This dataset is about book subjects. It has 7 rows and is filtered where the books is The trickle-up economy : how we take from the poor and middle class and give to the rich. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

This data collection focuses on the federal budget deficit and on issues dealing with the rich and the poor in America. Respondents were asked if they approved of the way George Bush, Democrats in Congress, and Republicans in Congress were handling the the federal budget deficit, and who was more to blame for the larger deficit. Additionally, respondents were asked how much money it takes to be rich in the United States, whether they would want to be rich, how likely it was that they would ever be rich or poor, whether the percentage of Americans who are rich was increasing, and whether they respected and admired rich people. Other questions asked respondents if they characterized rich people as more likely to be honest, snobbish, intelligent, and a variety of other traits, whether respondents would be more or less likely to vote for a candidate who was a millionaire/self-made millionaire, and which political party better represented the interests of poor, rich, and middle class people. Background information on respondents includes political alignment, 1988 presidential vote choice, registered voter status, education, age, religion, social class, marital status, number of people in the household, labor union membership, employment status, race, income, sex, and state/region of residence.

This poll, fielded April 1-5, 2009, is a part of a continuing series of monthly surveys that solicit public opinion on the presidency and on a range of other political and social issues. Respondents were asked whether they approved of the way Barack Obama was handling the presidency and issues such as the economy and foreign policy. A series of questions addressed the Obama Administration's approach to solving economic problems and whether the administration's policies favored the rich, the middle class, or the poor. Respondents gave their opinions of First Lady Michelle Obama, the United States Congress, the Republican and Democratic parties, and whether President Obama or the Republicans in Congress were more likely to make the right decisions about the national economy and national security. Views were sought on President Obama's proposed budget plan, including changes in federal income taxes and government spending, and proposals to give financial assistance to the banking and automotive industries. A series of questions addressed the condition of the national economy, the most important economic problem facing the nation, the financial situation of the respondent's household, and how the recession was affecting their life. Respondents compared their current standard of living with that of their parents at the same age and gave their expectations about the standard of living of their children. Other questions asked respondents what the phrase "American dream" meant to them and whether they had achieved the "American dream" or expected to in their lifetime. Additional topics addressed the bonuses given to AIG insurance company executives, the wars in Iraq and Afghanistan, international trade, health insurance coverage, and government spending on cancer research. Demographic variables include sex, age, race, education level, marital status, household income, employment status, perceived social class, political party affiliation, political philosophy, voter registration status and participation history, religious preference, whether respondents had children under the age of 18 years, and whether respondents considered themselves to be a born-again Christian.

Abstract

Dataset used in World Bank Policy Research Working Paper #2876, published in World Bank Economic Review, No. 1, 2005, pp. 21-44.

The effects of globalization on income distribution in rich and poor countries are a matter of controversy. While international trade theory in its most abstract formulation implies that increased trade and foreign investment should make income distribution more equal in poor countries and less equal in rich countries, finding these effects has proved elusive. The author presents another attempt to discern the effects of globalization by using data from household budget surveys and looking at the impact of openness and foreign direct investment on relative income shares of low and high deciles. The author finds some evidence that at very low average income levels, it is the rich who benefit from openness. As income levels rise to those of countries such as Chile, Colombia, or Czech Republic, for example, the situation changes, and it is the relative income of the poor and the middle class that rises compared with the rich. It seems that openness makes income distribution worse before making it better-or differently in that the effect of openness on a country's income distribution depends on the country's initial income level.

Kind of data

Aggregate data [agg]

As of 2022, the average personal wealth in low-income countries in the Middle East and North Africa (MENA) amounted to just over ************** U.S. dollars. In comparison, the average personal wealth in MENA low-income nations in 2000 was *** thousand U.S. dollars.

As of 2022, the share of national wealth held by the richest ** percent in middle-income countries in the Middle East and North Africa (MENA) amounted to **** percent of the total. In comparison, the share of national wealth for the richest ** percent in 2000 in MENA middle-income nations was **** percent.

ObjectivesTo assess the magnitude and pattern of socioeconomic inequality in current smoking in low and middle income countries. MethodsWe used data from the World Health Survey [WHS] in 48 low-income and middle-income countries to estimate the crude prevalence of current smoking according to household wealth quintile. A Poisson regression model with a robust variance was used to generate the Relative Index of Inequality [RII] according to wealth within each of the countries studied. ResultsIn males, smoking was disproportionately prevalent in the poor in the majority of countries. In numerous countries the poorest men were over 2.5 times more likely to smoke than the richest men. Socioeconomic inequality in women was more varied showing patterns of both pro-rich and pro-poor inequality. In 20 countries pro-rich relative socioeconomic inequality was statistically significant: the poorest women had a higher prevalence of smoking compared to the richest women. Conversely, in 9 countries women in the richest population groups had a statistically significant greater risk of smoking compared to the poorest groups. ConclusionBoth the pattern and magnitude of relative inequality may vary greatly between countries. Prevention measures should address the specific pattern of smoking inequality observed within a population.

Material wealth is a key factor shaping human development and well-being. Every year, hundreds of studies in social science and policy fields assess material wealth in low- and middle-income countries assuming that there is a single dimension by which households can move from poverty to prosperity. However, a one-dimensional model may miss important kinds of prosperity, particularly in countries where traditional subsistence-based livelihoods coexist with modern cash economies. Using multiple correspondence analysis to analyze representative household data from six countries—Nepal, Bangladesh, Ethiopia, Kenya, Tanzania and Guatemala—across three world regions, we identify a number of independent dimension of wealth, each with a clear link to locally relevant pathways to success in cash and agricultural economies. In all cases, the first dimension identified by this approach replicates standard one-dimensional estimates and captures success in cash economies. The novel dimensions we identify reflect success in different agricultural sectors and are independently associated with key benchmarks of food security and human growth, such as adult body mass index and child height. The multidimensional models of wealth we describe here provide new opportunities for examining the causes and consequences of wealth inequality that go beyond success in cash economies, for tracing the emergence of hybrid pathways to prosperity, and for assessing how these different pathways to economic success carry different health risks and social opportunities.

In the financial year 2021, a majority of Indian households fell under the aspirers category, earning between ******* and ******* Indian rupees a year. On the other hand, about ***** percent of households that same year, accounted for the rich, earning over * million rupees annually. The middle class more than doubled that year compared to ** percent in financial year 2005. Middle-class income group and the COVID-19 pandemic During the COVID-19 pandemic specifically during the lockdown in March 2020, loss of incomes hit the entire household income spectrum. However, research showed the severest affected groups were the upper middle- and middle-class income brackets. In addition, unemployment rates were rampant nationwide that further lead to a dismally low GDP. Despite job recoveries over the last few months, improvement in incomes were insignificant. Economic inequality While India maybe one of the fastest growing economies in the world, it is also one of the most vulnerable and severely afflicted economies in terms of economic inequality. The vast discrepancy between the rich and poor has been prominent since the last ***** decades. The rich continue to grow richer at a faster pace while the impoverished struggle more than ever before to earn a minimum wage. The widening gaps in the economic structure affect women and children the most. This is a call for reinforcement in in the country’s social structure that emphasizes access to quality education and universal healthcare services.

As of 2022, the share of national wealth held by the poorest 50 percent in middle-income countries in the Middle East and North Africa (MENA) decreased to *** percent of the total. In comparison, the share of wealth for the bottom half of the population in MENA middle-income nations in 2000 was *** percent.

BackgroundAdult height is a useful biological measure of long term population health and well being. We examined the cohort differences and socioeconomic patterning in adult height in low- to middle-income countries. Methods/FindingsWe analyzed cross-sectional, representative samples of 364538 women aged 25-49 years drawn from 54 Demographic and Health Surveys (DHS) conducted between 1994 and 2008. Linear multilevel regression models included year of birth, household wealth, education, and area of residence, and accounted for clustering by primary sampling units and countries. Attained height was measured using an adjustable measuring board. A yearly change in birth cohorts starting with those born in 1945 was associated with a 0.0138 cm (95% CI 0.0107, 0.0169) increase in height. Increases in heights in more recent birth year cohorts were largely concentrated in women from the richer wealth quintiles. 35 of the 54 countries experienced a decline (14) or stagnation (21) in height. The decline in heights was largely concentrated among the poorest wealth quintiles. There was a strong positive association between height and household wealth; those in two richest quintiles of household wealth were 1.988 cm (95% CI 1.886, 2.090) and 1.018 cm (95% CI 0.916, 1.120) taller, compared to those in the poorest wealth quintile. The strength of the association between wealth and height was positive (0.05 to 1.16) in 96% (52/54) countries. ConclusionsSocioeconomic inequalities in height remain persistent. Height has stagnated or declined over the last decades in low- to middle-income countries, particularly in Africa, suggesting worsening nutritional and environmental circumstances during childhood.

The COVID-19 pandemic has brought about massive declines in well-being around the world. This paper seeks to quantify and compare two important components of those losses—increased mortality and higher poverty—using years of human life as a common metric. The paper estimates that almost 20 million life-years were lost to COVID-19 by December 2020. Over the same period and by the most conservative definition, more than 120 million additional years were spent in poverty because of the pandemic. The mortality burden, whether estimated in lives or years of life lost, increases sharply with gross domestic product per capita. By contrast, the poverty burden declines with per capita national income when a constant absolute poverty line is used, or is uncorrelated with national income when a more relative approach is taken to poverty lines. In both cases, the poverty burden of the pandemic, relative to the mortality burden, is much higher for poor countries. The distribution of aggregate welfare losses—combining mortality and poverty and expressed in terms of life-years —depends on the choice of poverty line(s) and the relative weights placed on mortality and poverty. With a constant absolute poverty line and a relatively low welfare weight on mortality, poorer countries are found to bear a greater welfare loss from the pandemic. When poverty lines are set differently for poor, middle-income, and high-income countries and/or a greater welfare weight is placed on mortality, upper-middle-income and rich countries suffer the most.

Measuring Human Settlement Wealth Index at 10-Km Resolution in Low- and Middle-Income Countries from 2005 to 2020 Using Multi-Source Remote Sensing Data

BackgroundIn high-income countries, obesity prevalence (body mass index greater than or equal to 30 kg/m2) is highest among the poor, while overweight (body mass index greater than or equal to 25 kg/m2) is prevalent across all wealth groups. In contrast, in low-income countries, the prevalence of overweight and obesity is higher among wealthier individuals than among poorer individuals. We characterize the transition of overweight and obesity from wealthier to poorer populations as countries develop, and project the burden of overweight and obesity among the poor for 103 countries.Methods and findingsOur sample used 182 Demographic and Health Surveys and World Health Surveys (n = 2.24 million respondents) from 1995 to 2016. We created a standard wealth index using household assets common among all surveys and linked national wealth by country and year identifiers. We then estimated the changing probability of overweight and obesity across every wealth decile as countries’ per capita gross domestic product (GDP) rises using logistic and linear fixed-effect regression models. We found that obesity rates among the wealthiest decile were relatively stable with increasing national wealth, and the changing gradient was largely due to increasing obesity prevalence among poorer populations (3.5% [95% uncertainty interval: 0.0%–8.3%] to 14.3% [9.7%–19.0%]). Overweight prevalence among the richest (45.0% [35.6%–54.4%]) and the poorest (45.5% [35.9%–55.0%]) were roughly equal in high-income settings. At $8,000 GDP per capita, the adjusted probability of being obese was no longer highest in the richest decile, and the same was true of overweight at $10,000. Above $25,000, individuals in the richest decile were less likely than those in the poorest decile to be obese, and the same was true of overweight at $50,000. We then projected overweight and obesity rates by wealth decile to 2040 for all countries to quantify the expected rise in prevalence in the relatively poor. Our projections indicated that, if past trends continued, the number of people who are poor and overweight will increase in our study countries by a median 84.4% (range 3.54%–383.4%), most prominently in low-income countries. The main limitations of this study included the inclusion of cross-sectional, self-reported data, possible reverse causality of overweight and obesity on wealth, and the lack of physical activity and food price data.ConclusionsOur findings indicate that as countries develop economically, overweight prevalence increased substantially among the poorest and stayed mostly unchanged among the wealthiest. The relative poor in upper- and lower-middle income countries may have the greatest burden, indicating important planning and targeting needs for national health programs.

The Relative Wealth Index predicts the relative standard of living within countries using de-identified connectivity data, satellite imagery and other nontraditional data sources. It has been built by researchers at the University of Carlifornia - Berkeley and Facebook. The estimates are built by applying machine learning algorithms to vast and heterogeneous data from satellites, mobile phone networks, topographic maps, as well as aggregated and de-identified connectivity data from Facebook. They train and calibrate the estimates using nationally-representative household survey 20 data from 56 LMICs, then validate their accuracy using four independent sources of household survey data from 18 countries. They also provide confidence intervals for each micro-estimate to facilitate responsible downstream use. The data is provided for 93 low and middle-income countries at 2.4km resolution. It covers the time between April 01, 2021 and December 22, 2023.

An interactive map of the Relative Wealth Index is available here: http://beta.povertymaps.net/

Please cite / attribute any use of this dataset using the following: Microestimates of wealth for all low- and middle-income countries Guanghua Chi, Han Fang, Sourav Chatterjee, Joshua E. Blumenstock Proceedings of the National Academy of Sciences Jan 2022, 119 (3) e2113658119; DOI: 10.1073/pnas.2113658119

Over ** million Russians aged 20 years and above, or approximately ** percent of the total adult population of the country, had wealth under 10,000 U.S. dollars in 2022. To compare, on average around the globe, the share of residents belonging to this wealth range was measured at **** percent in the same year. Economic inequality in Russia The latest available data by the World Bank recorded Russia’s Gini index, used as a measurement of income or wealth inequality, at **. The organization classified Russia as an upper-middle-income economy. Over ** percent of Russians considered themselves belonging to the middle class in 2020. HNWIs in Russia Approximately *** percent of Russian adults, or ******* residents, owned over *********** U.S. dollars, or were referred to as high-net-worth individuals (HNWIs). In 2021, the total wealth of the adult population in the country reached nearly *** trillion U.S. dollars. A significant portion of it belonged to roughly ***** ultra-high-net-worth individuals (UHNWIs) whose net worth exceeded ** billion U.S. dollars.

BackgroundWealth quintiles derived from household asset indices are routinely used for measuring socioeconomic inequalities in the health of women and children in low and middle-income countries. We explore whether the use of wealth deciles rather than quintiles may be advantageous.MethodsWe selected 46 countries with available national surveys carried out between 2003 and 2013 and with a sample size of at least 3000 children. The outcomes were prevalence of under-five stunting and delivery by a skilled birth attendant (SBA). Differences and ratios between extreme groups for deciles (D1 and D10) and quintiles (Q1 and Q5) were calculated, as well as two summary measures: the slope index of inequality (SII) and concentration index (CIX).ResultsIn virtually all countries, stunting prevalence was highest among the poor, and there were larger differences between D1 and D10 than between Q1 and Q5. SBA coverage showed pro-rich patterns in all countries; in four countries the gap was greater than 80 pct points. With one exception, differences between extreme deciles were larger than between quintiles. Similar patterns emerged when using ratios instead of differences. The two summary measures provide very similar results for quintiles and deciles. Patterns of top or bottom inequality varied with national coverage levels.ConclusionResearchers and policymakers should consider breakdowns by wealth deciles, when sample sizes allow. Use of deciles may contribute to advocacy efforts, monitoring inequalities over time, and targeting health interventions. Summary indices of inequalities were unaffected by the use of quintiles or deciles in their calculation.

A comprehensive overview on the contents, the structure and basiccoding rules of both data files can be found in the following guide: Guide for the ISSP ´Social Inequality´ cumulation of the years 1987,1992, 1999 and 2009 Attitudes to social inequality. Themes: Importance of social background and other factors asprerequisites for personal success in society (wealthy family,well-educated parents, good education, ambitions, natural ability, hardwork, knowing the right people, political connections, person´s raceand religion, the part of a country a person comes from, gender andpolitical beliefs); chances to increase personal standard of living(social mobility); corruption as criteria for social mobility;importance of differentiated payment; higher payment with acceptance ofincreased responsibility; higher payment as incentive for additionalqualification of workers; avoidability of inequality of society;increased income expectation as motivation for taking up studies; goodprofits for entrepreneurs as best prerequisite for increase in generalstandard of living; insufficient solidarity of the average populationas reason for the persistence of social inequalities; opinion about ownsalary: actual occupational earning is adequate; income differences aretoo large in the respondent´s country; responsibility of government toreduce income differences; government should provide chances for poorchildren to go to university; jobs for everyone who wants one;government should provide a decent living standard for the unemployedand spend less on benefits for poor people; demand for basic income forall; opinion on taxes for people with high incomes; judgement on totaltaxation for recipients of high, middle and low incomes; justificationof better medical supply and better education for richer people;perception of class conflicts between social groups in the country(poor and rich people, working class and middle class, unemployed andemployed people, management and workers, farmers and city people,people at the top of society and people at the bottom, young people andolder people); salary criteria (scale: job responsibility, years ofeducation and training, supervising others, needed support for familiyand children, quality of job performance or hard work at the job);feeling of a just payment; perceived and desired social structure ofcountry; self-placement within social structure of society; number ofbooks in the parental home in the respondent´s youth (culturalresources); self-assessment of social class; level of status ofrespondent´s job compared to father (social mobility); self-employment,employee of a private company or business or government, occupation(ILO, ISCO 1988), type of job of respondent´s father in therespondent´s youth; mother´s occupation (ILO, ISCO 1988) in therespondent´s youth; respondent´s type of job in first and current(last) job; self-employment of respondent´ first job or worked forsomeone else. Demograpy: sex; age; marital status; steady life partner; education ofrespondent: years of schooling and highest education level; currentemployment status; hours worked weekly; occupation (ILO, ISCO 1988);self-employment; supervising function at work; working-type: workingfor private or public sector or self-employed; if self-employed: numberof employees; trade union membership; highest education level of fatherand mother; education of spouse or partner: years of schooling andhighest education level; current employment status of spouse orpartner; occupation of spouse or partner (ILO, ISCO 1988);self-employment of spouse or partner; size of household; householdcomposition (children and adults); type of housing; party affiliation(left-right (derived from affiliation to a certain party); partyaffiliation (derived from question on left-right placement); partypreference; participation in last election; perceived position of partyvoted for on left-right-scale; attendance of religious services;religious main groups (derived); self-placement on a top-bottom scale;region. Additionally coded: several country variables; weighting factor.

This Commentary investigates whether there has been a growing divergence in the consumption of luxury and necessity goods across income classes. The analysis shows that while necessities represent a majority of the consumption basket for lower and middle income quintiles, their consumption of necessities in inflation-adjusted dollars has been declining in the face of higher prices of such goods and stagnant income growth. Higher income quintiles have seen increases in their consumption of luxuries, simultaneous with a decline in their consumption of necessities.

S1 File Covers the structure of the samples used in the analyses, i.e., the countries, the waves and the years of data collection. (XLSX)