-based model based on replicator dynamics. As a result of the simulation in this paper, in general, in countries with the high marginal propensity to consume, long-term growth can be maintained by inducing equality in income distribution. On the other hand, a mature country with a low marginal propensity to consume can sustain not so high but stable growth despite increasing inequality in income distribution. According to simulation results based on OECD (Organisation for Economic Co-operation and Development) data, in the former UK, US, and Japan, the lower the Gini coefficient is, the higher the growth potential is, while in the latter Norway and Luxembourg, relatively stable growth is maintained even if the Gini coefficient increases.

Economic well-being is a difficult concept to measure. It is defined theoretically by a household's or individual's total access to goods and services. However, economic well-being is almost always measured empirically by money income (Moon and Smolensky). While money income provides a fairly accurate indicator of access to goods and services that can be purchased in the marketplace, it fails to measure access to goods and services that are a result of household production. Such an omission means that empirical estimates of economic well-being based solely on money income are biased if money income and household production are correlated. Concern about potential bias increases when attention is focused on comparing the economic well-being of groups-such as rural and urban households-which may differ in their reliance on household production. Historically, rural households have had less equal money income distributions than urban households (Foley). However, family members in rural households also spend more time in household production than do their urban counterparts (Goebel and Hennon, Olson et al.). Could it be that the relatively greater unevenness in the distribution of rural households' money income is in part compensated for by differences in home productivity? Or would the addition of home production to measures of economic well-being make the distribution of income across rural households even more unequal than their urban counterparts?' In this paper we explore how rural and urban income distributions change if the value of household production is added to money income.

Development aims to improve the welfare of the people. To improve welfare, it requires economic growth that is quitte high, stable and equiable in income. High enough economic growth must be balanced with equity, so as not to create ineqalty. Growth is not a goal, but only a tool as a process to reduce proverty and redurce inequality in income distribution. Hence the reduction of inequality ofincome distribution is the essence of development results can be enjoyed fairly and equitably by all people, the problemof unequal income distribution will not arise. If the economic proformance is betteror is experiencing progress, then all people must also feel the impact of this progress in the form of an increase in the level of income. Because the distribution of income is very useful in increasing economic growth and development,it is important for us to know whar factor affect in the inequality of income didtribution in Java. This variables used are econoc growth, provincial minium wages , open employment rate, ddegree of fiscal decentralization and growth in the human development index with multiple regression analysis for 2014-2019. The results showed that the only variables affecting income inequality were the provincial minimum wage and the open unemployment rate. The open unemployment rate variable has a coefficient value of -0.0502438. This means that when the exchange rate increases by Rp.1, income inequality will decrease by 0.0502438%. The open unemployment rate variable has a coefficient value of 0.0056812. This means that when the open unemployment rate increases by one percent, income inequality will increase by 0.0056812%. Meanwhile, economic growth, the degree of fiscal decentralization and the human development index have no effect on income inequality

The Miombo woodlands that cover around 93% of forested area in Tanzania are central to livelihoods of rural dwellers. Nevertheless, there is paucity of scientific studies and associated knowledge on the dependence, distribution, and diversification aspects of livelihoods in such ecosystems. Our empirical case-based findings indicate the dependence on Miombo woodlands was relatively high contributing 33.8% to total annual household income after tobacco cultivation at 39.6%. As such, forest incomes are vital for rural households living around such ecosystems. Among the poorest groups, forest income contributed to 40% of the total annual income whilst decreasing slightly as wealth increased reaching 32% among the better-off. On issues of livelihood distribution, forest incomes played a role in equalizing income distribution with a Gini change of about 0.05, however, it was tobacco cultivation that was more responsible for lowering the gap between income inequality levels with a Gini change of 0.08. In terms of diversification, rural households displayed a high level of diversity of livelihood options at a diversity index of 0.7 and forests were a diversification option. These findings contribute a policy lesson that reduced access to the miombo woodlands through exclusionary conservation mechanisms would result in considerable negative impacts on rural households’ welfare and exacerbate income differentiation in the area.