The OECD Income Distribution database (IDD) has been developed to benchmark and monitor countries' performance in the field of income inequality and poverty. It contains a number of standardised indicators based on the central concept of "equivalised household disposable income", i.e. the total income received by the households less the current taxes and transfers they pay, adjusted for household size with an equivalence scale. While household income is only one of the factors shaping people's economic well-being, it is also the one for which comparable data for all OECD countries are most common. Income distribution has a long-standing tradition among household-level statistics, with regular data collections going back to the 1980s (and sometimes earlier) in many OECD countries.

Achieving comparability in this field is a challenge, as national practices differ widely in terms of concepts, measures, and statistical sources. In order to maximise international comparability as well as inter-temporal consistency of data, the IDD data collection and compilation process is based on a common set of statistical conventions (e.g. on income concepts and components). The information obtained by the OECD through a network of national data providers, via a standardized questionnaire, is based on national sources that are deemed to be most representative for each country.

Small changes in estimates between years should be treated with caution as they may not be statistically significant.

Fore more details, please refer to: https://www.oecd.org/els/soc/IDD-Metadata.pdf and https://www.oecd.org/social/income-distribution-database.htm

The World Economic Outlook (WEO) database contains selected macroeconomic data series from the statistical appendix of the World Economic Outlook report, which presents the IMF staff's analysis and projections of economic developments at the global level, in major country groups and individual countries. The WEO dataset is released twice a year: April and September/October. Please fill out this online form for access to the confidential version--not for redistribution or transfer to any unauthorized third party. The public version is available on the IMF website.

The IMF's World Economic Outlook uses a "bottom-up" approach in producing its forecasts; that is, country teams within the IMF generate projections for individual countries. These are then aggregated, and through a series of iterations where the aggregates feed back into individual countries' forecasts, forecasts converge to the projections reported in the WEO.

Because forecasts are made by the individual country teams, the methodology can vary from country to country and series to series depending on many factors. To get more information on a specific country and series forecast, you may contact the country teams directly; from the Countries tab on the IMF website. (From: https://www.imf.org/en/Publications/WEO/frequently-asked-questions#:~:text=%2Ddatabase%2FDisclaimer.-,Q.,generate%20projections%20for%20individual%20countries.)

Will all children be able to read by 2030? The ability to read with comprehension is a foundational skill that every education system around the world strives to impart by late in primary school—generally by age 10. Moreover, attaining the ambitious Sustainable Development Goals (SDGs) in education requires first achieving this basic building block, and so does improving countries’ Human Capital Index scores. Yet past evidence from many low- and middle-income countries has shown that many children are not learning to read with comprehension in primary school. To understand the global picture better, we have worked with the UNESCO Institute for Statistics (UIS) to assemble a new dataset with the most comprehensive measures of this foundational skill yet developed, by linking together data from credible cross-national and national assessments of reading. This dataset covers 115 countries, accounting for 81% of children worldwide and 79% of children in low- and middle-income countries. The new data allow us to estimate the reading proficiency of late-primary-age children, and we also provide what are among the first estimates (and the most comprehensive, for low- and middle-income countries) of the historical rate of progress in improving reading proficiency globally (for the 2000-17 period). The results show that 53% of all children in low- and middle-income countries cannot read age-appropriate material by age 10, and that at current rates of improvement, this “learning poverty” rate will have fallen only to 43% by 2030. Indeed, we find that the goal of all children reading by 2030 will be attainable only with historically unprecedented progress. The high rate of “learning poverty” and slow progress in low- and middle-income countries is an early warning that all the ambitious SDG targets in education (and likely of social progress) are at risk. Based on this evidence, we suggest a new medium-term target to guide the World Bank’s work in low- and middle- income countries: cut learning poverty by at least half by 2030. This target, together with improved measurement of learning, can be as an evidence-based tool to accelerate progress to get all children reading by age 10.

For further details, please refer to https://thedocs.worldbank.org/en/doc/e52f55322528903b27f1b7e61238e416-0200022022/original/Learning-poverty-report-2022-06-21-final-V7-0-conferenceEdition.pdf

The database (version August 2022) is built upon the released Global Subnational Atlas of Poverty (GSAP) (World Bank, 2021). In this database, we assemble a new panel dataset that provides different measures of inequality. This database is generated using household income and consumption surveys from the World Bank’s Global Monitoring Database (GMD), which underlie country official poverty statistics, and offers the most detailed subnational poverty data on a global scale to date. The Global Subnational Atlas of Poverty (GSAP) is produced by the World Bank’s Poverty and Equity Global Practice, coordinated by the Data for Goals (D4G) team, and supported by the six regional statistics teams in the Poverty and Equity Global Practice, and Global Poverty & Inequality Data Team (GPID) in Development Economics Data Group (DECDG) at the World Bank. The Global Monitoring Database (GMD) is the World Bank’s repository of multitopic income and expenditure household surveys used to monitor global poverty and shared prosperity. The household survey data are typically collected by national statistical offices in each country, and then compiled, processed, and harmonized. The process is coordinated by the Data for Goals (D4G) team and supported by the six regional statistics teams in the Poverty and Equity Global Practice. Global Poverty & Inequality Data Team (GPID) in Development Economics Data Group (DECDG) also contributed historical data from before 1990, and recent survey data from Luxemburg Income Studies (LIS). Selected variables have been harmonized to the extent possible such that levels and trends in poverty and other key sociodemographic attributes can be reasonably compared across and within countries over time. The GMD’s harmonized microdata are currently used in Poverty and Inequality Platform (PIP), World Bank’s Multidimensional Poverty Measures (WB MPM), the Global Database of Shared Prosperity (GDSP), and Poverty and Shared Prosperity Reports. Reference: World Bank. (2021). World Bank estimates based on data from the Global Subnational Atlas of Poverty, Global Monitoring Database. World Bank: Washington. https://datacatalog.worldbank.org/search/dataset/0042041

United States US: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data was reported at 1.310 % in 2016. United States US: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data is updated yearly, averaging 1.310 % from Dec 2016 (Median) to 2016, with 1 observations. United States US: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Poverty. The growth rate in the welfare aggregate of the bottom 40% is computed as the annualized average growth rate in per capita real consumption or income of the bottom 40% of the population in the income distribution in a country from household surveys over a roughly 5-year period. Mean per capita real consumption or income is measured at 2011 Purchasing Power Parity (PPP) using the PovcalNet (http://iresearch.worldbank.org/PovcalNet). For some countries means are not reported due to grouped and/or confidential data. The annualized growth rate is computed as (Mean in final year/Mean in initial year)^(1/(Final year - Initial year)) - 1. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported. The initial year refers to the nearest survey collected 5 years before the most recent survey available, only surveys collected between 3 and 7 years before the most recent survey are considered. The final year refers to the most recent survey available between 2011 and 2015. Growth rates for Iraq are based on survey means of 2005 PPP$. The coverage and quality of the 2011 PPP price data for Iraq and most other North African and Middle Eastern countries were hindered by the exceptional period of instability they faced at the time of the 2011 exercise of the International Comparison Program. See PovcalNet for detailed explanations.; ; World Bank, Global Database of Shared Prosperity (GDSP) circa 2010-2015 (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).; ; The comparability of welfare aggregates (consumption or income) for the chosen years T0 and T1 is assessed for every country. If comparability across the two surveys is a major concern for a country, the selection criteria are re-applied to select the next best survey year(s). Annualized growth rates are calculated between the survey years, using a compound growth formula. The survey years defining the period for which growth rates are calculated and the type of welfare aggregate used to calculate the growth rates are noted in the footnotes.

Data for replicating The Global Spatial Distribution of Economic Activity: Nature, History, and the Role of Trade (forthcoming 2018; with Vernon Henderson, Tim Squires and David N. Weil) Quarterly Journal of Economics We explore the role of natural characteristics in determining the worldwide spatial distribution of economic activity, as proxied by lights at night, observed across 240,000 grid cells. A parsimonious set of 24 physical geography attributes explains 47% of worldwide variation and 35% of within-country variation in lights. We divide geographic characteristics into two groups, those primarily important for agriculture and those primarily important for trade, and confront a puzzle. In examining within-country variation in lights, among countries that developed early, agricultural variables incrementally explain over 6 times as much variation in lights as do trade variables, while among late developing countries the ratio is only about 1.5, even though the latter group is far more dependent on agriculture. Correspondingly, the marginal effects of agricultural variables as a group on lights are larger in absolute value, and those for trade smaller, for early developers than for late developers. We show that this apparent puzzle is explained by persistence and the differential timing of technological shocks in the two sets of countries. For early developers, structural transformation due to rising agricultural productivity began when transport costs were still high, so cities were localized in agricultural regions. When transport costs fell, these agglomerations persisted. In late-developing countries, transport costs fell before structural transformation. To exploit urban scale economies, manufacturing agglomerated in relatively few, often coastal, locations. Consistent with this explanation, countries that developed earlier are more spatially equal in their distribution of education and economic activity than late developers. This dataset is part of the Global Research Program on Spatial Development of Cities funded by the Multi-Donor Trust Fund on Sustainable Urbanization of the World Bank and supported by the U.K. Department for International Development.

This dataset provides values for GDP PER CAPITA PPP reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

The Equality of Opportunity for Sexual and Gender Minorities (EQOSOGI) project collects comparable cross-country data on legal frameworks that impact sexual and gender minorities' access to markets, services, and spaces in a country and examines how those laws either enable or inhibit the inclusion of sexual and gender minorities. Laws and regulations that discriminate against sexual and gender minorities not only impede social and economic prosperity for the individuals concerned, but can limit a country's wider economic prosperity and development. The EQOSOGI data in this dataset were collected in 2020 in 16 pilot countries covering a range of World Bank regions and income groups. Data presented in Equality of Opportunity for Sexual and Gender Minorities are current as of February 28, 2020. The second round of data will be collected in 2023 and include the 16 original countries and add data for an additional 46 countries. The EQOSOGI project aims to continue expanding its dataset to more countries in the future and also set up a historical data panel showing the path of reform over multiple years. As the dataset grows, it will allow for simple correlation analysis to compare the EQOSOGI data on laws and regulations with measures of economic growth and prosperity.

Colombia CO: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data was reported at -2.590 % in 2021. Colombia CO: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data is updated yearly, averaging -2.590 % from Dec 2021 (Median) to 2021, with 1 observations. The data reached an all-time high of -2.590 % in 2021 and a record low of -2.590 % in 2021. Colombia CO: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Colombia – Table CO.World Bank.WDI: Social: Poverty and Inequality. The growth rate in the welfare aggregate of the bottom 40% is computed as the annualized average growth rate in per capita real consumption or income of the bottom 40% of the population in the income distribution in a country from household surveys over a roughly 5-year period. Mean per capita real consumption or income is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries means are not reported due to grouped and/or confidential data. The annualized growth rate is computed as (Mean in final year/Mean in initial year)^(1/(Final year - Initial year)) - 1. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported. The initial year refers to the nearest survey collected 5 years before the most recent survey available, only surveys collected between 3 and 7 years before the most recent survey are considered. The coverage and quality of the 2017 PPP price data for Iraq and most other North African and Middle Eastern countries were hindered by the exceptional period of instability they faced at the time of the 2017 exercise of the International Comparison Program. See the Poverty and Inequality Platform for detailed explanations.;World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).;;The comparability of welfare aggregates (consumption or income) for the chosen years T0 and T1 is assessed for every country. If comparability across the two surveys is a major concern for a country, the selection criteria are re-applied to select the next best survey year(s). Annualized growth rates are calculated between the survey years, using a compound growth formula. The survey years defining the period for which growth rates are calculated and the type of welfare aggregate used to calculate the growth rates are noted in the footnotes.

A key challenge for a future climate change agreement is allocating emissions targets for individual developed countries that are perceived as equitable given differing national circumstances. Many economics-based frameworks for evaluating future targets use as a key criterion for individual country targets the notion that mitigation measures should result in similar costs (specifically, that the required mitigation actions relative to baseline emissions result in a similar percentage reduction of individual countries’ GDP in the target year or period). Such an economic criterion provides a transparent and objective basis for comparison, but it does not necessarily mean that comparable targets for individual countries are also equitable. A set of thought experiments demonstrates that such an approach indeed does not reflect equity between countries. This is because future business-as-usual emissions, against which the costs of mitigation are assessed, depend on past policy choices and mitigation pathways. An approach that sets future emissions targets at a specific date based on comparable costs, without regard to past policy choices and commitments, would penalise countries that have taken early action and provides a disincentive for taking strong domestic mitigation actions in future. This analysis suggests that the choice of ‘business-as-usual’ emissions against which the future costs of mitigation are assessed needs to receive more attention if economic comparability is intended to also reflect equity of emissions targets over time.

Series Name: Average tariff applied by developed countries most-favored nation status by type of product (percent)Series Code: TM_TAX_DMFNRelease Version: 2021.Q2.G.03 This dataset is part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 17.12.1: Weighted average tariffs faced by developing countries, least developed countries and small island developing StatesTarget 17.12: Realize timely implementation of duty-free and quota-free market access on a lasting basis for all least developed countries, consistent with World Trade Organization decisions, including by ensuring that preferential rules of origin applicable to imports from least developed countries are transparent and simple, and contribute to facilitating market accessGoal 17: Strengthen the means of implementation and revitalize the Global Partnership for Sustainable DevelopmentFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

The International Financial Statistics database covers about 200 countries and areas, with some aggregates calculated for selected regions, plus some world totals. Topics covered include balance of payments, commodity prices, exchange rates, fund position, government finance, industrial production, interest rates, international investment position, international liquidity, international transactions, labor statistics, money and banking, national accounts, population, prices, and real effective exchange rates.

The International Financial Statistics is based on various IMF data collections. It includes exchange rates series for all Fund member countries plus Anguilla, Aruba, China, P.R.: Hong Kong, China, P.R.: Macao, Montserrat, and the Netherlands Antilles. It also includes major Fund accounts series, real effective exchange rates, and other world, area, and country series. Data are available for most IMF member countries with some aggregates calculated for select regions, plus some world totals.

Series Name: Developing countries’ and least developed countries’ share of global services imports (percent)Series Code: TX_IMP_GBSVRRelease Version: 2020.Q2.G.03 This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 17.11.1: Developing countries’ and least developed countries’ share of global exportsTarget 17.11: Significantly increase the exports of developing countries, in particular with a view to doubling the least developed countries’ share of global exports by 2020Goal 17: Strengthen the means of implementation and revitalize the Global Partnership for Sustainable DevelopmentFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

Greece GR: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data was reported at -8.350 % in 2015. Greece GR: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data is updated yearly, averaging -8.350 % from Dec 2015 (Median) to 2015, with 1 observations. Greece GR: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Greece – Table GR.World Bank.WDI: Poverty. The growth rate in the welfare aggregate of the bottom 40% is computed as the annualized average growth rate in per capita real consumption or income of the bottom 40% of the population in the income distribution in a country from household surveys over a roughly 5-year period. Mean per capita real consumption or income is measured at 2011 Purchasing Power Parity (PPP) using the PovcalNet (http://iresearch.worldbank.org/PovcalNet). For some countries means are not reported due to grouped and/or confidential data. The annualized growth rate is computed as (Mean in final year/Mean in initial year)^(1/(Final year - Initial year)) - 1. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported. The initial year refers to the nearest survey collected 5 years before the most recent survey available, only surveys collected between 3 and 7 years before the most recent survey are considered. The final year refers to the most recent survey available between 2011 and 2015. Growth rates for Iraq are based on survey means of 2005 PPP$. The coverage and quality of the 2011 PPP price data for Iraq and most other North African and Middle Eastern countries were hindered by the exceptional period of instability they faced at the time of the 2011 exercise of the International Comparison Program. See PovcalNet for detailed explanations.; ; World Bank, Global Database of Shared Prosperity (GDSP) circa 2010-2015 (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).; ; The comparability of welfare aggregates (consumption or income) for the chosen years T0 and T1 is assessed for every country. If comparability across the two surveys is a major concern for a country, the selection criteria are re-applied to select the next best survey year(s). Annualized growth rates are calculated between the survey years, using a compound growth formula. The survey years defining the period for which growth rates are calculated and the type of welfare aggregate used to calculate the growth rates are noted in the footnotes.

American Labor Who's Who dataset, version 2.2.0

A dataset derived from the digitized text of Solon de Leon, et al., The American Labor Who's Who (New York: Hanford Press, 1925). This release includes separate files the U.S. and "Other Countries" sections of the directory.

The American Labor Who's Who (ALWW), published in 1925, is a directory of activists in the fields of trade unionism, immigrant rights, civil liberties, progressive and radical politics. The directory includes roughly 1,300 entries for U.S. activists and 300 additional non-US activists. Each entry is a telegraphic biography. Some provide only name, professional title and address at the time of publication, but many sketch rich life histories. Nearly all provide details on birth date and place, family background, education, migration, and work histories, as well as key organizations, events publications, home and work addresses.

The ALWW dataset is derived from the text hosted on the HathiTrust digital library: https://catalog.hathitrust.org/Record/000591300. Faculty, staff, and students at UCLA corrected the plain text from the scanned document and parsed the text into comma-separated fields. This release includes separate files for US entries and "Other Countries" entries. About 30 individuals are listed in the US section with the notation "see other countries," mainly Canadians and Mexicans. This subset is also in a separate file in this release.

For more information about this and related projects see: http://socialjusticehistory.org/projects/networkedlabor/.

Contributors Tobias Higbie, Principal Investigator, UCLA History Department Craig Messner, UCLA Center for Digital Humanities Nick de Carlo, UCLA Center for Digital Humanities Zoe Borovsky, UCLA Library

Contents of Release The US and Other Country datasets were developed separately as reflected in their different version numbers. The US entries are more developed and clean. Consider the Other Country files as beta releases. The files listed below are the most up-to-date available. Previous versions are also available via GitHub.

• alww-us-2-2-0.csv (all US entries)
• alww-othercountries-o.3.2.csv (all other country entries)
• alww-othercountries-0.3.2-subset-crossrefd.csv (other country entries cross-referenced in the US entry section)

Field Layouts

The field layouts for the US and Other Country files are slightly different in this release.

US Entries The fields for the US file (alww-us-2-2-0.csv) include: NAME [first and last], NAME-ALWW [name as it appears in the original text], TITLES [named offices or occupations in 1925], ORGS [compiled list of organizations belonged to at any time], BIRTHDATES [m/d/y where present], BIRTHCOUNTRY [derived from Birthplace], BIRTHPLACE [as listed], FATHER [father's occupation, in a few cases includes mother], CAREER (UNABBREVIATED) [education and experience, usually chronological, most common abbreviations expanded to full words], CAREER (ABBREVIATED) [same as previous with original abbreviations], HOME ADDRESS [where present], WORK ADDRESS [where present], PUBLICATIONS [incomplete], INDEX CATEGORY 1 [categories derived from the ALWW index, many have more than one category], INDEX CATEGORY 2, INDEX CATEGORY 3, INDEX CATEGORY 4, INDEX CATEGORY 5, INDEX CATEGORY 6, INDEX CATEGORY 7, INDEX CATEGORY 8, ORIGINAL [unparsed entry text carried over from earlier versions].

Other Countries The other country files (alww-othercountries-o.3.2.csv and alww-othercountries-0.3.2-subset-crossrefd.csv) include these fields: Name [last, first], Titles [named offices or occupations in 1925], Organizations [compiled list of organizations belonged to at any time], Birthdate [as listed], Birthplace [as listed], Father [father's occupation], Other [same as Career above], HomeAddress [as listed], WorkAddress [as listed], Publications [derived from entries].

Related datasets American Labor Press Directory (1925); American Labor Press Directory (1940); Who's Who in Labor (1947).

Judgement on American and Soviet foreign policy. Attitude to selected countries and NATO. Topics: Most important problems of the country; attitude to France, Germany, Great Britain, the USSR and the USA as well as perceived changes in the last few years; assumed reputation of one´s own country abroad; trust in the USA and the USSR to solve world problems; judgement on the agreement of words and deeds in foreign policy as well as the seriousness of the peace efforts of the two great powers; the USSR or the USA as current and as future world power in the military and scientific area as well as in space research; benefit of space travel; attitude to a strengthening of space flight efforts; knowledge about the landing on the moon; necessity of NATO; trust in NATO; judgement on the contribution of one´s own country to NATO; preference for acceptance of political functions by NATO; attitude to a reduction in US soldiers stationed in Western Europe; expected reductions of American obligations in Europe; probability of European unification; desired activities of government in the direction of European unification; preference for a European nuclear force; judgement on the disarmament negotiations between the USA and the USSR; expected benefit of such negotiations for one´s own country and expected consideration of European interests; increased danger of war from the new missile defense systems; prospects of the so-called Budapest recommendation; attitude to the American Vietnam policy; negotiating party that can be held responsible for the failure of the Paris talks; sympathy for Arabs or Israelis in the Middle East Conflict; preference for withdrawal of the Israelis from the occupied territories; attitude to an increase in the total population in one´s country and in the whole world; attitude to birth control in one´s country; attitude to economic aid for lesser developed countries; judgement on the influence and advantageousness of American investments as well as American way of life for one´s own country; autostereotype and description of the American character by means of the same list of characteristics (stereotype); general attitude to American culture; perceived increase in American prosperity; trust in the ability of American politics to solve their own economic and social problems; judgement on the treatment of blacks in the USA and determined changes; proportion of poor in the USA; comparison of proportion of violence or crime in the USA with one´s own country; general judgement on the youth in one´s country in comparison to the USA; assessment of the persuasiveness of the American or Soviet view; religiousness; city size. Also encoded was: length of interview; number of contact attempts; presence of other persons during the interview; willingness of respondent to cooperate; understanding difficulties of respondent. Beurteilung der amerikanischen und sowjetischen Außenpolitik. Einstellung zu ausgewählten Ländern und zur Nato. Themen: Wichtigste Probleme des Landes; Einstellung zu Frankreich, Deutschland, Großbritannien, UdSSR und USA sowie wahrgenommene Veränderungen in den letzten Jahren; vermutetes Ansehen des eigenen Landes im Ausland; Vertrauen in die USA und die UdSSR zur Lösung der Weltprobleme; Beurteilung der Übereinstimmung von Worten und Taten in der Außenpolitik sowie der Ernsthaftigkeit der Friedensbemühungen der beiden Großmächte; UdSSR oder USA als derzeitige und als künftige Weltmacht im militärischen, wissenschaftlichen Bereich sowie in der Weltraumforschung; Nutzen der Weltraumfahrt; Einstellung zu einer Verstärkung von Raumfahrtanstrengungen; Kenntnisse über die Mondlandung; Notwendigkeit der Nato; Vertrauen in die Nato; Beurteilung des Beitrags des eigenen Landes zur Nato; Präferenz für die Übernahme politischer Funktionen durch die Nato; Einstellung zu einer Verringerung der stationierten US-Soldaten in Westeuropa; erwartete Einschränkungen der amerikanischen Verpflichtungen in Europa; Wahrscheinlichkeit einer europäischen Vereinigung; gewünschte Aktivitäten der Regierung in Richtung europäische Einigung; Präferenz für eine europäische Atomstreitmacht; Beurteilung der Abrüstungsverhandlungen zwischen den USA und der UdSSR; erwarteter Nutzen solcher Verhandlungen für das eigene Land und erwartete Berücksichtigung der europäischen Interessen; erhöhte Kriegsgefahr durch die neuen Raketenabwehrsysteme; Aussichten des sogenannten Budapest-Vorschlags; Einstellung zur amerikanischen Vietnam-Politik; Verhandlungspartei, der die Mißerfolge der Pariser Gespräche zugeschrieben werden; Sympathie für die Araber oder Israelis im Nahost-Konflikt; Präferenz für einen Abzug der Israelis aus den besetzten Gebieten; Einstellung zu einer Erhöhung der Bevölkerungszahl im eigenen Land und auf der ganzen Welt; Einstellung zu einer Geburtenkontrolle im eigenen Land; Einstellung zur Wirtschaftshilfe an weniger entwickelte Länder; Beurteilung des Einflusses und der Vorteilhaftigkeit amerikanischer Investitionen sowie amerikanischer Lebensart für das eigene Land; Autostereotyp und Beschreibung des amerikanischen Charakters anhand der gleichen Eigenschaftsliste (Stereotyp); allgemeine Einstellung zur amerikanischen Kultur; wahrgenommene Steigerung des amerikanischen Wohlstands; Vertrauen in die Kompetenz amerikanischer Politik zur Lösung ihrer eigenen wirtschaftlichen und sozialen Probleme; Beurteilung der Behandlung von Schwarzen in den USA und festgestellte Veränderungen; Armenanteil in den USA; Vergleich des Gewaltanteils bzw. der Kriminalität in den USA mit dem eigenen Land; allgemeine Beurteilung der Jugend im eigenen Land im Vergleich zu den USA; Einschätzung der Überzeugungskraft amerikanischer bzw. sowjetischer Anschauung; Religiosität; Ortsgröße. Zusätzlich verkodet wurde: Interviewdauer; Anzahl der Kontaktversuche; Anwesenheit anderer Personen beim Interview; Kooperationsbereitschaft des Befragten; Verständnisschwierigkeiten des Befragten.

CL: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data was reported at 3.140 % in 2022. CL: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data is updated yearly, averaging 3.140 % from Dec 2022 (Median) to 2022, with 1 observations. The data reached an all-time high of 3.140 % in 2022 and a record low of 3.140 % in 2022. CL: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chile – Table CL.World Bank.WDI: Social: Poverty and Inequality. The growth rate in the welfare aggregate of the bottom 40% is computed as the annualized average growth rate in per capita real consumption or income of the bottom 40% of the population in the income distribution in a country from household surveys over a roughly 5-year period. Mean per capita real consumption or income is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries means are not reported due to grouped and/or confidential data. The annualized growth rate is computed as (Mean in final year/Mean in initial year)^(1/(Final year - Initial year)) - 1. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported. The initial year refers to the nearest survey collected 5 years before the most recent survey available, only surveys collected between 3 and 7 years before the most recent survey are considered. The coverage and quality of the 2017 PPP price data for Iraq and most other North African and Middle Eastern countries were hindered by the exceptional period of instability they faced at the time of the 2017 exercise of the International Comparison Program. See the Poverty and Inequality Platform for detailed explanations.;World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).;;The comparability of welfare aggregates (consumption or income) for the chosen years T0 and T1 is assessed for every country. If comparability across the two surveys is a major concern for a country, the selection criteria are re-applied to select the next best survey year(s). Annualized growth rates are calculated between the survey years, using a compound growth formula. The survey years defining the period for which growth rates are calculated and the type of welfare aggregate used to calculate the growth rates are noted in the footnotes.

We developed the DAMA (Distribution of Alien MAmmals) database, a comprehensive source reporting the global distribution of the 230 species of mammals that have established, self-sustaining and free-ranging populations outside their native range due to direct or indirect human action. Every alien range is accompanied by information on its invasion stage, pathway, method of introduction and date of introduction. We collected information from 827 different sources (scientific literature, books, risk assessments, reports, online biodiversity databases and websites), and used it to draw alien range maps for these species following the IUCN mapping framework. DAMA comprises 2726 range polygons, covering 199 Countries, 2190 level 1 administrative areas and 11 zoogeographic realms for the period 21500 BC-AD 2017. The most represented orders among introduced mammal species are Rodentia (n=58, 25.22%), Cetartiodactyla (n=49 species, 21.30%), Carnivora (n=30 species, 13.04%), Diprotodontia (n=28, 12.17%) and Primates (n=26, 11.30%). Mammal species have been frequently introduced for hunting (n=100), pet trade (n=57), conservation (n=51) and fauna improvement (n=42). The majority of range polygons are placed on islands (n=2196, 80.56%), encompass populations that have moved beyond establishment and into the invasion stage (n=1655, 60.71%), and originated from 1500 AD to the present (n=1496, 54.88%). Despite inheriting literature biases towards more studied regions (e.g., developed Countries), DAMA is the most up-to-date picture of alien mammal global distribution and can be used to investigate their invasion ecology across different biogeographical regions.

Series Name: Average tariff applied by developed countries preferential status by type of product (percent)Series Code: TM_TAX_DPRFRelease Version: 2020.Q2.G.03 This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 17.12.1: Weighted average tariffs faced by developing countries, least developed countries and small island developing StatesTarget 17.12: Realize timely implementation of duty-free and quota-free market access on a lasting basis for all least developed countries, consistent with World Trade Organization decisions, including by ensuring that preferential rules of origin applicable to imports from least developed countries are transparent and simple, and contribute to facilitating market accessGoal 17: Strengthen the means of implementation and revitalize the Global Partnership for Sustainable DevelopmentFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

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