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奥地利

  • 总统:Dr. Alexander Van der Bellen
  • 总理:Brigitte Bierlein
  • 首都:Vienna
  • 语言:German (official nationwide) 88.6%, Turkish 2.3%, Serbian 2.2%, Croatian (official in Burgenland) 1.6%, other (includes Slovene, official in South Carinthia, and Hungarian, official in Burgenland) 5.3% (2001 est.)
  • 政府
  • 国家统计局
  • 人口,人口:8,847,037 (2018)
  • 面积,平方公里:82,523
  • 人均国内生产总值,美元:51,513 (2018)
  • GDP,目前美元十亿美元:455.7 (2018)
  • 基尼系数:No data
  • 经商容易度排名:26

Gender

所有数据集:  G H M P S T W
  • G
    • 十一月 2019
      来源: Eurostat
      上传者: Knoema
      访问日期: 15 十一月, 2019
      选择数据集
      The domain "Income and living conditions" covers four topics: people at risk of poverty or social exclusion, income distribution and monetary poverty, living conditions and material deprivation, which are again structured into collections of indicators on specific topics. The collection "People at risk of poverty or social exclusion" houses main indicator on risk of poverty or social inclusion included in the Europe 2020 strategy as well as the intersections between sub-populations of all Europe 2020 indicators on poverty and social exclusion. The collection "Income distribution and monetary poverty" houses collections of indicators relating to poverty risk, poverty risk of working individuals as well as the distribution of income. The collection "Living conditions" hosts indicators relating to characteristics and living conditions of households, characteristics of the population according to different breakdowns, health and labour conditions, housing conditions as well as childcare related indicators. The collection "Material deprivation" covers indicators relating to economic strain, durables, housing deprivation and environment of the dwelling.
    • 十一月 2019
      来源: Eurostat
      上传者: Knoema
      访问日期: 15 十一月, 2019
      选择数据集
      The domain "Income and living conditions" covers four topics: people at risk of poverty or social exclusion, income distribution and monetary poverty, living conditions and material deprivation, which are again structured into collections of indicators on specific topics. The collection "People at risk of poverty or social exclusion" houses main indicator on risk of poverty or social inclusion included in the Europe 2020 strategy as well as the intersections between sub-populations of all Europe 2020 indicators on poverty and social exclusion. The collection "Income distribution and monetary poverty" houses collections of indicators relating to poverty risk, poverty risk of working individuals as well as the distribution of income. The collection "Living conditions" hosts indicators relating to characteristics and living conditions of households, characteristics of the population according to different breakdowns, health and labour conditions, housing conditions as well as childcare related indicators. The collection "Material deprivation" covers indicators relating to economic strain, durables, housing deprivation and environment of the dwelling.
    • 十一月 2019
      来源: Eurostat
      上传者: Knoema
      访问日期: 15 十一月, 2019
      选择数据集
      The domain "Income and living conditions" covers four topics: people at risk of poverty or social exclusion, income distribution and monetary poverty, living conditions and material deprivation, which are again structured into collections of indicators on specific topics. The collection "People at risk of poverty or social exclusion" houses main indicator on risk of poverty or social inclusion included in the Europe 2020 strategy as well as the intersections between sub-populations of all Europe 2020 indicators on poverty and social exclusion. The collection "Income distribution and monetary poverty" houses collections of indicators relating to poverty risk, poverty risk of working individuals as well as the distribution of income. The collection "Living conditions" hosts indicators relating to characteristics and living conditions of households, characteristics of the population according to different breakdowns, health and labour conditions, housing conditions as well as childcare related indicators. The collection "Material deprivation" covers indicators relating to economic strain, durables, housing deprivation and environment of the dwelling.
    • 十一月 2019
      来源: Eurostat
      上传者: Knoema
      访问日期: 15 十一月, 2019
      选择数据集
      The domain "Income and living conditions" covers four topics: people at risk of poverty or social exclusion, income distribution and monetary poverty, living conditions and material deprivation, which are again structured into collections of indicators on specific topics. The collection "People at risk of poverty or social exclusion" houses main indicator on risk of poverty or social inclusion included in the Europe 2020 strategy as well as the intersections between sub-populations of all Europe 2020 indicators on poverty and social exclusion. The collection "Income distribution and monetary poverty" houses collections of indicators relating to poverty risk, poverty risk of working individuals as well as the distribution of income. The collection "Living conditions" hosts indicators relating to characteristics and living conditions of households, characteristics of the population according to different breakdowns, health and labour conditions, housing conditions as well as childcare related indicators. The collection "Material deprivation" covers indicators relating to economic strain, durables, housing deprivation and environment of the dwelling.
    • 十一月 2019
      来源: Eurostat
      上传者: Knoema
      访问日期: 15 十一月, 2019
      选择数据集
      The domain "Income and living conditions" covers four topics: people at risk of poverty or social exclusion, income distribution and monetary poverty, living conditions and material deprivation, which are again structured into collections of indicators on specific topics. The collection "People at risk of poverty or social exclusion" houses main indicator on risk of poverty or social inclusion included in the Europe 2020 strategy as well as the intersections between sub-populations of all Europe 2020 indicators on poverty and social exclusion. The collection "Income distribution and monetary poverty" houses collections of indicators relating to poverty risk, poverty risk of working individuals as well as the distribution of income. The collection "Living conditions" hosts indicators relating to characteristics and living conditions of households, characteristics of the population according to different breakdowns, health and labour conditions, housing conditions as well as childcare related indicators. The collection "Material deprivation" covers indicators relating to economic strain, durables, housing deprivation and environment of the dwelling.
    • 十月 2019
      来源: Eurostat
      上传者: Knoema
      访问日期: 10 十月, 2019
      选择数据集
      The gender employment gap is defined as the difference between the employment rates of men and women aged 20-64. The indicator is based on the EU Labour Force Survey.
    • 十月 2019
      来源: Eurostat
      上传者: Knoema
      访问日期: 10 十月, 2019
      选择数据集
      The gender overall earnings gap is a synthetic indicator. It measures the impact of the three combined factors, namely: (1) the average hourly earnings, (2) the monthly average of the number of hours paid (before any adjustment for part-time work) and (3) the employment rate, on the average earnings of all women of working age - whether employed or not employed - compared to men.
    • 七月 2019
      来源: Eurostat
      上传者: Knoema
      访问日期: 18 七月, 2019
      选择数据集
      The unadjusted Gender Pay Gap (GPG) represents the difference between average gross hourly earnings of male paid employees and of female paid employees as a percentage of average gross hourly earnings of male paid employees. The population consists of all paid employees in enterprises with 10 employees or more in NACE Rev. 2 aggregate B to S (excluding O). The GPG indicator is calculated within the framework of the data collected according to the methodology of the Structure of Earnings Survey.
    • 三月 2018
      来源: Eurostat
      上传者: Knoema
      访问日期: 17 三月, 2018
      选择数据集
      The unadjusted Gender Pay Gap (GPG) represents the difference between average gross hourly earnings of male paid employees and of female paid employees as a percentage of average gross hourly earnings of male paid employees. All employees working in firms with ten or more employees, without restrictions for age and hours worked, are included.
    • 二月 2019
      来源: Eurostat
      上传者: Knoema
      访问日期: 04 三月, 2019
      选择数据集
      The unadjusted gender pay gap (GPG) represents the difference between average gross hourly earnings of male paid employees and of female paid employees as a percentage of average gross hourly earnings of male paid employees. The GPG is calculated on the basis of: - the four-yearly Structure of Earnings Survey (SES) 2002, 2006, 2010, etc., and with the scope as required by the SES regulation,  - national estimates based on national sources for the years between the SES years, from reference year 2007 onwards, with the same coverage as the SES. Data are broken down by economic activity (Statistical Classification of Economic Activities in the European Community - NACE), economic control (public/private) of the enterprise as well as working time (full-time/part-time) and age (six age groups) of employees. Data are released in February/March on the basis of information provided by national statistical institutes.
    • 二月 2019
      来源: Eurostat
      上传者: Knoema
      访问日期: 04 三月, 2019
      选择数据集
      Eurostat Dataset Id:earn_gr_gpgr2wt The unadjusted Gender Pay Gap (GPG) represents the difference between average gross hourly earnings of male paid employees and of female paid employees as a percentage of average gross hourly earnings of male paid employees. From reference year 2006 onwards, the new GPG data is based on the methodology of the Structure of Earnings Survey (COUNCIL REGULATION EC No 530/1999 of 9 March 1999 concerning structural statistics on earnings and on labour costs) which is carried out every four years. The most recent available data refers to reference years 2002, 2006 and 2010. Whereas the GPG figures for 2006 and 2010 are directly computed from the 4-yearly SES, for the intermediate years countries provide annual estimates which every 4 years are revised, benchmarked on the SES results in the two respective years. Some countries calculate the annual GPG on a yearly SES and hence their data needs no further adjustment or revisions as the majority of the others. Data are broken down by economic activity (NACE: Statistical Classification of Economic Activities in the European Community), form of economic and financial control (public/private) of the enterprise, working profile (full-time / part-time) and age classes (six age groups) of employees.
    • 三月 2019
      来源: Eurostat
      上传者: Knoema
      访问日期: 18 三月, 2019
      选择数据集
      The unadjusted gender pay gap (GPG) represents the difference between average gross hourly earnings of male paid employees and of female paid employees as a percentage of average gross hourly earnings of male paid employees. The GPG is calculated on the basis of: - the four-yearly Structure of Earnings Survey (SES) 2002, 2006, 2010, etc., and with the scope as required by the SES regulation,  - national estimates based on national sources for the years between the SES years, from reference year 2007 onwards, with the same coverage as the SES. Data are broken down by economic activity (Statistical Classification of Economic Activities in the European Community - NACE), economic control (public/private) of the enterprise as well as working time (full-time/part-time) and age (six age groups) of employees. Data are released in February/March on the basis of information provided by national statistical institutes.
    • 八月 2013
      来源: Eurostat
      上传者: Knoema
      访问日期: 12 十二月, 2015
      选择数据集
      Eurostat Dataset Id:earn_gr_hgpg The gender pay gap is given as the difference between average gross hourly earnings of male paid employees and of female paid employees as a percentage of average gross hourly earnings of male paid employees. The gender pay gap is based on several data sources, including the European Community Household Panel (ECHP), the EU Survey on Income and Living Conditions (EU-SILC) and national sources.
    • 十一月 2019
      来源: World Bank
      上传者: Knoema
      访问日期: 06 十一月, 2019
      选择数据集
      Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Gender Statistics Publication: https://datacatalog.worldbank.org/dataset/gender-statistics License: http://creativecommons.org/licenses/by/4.0/
    • 十月 2019
      来源: Organisation for Economic Co-operation and Development
      上传者: Knoema
      访问日期: 15 十月, 2019
      选择数据集
      The GID-DB is a database providing researchers and policymakers with key data on gender-based discrimination in social institutions. This data helps analyse women’s empowerment and understand gender gaps in other key areas of development.Covering 180 countries and territories, the GID-DB contains comprehensive information on legal, cultural and traditional practices that discriminate against women and girls.
    • 十二月 2018
      来源: World Economic Forum
      上传者: Shakthi Krishnan
      访问日期: 03 一月, 2019
      选择数据集
      Data cited at: The World Economic Forum https://www.weforum.org/ Topic:  The Global Gender Gap Report 2018 Publication URL: https://www.weforum.org/reports/the-global-gender-gap-report-2018 License: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode   Gender parity is fundamental to whether and how economies and societies thrive. Ensuring the full development and appropriate deployment of half of the world’s total talent pool has a vast bearing on the growth, competitiveness and future-readiness of economies and businesses worldwide. The Global Gender Gap Report benchmarks 149 countries on their progress towards gender parity across four thematic dimensions: Economic Participation and Opportunity, Educational Attainment, Health and Survival, and Political Empowerment. In addition, this year’s edition studies skills gender gaps related to Artificial Intelligence (AI)
  • H
    • 八月 2018
      来源: United Nations Development Programme
      上传者: Knoema
      访问日期: 20 十二月, 2018
      选择数据集
      The Human Development Index (HDI) is a summary measure of achievements in three key dimensions of human development: a long and healthy life, access to knowledge and a decent standard of living. The HDI is the geometric mean of normalized indices for each of the the three dimensions.
  • M
    • 三月 2019
      来源: World Bank
      上传者: Knoema
      访问日期: 20 三月, 2019
      选择数据集
      Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Millennium Development Goals Publication: https://datacatalog.worldbank.org/dataset/millennium-development-goals License: http://creativecommons.org/licenses/by/4.0/   Relevant indicators drawn from the World Development Indicators, reorganized according to the goals and targets of the Millennium Development Goals (MDGs). The MDGs focus the efforts of the world community on achieving significant, measurable improvements in people's lives by the year 2015: they establish targets and yardsticks for measuring development results. Gender Parity Index (GPI)= Value of indicator for Girls/ Value of indicator for Boys. For e.g GPI=School enrolment for Girls/School enrolment for Boys. A value of less than one indicates differences in favor of boys, whereas a value near one (1) indicates that parity has been more or less achieved. The greater the deviation from 1 greater the disparity is.
  • P
    • 十月 2019
      来源: Eurostat
      上传者: Knoema
      访问日期: 23 十月, 2019
      选择数据集
      The Gender Statistics Database (GSD) of the European Institute for Gender Equality (EIGE) contains data on the numbers of women and men in key decision-making positions. "Board members" refer to members of the highest decision-making body of the largest (max. 50) nationally registered companies listed on the national stock exchange. "Executives" refer to executive members of the two highest decision-making bodies of the largest (max. 50) nationally registered companies listed on the national stock exchange.
  • S
    • 十月 2018
      来源: Eurostat
      上传者: Knoema
      访问日期: 03 十一月, 2018
      选择数据集
      This indicator presents the percentage of women among all students in tertiary education irrespective of field of education and among all students in the fields of mathematics, science and computing and in the fields of engineering, manufacturing and construction. The levels and fields of education and training used, follow the 1997 version of the International Standard Classification of Education (ISCED97) and the Eurostat manual of fields of education and training (1999).
    • 六月 2019
      来源: Eurostat
      上传者: Knoema
      访问日期: 27 六月, 2019
      选择数据集
      Researchers are professionals engaged in the conception or creation of new knowledge, products, processes, methods and systems, and in the management of the projects concerned. FTE (Full-time equivalent) corresponds to one year's work by one person (for example, a person who devotes 40 % of his time to R&D) is counted as 0.4 FTE. The share of women researchers among total researchers in FTE in all sectors of performance is shown.
    • 六月 2019
      来源: Eurostat
      上传者: Knoema
      访问日期: 27 六月, 2019
      选择数据集
      Researchers are professionals engaged in the conception or creation of new knowledge, products, processes, methods and systems, and in the management of the projects concerned. The share of women researchers among total researchers in head count in all institutional sectors is shown.
    • 四月 2019
      来源: Organisation for Economic Co-operation and Development
      上传者: Knoema
      访问日期: 12 四月, 2019
      选择数据集
      The SIGI is built on 27 innovative variables measuring discriminatory social institutions, which are grouped into 4 dimensions: discrimination in the family, restricted physical integrity, restricted access to productive and financial resources, and restricted civil liberties.Lower values indicate lower levels of discrimination in social institutions: the SIGI ranges from 0% for no discrimination to 100% for very high discrimination.
  • T
  • W
    • 六月 2019
      来源: Eurostat
      上传者: Knoema
      访问日期: 07 六月, 2019
      选择数据集
      These metadata refer to the annual population data under Population / Demography domain in Eurostat's Dissemination data tree. Eurostat carries on annual demography data collections with the aim of collecting from the National Statistical Institutes detailed data on population, vital events, marriages and divorces. These data are validated, processed and disseminated. Further on, Eurostat uses the collected detailed data to compute and disseminate demographic indicators at country level, at regional level and at EU level, by applying harmonized methods of calculation. The demography data collections are done on voluntary basis and the completeness of information depends on the availability of data reported by the National Statistical Institutes. The first demography data collection of each year, named Rapid, is carried out in April-May (deadline 15 May). Within this data collection the first results on the main demographic developments in the previous year (T-1) and the population on 1st January of the current year (T) are collected from the National Statistical Institutes. A second annual data collection, Joint Demography data collection, is carried out in cooperation with United Nation Statistical Division (UNSD) in the summer of each year, having the deadline 15 September. Within this data collection Eurostat collects from the National Statistical Institutes detailed data on the demographic events (births, deaths, marriages and divorces) of the previous year (T-1) and the population on 1st January of the current year (T), broken down by sex, age and other characteristics. The Nowcast Demography data collection is carried out in October-November (deadline 15 November). The monthly time series on births, deaths, immigrants and emigrants available from the beginning of current year (T) are collected, with the purpose of producing by the end of the current year (T) a forecast on 1st January population of the following year (T+1). The Regional Demography data collection is carried out in November-December (deadline 15 December). It is based on the regional breakdown of the countries agreed at EU level using the latest version of the Nomenclature of Territorial Units for Statistics (NUTS) and of the Statistical regions for the EFTA and Candidate countries. Within this data collection Eurostat collects from the National Statistical Institutes data by NUTS level 1, 2 and 3 for the vital events taking place in the previous year (T-1) and the population figures on 1st January of the current year (T). Any updates sent by the National Statistical Institutes in-between data collections are validated, processed and disseminated in Eurostat's online database as soon as possible. The European aggregates and the demographic indicators are updated accordingly. Please note:The tables presenting population on 1 January figures by various breakdowns may display variations in the total population for some countries at a given moment in time. This may occur due to one of the following reasons: - The timing of the transmission to Eurostat of the population data for various breakdown may lead to different population on 1 January figures displayed in different population tables at a given moment in time. - The transmission to Eurostat of the post-census population revisions (following the 2011 population Censuses) is expected to be done by the national statistical offices gradually for the population breakdowns. The time series of populations between the previous census taking place in the country and 2011 will be revised by end 2013 by some of the countries, taking into account Eurostat’s recommendation. The following countries have transmitted to Eurostat post-2011 Census population revisions, broken down by age and sex, by autumn of 2013, which are reflected in the tables ‘Demographic balance and crude rates (demo_gind)’, ‘Population on 1 January by age and sex (demo_pjan)’, ‘Population on 1 January by five years age groups and sex (demo_pjangroup)’ and ‘Population on 1 January by broad age group and sex (demo_pjanbroad)’: BG 2007-2011; CZ 2001-2011; EE 2000-2011; IE 2007-2011; EL 2011; ES 2002-2011; HR 2001-2011; CY 2003-2011; LV 2001-2011; LT 2001-2011; MT 2006-2011; AT 2008-2011; PT 1992-2011; RO 2002-2011; SK 2002-2011; UK 2002-2011 (not including post-2011 Census data for Scotland); ME 2010-2011; RS 2011. As regards the the population data for the year 2012 and after, for most of the countries these take into account the results of the latest population census (held in 2011). IT 2012-2013 and DE 2012-2013 reported only the total post-2011 Census populations which are published in the table ‘Demographic balance and crude rates (demo_gind)’. The breakdown by age and sex will follow later on. - The succession of the annual demography data collections described above, which collect and update population breakdowns at different moment during the calendar year. - The calendar of the national statistical offices for producing and releasing population broken down by various topics, respectively the timings when data are transmitted to Eurostat. The most updated data on total population on 1st January and on the total number of live births and deaths may be found in the table 'Demographic balance and crude rates (demo_gind)' of the online 'Database by theme'. This table includes the latest updates (or revised data) on total population, births and deaths reported by the countries, while the detailed breakdowns by various characteristics included in the rest of the tables of the Demography domain (and also for Population by citizenship and by country of birth) may be transmitted to Eurostat at a subsequent date.
    • 十月 2019
      来源: World Bank
      上传者: Knoema
      访问日期: 06 十一月, 2019
      选择数据集
      世界银行从官方认可的国际来源编制的发展指标的主要收集。它提供了目前最准确的全球发展数据, 包括国家、区域和全球估计数

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