Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Analysis of ‘Population aged 25 to under 65 in NRW by immigration status, gender and highest vocational education’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/ab109bdf-d992-5cee-a61a-2c8eaffcda1e on 18 January 2022.
--- Dataset description provided by original source is as follows ---
The statistics show population aged 25 to under 65 in NRW by immigration status, gender and highest vocational education degree. People who are still in school or are in training — i.e. trainees, pupils and students — are not included in the analyses. The highest level of vocational education is distinguished in: without a degree, completed vocational training, tertiary education. Other key data are: German (citizens, emigrants), not German (including Turkish nationality), with migration background, without migration background, overall.
--- Original source retains full ownership of the source dataset ---
A wide-ranging representative longitudinal study of private households that permits researchers to track yearly changes in the health and economic well-being of older people relative to younger people in Germany from 1984 to the present. Every year, there were nearly 11,000 households, and more than 20,000 persons sampled by the fieldwork organization TNS Infratest Sozialforschung. The data provide information on all household members, consisting of Germans living in the Old and New German States, Foreigners, and recent Immigrants to Germany. The Panel was started in 1984. Some of the many topics include household composition, occupational biographies, employment, earnings, health and satisfaction indicators. In addition to standard demographic information, the GSOEP questionnaire also contains objective measuresuse of time, use of earnings, income, benefit payments, health, etc. and subjective measures - level of satisfaction with various aspects of life, hopes and fears, political involvement, etc. of the German population. The first wave, collected in 1984 in the western states of Germany, contains 5,921 households in two randomly sampled sub-groups: 1) German Sub-Sample: people in private households where the head of household was not of Turkish, Greek, Yugoslavian, Spanish, or Italian nationality; 2) Foreign Sub-Sample: people in private households where the head of household was of Turkish, Greek, Yugoslavian, Spanish, or Italian nationality. In each year since 1984, the GSOEP has attempted to re-interview original sample members unless they leave the country. A major expansion of the GSOEP was necessitated by German reunification. In June 1990, the GSOEP fielded a first wave of the eastern states of Germany. This sub-sample includes individuals in private households where the head of household was a citizen of the German Democratic Republic. The first wave contains 2,179 households. In 1994 and 1995, the GSOEP added a sample of immigrants to the western states of Germany from 522 households who arrived after 1984, which in 2006 included 360 households and 684 respondents. In 1998 a new refreshment sample of 1,067 households was selected from the population of private households. In 2000 a sample was drawn using essentially similar selection rules as the original German sub-sample and the 1998 refreshment sample with some modifications. The 2000 sample includes 6,052 households covering 10,890 individuals. Finally, in 2002, an overrepresentation of high-income households was added with 2,671 respondents from 1,224 households, of which 1,801 individuals (689 households) were still included in the year 2006. Data Availability: The data are available to researchers in Germany and abroad in SPSS, SAS, TDA, STATA, and ASCII format for immediate use. Extensive documentation in English and German is available online. The SOEP data are available in German and English, alone or in combination with data from other international panel surveys (e.g., the Cross-National Equivalent Files which contain panel data from Canada, Germany, and the United States). The public use file of the SOEP with anonymous microdata is provided free of charge (plus shipping costs) to universities and research centers. The individual SOEP datasets cannot be downloaded from the DIW Web site due to data protection regulations. Use of the data is subject to special regulations, and data privacy laws necessitate the signing of a data transfer contract with the DIW. The English Language Public Use Version of the GSOEP is distributed and administered by the Department of Policy Analysis and Management, Cornell University. The data are available on CD-ROM from Cornell for a fee. Full instructions for accessing GSOEP data may be accessed on the project website, http://www.human.cornell.edu/che/PAM/Research/Centers-Programs/German-Panel/cnef.cfm * Dates of Study: 1984-present * Study Features: Longitudinal, International * Sample Size: ** 1984: 12,290 (GSOEP West) ** 1990: 4,453 (GSOEP East) ** 2000: 20,000+ Links: * Cornell Project Website: http://www.human.cornell.edu/che/PAM/Research/Centers-Programs/German-Panel/cnef.cfm * GSOEP ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00131
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
- `visit_concert`: This is a standard CAP variables about visiting frequencies.
- `is_visit_concert`: binary variable, 0 if the person had not visited concerts in the previous 12 months.
- `artistic_activity_played_music`: A variable of the frequency of playing music as an amateur or professional practice, in some surveys we have only a binary variable (played in the last 12 months or not) in other we have frequencies. We will convert this into a binary variable.
- `artistic_activity_sung`: A variable of the frequency of singing as an amateur or professional practice, like played_muisc. Because of the liturgical use of singing, and the differences of religious practices among countries and gender, this is a significantly different variable from played_music.
- `age_exact`: The respondent’s age as an integer number.
- `country_code`: an ISO country code
- `geo`: an ISO code that separates Germany to the former East and West Germany, and the United Kingdom to Great Britain and Northern Ireland, and Cyprus to Cyprus and the Turiksh Cypriot community.[we may leave Turkish Cyprus out for practical reasons.]
- `age_education`: This is a harmonized education proxy. Because we work with the data of more than 30 countries, education levels are difficult to harmonize, and we use the Eurobarometer standard proxy, age of leaving education. It is a specially coded variable, and we will re-code them into two variables, `age_education` and `is_student`.
- `is_student`: is a dummy variable for the special coding in age_education for “still studying”, i.e. the person does not have yet a school leaving age. It would be tempting to impute `age` in this case to `age_education`, but we will show why this is not a good strategy.
- `w`, `w1`: Post-stratification weights for the 15+ years old population of each country. Use `w1` for averages of `geo` entities treating Northern Ireland, Great Britain, the United Kingdom, the former GDR, the former West Germany, and Germany as geographical areas. Use `w` when treating the United Kingdom and Germany as one territory.
- `wex`: Projected weight variable. For weighted average values, use `w`, `w1`, for projections on the population size, i.e., use with sums, use `wex`.
- `id`: The identifier of the original survey.
- `rowid``: A new unique identifier that is unique in all harmonized surveys, i.e., remains unique in the harmonized dataset.
Changes since the last version: in the .csv export there was a naming problem. - visit_concert
: This is a standard CAP variables about visiting frequencies, in numeric form. - fct_visit_concert
: This is a standard CAP variables about visiting frequencies, in categorical form. - is_visit_concert
: binary variable, 0 if the person had not visited concerts in the previous 12 months. - artistic_activity_played_music
: A variable of the frequency of playing music as an amateur or professional practice, in some surveys we have only a binary variable (played in the last 12 months or not) in other we have frequencies. We will convert this into a binary variable. - fct_artistic_activity_played_music
: The artistic_activity_played_music
in categorical representation. - artistic_activity_sung
: A variable of the frequency of singing as an amateur or professional practice, like played_muisc. Because of the liturgical use of singing, and the differences of religious practices among countries and gender, this is a significantly different variable from played_music. - fct_artistic_activity_sung
: The artistic_activity_sung
variable in categorical representation. - age_exact
: The respondent’s age as an integer number. - country_code
: an ISO country code - geo
: an ISO code that separates Germany to the former East and West Germany, and the United Kingdom to Great Britain and Northern Ireland, and Cyprus to Cyprus and the Turiksh Cypriot community.[we may leave Turkish Cyprus out for practical reasons.] - age_education
: This is a harmonized education proxy. Because we work with the data of more than 30 countries, education levels are difficult to harmonize, and we use the Eurobarometer standard proxy, age of leaving education. It is a specially coded variable, and we will re-code them into two variables, age_education
and is_student
. - is_student
: is a dummy variable for the special coding in age_education for “still studying”, i.e. the person does not have yet a school leaving age. It would be tempting to impute age
in this case to age_education
, but we will show why this is not a good strategy. - w
, w1
: Post-stratification weights for the 15+ years old population of each country. Use w1
for averages of geo
entities treating Northern Ireland, Great Britain, the United Kingdom, the former GDR, the former West Germany, and Germany as geographical areas. Use w
when treating the United Kingdom and Germany as one territory. - wex
: Projected weight variable. For weighted average values, use w
, w1
, for projections on the population size, i.e., use with sums, use wex
. - id
: The identifier of the original survey. - rowid
`: A new unique identifier that is unique in all harmonized surveys, i.e., remains unique in the harmonized dataset.
Not seeing a result you expected?
Learn how you can add new datasets to our index.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Analysis of ‘Population aged 25 to under 65 in NRW by immigration status, gender and highest vocational education’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/ab109bdf-d992-5cee-a61a-2c8eaffcda1e on 18 January 2022.
--- Dataset description provided by original source is as follows ---
The statistics show population aged 25 to under 65 in NRW by immigration status, gender and highest vocational education degree. People who are still in school or are in training — i.e. trainees, pupils and students — are not included in the analyses. The highest level of vocational education is distinguished in: without a degree, completed vocational training, tertiary education. Other key data are: German (citizens, emigrants), not German (including Turkish nationality), with migration background, without migration background, overall.
--- Original source retains full ownership of the source dataset ---