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]

1) Data Introduction • The Income Classification dataset provides data extracted from the U.S. Census Bureau database, aimed at predicting whether an individual's income exceeds $50,000 per year. This dataset is commonly known as the "Adult" dataset and includes features such as age, work class, education, marital status, occupation, race, gender, native-country, and others.

2) Data Utilization (1) Income data has characteristics that: • It includes both continuous and categorical data, enabling various types of analysis to understand the economic demographics of the U.S. • The dataset is often used in predictive modeling to forecast income levels based on demographic and employment information. (2) Income data can be used to: • Economic Research: Analysts use this dataset to study income distribution and the factors affecting economic disparities. • Policy Making: Helps policymakers design more effective social welfare programs targeting low-income families.

Low income cut-offs (LICOs) before and after tax by community size and family size, in current dollars, annual.

Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.

Tags Social system, socio-economic resources, justice, BES, Environmental Justice, Environmental disamentities, Zoning Board of Appeals Summary For use in the environmental injustices study of Baltimore relating to patterns of environmental disamenties in relation to low income/minority communities. Description This feature class layer is a point dataset of appeals to the Zoning Board of Appeals (ZBA) from 1938 to 1999 concerning identified environmental disamentities. The data was gathered from records from the Zoning Board of Appeals decisions since 1931 relating to environmental disamentities and to be used to examine environmental injustices involving low income/minority communities in Baltimore. To see if environmental injustices exist in Baltimore, this point layer will be overlayed with race/income data to determine if patterns of inequity exist. Points were placed manually using the associated addresses from the ZBA_master dataset. The ID number associated with each point is related to its appeal number from the Zoning Board of Appeals. Multiple points on the data layer have the same ZBA_ID number, making it a one-to-many relationship. This layer can be joined with the ZBA_master table using the "ZBA_point_relationship" and the field "ZBA_ID". Credits UVM Spatial Analysis Lab Use limitations None. There are no restrictions on the use of this dataset. The authors of this dataset make no representations of any kind, including but not limited to the warranties of merchantability or fitness for a particular use, nor are any such warranties to be implied with respect to the data. Extent West -76.708848 East -76.527906 North 39.371642 South 39.199548 This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

The Corona crisis (COVID-19) affects a large proportion of companies and freelancers in Germany. Against this background, the study examines the personal situation and working conditions of employees in Germany in times of corona. The analysis mainly refers to the situation in May 2020 and can only make limited statements about the further situation of the employed persons in the course of the corona pandemic. Personal situation: change in working times during the corona crisis; current work situation (local focus of one´s own work); preference for home office; preference for future home office; financial losses due to the corona crisis; concerns about the financial and economic consequences of the corona crisis in Germany; concerns about the corona crisis in personal areas (job security, current working conditions, financial situation, career opportunities, family situation, health, psychological well-being, housing situation); support from the employer in the corona crisis. 2. Economy and welfare state: political interest; assessment of the economic situation in Germany; preferred form of government (strong vs. liberal state); agreement on various statements on the weighing of values in the Corona crisis (the restrictions on public life to protect the population from Corona are not in proportion to the economic crisis caused by it, the money now being made available for economic aid will later be lacking in other important areas such as education, infrastructure or climate protection, for politicians, the health of the population is the top priority, the interests of the economy influence them less strongly with regard to the corona crisis, the worst part of the crisis is now behind us, as a result of the economic effects of the corona crisis the contrast between rich and poor in Germany will become even more pronounced, the corona crisis affects the low earners more than the middle class, the corona crisis significantly advances the digitalisation of the world of work); perception of state action in the corona crisis on the basis of pairs of opposites (e.g. bureaucratic - unbureaucratic, passive - active, etc.); responsibility of the state to provide financial support to companies in the corona crisis; responsibility of the state to provide financial support to private individuals in the corona crisis over and above basic provision; recipients of state financial aid in the corona crisis (companies, directly to needy private individuals, companies and private individuals alike); assessment of the bureaucracy involved in state financial aid (speed vs. exact examination). 3. Measures: awareness of current measures to support business and individuals in the corona crisis; assessment of current measures to support business and individuals in the corona crisis; reliance on assistance in the corona crisis; nature of assistance used in the corona crisis; barriers to use of assistance in the corona crisis; assessment of the effectiveness of the state measures to cope with the corona crisis; appropriate additional measures to mitigate the economic consequences; concerns about the consequences of the planned state measures (increasing tax burden, rising social contributions, rising inflation, stagnating pension levels, rising retirement age, reduction of other state transfers, safeguarding savings). 4. Information: active search for information on financial assistance offers by the Federal Government in the corona crisis; self-assessment of the level of information on measures to support business and private individuals in the corona crisis; request for detailed information on state assistance measures in the corona crisis (e.g. application process, sources of funding, conditions for receiving assistance, etc.) sources of information used about state aid measures in the Corona crisis; contact with institutions offering economic and financial aid during the Corona crisis (development bank/ municipal development agency, employment agency, tax office, none of them); experience with institutions offering economic and financial aid during the Corona crisis (appropriate treatment). 5. Outlook: assessment of the future economic situation in Germany; assessment of Germany´s future as a strong business location; assessment of its own future economic situation; assessment of the duration of the economic impairment caused by the Corona crisis. Demography: age; sex; education; employment; self-localization social class; net household income; current household income; household income before the crisis; occupational activity; belonging to systemically important occupations; number of persons in the household; number of children under 18 in the household; size of town; party sympathy; migration background. Additionally coded: current number; federal state; education (low, medium, high); weighting factor.

Tags

   social system, socio-economic resources, justice, BES, Environmental disamentities, Environmental Justice, Zoning Board of Appeals




   Summary


   For use in the environmental injustices study of Baltimore relating to patterns of environmental disamenties in relation to low income/minority communities.


   Description


   This feature class layer is a point dataset of authorizing ordinances from the Baltimore City Council and Mayor from 1930 until 1999 concerning identified environmental disamentities. The data was gathered from records from the City Council since 1930 relating to decisions concerning land-uses considered to be environmental disamentities and is to be used to examine environmental injustices involving low income/minority communities in Baltimore. To examine if environmental injustices exist in Baltimore, this point layer will be overlayed with race/income data to determine if patterns of inequity exist. Points were placed manually using the associated addresses from the Ordinance_master dataset and using ISTAR 2004 data in conjunction with Baltimore parcel data. The Ordinance_ID number associated with each point relates to its appeal number from the City Council. Multiple points on the data layer have the same Ordinance_ID. This point layer can be joined with the Ordinance_master data layer based on the field "Ordinance_ID" and using the relationship "Ordinance_point_relationship".


   Credits


   UVM Spatial Analysis Lab


   Use limitations


   None. There are no restrictions on the use of this dataset. The authors of this dataset make no representations of any kind, including but not limited to the warranties of merchantability or fitness for a particular use, nor are any such warranties to be implied with respect to the data.



   This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase.


   The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive.


   The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders.


   Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

This table presents income shares, thresholds, tax shares, and total counts of individual Canadian tax filers, with a focus on high income individuals (95% income threshold, 99% threshold, etc.). Income thresholds are based on national threshold values, regardless of selected geography; for example, the number of Nova Scotians in the top 1% will be calculated as the number of taxfiling Nova Scotians whose total income exceeded the 99% national income threshold. Different definitions of income are available in the table namely market, total, and after-tax income, both with and without capital gains.

Trend study of changes in general opinions and attitudes of ( parts of ) the Dutch population / willingness to offer income for a shorter working week / job satisfaction, worries, future/ satisfaction with education / satisfaction with present life / importance of and satisfaction with work and leisure / media exposure concerning news and politics / average time of watching tv / subscription to a national newspaper / idea of what welfare means / present welfare in the Netherlands and in own family / opinion about borrowing money from a bank and about payment by instalments / satisfaction with present society in the Netherlands / government should have more or less money to finance public facilities / measures of government concerning facilities for pupils who have difficulties making their homework at home/ study grants for children from low income groups / good and cheap housing / minimum wages / free education until 18 / pollution / compulsory education until 18 / subsidies for art / day nurseries for children from working mothers / various taxes / government spendings should increase or decrease / personal life worries/ fears/ enough leisure/ feelings of loneliness and senselessness / measures for commercial organizations making losses / firing personnel/ firing management/ cutting down wages/ state aid / satisfaction with housing/ health/ happiness/ marriage/ education/ income/ social securities / opinions about maximum wages/ abuse of social benefits/ income differences/ property differences/ participation of labourers in management / not being entitled to financial aid/ work with future/ as much education as wanted/ comfortable housing situation / one has to be free to demonstrate/ criticize royal family/ strike for wages/ refuse military service/ squat buildings for a just cause/ freedom of speech and press / view of life / religion and political and social organizations / most important things in life / society transparency/ information about duties and rights/ just treatment / most important problems in society / energy problem and measures for economization / participation in educational system and in local and provincial politics / opinions on differences in social status/ emancipation of labour class/ abortion/ emancipation of women/ work, leisure/ forced measures of government concerning energy economization/ taxes/ ways of protesting / type of person that should get a house first, should be fired first, should be promoted first: married, unmarried/ foreigner, Dutch/ young, old/ man, woman/ someone from Surinam or Holland/ white, non-white/ big family, small family / attitudes on man and society / political interest, preference, participation / membership of union / working mothers / euthanasia / non-whites as neighbours / politics mainly a man's business / again personal feelings and behaviour worries, happiness, temper, nightmares, coping with problems, decision making/ boasting, being polite, gossiping, talking about something without knowledge, opinions about other people, answering personal letters, declaring goods at border. Background variables: basic characteristics/ place of birth/ residence/ household characteristics/ occupation/employment/ income/capital assets/ education/ social class/ politics/ religion/ readership, mass media, and 'cultural' exposure/ organizational membership.The data- and documentation files of this dataset can be downloaded via the option Data Files. Het Sociaal en Cultureel Planbureau (SCP) voert sinds 1975 (twee)jaarlijks het onderzoek Culturele Veranderingen in Nederland uit. De reeks bestaat inmiddels uit 30 onderzoeken en bevat zo’n 3500 variabelen en gegevens over meer dan 50.000 respondenten.De onderzoeken Culturele Veranderingen in Nederland (CV) en SCP Leefsituatie Index (SLI) worden sinds 2004 tweejaarlijks gecombineerd uitgevoerd in samenwerking door het Sociaal Cultureel Planbureau (SCP) en het Centraal Bureau voor de Statistiek (CBS).Doel van CV is vaststellen welke opvattingen “de Nederlander” heeft over samenleving en cultuur en hoe deze in de loop van de tijd zijn veranderd. Doel van SLI is het ontwikkelen van een indicator om de sociale leefsituatie van Nederland in kaart te brengen en het monitoren van de ontwikkeling van de sociale leefsituatie van de Nederlandse bevolking.De onderzoeken liggen aan de basis van veel onderzoek uit het werkprogramma van het SCP. Door het CBS zullen de data vooral worden gebruikt ten behoeve van het speerpunt Sociale Samenhang.

Graph and download economic data for Median Household Income in California (MEHOINUSCAA646N) from 1984 to 2023 about CA, households, median, income, and USA.

Families of tax filers; Single-earner and dual-earner census families by number of children (final T1 Family File; T1FF).

A dataset listing the richest zip codes in Missouri per the most current US Census data, including information on rank and average income.

Egypt Average Household Income: Value data was reported at 81,466.600 EGP in 2022. This records an increase from the previous number of 69,059.600 EGP for 2020. Egypt Average Household Income: Value data is updated yearly, averaging 37,342.750 EGP from Jun 2005 (Median) to 2022, with 8 observations. The data reached an all-time high of 81,466.600 EGP in 2022 and a record low of 13,457.900 EGP in 2005. Egypt Average Household Income: Value data remains active status in CEIC and is reported by Central Agency for Public Mobilization and Statistics. The data is categorized under Global Database’s Egypt – Table EG.H012: Average Household Income.

A dataset listing the richest zip codes in North Carolina per the most current US Census data, including information on rank and average income.

A dataset listing the richest zip codes in New York per the most current US Census data, including information on rank and average income.