Data Source

Registry

Type of Study

Registry

Data gathering method

Administrative records of individuals recieving social security benefits. Insurance providers that are legally obliged to do so submit personal information on individuals who have applied for and who receive benefits.

Data Source

Registry

Type of Study

Registry

Data gathering method

Administrative records of individuals recieving social security benefits. Insurance providers that are legally obliged to do so submit personal information on individuals who have applied for and who receive benefits.

Conditions of access

Formal agreements (e.g. fees, research contracts, institutional agreements, etc.)

Access to database available upon request to governing institution

Type of available data (e.g. anonymised microdata, aggregated tables, etc.)

Anonymised microdata

Language issues

Reports and tables are only available in German.

Conditions of access

Formal agreements (e.g. fees, research contracts, institutional agreements, etc.)

Access to database available upon request to governing institution

Type of available data (e.g. anonymised microdata, aggregated tables, etc.)

Anonymised microdata

Language issues

Reports and tables are only available in German.

Years of collection, reference years, and sample sizes

Different data series included in the CSSR have been collected for varying numbers of years, with the earliest data collection in (more or less) its current format dating back 21 years (1992) The sample is made up of the entire Austrian population registered with the Central National Registry and with the CSSR. Currently the data set contains information of about 10 million individuals with 56 million insurance spells (Versicherungszeiten).

First year of collection

1972

Stratification if applicable

NA

Base used for sampling

Registry

Geographical coverage and breakdowns

By state (Bundesland)

Age range

No age range specified

Coverage of main and cross-cutting topics

Data collected on: (a)Labour market status and monthly salary, (b)health insurance (Insured and services), (c)pension insurance (insured and pensions), (d)accident insurance (insured, accidents at work, services), (e)long-term care benefits (a) Labour market status and monthly salary: employment status and monthly salary levels by region, age, gender and nationality. (b) Health insurance: eligible persons; persons insured by the federal health insurance fund by type of insurance, by state and insurance areas, by insurance providers, and by state and gender; insured status of self-employed and regularly employed persons; health insurance for farmers; sick leave; service costs of the health insurance fund (c) Pension insurance: pension status by gender, all pensions received and amounts, pension provider, and by state; self-employed and regularly employed persons receiving pension benefits; status of the pensioner by age; status of pensioners by capacity and reduced capacity to work; newly awarded pension benefits by age (d) Accident insurance: recognized accident insurance claims by insurance provider and category of insured persons, recognized road and labour accident insurance claims, disabilty benefits by age and gender (e) Long-term care benefits: beneficiaries of long-term care allowances by level of care (1-7), region, gender, age, as well as annual expenditure on long-term care benefits provided by both federal and state governments from 2000 to 2012. Statistik Austria provides additional information on the full cost of long-term care services by care type (in-patient, out-patient, home care, day care) and by region Corresponds to: Social Systems and Welfare and Work and Productivity topics

Further Reading

• "Austrian Social Security in Numbers" (Die österreichische Sozialversicherung in Zahlen) • "Handbook of Austrian Social Security, 2013" (Handbuch der österreichischen Sozialversicherung, 2013) • "Social Protection in Austria, 2012" BMASK • Staubli, S., & Zweimüller, J. “Does Raising the Retirement Age Increase Employment of Older Workers?” Institute for the Study of Labor, Bonn (2011). Available at http://ftp.iza.org/dp5863.pdf

Years of collection, reference years, and sample sizes

i. Different data series included in the CSSR have been collected for varying numbers of years, with the earliest data collection in (more or less) its current format dating back 21 years (1992) ii. NA Iii. The sample is made up of the entire Austrian population registered with the Central National Registry and with the CSSR. Currently the data set contains information of about 10 million individuals with 56 million insurance spells (Versicherungszeiten).

First year of collection

1972

Stratification if applicable

NA

Base used for sampling

Registry

Geographical coverage and breakdowns

By state (Bundesland)

Age range

No age range specified

Coverage of main and cross-cutting topics

Data collected on: (a)Labour market status and monthly salary, (b)health insurance (Insured and services), (c)pension insurance (insured and pensions), (d)accident insurance (insured, accidents at work, services), (e)long-term care benefits (a) Labour market status and monthly salary: employment status and monthly salary levels by region, age, gender and nationality. (b) Health insurance: eligible persons; persons insured by the federal health insurance fund by type of insurance, by state and insurance areas, by insurance providers, and by state and gender; insured status of self-employed and regularly employed persons; health insurance for farmers; sick leave; service costs of the health insurance fund (c) Pension insurance: pension status by gender, all pensions received and amounts, pension provider, and by state; self-employed and regularly employed persons receiving pension benefits; status of the pensioner by age; status of pensioners by capacity and reduced capacity to work; newly awarded pension benefits by age (d) Accident insurance: recognized accident insurance claims by insurance provider and category of insured persons, recognized road and labour accident insurance claims, disabilty benefits by age and gender (e) Long-term care benefits: beneficiaries of long-term care allowances by level of care (1-7), region, gender, age, as well as annual expenditure on long-term care benefits provided by both federal and state governments from 2000 to 2012. Statistik Austria provides additional information on the full cost of long-term care services by care type (in-patient, out-patient, home care, day care) and by region Corresponds to: Social Systems and Welfare and Work and Productivity topics

Further Reading

• "Austrian Social Security in Numbers" (Die österreichische Sozialversicherung in Zahlen) • "Handbook of Austrian Social Security, 2013" (Handbuch der österreichischen Sozialversicherung, 2013) • "Social Protection in Austria, 2012" BMASK • Staubli, S., & Zweimüller, J. “Does Raising the Retirement Age Increase Employment of Older Workers?” Institute for the Study of Labor, Bonn (2011). Available at http://ftp.iza.org/dp5863.pdf

Possibility of linkage among databases

Linkage is possible with the Central Population Register (CPR), Tax Register (TR), the Unemployment Register (UR), the Register of Educational Attainment (EAR), Business Register of Enterprises including their local units (BR) and Housing Register of buildings and dwellings (HR).

Possibility of linkage among databases

Linkage is possible with the Central Population Register (CPR), Tax Register (TR), the Unemployment Register (UR), the Register of Educational Attainment (EAR), Business Register of Enterprises including their local units (BR) and Housing Register of buildings and dwellings (HR).

Entry errors if applicable

Not reported

Breaks

Not reported

Consistency of terminology or coding used during collection

Not reported

Entry errors if applicable

Not reported

Breaks

Not reported

Consistency of terminology or coding used during collection

Not reported

Strengths: Because administrative data are used for determining eligibility and benefit amounts for social insurance programs, they are subject to stringent quality control procedures and data are very reliable. The data has an (almost) universal coverage and is both cross-sectional and longitudinal. Weaknesses: As the data are limited to information required for program administration, they are restricted in scope and do not include broader variables of interest to the research community. A prime problem is the lack of socio-economic characteristics of the persons (i.e. educational attainment, working hours, family affiliation). This drawback can be overcome by matching social security data with other datasets (i.e. an unemployment register which contains information on education and family status; tax registry data on gross yearly income, paid taxes, extra compensation and seniority bonuses or with the Microcensus). A further disadvantage is that data handling is relatively complex.

Strengths: Because administrative data are used for determining eligibility and benefit amounts for social insurance programs, they are subject to stringent quality control procedures and data are very reliable. The data has an (almost) universal coverage and is both cross-sectional and longitudinal. Weaknesses: As the data are limited to information required for program administration, they are restricted in scope and do not include broader variables of interest to the research community. A prime problem is the lack of socio-economic characteristics of the persons (i.e. educational attainment, working hours, family affiliation). This drawback can be overcome by matching social security data with other datasets (i.e. an unemployment register which contains information on education and family status; tax registry data on gross yearly income, paid taxes, extra compensation and seniority bonuses or with the Microcensus). A further disadvantage is that data handling is relatively complex.