Joint Programming Initiative

More Years, Better Lives

The Potential and Challenges of Demographic Change

SHARE – Survey of Health, Ageing and Retirement in Europe
SHARE – Survey of Health, Ageing and Retirement in Europe

Topic
Public Attitudes towards Older Age
Health and Performance
Social Systems and Welfare
Work and Productivity
Education and Learning
Housing, Urban Development and Mobility
Social, Civic and Cultural Engagement
Uses of Technology
Wellbeing
Intergenerational Relationships
Relevance for this Topic
Country Europe
URL
More Topics

Governance

Contact information

Munich Center for the Economics of Aging / SHARE: http://www.share-project.org/contact-organisation/project-coordination.html
Max Planck Institute for Social Law and Social Policy, Munich Center for the Economics of Aging (MEA)
Amalienstr. 33
80799 Munich
Germany
Fax: +49 89 38602390
Email: info(at)share-project.org
Url: http://www.share-project.org

Timeliness, transparency

Wave 1 SHARE baseline study: data collected in 2004 and first released in 2005 Wave 2: data collected in 2006/07 and first released in 2008 Wave 3 (SHARELIFE): data collected in 2008/09 and first released in 2010 Wave 4: data collected in 2010/11 and first released in 2012. Fieldwork in Poland was somewhat longer and continued until 2012.

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample

Data gathering method

Telephone interview (CATI)

Face-to-face interview (CAPI, PAPI)


The interviewers used computer-assisted personal interviewing (CAPI) to collect most of the data in all waves. Self-administered questionnaires were handed out in Waves 1, 2, and 4 after completion of the CAPI. Starting in Wave 2, end-of-life interviews (CATI, CAPI) on deceased respondents were administered to relatives or other individuals (proxy) close to the deceased. Proxy interviews were also used when the respondent was not able to do the interview due to for example health problems.

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample

Data gathering method

Telephone interview (CATI)

Face-to-face interview (CAPI, PAPI)


The interviewers used computer-assisted personal interviewing (CAPI) to collect most of the data in all waves. Self-administered questionnaires were handed out in Waves 1, 2, and 4 after completion of the CAPI. Starting in Wave 2, end-of-life interviews (CATI, CAPI) on deceased respondents were administered to relatives or other individuals (proxy) close to the deceased. Proxy interviews were also used when the respondent was not able to do the interview due to for example health problems.

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample

Data gathering method

Telephone interview (CATI)

Face-to-face interview (CAPI, PAPI)


The interviewers used computer-assisted personal interviewing (CAPI) to collect most of the data in all waves. Self-administered questionnaires were handed out in Waves 1, 2, and 4 after completion of the CAPI. Starting in Wave 2, end-of-life interviews (CATI, CAPI) on deceased respondents were administered to relatives or other individuals (proxy) close to the deceased. Proxy interviews were also used when the respondent was not able to do the interview due to for example health problems.

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample

Data gathering method

Telephone interview (CATI)

Face-to-face interview (CAPI, PAPI)


The interviewers used computer-assisted personal interviewing (CAPI) to collect most of the data in all waves. Self-administered questionnaires were handed out in Waves 1, 2, and 4 after completion of the CAPI. Starting in Wave 2, end-of-life interviews (CATI, CAPI) on deceased respondents were administered to relatives or other individuals (proxy) close to the deceased. Proxy interviews were also used when the respondent was not able to do the interview due to for example health problems.

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample

Data gathering method

Telephone interview (CATI)

Face-to-face interview (CAPI, PAPI)


The interviewers used computer-assisted personal interviewing (CAPI) to collect most of the data in all waves. Self-administered questionnaires were handed out in Waves 1, 2, and 4 after completion of the CAPI. Starting in Wave 2, end-of-life interviews (CATI, CAPI) on deceased respondents were administered to relatives or other individuals (proxy) close to the deceased. Proxy interviews were also used when the respondent was not able to do the interview due to for example health problems.

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample

Data gathering method

Telephone interview (CATI)

Face-to-face interview (CAPI, PAPI)


The interviewers used computer-assisted personal interviewing (CAPI) to collect most of the data in all waves. Self-administered questionnaires were handed out in Waves 1, 2, and 4 after completion of the CAPI. Starting in Wave 2, end-of-life interviews (CATI, CAPI) on deceased respondents were administered to relatives or other individuals (proxy) close to the deceased. Proxy interviews were also used when the respondent was not able to do the interview due to for example health problems.

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample

Data gathering method

Telephone interview (CATI)

Face-to-face interview (CAPI, PAPI)


The interviewers used computer-assisted personal interviewing (CAPI) to collect most of the data in all waves. Self-administered questionnaires were handed out in Waves 1, 2, and 4 after completion of the CAPI. Starting in Wave 2, end-of-life interviews (CATI, CAPI) on deceased respondents were administered to relatives or other individuals (proxy) close to the deceased. Proxy interviews were also used when the respondent was not able to do the interview due to for example health problems.

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample

Data gathering method

Telephone interview (CATI)

Face-to-face interview (CAPI, PAPI)


The interviewers used computer-assisted personal interviewing (CAPI) to collect most of the data in all waves. Self-administered questionnaires were handed out in Waves 1, 2, and 4 after completion of the CAPI. Starting in Wave 2, end-of-life interviews (CATI, CAPI) on deceased respondents were administered to relatives or other individuals (proxy) close to the deceased. Proxy interviews were also used when the respondent was not able to do the interview due to for example health problems.

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample

Data gathering method

Telephone interview (CATI)

Face-to-face interview (CAPI, PAPI)


The interviewers used computer-assisted personal interviewing (CAPI) to collect most of the data in all waves. Self-administered questionnaires were handed out in Waves 1, 2, and 4 after completion of the CAPI. Starting in Wave 2, end-of-life interviews (CATI, CAPI) on deceased respondents were administered to relatives or other individuals (proxy) close to the deceased. Proxy interviews were also used when the respondent was not able to do the interview due to for example health problems.

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample

Data gathering method

Telephone interview (CATI)

Face-to-face interview (CAPI, PAPI)


The interviewers used computer-assisted personal interviewing (CAPI) to collect most of the data in all waves. Self-administered questionnaires were handed out in Waves 1, 2, and 4 after completion of the CAPI. Starting in Wave 2, end-of-life interviews (CATI, CAPI) on deceased respondents were administered to relatives or other individuals (proxy) close to the deceased. Proxy interviews were also used when the respondent was not able to do the interview due to for example health problems.


Access to data


Access to data is granted for scientific purposes after registry and is free of charge. Data is easily downloadable from the project's website. Researchers must submit an application (available at: http://www.share-project.org/fileadmin/pdf_documentation/SHARE_Data_Statement.pdf) in order to obtain a login and password for the data download. The login details remain valid for all further releases of SHARE data as long as the scientific affiliation indicated at registration does not change.

Conditions of access


Access to data is restricted to scientific research purposes (signed agreement needed). Data is available free of charge.


Within a few days


microdata


SPSS, STATA


Data and documentation are available in English.

Access to data


Access to data is granted for scientific purposes after registry and is free of charge. Data is easily downloadable from the project's website. Researchers must submit an application (available at: http://www.share-project.org/fileadmin/pdf_documentation/SHARE_Data_Statement.pdf) in order to obtain a login and password for the data download. The login details remain valid for all further releases of SHARE data as long as the scientific affiliation indicated at registration does not change.

Conditions of access


Access to data is restricted to scientific research purposes (signed agreement needed). Data is available free of charge.


Within a few days


microdata


SPSS, STATA


Data and documentation are available in English.

Access to data


Access to data is granted for scientific purposes after registry and is free of charge. Data is easily downloadable from the project's website. Researchers must submit an application (available at: http://www.share-project.org/fileadmin/pdf_documentation/SHARE_Data_Statement.pdf) in order to obtain a login and password for the data download. The login details remain valid for all further releases of SHARE data as long as the scientific affiliation indicated at registration does not change.

Conditions of access


Access to data is restricted to scientific research purposes (signed agreement needed). Data is available free of charge.


Within a few days


microdata


SPSS, STATA


Data and documentation are available in English.

Access to data


Access to data is granted for scientific purposes after registry and is free of charge. Data is easily downloadable from the project's website. Researchers must submit an application (available at: http://www.share-project.org/fileadmin/pdf_documentation/SHARE_Data_Statement.pdf) in order to obtain a login and password for the data download. The login details remain valid for all further releases of SHARE data as long as the scientific affiliation indicated at registration does not change.

Conditions of access


Access to data is restricted to scientific research purposes (signed agreement needed). Data is available free of charge.


Within a few days


microdata


SPSS, STATA


Data and documentation are available in English.

Access to data


Access to data is granted for scientific purposes after registry and is free of charge. Data is easily downloadable from the project's website. Researchers must submit an application (available at: http://www.share-project.org/fileadmin/pdf_documentation/SHARE_Data_Statement.pdf) in order to obtain a login and password for the data download. The login details remain valid for all further releases of SHARE data as long as the scientific affiliation indicated at registration does not change.

Conditions of access


Access to data is restricted to scientific research purposes (signed agreement needed). Data is available free of charge.


Within a few days


microdata


SPSS, STATA


Data and documentation are available in English.

Access to data


Access to data is granted for scientific purposes after registry and is free of charge. Data is easily downloadable from the project's website. Researchers must submit an application (available at: http://www.share-project.org/fileadmin/pdf_documentation/SHARE_Data_Statement.pdf) in order to obtain a login and password for the data download. The login details remain valid for all further releases of SHARE data as long as the scientific affiliation indicated at registration does not change.

Conditions of access


Access to data is restricted to scientific research purposes (signed agreement needed). Data is available free of charge.


Within a few days


microdata


SPSS, STATA


Data and documentation are available in English.

Access to data


Access to data is granted for scientific purposes after registry and is free of charge. Data is easily downloadable from the project's website. Researchers must submit an application (available at: http://www.share-project.org/fileadmin/pdf_documentation/SHARE_Data_Statement.pdf) in order to obtain a login and password for the data download. The login details remain valid for all further releases of SHARE data as long as the scientific affiliation indicated at registration does not change.

Conditions of access


Access to data is restricted to scientific research purposes (signed agreement needed). Data is available free of charge.


Within a few days


microdata


SPSS, STATA


Data and documentation are available in English.

Access to data


Access to data is granted for scientific purposes after registry and is free of charge. Data is easily downloadable from the project's website. Researchers must submit an application (available at: http://www.share-project.org/fileadmin/pdf_documentation/SHARE_Data_Statement.pdf) in order to obtain a login and password for the data download. The login details remain valid for all further releases of SHARE data as long as the scientific affiliation indicated at registration does not change.

Conditions of access


Access to data is restricted to scientific research purposes (signed agreement needed). Data is available free of charge.


Within a few days


microdata


SPSS, STATA


Data and documentation are available in English.

Access to data


Access to data is granted for scientific purposes after registry and is free of charge. Data is easily downloadable from the project's website. Researchers must submit an application (available at: http://www.share-project.org/fileadmin/pdf_documentation/SHARE_Data_Statement.pdf) in order to obtain a login and password for the data download. The login details remain valid for all further releases of SHARE data as long as the scientific affiliation indicated at registration does not change.

Conditions of access


Access to data is restricted to scientific research purposes (signed agreement needed). Data is available free of charge.


Within a few days


microdata


SPSS, STATA


Data and documentation are available in English.

Access to data


Access to data is granted for scientific purposes after registry and is free of charge. Data is easily downloadable from the project's website. Researchers must submit an application (available at: http://www.share-project.org/fileadmin/pdf_documentation/SHARE_Data_Statement.pdf) in order to obtain a login and password for the data download. The login details remain valid for all further releases of SHARE data as long as the scientific affiliation indicated at registration does not change.

Conditions of access


Access to data is restricted to scientific research purposes (signed agreement needed). Data is available free of charge.


Within a few days


microdata


SPSS, STATA


Data and documentation are available in English.


Coverage


Wave 1 SHARE baseline study: data collected in 2004/2005; sample size of 31,115 interviews (release 2.5.0). Wave 2: data collected in 2006/07; sample size of 34,415 Wave 2 interviews, 533 end-of-life interviews, and 18,742 longitudinal interviews (release 2.5.0). Wave 3 (SHARELIFE): data collected in 2008/09; sample size of 26,836 interviews, 1,139 end-of-life interviews, and 1,158 first interviews with new or previously non-cooperating spouses (release 1.0.0). Wave 4: data collected in 2010/11; sample size of 58,489 interviews, of which 21,566 were longitudinal, 1,110 end-of-life interviews (release 1.1.1). All respondents who were interviewed in any previous wave and their partners are part of the longitudinal sample.


2004


Based on age; in Germany and the Netherlands stratification is based on region.


Random (probability) sample, vignette samples, multi-stage sampling design. National sample frames are chosen to achieve full probability sampling. SHARE data is weighted in order to compensate for unequal selection probabilities in the various sample units. The sample excluded those individuals who were incarcerated, hospitalized or out of the country during the entire survey period, unable to speak the country’s language(s) or have moved to an unknown address. In addition, all respondents who were interviewed in any previous wave and their current partners are part of the longitudinal sample.


2004 SHARE baseline study: Austria, Belgium, Denmark, Spain, France, Germany, Greece, Israel, Italy, The Netherlands, Sweden, Switzerland. Wave 2: 15 countries (+ the Czech Republic, Ireland, and Poland). Wave 3 (SHARELIFE): 14 countries. Wave 4: 16 countries (+ Estonia, Hungary, Slovenia, and Portugal), excluding Greece, which could not take part in wave 4 due to the financial crisis. The Irish SHARE study was merged with TILDA – the Irish Longitudinal Study on Ageing - and there is no stand-alone SHARE in Ireland after wave 3.


Population aged 50+; Wave 1 SHARE baseline study: all individuals born in 1954 or earlier; Wave 2: all individuals born in 1956 or earlier; Wave 4: all individuals born in 1960 or earlier


The main goal of SHARE is to provide data to better understand the ageing process and how it affects individuals in the diverse cultural settings of Europe. The SHARE dataset includes cross-national information on economic circumstances, health, wellbeing, as well as integration into family and social networks. It also includes rich information on the socio-economic background of the surveyed individuals and their family members (parents and children), such as gender, age, marital status, educational level, current work, income, and living arrangements. SHARE data from Waves 1, 2 and 4 deal with respondents’ current living conditions, whereas Wave 3 (SHARELIFE) was conducted as retrospective survey and provides information about life histories. More specifically, SHARELIFE data provides information about childhood living circumstances, partners, children, accommodation, employment and wellbeing and health conditions. Thus, it allows for the study of ageing from a life-course perspective. Wave 4 data can also be used to disentangle the influences of the economic crisis on healthy ageing and intergenerational solidarity in different European countries. More specifically, the SHARE data covers: Public Attitudes towards Old Age SHARE data allows for studying attitudes towards retirement, plans to retire early and determinants of actual early retirement. It also allows for the study of age-related perceptions and financial expectations. The dataset is suitable for examining the relationship between early retirement and wellbeing, living conditions, and life satisfaction.


• Abuladze, L., & Sakkeus, L. “27 Social networks and everyday activity limitations.” In Börsch-Supan, A., Brandt, M., Litwin, H., / Weber, G. (eds.) “Active ageing and solidarity between generations in Europe” DE GRUYTER, Berlin, Boston (2013): 311-322. • Angelini, V., Brugiavini, A., & Weber, G. “Ageing and unused capacity in Europe: Is there an early retirement trap?” Economic Policy 24(7) (2009): 463-508. DOI: 10.1111/j.1468-0327.2009.00227.x. • Angelini, V., Cavapozzi, D., Corazzini, L., & Pacagnella, O. “Age, health and life satisfaction among older Europeans.” Social Indicators Research 105(2) (2012): 293-308 DOI: 10.1007/s11205-011-9882-x. • Angelini, V., Laferrere, A., & Weber, G.“ Home-ownership in Europe: How did it happen?” Advances in Life Course Research 18 (2013): 83-90. • Avendano, M., Jürges, H., & Mackenbach, J.P. “Educational level and changes in health across Europe: Longitudinal results from SHARE.” Journal of European Social Policy 19(4) (2009): 301-316. DOI: 10.1177/1350506809341512. • Ayalon, L., Heinik, J., & Litwin, H. “Population group differences in cognitive functioning in a national sample of Israelis fifty years and older.” Research on Aging 32(3) (2010): 304-322. DOI: 10.1177/0164027509356875. • Börsch-Supan, A., Hank, K., & Jürges, H. “A new comprehensive and international view on ageing: introducing the ‘Survey of Health, Ageing and Retirement in Europe’.” European Journal of Ageing 2(4) (2005): 245-253. • Börsch-Supan, A., Brandt, M. , Litwin, H., & Weber, G. (Eds). “Active ageing and solidarity between generations in Europe: First results from SHARE after the economic crisis.” De Gruyter, Berlin (2013). • Börsch-Supan, A., Brandt, M., Hank, K., & Schröder, M. (Eds). “The individual and the welfare state. Life histories in Europe.” Springer, Heidelberg (2011). • Börsch-Supan, A., Brugiavini, A., Jürges, H., et al. “First results from the Survey of Health, Ageing and Retirement in Europe (2004-2007). Starting the longitudinal dimension.” Mannheim Research Institute for the Economics of Aging (MEA), Mannheim (2008). • Börsch-Supan, A., Brugiavini, A., Jürges, H., et al. “Health, ageing and retirement in Europe – First results from the Survey of Health, Ageing and Retirement in Europe.” Mannheim Research Institute for the Economics of Aging (MEA), Mannheim (2005). • Borsch-Supan, A., Brandt, M., Hunkler, C., et al. „Data Resource Profile: The Survey of Health, Ageing and Retirement in Europe (SHARE).” International Journal of Epidemiology 1(10) (2013). DOI: 10.1093/ije/dyt088. • Börsch-Supan, A., & Jürges, H. (Eds). “The Survey of Health, Ageing and Retirement in Europe – Methodology.” MEA, Mannheim (2005). • Brandt, M., Deindl, C., & Hank, K. “Tracing the origins of successful aging: The role of childhood conditions and societal context.” Social Science and Medicine 74(9) (2012): 1418–1425. DOI: 10.1016/j.socscimed.2012.01.004. • Brandt, M., & Deindl, C. “Intergenerational Transfers to Adult Children in Europe: Do Social Policies Matter?” Journal of Marriage and Family 75 (2013): 235-251. • Buber, I., & Engelhardt, H. “Children’s impact on the mental health of their older mothers and fathers: findings from the Survey of Health, Ageing and Retirement in Europe.” European Journal of Ageing 5(1) (2008): 31-45. • Buber, I. “Ageing in Austria: An overview of “Survey Health, Ageing and Retirement in Europe” (SHARE) with special focus on aspects of health.” Vienna Yearbook of Population Research (2007): 309-326. • D’Uva, T. B., O’Donnell, O., & van Doorslaer, E. “Differential health reporting by educational level and its impact on the measurement of health inequalities among older Europeans.” International Journal of Epidemiology 37 (2008): 1375-1383. • Deindl. C. “The influence of living conditions in early life on satisfaction in old age.” Advances in Life Course Research 18(1) (2013): 107-114. DOI: 10.1016/j.alcr.2012.10.008. • Dewey, M.E., & Prince, M.J. “Cognitive function.” In:Börsch-Supan, A., et al. ”Health, Ageing and Retirement in Europe - First Results from the Survey of Health, Ageing and Retirement in Europe” MEA, Mannheim (2005): 118-125. • Donfut-Attias, C., Ogg, J., & Wolff, F.-C. “European patterns of intergenerational financial and time transfers.” European Journal of Ageing 2 (2005):161-173. • Engelhardt, H. “Late careers in Europe: Effects of individual and institutional factors.” European Sociological Review 28(4) (2012): 550-563. DOI: 10.1093/esr/jcr024. • Erlinghagen, M., & Hank, K. “Participation of Older Europeans in Voluntary Work.” Ageing and Society 26(4) (2006): 657-584. • Gaymu, J., & Springer, S. “Living conditions and life satisfaction of older Europeans living alone: A gender and cross-country analysis.” Ageing and Society 30 (2010): 1153-1175. DOI: 10.1017/S0144686X10000231. • Gwozdz, W., & Sousa-Poza, A. “Ageing, health and life satisfaction of the oldest old: An analysis for Germany.” Social Indicators Research 97(3) (2010): 397-417. DOI: 10.1007/s11205-009-9508-8. • Hank, K., & Buber, I. “Grandparents Caring for Their Grandchildren Findings From the 2004 Survey of Health, Ageing, and Retirement in Europe.” Journal of Family Issues 30(1) (2009): 53-73. • Hochman, O., & Lewin-Epstein, N. “Determinants of early retirement preferences in Europe: The role of grandparenthood.” International Journal of Comparative Sociology 54(1) (2013): 29-47 DOI: 10.1177/0020715213480977. • Horner, E.M. “Subjective well-being and retirement: Analysis and policy recommendations.” Journal of Happiness Studies forthcoming. DOI: 10.1007/s10902-012-9399-2. • Jagger, C., et al. “The global Activity Limitation Index measured function and disability similarly across European countries.” Journal of Clinical Epidimiology 63 (2010): 892-899. • Jürges, H., & van Soest, A. “Comparing the wellbeing of older Europeans: Introduction.” Social Indicator Research 105 (2012): 187-190. • Jürges, H. “Healthy minds in healthy bodies: An international comparison of education-related inequality in physical health among older adults.” Scottish Journal of Political Economy 56(3) (2009): 296-320. DOI: 10.1111/j.1467-9485.2009.00485.x. • Kavé, G., Shrira, A., Palgi, Y., et al. “Formal education level versus self-rated literacy as predictors of cognitive aging.” Journals of Gerontology Series B: Psychological Sciences and Social Sciences 67(6) (2012): 697-704. DOI: 10.1093/geronb/gbs031. • Litwin, H., & Sapir, E.V. “Perceived income adequacy among older adults in 12 countries: Findings from the Survey of Health, Ageing, and Retirement in Europe.” The Gerontologist 49(3) (2009): 397-406. • Malter, F. and Börsch-Supan, A. (Eds). (2013). SHARE Wave 4: Innovations & Methodology. Munich: MEA, Max Planck Institute for Social Law and Social Policy. • Mazzonna, F. “The effect of education on old age health and cognitive abilities - does the instrument matter?” SHARE working paper 10-2012, Munich Center for the Economics of Aging (MEA) (2012). • Mazzonna, F., & Peracchi, F. “Ageing, cognitive abilities and retirement.” European Economic Review 56(4) (2012): 691-710. DOI: 10.1016/j.euroecorev.2012.03.004. • Mielck, A., Kiess, R., Knesebeck, O., et al. “Association between forgone care and household income among the elderly in five Western European countries – analyses based on survey data from the SHARE-study.” BMC Health Services Research 9(52) (2009). • Romero-Ortuno, R., Walsh, C. D., Lawor, B.I., & Kenny, R.A. “A Frailty Instrument for primary care: findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).” BMC Geriatrics 10(57) (2010). • Romero-Ortuno, R., et al. “A frailty instrument for primary care: findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).” BMC geriatrics 10(1) (2010): 57. • Schneeweis, N., Skirbekk, V., & Winter-Ebmer, R. “Does schooling improve cognitive functioning at older ages?” Economic Working Paper (1211), University of Linz (2012). • Schröder, M. (2011). Retrospective data collection in the Survey of Health, Ageing and Retirement in Europe. SHARELIFE Methodology. Mannheim: MEA. • Siegrist, J., & Wahrendorf, M. “Quality of work, health and retirement.” The Lancet 374 (2009): 1872-1873. DOI: 10.1016/S0140-6736(09)61666-4. • Siegrist, J., et al. “Quality of work, well-being, and intended early retirement of older employees—baseline results from the SHARE Study." The European Journal of Public Health 17(1) (2007): 62-68. • Sirven, N., & Debrand, N. “Promoting social participation for healthy ageing. An International Comparison of Europeans Aged Fifty and Over.” IRDES Working Paper 7 (2008): 1-21.

Coverage


Wave 1 SHARE baseline study: data collected in 2004/2005; sample size of 31,115 interviews (release 2.5.0). Wave 2: data collected in 2006/07; sample size of 34,415 Wave 2 interviews, 533 end-of-life interviews, and 18,742 longitudinal interviews (release 2.5.0). Wave 3 (SHARELIFE): data collected in 2008/09; sample size of 26,836 interviews, 1,139 end-of-life interviews, and 1,158 first interviews with new or previously non-cooperating spouses (release 1.0.0). Wave 4: data collected in 2010/11; sample size of 58,489 interviews, of which 21,566 were longitudinal, 1,110 end-of-life interviews (release 1.1.1). All respondents who were interviewed in any previous wave and their partners are part of the longitudinal sample.


2004


Based on age; in Germany and the Netherlands stratification is based on region.


Random (probability) sample, vignette samples, multi-stage sampling design. National sample frames are chosen to achieve full probability sampling. SHARE data is weighted in order to compensate for unequal selection probabilities in the various sample units. The sample excluded those individuals who were incarcerated, hospitalized or out of the country during the entire survey period, unable to speak the country’s language(s) or have moved to an unknown address. In addition, all respondents who were interviewed in any previous wave and their current partners are part of the longitudinal sample.


2004 SHARE baseline study: Austria, Belgium, Denmark, Spain, France, Germany, Greece, Israel, Italy, The Netherlands, Sweden, Switzerland. Wave 2: 15 countries (+ the Czech Republic, Ireland, and Poland). Wave 3 (SHARELIFE): 14 countries. Wave 4: 16 countries (+ Estonia, Hungary, Slovenia, and Portugal), excluding Greece, which could not take part in wave 4 due to the financial crisis. The Irish SHARE study was merged with TILDA – the Irish Longitudinal Study on Ageing - and there is no stand-alone SHARE in Ireland after wave 3.


Population aged 50+; Wave 1 SHARE baseline study: all individuals born in 1954 or earlier; Wave 2: all individuals born in 1956 or earlier; Wave 4: all individuals born in 1960 or earlier


The main goal of SHARE is to provide data to better understand the ageing process and how it affects individuals in the diverse cultural settings of Europe. The SHARE dataset includes cross-national information on economic circumstances, health, wellbeing, as well as integration into family and social networks. It also includes rich information on the socio-economic background of the surveyed individuals and their family members (parents and children), such as gender, age, marital status, educational level, current work, income, and living arrangements. SHARE data from Waves 1, 2 and 4 deal with respondents’ current living conditions, whereas Wave 3 (SHARELIFE) was conducted as retrospective survey and provides information about life histories. More specifically, SHARELIFE data provides information about childhood living circumstances, partners, children, accommodation, employment and wellbeing and health conditions. Thus, it allows for the study of ageing from a life-course perspective. Wave 4 data can also be used to disentangle the influences of the economic crisis on healthy ageing and intergenerational solidarity in different European countries. More specifically, the SHARE data covers: Health and Performance: Within this main topic, SHARE covers data on physical functioning (objective health measures and biomarkers, such as blood pressure and cholesterol), self-reported health, psychological health, health behaviour, cognitive functioning, and use of health facilities. Given the wide range of health data that SHARE provides, it is a very suitable database to study different aspects of health among older people, as well as health care. For example, SHARE allows for studying mental and self-reported health, and their relationship with social support, work and retirement. With regard to self reported health, participants were asked to classify their own health in six domains: mobility, cognition, pain, sleep, breathing, and emotional health. Furthermore, SHARE allows for studying the unmet needs for health care and the reasons behind it. Since SHARE provides data on educational attainment, it is also possible to study the effect of education on health inequalities. Biomarkers also allow for studying the relationships between social status and health, as well as the identification of pre-disease pathways.


• Abuladze, L., & Sakkeus, L. “27 Social networks and everyday activity limitations.” In Börsch-Supan, A., Brandt, M., Litwin, H., / Weber, G. (eds.) “Active ageing and solidarity between generations in Europe” DE GRUYTER, Berlin, Boston (2013): 311-322. • Angelini, V., Brugiavini, A., & Weber, G. “Ageing and unused capacity in Europe: Is there an early retirement trap?” Economic Policy 24(7) (2009): 463-508. DOI: 10.1111/j.1468-0327.2009.00227.x. • Angelini, V., Cavapozzi, D., Corazzini, L., & Pacagnella, O. “Age, health and life satisfaction among older Europeans.” Social Indicators Research 105(2) (2012): 293-308 DOI: 10.1007/s11205-011-9882-x. • Angelini, V., Laferrere, A., & Weber, G.“ Home-ownership in Europe: How did it happen?” Advances in Life Course Research 18 (2013): 83-90. • Avendano, M., Jürges, H., & Mackenbach, J.P. “Educational level and changes in health across Europe: Longitudinal results from SHARE.” Journal of European Social Policy 19(4) (2009): 301-316. DOI: 10.1177/1350506809341512. • Ayalon, L., Heinik, J., & Litwin, H. “Population group differences in cognitive functioning in a national sample of Israelis fifty years and older.” Research on Aging 32(3) (2010): 304-322. DOI: 10.1177/0164027509356875. • Börsch-Supan, A., Hank, K., & Jürges, H. “A new comprehensive and international view on ageing: introducing the ‘Survey of Health, Ageing and Retirement in Europe’.” European Journal of Ageing 2(4) (2005): 245-253. • Börsch-Supan, A., Brandt, M. , Litwin, H., & Weber, G. (Eds). “Active ageing and solidarity between generations in Europe: First results from SHARE after the economic crisis.” De Gruyter, Berlin (2013). • Börsch-Supan, A., Brandt, M., Hank, K., & Schröder, M. (Eds). “The individual and the welfare state. Life histories in Europe.” Springer, Heidelberg (2011). • Börsch-Supan, A., Brugiavini, A., Jürges, H., et al. “First results from the Survey of Health, Ageing and Retirement in Europe (2004-2007). Starting the longitudinal dimension.” Mannheim Research Institute for the Economics of Aging (MEA), Mannheim (2008). • Börsch-Supan, A., Brugiavini, A., Jürges, H., et al. “Health, ageing and retirement in Europe – First results from the Survey of Health, Ageing and Retirement in Europe.” Mannheim Research Institute for the Economics of Aging (MEA), Mannheim (2005). • Borsch-Supan, A., Brandt, M., Hunkler, C., et al. „Data Resource Profile: The Survey of Health, Ageing and Retirement in Europe (SHARE).” International Journal of Epidemiology 1(10) (2013). DOI: 10.1093/ije/dyt088. • Börsch-Supan, A., & Jürges, H. (Eds). “The Survey of Health, Ageing and Retirement in Europe – Methodology.” MEA, Mannheim (2005). • Brandt, M., Deindl, C., & Hank, K. “Tracing the origins of successful aging: The role of childhood conditions and societal context.” Social Science and Medicine 74(9) (2012): 1418–1425. DOI: 10.1016/j.socscimed.2012.01.004. • Brandt, M., & Deindl, C. “Intergenerational Transfers to Adult Children in Europe: Do Social Policies Matter?” Journal of Marriage and Family 75 (2013): 235-251. • Buber, I., & Engelhardt, H. “Children’s impact on the mental health of their older mothers and fathers: findings from the Survey of Health, Ageing and Retirement in Europe.” European Journal of Ageing 5(1) (2008): 31-45. • Buber, I. “Ageing in Austria: An overview of “Survey Health, Ageing and Retirement in Europe” (SHARE) with special focus on aspects of health.” Vienna Yearbook of Population Research (2007): 309-326. • D’Uva, T. B., O’Donnell, O., & van Doorslaer, E. “Differential health reporting by educational level and its impact on the measurement of health inequalities among older Europeans.” International Journal of Epidemiology 37 (2008): 1375-1383. • Deindl. C. “The influence of living conditions in early life on satisfaction in old age.” Advances in Life Course Research 18(1) (2013): 107-114. DOI: 10.1016/j.alcr.2012.10.008. • Dewey, M.E., & Prince, M.J. “Cognitive function.” In:Börsch-Supan, A., et al. ”Health, Ageing and Retirement in Europe - First Results from the Survey of Health, Ageing and Retirement in Europe” MEA, Mannheim (2005): 118-125. • Donfut-Attias, C., Ogg, J., & Wolff, F.-C. “European patterns of intergenerational financial and time transfers.” European Journal of Ageing 2 (2005):161-173. • Engelhardt, H. “Late careers in Europe: Effects of individual and institutional factors.” European Sociological Review 28(4) (2012): 550-563. DOI: 10.1093/esr/jcr024. • Erlinghagen, M., & Hank, K. “Participation of Older Europeans in Voluntary Work.” Ageing and Society 26(4) (2006): 657-584. • Gaymu, J., & Springer, S. “Living conditions and life satisfaction of older Europeans living alone: A gender and cross-country analysis.” Ageing and Society 30 (2010): 1153-1175. DOI: 10.1017/S0144686X10000231. • Gwozdz, W., & Sousa-Poza, A. “Ageing, health and life satisfaction of the oldest old: An analysis for Germany.” Social Indicators Research 97(3) (2010): 397-417. DOI: 10.1007/s11205-009-9508-8. • Hank, K., & Buber, I. “Grandparents Caring for Their Grandchildren Findings From the 2004 Survey of Health, Ageing, and Retirement in Europe.” Journal of Family Issues 30(1) (2009): 53-73. • Hochman, O., & Lewin-Epstein, N. “Determinants of early retirement preferences in Europe: The role of grandparenthood.” International Journal of Comparative Sociology 54(1) (2013): 29-47 DOI: 10.1177/0020715213480977. • Horner, E.M. “Subjective well-being and retirement: Analysis and policy recommendations.” Journal of Happiness Studies forthcoming. DOI: 10.1007/s10902-012-9399-2. • Jagger, C., et al. “The global Activity Limitation Index measured function and disability similarly across European countries.” Journal of Clinical Epidimiology 63 (2010): 892-899. • Jürges, H., & van Soest, A. “Comparing the wellbeing of older Europeans: Introduction.” Social Indicator Research 105 (2012): 187-190. • Jürges, H. “Healthy minds in healthy bodies: An international comparison of education-related inequality in physical health among older adults.” Scottish Journal of Political Economy 56(3) (2009): 296-320. DOI: 10.1111/j.1467-9485.2009.00485.x. • Kavé, G., Shrira, A., Palgi, Y., et al. “Formal education level versus self-rated literacy as predictors of cognitive aging.” Journals of Gerontology Series B: Psychological Sciences and Social Sciences 67(6) (2012): 697-704. DOI: 10.1093/geronb/gbs031. • Litwin, H., & Sapir, E.V. “Perceived income adequacy among older adults in 12 countries: Findings from the Survey of Health, Ageing, and Retirement in Europe.” The Gerontologist 49(3) (2009): 397-406. • Malter, F. and Börsch-Supan, A. (Eds). (2013). SHARE Wave 4: Innovations & Methodology. Munich: MEA, Max Planck Institute for Social Law and Social Policy. • Mazzonna, F. “The effect of education on old age health and cognitive abilities - does the instrument matter?” SHARE working paper 10-2012, Munich Center for the Economics of Aging (MEA) (2012). • Mazzonna, F., & Peracchi, F. “Ageing, cognitive abilities and retirement.” European Economic Review 56(4) (2012): 691-710. DOI: 10.1016/j.euroecorev.2012.03.004. • Mielck, A., Kiess, R., Knesebeck, O., et al. “Association between forgone care and household income among the elderly in five Western European countries – analyses based on survey data from the SHARE-study.” BMC Health Services Research 9(52) (2009). • Romero-Ortuno, R., Walsh, C. D., Lawor, B.I., & Kenny, R.A. “A Frailty Instrument for primary care: findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).” BMC Geriatrics 10(57) (2010). • Romero-Ortuno, R., et al. “A frailty instrument for primary care: findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).” BMC geriatrics 10(1) (2010): 57. • Schneeweis, N., Skirbekk, V., & Winter-Ebmer, R. “Does schooling improve cognitive functioning at older ages?” Economic Working Paper (1211), University of Linz (2012). • Schröder, M. (2011). Retrospective data collection in the Survey of Health, Ageing and Retirement in Europe. SHARELIFE Methodology. Mannheim: MEA. • Siegrist, J., & Wahrendorf, M. “Quality of work, health and retirement.” The Lancet 374 (2009): 1872-1873. DOI: 10.1016/S0140-6736(09)61666-4. • Siegrist, J., et al. “Quality of work, well-being, and intended early retirement of older employees—baseline results from the SHARE Study." The European Journal of Public Health 17(1) (2007): 62-68. • Sirven, N., & Debrand, N. “Promoting social participation for healthy ageing. An International Comparison of Europeans Aged Fifty and Over.” IRDES Working Paper 7 (2008): 1-21.

Coverage


Wave 1 SHARE baseline study: data collected in 2004/2005; sample size of 31,115 interviews (release 2.5.0). Wave 2: data collected in 2006/07; sample size of 34,415 Wave 2 interviews, 533 end-of-life interviews, and 18,742 longitudinal interviews (release 2.5.0). Wave 3 (SHARELIFE): data collected in 2008/09; sample size of 26,836 interviews, 1,139 end-of-life interviews, and 1,158 first interviews with new or previously non-cooperating spouses (release 1.0.0). Wave 4: data collected in 2010/11; sample size of 58,489 interviews, of which 21,566 were longitudinal, 1,110 end-of-life interviews (release 1.1.1). All respondents who were interviewed in any previous wave and their partners are part of the longitudinal sample.


2004


Based on age; in Germany and the Netherlands stratification is based on region.


Random (probability) sample, vignette samples, multi-stage sampling design. National sample frames are chosen to achieve full probability sampling. SHARE data is weighted in order to compensate for unequal selection probabilities in the various sample units. The sample excluded those individuals who were incarcerated, hospitalized or out of the country during the entire survey period, unable to speak the country’s language(s) or have moved to an unknown address. In addition, all respondents who were interviewed in any previous wave and their current partners are part of the longitudinal sample.


2004 SHARE baseline study: Austria, Belgium, Denmark, Spain, France, Germany, Greece, Israel, Italy, The Netherlands, Sweden, Switzerland. Wave 2: 15 countries (+ the Czech Republic, Ireland, and Poland). Wave 3 (SHARELIFE): 14 countries. Wave 4: 16 countries (+ Estonia, Hungary, Slovenia, and Portugal), excluding Greece, which could not take part in wave 4 due to the financial crisis. The Irish SHARE study was merged with TILDA – the Irish Longitudinal Study on Ageing - and there is no stand-alone SHARE in Ireland after wave 3.


Population aged 50+; Wave 1 SHARE baseline study: all individuals born in 1954 or earlier; Wave 2: all individuals born in 1956 or earlier; Wave 4: all individuals born in 1960 or earlier


The main goal of SHARE is to provide data to better understand the ageing process and how it affects individuals in the diverse cultural settings of Europe. The SHARE dataset includes cross-national information on economic circumstances, health, wellbeing, as well as integration into family and social networks. It also includes rich information on the socio-economic background of the surveyed individuals and their family members (parents and children), such as gender, age, marital status, educational level, current work, income, and living arrangements. SHARE data from Waves 1, 2 and 4 deal with respondents’ current living conditions, whereas Wave 3 (SHARELIFE) was conducted as retrospective survey and provides information about life histories. More specifically, SHARELIFE data provides information about childhood living circumstances, partners, children, accommodation, employment and wellbeing and health conditions. Thus, it allows for the study of ageing from a life-course perspective. Wave 4 data can also be used to disentangle the influences of the economic crisis on healthy ageing and intergenerational solidarity in different European countries. More specifically, the SHARE data covers: Social Systems and Welfare: SHARE includes rich data on the social system and help provided by the state in terms of, for example, unemployment and sickness benefits. The survey therefore allows for studying the relationship between work, receiving social benefits and retirement. It is also possible to study national pension systems in terms of pension claims, actual pension received, and contribution to pension plans.


• Abuladze, L., & Sakkeus, L. “27 Social networks and everyday activity limitations.” In Börsch-Supan, A., Brandt, M., Litwin, H., / Weber, G. (eds.) “Active ageing and solidarity between generations in Europe” DE GRUYTER, Berlin, Boston (2013): 311-322. • Angelini, V., Brugiavini, A., & Weber, G. “Ageing and unused capacity in Europe: Is there an early retirement trap?” Economic Policy 24(7) (2009): 463-508. DOI: 10.1111/j.1468-0327.2009.00227.x. • Angelini, V., Cavapozzi, D., Corazzini, L., & Pacagnella, O. “Age, health and life satisfaction among older Europeans.” Social Indicators Research 105(2) (2012): 293-308 DOI: 10.1007/s11205-011-9882-x. • Angelini, V., Laferrere, A., & Weber, G.“ Home-ownership in Europe: How did it happen?” Advances in Life Course Research 18 (2013): 83-90. • Avendano, M., Jürges, H., & Mackenbach, J.P. “Educational level and changes in health across Europe: Longitudinal results from SHARE.” Journal of European Social Policy 19(4) (2009): 301-316. DOI: 10.1177/1350506809341512. • Ayalon, L., Heinik, J., & Litwin, H. “Population group differences in cognitive functioning in a national sample of Israelis fifty years and older.” Research on Aging 32(3) (2010): 304-322. DOI: 10.1177/0164027509356875. • Börsch-Supan, A., Hank, K., & Jürges, H. “A new comprehensive and international view on ageing: introducing the ‘Survey of Health, Ageing and Retirement in Europe’.” European Journal of Ageing 2(4) (2005): 245-253. • Börsch-Supan, A., Brandt, M. , Litwin, H., & Weber, G. (Eds). “Active ageing and solidarity between generations in Europe: First results from SHARE after the economic crisis.” De Gruyter, Berlin (2013). • Börsch-Supan, A., Brandt, M., Hank, K., & Schröder, M. (Eds). “The individual and the welfare state. Life histories in Europe.” Springer, Heidelberg (2011). • Börsch-Supan, A., Brugiavini, A., Jürges, H., et al. “First results from the Survey of Health, Ageing and Retirement in Europe (2004-2007). Starting the longitudinal dimension.” Mannheim Research Institute for the Economics of Aging (MEA), Mannheim (2008). • Börsch-Supan, A., Brugiavini, A., Jürges, H., et al. “Health, ageing and retirement in Europe – First results from the Survey of Health, Ageing and Retirement in Europe.” Mannheim Research Institute for the Economics of Aging (MEA), Mannheim (2005). • Borsch-Supan, A., Brandt, M., Hunkler, C., et al. „Data Resource Profile: The Survey of Health, Ageing and Retirement in Europe (SHARE).” International Journal of Epidemiology 1(10) (2013). DOI: 10.1093/ije/dyt088. • Börsch-Supan, A., & Jürges, H. (Eds). “The Survey of Health, Ageing and Retirement in Europe – Methodology.” MEA, Mannheim (2005). • Brandt, M., Deindl, C., & Hank, K. “Tracing the origins of successful aging: The role of childhood conditions and societal context.” Social Science and Medicine 74(9) (2012): 1418–1425. DOI: 10.1016/j.socscimed.2012.01.004. • Brandt, M., & Deindl, C. “Intergenerational Transfers to Adult Children in Europe: Do Social Policies Matter?” Journal of Marriage and Family 75 (2013): 235-251. • Buber, I., & Engelhardt, H. “Children’s impact on the mental health of their older mothers and fathers: findings from the Survey of Health, Ageing and Retirement in Europe.” European Journal of Ageing 5(1) (2008): 31-45. • Buber, I. “Ageing in Austria: An overview of “Survey Health, Ageing and Retirement in Europe” (SHARE) with special focus on aspects of health.” Vienna Yearbook of Population Research (2007): 309-326. • D’Uva, T. B., O’Donnell, O., & van Doorslaer, E. “Differential health reporting by educational level and its impact on the measurement of health inequalities among older Europeans.” International Journal of Epidemiology 37 (2008): 1375-1383. • Deindl. C. “The influence of living conditions in early life on satisfaction in old age.” Advances in Life Course Research 18(1) (2013): 107-114. DOI: 10.1016/j.alcr.2012.10.008. • Dewey, M.E., & Prince, M.J. “Cognitive function.” In:Börsch-Supan, A., et al. ”Health, Ageing and Retirement in Europe - First Results from the Survey of Health, Ageing and Retirement in Europe” MEA, Mannheim (2005): 118-125. • Donfut-Attias, C., Ogg, J., & Wolff, F.-C. “European patterns of intergenerational financial and time transfers.” European Journal of Ageing 2 (2005):161-173. • Engelhardt, H. “Late careers in Europe: Effects of individual and institutional factors.” European Sociological Review 28(4) (2012): 550-563. DOI: 10.1093/esr/jcr024. • Erlinghagen, M., & Hank, K. “Participation of Older Europeans in Voluntary Work.” Ageing and Society 26(4) (2006): 657-584. • Gaymu, J., & Springer, S. “Living conditions and life satisfaction of older Europeans living alone: A gender and cross-country analysis.” Ageing and Society 30 (2010): 1153-1175. DOI: 10.1017/S0144686X10000231. • Gwozdz, W., & Sousa-Poza, A. “Ageing, health and life satisfaction of the oldest old: An analysis for Germany.” Social Indicators Research 97(3) (2010): 397-417. DOI: 10.1007/s11205-009-9508-8. • Hank, K., & Buber, I. “Grandparents Caring for Their Grandchildren Findings From the 2004 Survey of Health, Ageing, and Retirement in Europe.” Journal of Family Issues 30(1) (2009): 53-73. • Hochman, O., & Lewin-Epstein, N. “Determinants of early retirement preferences in Europe: The role of grandparenthood.” International Journal of Comparative Sociology 54(1) (2013): 29-47 DOI: 10.1177/0020715213480977. • Horner, E.M. “Subjective well-being and retirement: Analysis and policy recommendations.” Journal of Happiness Studies forthcoming. DOI: 10.1007/s10902-012-9399-2. • Jagger, C., et al. “The global Activity Limitation Index measured function and disability similarly across European countries.” Journal of Clinical Epidimiology 63 (2010): 892-899. • Jürges, H., & van Soest, A. “Comparing the wellbeing of older Europeans: Introduction.” Social Indicator Research 105 (2012): 187-190. • Jürges, H. “Healthy minds in healthy bodies: An international comparison of education-related inequality in physical health among older adults.” Scottish Journal of Political Economy 56(3) (2009): 296-320. DOI: 10.1111/j.1467-9485.2009.00485.x. • Kavé, G., Shrira, A., Palgi, Y., et al. “Formal education level versus self-rated literacy as predictors of cognitive aging.” Journals of Gerontology Series B: Psychological Sciences and Social Sciences 67(6) (2012): 697-704. DOI: 10.1093/geronb/gbs031. • Litwin, H., & Sapir, E.V. “Perceived income adequacy among older adults in 12 countries: Findings from the Survey of Health, Ageing, and Retirement in Europe.” The Gerontologist 49(3) (2009): 397-406. • Malter, F. and Börsch-Supan, A. (Eds). (2013). SHARE Wave 4: Innovations & Methodology. Munich: MEA, Max Planck Institute for Social Law and Social Policy. • Mazzonna, F. “The effect of education on old age health and cognitive abilities - does the instrument matter?” SHARE working paper 10-2012, Munich Center for the Economics of Aging (MEA) (2012). • Mazzonna, F., & Peracchi, F. “Ageing, cognitive abilities and retirement.” European Economic Review 56(4) (2012): 691-710. DOI: 10.1016/j.euroecorev.2012.03.004. • Mielck, A., Kiess, R., Knesebeck, O., et al. “Association between forgone care and household income among the elderly in five Western European countries – analyses based on survey data from the SHARE-study.” BMC Health Services Research 9(52) (2009). • Romero-Ortuno, R., Walsh, C. D., Lawor, B.I., & Kenny, R.A. “A Frailty Instrument for primary care: findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).” BMC Geriatrics 10(57) (2010). • Romero-Ortuno, R., et al. “A frailty instrument for primary care: findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).” BMC geriatrics 10(1) (2010): 57. • Schneeweis, N., Skirbekk, V., & Winter-Ebmer, R. “Does schooling improve cognitive functioning at older ages?” Economic Working Paper (1211), University of Linz (2012). • Schröder, M. (2011). Retrospective data collection in the Survey of Health, Ageing and Retirement in Europe. SHARELIFE Methodology. Mannheim: MEA. • Siegrist, J., & Wahrendorf, M. “Quality of work, health and retirement.” The Lancet 374 (2009): 1872-1873. DOI: 10.1016/S0140-6736(09)61666-4. • Siegrist, J., et al. “Quality of work, well-being, and intended early retirement of older employees—baseline results from the SHARE Study." The European Journal of Public Health 17(1) (2007): 62-68. • Sirven, N., & Debrand, N. “Promoting social participation for healthy ageing. An International Comparison of Europeans Aged Fifty and Over.” IRDES Working Paper 7 (2008): 1-21.

Coverage


Wave 1 SHARE baseline study: data collected in 2004/2005; sample size of 31,115 interviews (release 2.5.0). Wave 2: data collected in 2006/07; sample size of 34,415 Wave 2 interviews, 533 end-of-life interviews, and 18,742 longitudinal interviews (release 2.5.0). Wave 3 (SHARELIFE): data collected in 2008/09; sample size of 26,836 interviews, 1,139 end-of-life interviews, and 1,158 first interviews with new or previously non-cooperating spouses (release 1.0.0). Wave 4: data collected in 2010/11; sample size of 58,489 interviews, of which 21,566 were longitudinal, 1,110 end-of-life interviews (release 1.1.1). All respondents who were interviewed in any previous wave and their partners are part of the longitudinal sample.


2004


Based on age; in Germany and the Netherlands stratification is based on region.


Random (probability) sample, vignette samples, multi-stage sampling design. National sample frames are chosen to achieve full probability sampling. SHARE data is weighted in order to compensate for unequal selection probabilities in the various sample units. The sample excluded those individuals who were incarcerated, hospitalized or out of the country during the entire survey period, unable to speak the country’s language(s) or have moved to an unknown address. In addition, all respondents who were interviewed in any previous wave and their current partners are part of the longitudinal sample.


2004 SHARE baseline study: Austria, Belgium, Denmark, Spain, France, Germany, Greece, Israel, Italy, The Netherlands, Sweden, Switzerland. Wave 2: 15 countries (+ the Czech Republic, Ireland, and Poland). Wave 3 (SHARELIFE): 14 countries. Wave 4: 16 countries (+ Estonia, Hungary, Slovenia, and Portugal), excluding Greece, which could not take part in wave 4 due to the financial crisis. The Irish SHARE study was merged with TILDA – the Irish Longitudinal Study on Ageing - and there is no stand-alone SHARE in Ireland after wave 3.


Population aged 50+; Wave 1 SHARE baseline study: all individuals born in 1954 or earlier; Wave 2: all individuals born in 1956 or earlier; Wave 4: all individuals born in 1960 or earlier


The main goal of SHARE is to provide data to better understand the ageing process and how it affects individuals in the diverse cultural settings of Europe. The SHARE dataset includes cross-national information on economic circumstances, health, wellbeing, as well as integration into family and social networks. It also includes rich information on the socio-economic background of the surveyed individuals and their family members (parents and children), such as gender, age, marital status, educational level, current work, income, and living arrangements. SHARE data from Waves 1, 2 and 4 deal with respondents’ current living conditions, whereas Wave 3 (SHARELIFE) was conducted as retrospective survey and provides information about life histories. More specifically, SHARELIFE data provides information about childhood living circumstances, partners, children, accommodation, employment and wellbeing and health conditions. Thus, it allows for the study of ageing from a life-course perspective. Wave 4 data can also be used to disentangle the influences of the economic crisis on healthy ageing and intergenerational solidarity in different European countries. More specifically, the SHARE data covers: Work and Productivity: SHARE covers data on employment history, working arrangements and time, income, reasons for retirement, plans for early retirement, as well as perceptions regarding retirement age. It allows for studying the involvement of older people in paid and unpaid work, and voluntary work. The survey also allows for studying the quality of work and working conditions, and its relationship with early retirement. With regard to quality of work, SHARELIFE provides retrospective information on the effort-reward imbalance and control at work.


• Abuladze, L., & Sakkeus, L. “27 Social networks and everyday activity limitations.” In Börsch-Supan, A., Brandt, M., Litwin, H., / Weber, G. (eds.) “Active ageing and solidarity between generations in Europe” DE GRUYTER, Berlin, Boston (2013): 311-322. • Angelini, V., Brugiavini, A., & Weber, G. “Ageing and unused capacity in Europe: Is there an early retirement trap?” Economic Policy 24(7) (2009): 463-508. DOI: 10.1111/j.1468-0327.2009.00227.x. • Angelini, V., Cavapozzi, D., Corazzini, L., & Pacagnella, O. “Age, health and life satisfaction among older Europeans.” Social Indicators Research 105(2) (2012): 293-308 DOI: 10.1007/s11205-011-9882-x. • Angelini, V., Laferrere, A., & Weber, G.“ Home-ownership in Europe: How did it happen?” Advances in Life Course Research 18 (2013): 83-90. • Avendano, M., Jürges, H., & Mackenbach, J.P. “Educational level and changes in health across Europe: Longitudinal results from SHARE.” Journal of European Social Policy 19(4) (2009): 301-316. DOI: 10.1177/1350506809341512. • Ayalon, L., Heinik, J., & Litwin, H. “Population group differences in cognitive functioning in a national sample of Israelis fifty years and older.” Research on Aging 32(3) (2010): 304-322. DOI: 10.1177/0164027509356875. • Börsch-Supan, A., Hank, K., & Jürges, H. “A new comprehensive and international view on ageing: introducing the ‘Survey of Health, Ageing and Retirement in Europe’.” European Journal of Ageing 2(4) (2005): 245-253. • Börsch-Supan, A., Brandt, M. , Litwin, H., & Weber, G. (Eds). “Active ageing and solidarity between generations in Europe: First results from SHARE after the economic crisis.” De Gruyter, Berlin (2013). • Börsch-Supan, A., Brandt, M., Hank, K., & Schröder, M. (Eds). “The individual and the welfare state. Life histories in Europe.” Springer, Heidelberg (2011). • Börsch-Supan, A., Brugiavini, A., Jürges, H., et al. “First results from the Survey of Health, Ageing and Retirement in Europe (2004-2007). Starting the longitudinal dimension.” Mannheim Research Institute for the Economics of Aging (MEA), Mannheim (2008). • Börsch-Supan, A., Brugiavini, A., Jürges, H., et al. “Health, ageing and retirement in Europe – First results from the Survey of Health, Ageing and Retirement in Europe.” Mannheim Research Institute for the Economics of Aging (MEA), Mannheim (2005). • Borsch-Supan, A., Brandt, M., Hunkler, C., et al. „Data Resource Profile: The Survey of Health, Ageing and Retirement in Europe (SHARE).” International Journal of Epidemiology 1(10) (2013). DOI: 10.1093/ije/dyt088. • Börsch-Supan, A., & Jürges, H. (Eds). “The Survey of Health, Ageing and Retirement in Europe – Methodology.” MEA, Mannheim (2005). • Brandt, M., Deindl, C., & Hank, K. “Tracing the origins of successful aging: The role of childhood conditions and societal context.” Social Science and Medicine 74(9) (2012): 1418–1425. DOI: 10.1016/j.socscimed.2012.01.004. • Brandt, M., & Deindl, C. “Intergenerational Transfers to Adult Children in Europe: Do Social Policies Matter?” Journal of Marriage and Family 75 (2013): 235-251. • Buber, I., & Engelhardt, H. “Children’s impact on the mental health of their older mothers and fathers: findings from the Survey of Health, Ageing and Retirement in Europe.” European Journal of Ageing 5(1) (2008): 31-45. • Buber, I. “Ageing in Austria: An overview of “Survey Health, Ageing and Retirement in Europe” (SHARE) with special focus on aspects of health.” Vienna Yearbook of Population Research (2007): 309-326. • D’Uva, T. B., O’Donnell, O., & van Doorslaer, E. “Differential health reporting by educational level and its impact on the measurement of health inequalities among older Europeans.” International Journal of Epidemiology 37 (2008): 1375-1383. • Deindl. C. “The influence of living conditions in early life on satisfaction in old age.” Advances in Life Course Research 18(1) (2013): 107-114. DOI: 10.1016/j.alcr.2012.10.008. • Dewey, M.E., & Prince, M.J. “Cognitive function.” In:Börsch-Supan, A., et al. ”Health, Ageing and Retirement in Europe - First Results from the Survey of Health, Ageing and Retirement in Europe” MEA, Mannheim (2005): 118-125. • Donfut-Attias, C., Ogg, J., & Wolff, F.-C. “European patterns of intergenerational financial and time transfers.” European Journal of Ageing 2 (2005):161-173. • Engelhardt, H. “Late careers in Europe: Effects of individual and institutional factors.” European Sociological Review 28(4) (2012): 550-563. DOI: 10.1093/esr/jcr024. • Erlinghagen, M., & Hank, K. “Participation of Older Europeans in Voluntary Work.” Ageing and Society 26(4) (2006): 657-584. • Gaymu, J., & Springer, S. “Living conditions and life satisfaction of older Europeans living alone: A gender and cross-country analysis.” Ageing and Society 30 (2010): 1153-1175. DOI: 10.1017/S0144686X10000231. • Gwozdz, W., & Sousa-Poza, A. “Ageing, health and life satisfaction of the oldest old: An analysis for Germany.” Social Indicators Research 97(3) (2010): 397-417. DOI: 10.1007/s11205-009-9508-8. • Hank, K., & Buber, I. “Grandparents Caring for Their Grandchildren Findings From the 2004 Survey of Health, Ageing, and Retirement in Europe.” Journal of Family Issues 30(1) (2009): 53-73. • Hochman, O., & Lewin-Epstein, N. “Determinants of early retirement preferences in Europe: The role of grandparenthood.” International Journal of Comparative Sociology 54(1) (2013): 29-47 DOI: 10.1177/0020715213480977. • Horner, E.M. “Subjective well-being and retirement: Analysis and policy recommendations.” Journal of Happiness Studies forthcoming. DOI: 10.1007/s10902-012-9399-2. • Jagger, C., et al. “The global Activity Limitation Index measured function and disability similarly across European countries.” Journal of Clinical Epidimiology 63 (2010): 892-899. • Jürges, H., & van Soest, A. “Comparing the wellbeing of older Europeans: Introduction.” Social Indicator Research 105 (2012): 187-190. • Jürges, H. “Healthy minds in healthy bodies: An international comparison of education-related inequality in physical health among older adults.” Scottish Journal of Political Economy 56(3) (2009): 296-320. DOI: 10.1111/j.1467-9485.2009.00485.x. • Kavé, G., Shrira, A., Palgi, Y., et al. “Formal education level versus self-rated literacy as predictors of cognitive aging.” Journals of Gerontology Series B: Psychological Sciences and Social Sciences 67(6) (2012): 697-704. DOI: 10.1093/geronb/gbs031. • Litwin, H., & Sapir, E.V. “Perceived income adequacy among older adults in 12 countries: Findings from the Survey of Health, Ageing, and Retirement in Europe.” The Gerontologist 49(3) (2009): 397-406. • Malter, F. and Börsch-Supan, A. (Eds). (2013). SHARE Wave 4: Innovations & Methodology. Munich: MEA, Max Planck Institute for Social Law and Social Policy. • Mazzonna, F. “The effect of education on old age health and cognitive abilities - does the instrument matter?” SHARE working paper 10-2012, Munich Center for the Economics of Aging (MEA) (2012). • Mazzonna, F., & Peracchi, F. “Ageing, cognitive abilities and retirement.” European Economic Review 56(4) (2012): 691-710. DOI: 10.1016/j.euroecorev.2012.03.004. • Mielck, A., Kiess, R., Knesebeck, O., et al. “Association between forgone care and household income among the elderly in five Western European countries – analyses based on survey data from the SHARE-study.” BMC Health Services Research 9(52) (2009). • Romero-Ortuno, R., Walsh, C. D., Lawor, B.I., & Kenny, R.A. “A Frailty Instrument for primary care: findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).” BMC Geriatrics 10(57) (2010). • Romero-Ortuno, R., et al. “A frailty instrument for primary care: findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).” BMC geriatrics 10(1) (2010): 57. • Schneeweis, N., Skirbekk, V., & Winter-Ebmer, R. “Does schooling improve cognitive functioning at older ages?” Economic Working Paper (1211), University of Linz (2012). • Schröder, M. (2011). Retrospective data collection in the Survey of Health, Ageing and Retirement in Europe. SHARELIFE Methodology. Mannheim: MEA. • Siegrist, J., & Wahrendorf, M. “Quality of work, health and retirement.” The Lancet 374 (2009): 1872-1873. DOI: 10.1016/S0140-6736(09)61666-4. • Siegrist, J., et al. “Quality of work, well-being, and intended early retirement of older employees—baseline results from the SHARE Study." The European Journal of Public Health 17(1) (2007): 62-68. • Sirven, N., & Debrand, N. “Promoting social participation for healthy ageing. An International Comparison of Europeans Aged Fifty and Over.” IRDES Working Paper 7 (2008): 1-21.

Coverage


Wave 1 SHARE baseline study: data collected in 2004/2005; sample size of 31,115 interviews (release 2.5.0). Wave 2: data collected in 2006/07; sample size of 34,415 Wave 2 interviews, 533 end-of-life interviews, and 18,742 longitudinal interviews (release 2.5.0). Wave 3 (SHARELIFE): data collected in 2008/09; sample size of 26,836 interviews, 1,139 end-of-life interviews, and 1,158 first interviews with new or previously non-cooperating spouses (release 1.0.0). Wave 4: data collected in 2010/11; sample size of 58,489 interviews, of which 21,566 were longitudinal, 1,110 end-of-life interviews (release 1.1.1). All respondents who were interviewed in any previous wave and their partners are part of the longitudinal sample.


2004


Based on age; in Germany and the Netherlands stratification is based on region.


Random (probability) sample, vignette samples, multi-stage sampling design. National sample frames are chosen to achieve full probability sampling. SHARE data is weighted in order to compensate for unequal selection probabilities in the various sample units. The sample excluded those individuals who were incarcerated, hospitalized or out of the country during the entire survey period, unable to speak the country’s language(s) or have moved to an unknown address. In addition, all respondents who were interviewed in any previous wave and their current partners are part of the longitudinal sample.


2004 SHARE baseline study: Austria, Belgium, Denmark, Spain, France, Germany, Greece, Israel, Italy, The Netherlands, Sweden, Switzerland. Wave 2: 15 countries (+ the Czech Republic, Ireland, and Poland). Wave 3 (SHARELIFE): 14 countries. Wave 4: 16 countries (+ Estonia, Hungary, Slovenia, and Portugal), excluding Greece, which could not take part in wave 4 due to the financial crisis. The Irish SHARE study was merged with TILDA – the Irish Longitudinal Study on Ageing - and there is no stand-alone SHARE in Ireland after wave 3.


Population aged 50+; Wave 1 SHARE baseline study: all individuals born in 1954 or earlier; Wave 2: all individuals born in 1956 or earlier; Wave 4: all individuals born in 1960 or earlier


The main goal of SHARE is to provide data to better understand the ageing process and how it affects individuals in the diverse cultural settings of Europe. The SHARE dataset includes cross-national information on economic circumstances, health, wellbeing, as well as integration into family and social networks. It also includes rich information on the socio-economic background of the surveyed individuals and their family members (parents and children), such as gender, age, marital status, educational level, current work, income, and living arrangements. SHARE data from Waves 1, 2 and 4 deal with respondents’ current living conditions, whereas Wave 3 (SHARELIFE) was conducted as retrospective survey and provides information about life histories. More specifically, SHARELIFE data provides information about childhood living circumstances, partners, children, accommodation, employment and wellbeing and health conditions. Thus, it allows for the study of ageing from a life-course perspective. Wave 4 data can also be used to disentangle the influences of the economic crisis on healthy ageing and intergenerational solidarity in different European countries. More specifically, the SHARE data covers: Education and Learning SHARE allows for studying education and learning trajectories among older adults as the survey collects data about educational background (personal and children), childhood cultural capital, and cognitive decline in older age. The dataset furthermore contains wellbeing, family background, lifelong training and educational courses attended (retrospective), several social inequality and inclusion indicators, and specific activities performed, such as participation in religious or political organisations; reading books, magazines, newspapers; playing word or number games, card games or chess. Therefore, the database allows for the study of the links between lifelong learning, work quality and wellbeing, and early retirement.


• Abuladze, L., & Sakkeus, L. “27 Social networks and everyday activity limitations.” In Börsch-Supan, A., Brandt, M., Litwin, H., / Weber, G. (eds.) “Active ageing and solidarity between generations in Europe” DE GRUYTER, Berlin, Boston (2013): 311-322. • Angelini, V., Brugiavini, A., & Weber, G. “Ageing and unused capacity in Europe: Is there an early retirement trap?” Economic Policy 24(7) (2009): 463-508. DOI: 10.1111/j.1468-0327.2009.00227.x. • Angelini, V., Cavapozzi, D., Corazzini, L., & Pacagnella, O. “Age, health and life satisfaction among older Europeans.” Social Indicators Research 105(2) (2012): 293-308 DOI: 10.1007/s11205-011-9882-x. • Angelini, V., Laferrere, A., & Weber, G.“ Home-ownership in Europe: How did it happen?” Advances in Life Course Research 18 (2013): 83-90. • Avendano, M., Jürges, H., & Mackenbach, J.P. “Educational level and changes in health across Europe: Longitudinal results from SHARE.” Journal of European Social Policy 19(4) (2009): 301-316. DOI: 10.1177/1350506809341512. • Ayalon, L., Heinik, J., & Litwin, H. “Population group differences in cognitive functioning in a national sample of Israelis fifty years and older.” Research on Aging 32(3) (2010): 304-322. DOI: 10.1177/0164027509356875. • Börsch-Supan, A., Hank, K., & Jürges, H. “A new comprehensive and international view on ageing: introducing the ‘Survey of Health, Ageing and Retirement in Europe’.” European Journal of Ageing 2(4) (2005): 245-253. • Börsch-Supan, A., Brandt, M. , Litwin, H., & Weber, G. (Eds). “Active ageing and solidarity between generations in Europe: First results from SHARE after the economic crisis.” De Gruyter, Berlin (2013). • Börsch-Supan, A., Brandt, M., Hank, K., & Schröder, M. (Eds). “The individual and the welfare state. Life histories in Europe.” Springer, Heidelberg (2011). • Börsch-Supan, A., Brugiavini, A., Jürges, H., et al. “First results from the Survey of Health, Ageing and Retirement in Europe (2004-2007). Starting the longitudinal dimension.” Mannheim Research Institute for the Economics of Aging (MEA), Mannheim (2008). • Börsch-Supan, A., Brugiavini, A., Jürges, H., et al. “Health, ageing and retirement in Europe – First results from the Survey of Health, Ageing and Retirement in Europe.” Mannheim Research Institute for the Economics of Aging (MEA), Mannheim (2005). • Borsch-Supan, A., Brandt, M., Hunkler, C., et al. „Data Resource Profile: The Survey of Health, Ageing and Retirement in Europe (SHARE).” International Journal of Epidemiology 1(10) (2013). DOI: 10.1093/ije/dyt088. • Börsch-Supan, A., & Jürges, H. (Eds). “The Survey of Health, Ageing and Retirement in Europe – Methodology.” MEA, Mannheim (2005). • Brandt, M., Deindl, C., & Hank, K. “Tracing the origins of successful aging: The role of childhood conditions and societal context.” Social Science and Medicine 74(9) (2012): 1418–1425. DOI: 10.1016/j.socscimed.2012.01.004. • Brandt, M., & Deindl, C. “Intergenerational Transfers to Adult Children in Europe: Do Social Policies Matter?” Journal of Marriage and Family 75 (2013): 235-251. • Buber, I., & Engelhardt, H. “Children’s impact on the mental health of their older mothers and fathers: findings from the Survey of Health, Ageing and Retirement in Europe.” European Journal of Ageing 5(1) (2008): 31-45. • Buber, I. “Ageing in Austria: An overview of “Survey Health, Ageing and Retirement in Europe” (SHARE) with special focus on aspects of health.” Vienna Yearbook of Population Research (2007): 309-326. • D’Uva, T. B., O’Donnell, O., & van Doorslaer, E. “Differential health reporting by educational level and its impact on the measurement of health inequalities among older Europeans.” International Journal of Epidemiology 37 (2008): 1375-1383. • Deindl. C. “The influence of living conditions in early life on satisfaction in old age.” Advances in Life Course Research 18(1) (2013): 107-114. DOI: 10.1016/j.alcr.2012.10.008. • Dewey, M.E., & Prince, M.J. “Cognitive function.” In:Börsch-Supan, A., et al. ”Health, Ageing and Retirement in Europe - First Results from the Survey of Health, Ageing and Retirement in Europe” MEA, Mannheim (2005): 118-125. • Donfut-Attias, C., Ogg, J., & Wolff, F.-C. “European patterns of intergenerational financial and time transfers.” European Journal of Ageing 2 (2005):161-173. • Engelhardt, H. “Late careers in Europe: Effects of individual and institutional factors.” European Sociological Review 28(4) (2012): 550-563. DOI: 10.1093/esr/jcr024. • Erlinghagen, M., & Hank, K. “Participation of Older Europeans in Voluntary Work.” Ageing and Society 26(4) (2006): 657-584. • Gaymu, J., & Springer, S. “Living conditions and life satisfaction of older Europeans living alone: A gender and cross-country analysis.” Ageing and Society 30 (2010): 1153-1175. DOI: 10.1017/S0144686X10000231. • Gwozdz, W., & Sousa-Poza, A. “Ageing, health and life satisfaction of the oldest old: An analysis for Germany.” Social Indicators Research 97(3) (2010): 397-417. DOI: 10.1007/s11205-009-9508-8. • Hank, K., & Buber, I. “Grandparents Caring for Their Grandchildren Findings From the 2004 Survey of Health, Ageing, and Retirement in Europe.” Journal of Family Issues 30(1) (2009): 53-73. • Hochman, O., & Lewin-Epstein, N. “Determinants of early retirement preferences in Europe: The role of grandparenthood.” International Journal of Comparative Sociology 54(1) (2013): 29-47 DOI: 10.1177/0020715213480977. • Horner, E.M. “Subjective well-being and retirement: Analysis and policy recommendations.” Journal of Happiness Studies forthcoming. DOI: 10.1007/s10902-012-9399-2. • Jagger, C., et al. “The global Activity Limitation Index measured function and disability similarly across European countries.” Journal of Clinical Epidimiology 63 (2010): 892-899. • Jürges, H., & van Soest, A. “Comparing the wellbeing of older Europeans: Introduction.” Social Indicator Research 105 (2012): 187-190. • Jürges, H. “Healthy minds in healthy bodies: An international comparison of education-related inequality in physical health among older adults.” Scottish Journal of Political Economy 56(3) (2009): 296-320. DOI: 10.1111/j.1467-9485.2009.00485.x. • Kavé, G., Shrira, A., Palgi, Y., et al. “Formal education level versus self-rated literacy as predictors of cognitive aging.” Journals of Gerontology Series B: Psychological Sciences and Social Sciences 67(6) (2012): 697-704. DOI: 10.1093/geronb/gbs031. • Litwin, H., & Sapir, E.V. “Perceived income adequacy among older adults in 12 countries: Findings from the Survey of Health, Ageing, and Retirement in Europe.” The Gerontologist 49(3) (2009): 397-406. • Malter, F. and Börsch-Supan, A. (Eds). (2013). SHARE Wave 4: Innovations & Methodology. Munich: MEA, Max Planck Institute for Social Law and Social Policy. • Mazzonna, F. “The effect of education on old age health and cognitive abilities - does the instrument matter?” SHARE working paper 10-2012, Munich Center for the Economics of Aging (MEA) (2012). • Mazzonna, F., & Peracchi, F. “Ageing, cognitive abilities and retirement.” European Economic Review 56(4) (2012): 691-710. DOI: 10.1016/j.euroecorev.2012.03.004. • Mielck, A., Kiess, R., Knesebeck, O., et al. “Association between forgone care and household income among the elderly in five Western European countries – analyses based on survey data from the SHARE-study.” BMC Health Services Research 9(52) (2009). • Romero-Ortuno, R., Walsh, C. D., Lawor, B.I., & Kenny, R.A. “A Frailty Instrument for primary care: findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).” BMC Geriatrics 10(57) (2010). • Romero-Ortuno, R., et al. “A frailty instrument for primary care: findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).” BMC geriatrics 10(1) (2010): 57. • Schneeweis, N., Skirbekk, V., & Winter-Ebmer, R. “Does schooling improve cognitive functioning at older ages?” Economic Working Paper (1211), University of Linz (2012). • Schröder, M. (2011). Retrospective data collection in the Survey of Health, Ageing and Retirement in Europe. SHARELIFE Methodology. Mannheim: MEA. • Siegrist, J., & Wahrendorf, M. “Quality of work, health and retirement.” The Lancet 374 (2009): 1872-1873. DOI: 10.1016/S0140-6736(09)61666-4. • Siegrist, J., et al. “Quality of work, well-being, and intended early retirement of older employees—baseline results from the SHARE Study." The European Journal of Public Health 17(1) (2007): 62-68. • Sirven, N., & Debrand, N. “Promoting social participation for healthy ageing. An International Comparison of Europeans Aged Fifty and Over.” IRDES Working Paper 7 (2008): 1-21.

Coverage


Wave 1 SHARE baseline study: data collected in 2004/2005; sample size of 31,115 interviews (release 2.5.0). Wave 2: data collected in 2006/07; sample size of 34,415 Wave 2 interviews, 533 end-of-life interviews, and 18,742 longitudinal interviews (release 2.5.0). Wave 3 (SHARELIFE): data collected in 2008/09; sample size of 26,836 interviews, 1,139 end-of-life interviews, and 1,158 first interviews with new or previously non-cooperating spouses (release 1.0.0). Wave 4: data collected in 2010/11; sample size of 58,489 interviews, of which 21,566 were longitudinal, 1,110 end-of-life interviews (release 1.1.1). All respondents who were interviewed in any previous wave and their partners are part of the longitudinal sample.


2004


Based on age; in Germany and the Netherlands stratification is based on region.


Random (probability) sample, vignette samples, multi-stage sampling design. National sample frames are chosen to achieve full probability sampling. SHARE data is weighted in order to compensate for unequal selection probabilities in the various sample units. The sample excluded those individuals who were incarcerated, hospitalized or out of the country during the entire survey period, unable to speak the country’s language(s) or have moved to an unknown address. In addition, all respondents who were interviewed in any previous wave and their current partners are part of the longitudinal sample.


2004 SHARE baseline study: Austria, Belgium, Denmark, Spain, France, Germany, Greece, Israel, Italy, The Netherlands, Sweden, Switzerland. Wave 2: 15 countries (+ the Czech Republic, Ireland, and Poland). Wave 3 (SHARELIFE): 14 countries. Wave 4: 16 countries (+ Estonia, Hungary, Slovenia, and Portugal), excluding Greece, which could not take part in wave 4 due to the financial crisis. The Irish SHARE study was merged with TILDA – the Irish Longitudinal Study on Ageing - and there is no stand-alone SHARE in Ireland after wave 3.


Population aged 50+; Wave 1 SHARE baseline study: all individuals born in 1954 or earlier; Wave 2: all individuals born in 1956 or earlier; Wave 4: all individuals born in 1960 or earlier


The main goal of SHARE is to provide data to better understand the ageing process and how it affects individuals in the diverse cultural settings of Europe. The SHARE dataset includes cross-national information on economic circumstances, health, wellbeing, as well as integration into family and social networks. It also includes rich information on the socio-economic background of the surveyed individuals and their family members (parents and children), such as gender, age, marital status, educational level, current work, income, and living arrangements. SHARE data from Waves 1, 2 and 4 deal with respondents’ current living conditions, whereas Wave 3 (SHARELIFE) was conducted as retrospective survey and provides information about life histories. More specifically, SHARELIFE data provides information about childhood living circumstances, partners, children, accommodation, employment and wellbeing and health conditions. Thus, it allows for the study of ageing from a life-course perspective. Wave 4 data can also be used to disentangle the influences of the economic crisis on healthy ageing and intergenerational solidarity in different European countries. More specifically, the SHARE data covers: Housing, Urban Development and Mobility: Within this main field, SHARE provides data on living arrangements and type of housing. SHARE allows for studying (first-time) ownership and means for purchasing the property, moving intentions and the reasons behind it. Moreover, the dataset provides characteristics of the dwellings, such as adapted environments and special features that assist individuals with physical impairments or health problems (e.g. widened doorways, damps, alerting devices, kitchen or bathroom modifications).


• Abuladze, L., & Sakkeus, L. “27 Social networks and everyday activity limitations.” In Börsch-Supan, A., Brandt, M., Litwin, H., / Weber, G. (eds.) “Active ageing and solidarity between generations in Europe” DE GRUYTER, Berlin, Boston (2013): 311-322. • Angelini, V., Brugiavini, A., & Weber, G. “Ageing and unused capacity in Europe: Is there an early retirement trap?” Economic Policy 24(7) (2009): 463-508. DOI: 10.1111/j.1468-0327.2009.00227.x. • Angelini, V., Cavapozzi, D., Corazzini, L., & Pacagnella, O. “Age, health and life satisfaction among older Europeans.” Social Indicators Research 105(2) (2012): 293-308 DOI: 10.1007/s11205-011-9882-x. • Angelini, V., Laferrere, A., & Weber, G.“ Home-ownership in Europe: How did it happen?” Advances in Life Course Research 18 (2013): 83-90. • Avendano, M., Jürges, H., & Mackenbach, J.P. “Educational level and changes in health across Europe: Longitudinal results from SHARE.” Journal of European Social Policy 19(4) (2009): 301-316. DOI: 10.1177/1350506809341512. • Ayalon, L., Heinik, J., & Litwin, H. “Population group differences in cognitive functioning in a national sample of Israelis fifty years and older.” Research on Aging 32(3) (2010): 304-322. DOI: 10.1177/0164027509356875. • Börsch-Supan, A., Hank, K., & Jürges, H. “A new comprehensive and international view on ageing: introducing the ‘Survey of Health, Ageing and Retirement in Europe’.” European Journal of Ageing 2(4) (2005): 245-253. • Börsch-Supan, A., Brandt, M. , Litwin, H., & Weber, G. (Eds). “Active ageing and solidarity between generations in Europe: First results from SHARE after the economic crisis.” De Gruyter, Berlin (2013). • Börsch-Supan, A., Brandt, M., Hank, K., & Schröder, M. (Eds). “The individual and the welfare state. Life histories in Europe.” Springer, Heidelberg (2011). • Börsch-Supan, A., Brugiavini, A., Jürges, H., et al. “First results from the Survey of Health, Ageing and Retirement in Europe (2004-2007). Starting the longitudinal dimension.” Mannheim Research Institute for the Economics of Aging (MEA), Mannheim (2008). • Börsch-Supan, A., Brugiavini, A., Jürges, H., et al. “Health, ageing and retirement in Europe – First results from the Survey of Health, Ageing and Retirement in Europe.” Mannheim Research Institute for the Economics of Aging (MEA), Mannheim (2005). • Borsch-Supan, A., Brandt, M., Hunkler, C., et al. „Data Resource Profile: The Survey of Health, Ageing and Retirement in Europe (SHARE).” International Journal of Epidemiology 1(10) (2013). DOI: 10.1093/ije/dyt088. • Börsch-Supan, A., & Jürges, H. (Eds). “The Survey of Health, Ageing and Retirement in Europe – Methodology.” MEA, Mannheim (2005). • Brandt, M., Deindl, C., & Hank, K. “Tracing the origins of successful aging: The role of childhood conditions and societal context.” Social Science and Medicine 74(9) (2012): 1418–1425. DOI: 10.1016/j.socscimed.2012.01.004. • Brandt, M., & Deindl, C. “Intergenerational Transfers to Adult Children in Europe: Do Social Policies Matter?” Journal of Marriage and Family 75 (2013): 235-251. • Buber, I., & Engelhardt, H. “Children’s impact on the mental health of their older mothers and fathers: findings from the Survey of Health, Ageing and Retirement in Europe.” European Journal of Ageing 5(1) (2008): 31-45. • Buber, I. “Ageing in Austria: An overview of “Survey Health, Ageing and Retirement in Europe” (SHARE) with special focus on aspects of health.” Vienna Yearbook of Population Research (2007): 309-326. • D’Uva, T. B., O’Donnell, O., & van Doorslaer, E. “Differential health reporting by educational level and its impact on the measurement of health inequalities among older Europeans.” International Journal of Epidemiology 37 (2008): 1375-1383. • Deindl. C. “The influence of living conditions in early life on satisfaction in old age.” Advances in Life Course Research 18(1) (2013): 107-114. DOI: 10.1016/j.alcr.2012.10.008. • Dewey, M.E., & Prince, M.J. “Cognitive function.” In:Börsch-Supan, A., et al. ”Health, Ageing and Retirement in Europe - First Results from the Survey of Health, Ageing and Retirement in Europe” MEA, Mannheim (2005): 118-125. • Donfut-Attias, C., Ogg, J., & Wolff, F.-C. “European patterns of intergenerational financial and time transfers.” European Journal of Ageing 2 (2005):161-173. • Engelhardt, H. “Late careers in Europe: Effects of individual and institutional factors.” European Sociological Review 28(4) (2012): 550-563. DOI: 10.1093/esr/jcr024. • Erlinghagen, M., & Hank, K. “Participation of Older Europeans in Voluntary Work.” Ageing and Society 26(4) (2006): 657-584. • Gaymu, J., & Springer, S. “Living conditions and life satisfaction of older Europeans living alone: A gender and cross-country analysis.” Ageing and Society 30 (2010): 1153-1175. DOI: 10.1017/S0144686X10000231. • Gwozdz, W., & Sousa-Poza, A. “Ageing, health and life satisfaction of the oldest old: An analysis for Germany.” Social Indicators Research 97(3) (2010): 397-417. DOI: 10.1007/s11205-009-9508-8. • Hank, K., & Buber, I. “Grandparents Caring for Their Grandchildren Findings From the 2004 Survey of Health, Ageing, and Retirement in Europe.” Journal of Family Issues 30(1) (2009): 53-73. • Hochman, O., & Lewin-Epstein, N. “Determinants of early retirement preferences in Europe: The role of grandparenthood.” International Journal of Comparative Sociology 54(1) (2013): 29-47 DOI: 10.1177/0020715213480977. • Horner, E.M. “Subjective well-being and retirement: Analysis and policy recommendations.” Journal of Happiness Studies forthcoming. DOI: 10.1007/s10902-012-9399-2. • Jagger, C., et al. “The global Activity Limitation Index measured function and disability similarly across European countries.” Journal of Clinical Epidimiology 63 (2010): 892-899. • Jürges, H., & van Soest, A. “Comparing the wellbeing of older Europeans: Introduction.” Social Indicator Research 105 (2012): 187-190. • Jürges, H. “Healthy minds in healthy bodies: An international comparison of education-related inequality in physical health among older adults.” Scottish Journal of Political Economy 56(3) (2009): 296-320. DOI: 10.1111/j.1467-9485.2009.00485.x. • Kavé, G., Shrira, A., Palgi, Y., et al. “Formal education level versus self-rated literacy as predictors of cognitive aging.” Journals of Gerontology Series B: Psychological Sciences and Social Sciences 67(6) (2012): 697-704. DOI: 10.1093/geronb/gbs031. • Litwin, H., & Sapir, E.V. “Perceived income adequacy among older adults in 12 countries: Findings from the Survey of Health, Ageing, and Retirement in Europe.” The Gerontologist 49(3) (2009): 397-406. • Malter, F. and Börsch-Supan, A. (Eds). (2013). SHARE Wave 4: Innovations & Methodology. Munich: MEA, Max Planck Institute for Social Law and Social Policy. • Mazzonna, F. “The effect of education on old age health and cognitive abilities - does the instrument matter?” SHARE working paper 10-2012, Munich Center for the Economics of Aging (MEA) (2012). • Mazzonna, F., & Peracchi, F. “Ageing, cognitive abilities and retirement.” European Economic Review 56(4) (2012): 691-710. DOI: 10.1016/j.euroecorev.2012.03.004. • Mielck, A., Kiess, R., Knesebeck, O., et al. “Association between forgone care and household income among the elderly in five Western European countries – analyses based on survey data from the SHARE-study.” BMC Health Services Research 9(52) (2009). • Romero-Ortuno, R., Walsh, C. D., Lawor, B.I., & Kenny, R.A. “A Frailty Instrument for primary care: findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).” BMC Geriatrics 10(57) (2010). • Romero-Ortuno, R., et al. “A frailty instrument for primary care: findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).” BMC geriatrics 10(1) (2010): 57. • Schneeweis, N., Skirbekk, V., & Winter-Ebmer, R. “Does schooling improve cognitive functioning at older ages?” Economic Working Paper (1211), University of Linz (2012). • Schröder, M. (2011). Retrospective data collection in the Survey of Health, Ageing and Retirement in Europe. SHARELIFE Methodology. Mannheim: MEA. • Siegrist, J., & Wahrendorf, M. “Quality of work, health and retirement.” The Lancet 374 (2009): 1872-1873. DOI: 10.1016/S0140-6736(09)61666-4. • Siegrist, J., et al. “Quality of work, well-being, and intended early retirement of older employees—baseline results from the SHARE Study." The European Journal of Public Health 17(1) (2007): 62-68. • Sirven, N., & Debrand, N. “Promoting social participation for healthy ageing. An International Comparison of Europeans Aged Fifty and Over.” IRDES Working Paper 7 (2008): 1-21.

Coverage


Wave 1 SHARE baseline study: data collected in 2004/2005; sample size of 31,115 interviews (release 2.5.0). Wave 2: data collected in 2006/07; sample size of 34,415 Wave 2 interviews, 533 end-of-life interviews, and 18,742 longitudinal interviews (release 2.5.0). Wave 3 (SHARELIFE): data collected in 2008/09; sample size of 26,836 interviews, 1,139 end-of-life interviews, and 1,158 first interviews with new or previously non-cooperating spouses (release 1.0.0). Wave 4: data collected in 2010/11; sample size of 58,489 interviews, of which 21,566 were longitudinal, 1,110 end-of-life interviews (release 1.1.1). All respondents who were interviewed in any previous wave and their partners are part of the longitudinal sample.


2004


Based on age; in Germany and the Netherlands stratification is based on region.


Random (probability) sample, vignette samples, multi-stage sampling design. National sample frames are chosen to achieve full probability sampling. SHARE data is weighted in order to compensate for unequal selection probabilities in the various sample units. The sample excluded those individuals who were incarcerated, hospitalized or out of the country during the entire survey period, unable to speak the country’s language(s) or have moved to an unknown address. In addition, all respondents who were interviewed in any previous wave and their current partners are part of the longitudinal sample.


2004 SHARE baseline study: Austria, Belgium, Denmark, Spain, France, Germany, Greece, Israel, Italy, The Netherlands, Sweden, Switzerland. Wave 2: 15 countries (+ the Czech Republic, Ireland, and Poland). Wave 3 (SHARELIFE): 14 countries. Wave 4: 16 countries (+ Estonia, Hungary, Slovenia, and Portugal), excluding Greece, which could not take part in wave 4 due to the financial crisis. The Irish SHARE study was merged with TILDA – the Irish Longitudinal Study on Ageing - and there is no stand-alone SHARE in Ireland after wave 3.


Population aged 50+; Wave 1 SHARE baseline study: all individuals born in 1954 or earlier; Wave 2: all individuals born in 1956 or earlier; Wave 4: all individuals born in 1960 or earlier


The main goal of SHARE is to provide data to better understand the ageing process and how it affects individuals in the diverse cultural settings of Europe. The SHARE dataset includes cross-national information on economic circumstances, health, wellbeing, as well as integration into family and social networks. It also includes rich information on the socio-economic background of the surveyed individuals and their family members (parents and children), such as gender, age, marital status, educational level, current work, income, and living arrangements. SHARE data from Waves 1, 2 and 4 deal with respondents’ current living conditions, whereas Wave 3 (SHARELIFE) was conducted as retrospective survey and provides information about life histories. More specifically, SHARELIFE data provides information about childhood living circumstances, partners, children, accommodation, employment and wellbeing and health conditions. Thus, it allows for the study of ageing from a life-course perspective. Wave 4 data can also be used to disentangle the influences of the economic crisis on healthy ageing and intergenerational solidarity in different European countries. More specifically, the SHARE data covers: Social, Civic and Cultural Engagement: Within this cross-cutting topic, SHARE provides data on social networks and their structure, as well as on social activities. It includes not only household and family members, but also other relatives, friends, and neighbours, and therefore allows for studying the overall social environment of older Europeans. SHARE also allows for studying the frequency of interaction and the individual satisfaction with social contacts. Wave 4 implemented a new module on the respondents’ social connectedness. Moreover, the survey covers the participation in voluntary work. The specific question asks whether the respondent has been actively engaged in voluntary or charity work in the month before the interview.


• Abuladze, L., & Sakkeus, L. “27 Social networks and everyday activity limitations.” In Börsch-Supan, A., Brandt, M., Litwin, H., / Weber, G. (eds.) “Active ageing and solidarity between generations in Europe” DE GRUYTER, Berlin, Boston (2013): 311-322. • Angelini, V., Brugiavini, A., & Weber, G. “Ageing and unused capacity in Europe: Is there an early retirement trap?” Economic Policy 24(7) (2009): 463-508. DOI: 10.1111/j.1468-0327.2009.00227.x. • Angelini, V., Cavapozzi, D., Corazzini, L., & Pacagnella, O. “Age, health and life satisfaction among older Europeans.” Social Indicators Research 105(2) (2012): 293-308 DOI: 10.1007/s11205-011-9882-x. • Angelini, V., Laferrere, A., & Weber, G.“ Home-ownership in Europe: How did it happen?” Advances in Life Course Research 18 (2013): 83-90. • Avendano, M., Jürges, H., & Mackenbach, J.P. “Educational level and changes in health across Europe: Longitudinal results from SHARE.” Journal of European Social Policy 19(4) (2009): 301-316. DOI: 10.1177/1350506809341512. • Ayalon, L., Heinik, J., & Litwin, H. “Population group differences in cognitive functioning in a national sample of Israelis fifty years and older.” Research on Aging 32(3) (2010): 304-322. DOI: 10.1177/0164027509356875. • Börsch-Supan, A., Hank, K., & Jürges, H. “A new comprehensive and international view on ageing: introducing the ‘Survey of Health, Ageing and Retirement in Europe’.” European Journal of Ageing 2(4) (2005): 245-253. • Börsch-Supan, A., Brandt, M. , Litwin, H., & Weber, G. (Eds). “Active ageing and solidarity between generations in Europe: First results from SHARE after the economic crisis.” De Gruyter, Berlin (2013). • Börsch-Supan, A., Brandt, M., Hank, K., & Schröder, M. (Eds). “The individual and the welfare state. Life histories in Europe.” Springer, Heidelberg (2011). • Börsch-Supan, A., Brugiavini, A., Jürges, H., et al. “First results from the Survey of Health, Ageing and Retirement in Europe (2004-2007). Starting the longitudinal dimension.” Mannheim Research Institute for the Economics of Aging (MEA), Mannheim (2008). • Börsch-Supan, A., Brugiavini, A., Jürges, H., et al. “Health, ageing and retirement in Europe – First results from the Survey of Health, Ageing and Retirement in Europe.” Mannheim Research Institute for the Economics of Aging (MEA), Mannheim (2005). • Borsch-Supan, A., Brandt, M., Hunkler, C., et al. „Data Resource Profile: The Survey of Health, Ageing and Retirement in Europe (SHARE).” International Journal of Epidemiology 1(10) (2013). DOI: 10.1093/ije/dyt088. • Börsch-Supan, A., & Jürges, H. (Eds). “The Survey of Health, Ageing and Retirement in Europe – Methodology.” MEA, Mannheim (2005). • Brandt, M., Deindl, C., & Hank, K. “Tracing the origins of successful aging: The role of childhood conditions and societal context.” Social Science and Medicine 74(9) (2012): 1418–1425. DOI: 10.1016/j.socscimed.2012.01.004. • Brandt, M., & Deindl, C. “Intergenerational Transfers to Adult Children in Europe: Do Social Policies Matter?” Journal of Marriage and Family 75 (2013): 235-251. • Buber, I., & Engelhardt, H. “Children’s impact on the mental health of their older mothers and fathers: findings from the Survey of Health, Ageing and Retirement in Europe.” European Journal of Ageing 5(1) (2008): 31-45. • Buber, I. “Ageing in Austria: An overview of “Survey Health, Ageing and Retirement in Europe” (SHARE) with special focus on aspects of health.” Vienna Yearbook of Population Research (2007): 309-326. • D’Uva, T. B., O’Donnell, O., & van Doorslaer, E. “Differential health reporting by educational level and its impact on the measurement of health inequalities among older Europeans.” International Journal of Epidemiology 37 (2008): 1375-1383. • Deindl. C. “The influence of living conditions in early life on satisfaction in old age.” Advances in Life Course Research 18(1) (2013): 107-114. DOI: 10.1016/j.alcr.2012.10.008. • Dewey, M.E., & Prince, M.J. “Cognitive function.” In:Börsch-Supan, A., et al. ”Health, Ageing and Retirement in Europe - First Results from the Survey of Health, Ageing and Retirement in Europe” MEA, Mannheim (2005): 118-125. • Donfut-Attias, C., Ogg, J., & Wolff, F.-C. “European patterns of intergenerational financial and time transfers.” European Journal of Ageing 2 (2005):161-173. • Engelhardt, H. “Late careers in Europe: Effects of individual and institutional factors.” European Sociological Review 28(4) (2012): 550-563. DOI: 10.1093/esr/jcr024. • Erlinghagen, M., & Hank, K. “Participation of Older Europeans in Voluntary Work.” Ageing and Society 26(4) (2006): 657-584. • Gaymu, J., & Springer, S. “Living conditions and life satisfaction of older Europeans living alone: A gender and cross-country analysis.” Ageing and Society 30 (2010): 1153-1175. DOI: 10.1017/S0144686X10000231. • Gwozdz, W., & Sousa-Poza, A. “Ageing, health and life satisfaction of the oldest old: An analysis for Germany.” Social Indicators Research 97(3) (2010): 397-417. DOI: 10.1007/s11205-009-9508-8. • Hank, K., & Buber, I. “Grandparents Caring for Their Grandchildren Findings From the 2004 Survey of Health, Ageing, and Retirement in Europe.” Journal of Family Issues 30(1) (2009): 53-73. • Hochman, O., & Lewin-Epstein, N. “Determinants of early retirement preferences in Europe: The role of grandparenthood.” International Journal of Comparative Sociology 54(1) (2013): 29-47 DOI: 10.1177/0020715213480977. • Horner, E.M. “Subjective well-being and retirement: Analysis and policy recommendations.” Journal of Happiness Studies forthcoming. DOI: 10.1007/s10902-012-9399-2. • Jagger, C., et al. “The global Activity Limitation Index measured function and disability similarly across European countries.” Journal of Clinical Epidimiology 63 (2010): 892-899. • Jürges, H., & van Soest, A. “Comparing the wellbeing of older Europeans: Introduction.” Social Indicator Research 105 (2012): 187-190. • Jürges, H. “Healthy minds in healthy bodies: An international comparison of education-related inequality in physical health among older adults.” Scottish Journal of Political Economy 56(3) (2009): 296-320. DOI: 10.1111/j.1467-9485.2009.00485.x. • Kavé, G., Shrira, A., Palgi, Y., et al. “Formal education level versus self-rated literacy as predictors of cognitive aging.” Journals of Gerontology Series B: Psychological Sciences and Social Sciences 67(6) (2012): 697-704. DOI: 10.1093/geronb/gbs031. • Litwin, H., & Sapir, E.V. “Perceived income adequacy among older adults in 12 countries: Findings from the Survey of Health, Ageing, and Retirement in Europe.” The Gerontologist 49(3) (2009): 397-406. • Malter, F. and Börsch-Supan, A. (Eds). (2013). SHARE Wave 4: Innovations & Methodology. Munich: MEA, Max Planck Institute for Social Law and Social Policy. • Mazzonna, F. “The effect of education on old age health and cognitive abilities - does the instrument matter?” SHARE working paper 10-2012, Munich Center for the Economics of Aging (MEA) (2012). • Mazzonna, F., & Peracchi, F. “Ageing, cognitive abilities and retirement.” European Economic Review 56(4) (2012): 691-710. DOI: 10.1016/j.euroecorev.2012.03.004. • Mielck, A., Kiess, R., Knesebeck, O., et al. “Association between forgone care and household income among the elderly in five Western European countries – analyses based on survey data from the SHARE-study.” BMC Health Services Research 9(52) (2009). • Romero-Ortuno, R., Walsh, C. D., Lawor, B.I., & Kenny, R.A. “A Frailty Instrument for primary care: findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).” BMC Geriatrics 10(57) (2010). • Romero-Ortuno, R., et al. “A frailty instrument for primary care: findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).” BMC geriatrics 10(1) (2010): 57. • Schneeweis, N., Skirbekk, V., & Winter-Ebmer, R. “Does schooling improve cognitive functioning at older ages?” Economic Working Paper (1211), University of Linz (2012). • Schröder, M. (2011). Retrospective data collection in the Survey of Health, Ageing and Retirement in Europe. SHARELIFE Methodology. Mannheim: MEA. • Siegrist, J., & Wahrendorf, M. “Quality of work, health and retirement.” The Lancet 374 (2009): 1872-1873. DOI: 10.1016/S0140-6736(09)61666-4. • Siegrist, J., et al. “Quality of work, well-being, and intended early retirement of older employees—baseline results from the SHARE Study." The European Journal of Public Health 17(1) (2007): 62-68. • Sirven, N., & Debrand, N. “Promoting social participation for healthy ageing. An International Comparison of Europeans Aged Fifty and Over.” IRDES Working Paper 7 (2008): 1-21.

Coverage


Wave 1 SHARE baseline study: data collected in 2004/2005; sample size of 31,115 interviews (release 2.5.0). Wave 2: data collected in 2006/07; sample size of 34,415 Wave 2 interviews, 533 end-of-life interviews, and 18,742 longitudinal interviews (release 2.5.0). Wave 3 (SHARELIFE): data collected in 2008/09; sample size of 26,836 interviews, 1,139 end-of-life interviews, and 1,158 first interviews with new or previously non-cooperating spouses (release 1.0.0). Wave 4: data collected in 2010/11; sample size of 58,489 interviews, of which 21,566 were longitudinal, 1,110 end-of-life interviews (release 1.1.1). All respondents who were interviewed in any previous wave and their partners are part of the longitudinal sample.


2004


Based on age; in Germany and the Netherlands stratification is based on region.


Random (probability) sample, vignette samples, multi-stage sampling design. National sample frames are chosen to achieve full probability sampling. SHARE data is weighted in order to compensate for unequal selection probabilities in the various sample units. The sample excluded those individuals who were incarcerated, hospitalized or out of the country during the entire survey period, unable to speak the country’s language(s) or have moved to an unknown address. In addition, all respondents who were interviewed in any previous wave and their current partners are part of the longitudinal sample.


2004 SHARE baseline study: Austria, Belgium, Denmark, Spain, France, Germany, Greece, Israel, Italy, The Netherlands, Sweden, Switzerland. Wave 2: 15 countries (+ the Czech Republic, Ireland, and Poland). Wave 3 (SHARELIFE): 14 countries. Wave 4: 16 countries (+ Estonia, Hungary, Slovenia, and Portugal), excluding Greece, which could not take part in wave 4 due to the financial crisis. The Irish SHARE study was merged with TILDA – the Irish Longitudinal Study on Ageing - and there is no stand-alone SHARE in Ireland after wave 3.


Population aged 50+; Wave 1 SHARE baseline study: all individuals born in 1954 or earlier; Wave 2: all individuals born in 1956 or earlier; Wave 4: all individuals born in 1960 or earlier


The main goal of SHARE is to provide data to better understand the ageing process and how it affects individuals in the diverse cultural settings of Europe. The SHARE dataset includes cross-national information on economic circumstances, health, wellbeing, as well as integration into family and social networks. It also includes rich information on the socio-economic background of the surveyed individuals and their family members (parents and children), such as gender, age, marital status, educational level, current work, income, and living arrangements. SHARE data from Waves 1, 2 and 4 deal with respondents’ current living conditions, whereas Wave 3 (SHARELIFE) was conducted as retrospective survey and provides information about life histories. More specifically, SHARELIFE data provides information about childhood living circumstances, partners, children, accommodation, employment and wellbeing and health conditions. Thus, it allows for the study of ageing from a life-course perspective. Wave 4 data can also be used to disentangle the influences of the economic crisis on healthy ageing and intergenerational solidarity in different European countries. More specifically, the SHARE data covers: Uses of technology SHARE provides insights on housing adaptations and special features that assist individuals with physical impairments or health problems such as widened doorways, ramps, chair lifts, kitchen or bathroom modifications, and alerting devices. The topic of uses of technology will be extended in Wave 5 and thus SHARE will allow for studying a rather neglected topic in ageing research.


• Abuladze, L., & Sakkeus, L. “27 Social networks and everyday activity limitations.” In Börsch-Supan, A., Brandt, M., Litwin, H., / Weber, G. (eds.) “Active ageing and solidarity between generations in Europe” DE GRUYTER, Berlin, Boston (2013): 311-322. • Angelini, V., Brugiavini, A., & Weber, G. “Ageing and unused capacity in Europe: Is there an early retirement trap?” Economic Policy 24(7) (2009): 463-508. DOI: 10.1111/j.1468-0327.2009.00227.x. • Angelini, V., Cavapozzi, D., Corazzini, L., & Pacagnella, O. “Age, health and life satisfaction among older Europeans.” Social Indicators Research 105(2) (2012): 293-308 DOI: 10.1007/s11205-011-9882-x. • Angelini, V., Laferrere, A., & Weber, G.“ Home-ownership in Europe: How did it happen?” Advances in Life Course Research 18 (2013): 83-90. • Avendano, M., Jürges, H., & Mackenbach, J.P. “Educational level and changes in health across Europe: Longitudinal results from SHARE.” Journal of European Social Policy 19(4) (2009): 301-316. DOI: 10.1177/1350506809341512. • Ayalon, L., Heinik, J., & Litwin, H. “Population group differences in cognitive functioning in a national sample of Israelis fifty years and older.” Research on Aging 32(3) (2010): 304-322. DOI: 10.1177/0164027509356875. • Börsch-Supan, A., Hank, K., & Jürges, H. “A new comprehensive and international view on ageing: introducing the ‘Survey of Health, Ageing and Retirement in Europe’.” European Journal of Ageing 2(4) (2005): 245-253. • Börsch-Supan, A., Brandt, M. , Litwin, H., & Weber, G. (Eds). “Active ageing and solidarity between generations in Europe: First results from SHARE after the economic crisis.” De Gruyter, Berlin (2013). • Börsch-Supan, A., Brandt, M., Hank, K., & Schröder, M. (Eds). “The individual and the welfare state. Life histories in Europe.” Springer, Heidelberg (2011). • Börsch-Supan, A., Brugiavini, A., Jürges, H., et al. “First results from the Survey of Health, Ageing and Retirement in Europe (2004-2007). Starting the longitudinal dimension.” Mannheim Research Institute for the Economics of Aging (MEA), Mannheim (2008). • Börsch-Supan, A., Brugiavini, A., Jürges, H., et al. “Health, ageing and retirement in Europe – First results from the Survey of Health, Ageing and Retirement in Europe.” Mannheim Research Institute for the Economics of Aging (MEA), Mannheim (2005). • Borsch-Supan, A., Brandt, M., Hunkler, C., et al. „Data Resource Profile: The Survey of Health, Ageing and Retirement in Europe (SHARE).” International Journal of Epidemiology 1(10) (2013). DOI: 10.1093/ije/dyt088. • Börsch-Supan, A., & Jürges, H. (Eds). “The Survey of Health, Ageing and Retirement in Europe – Methodology.” MEA, Mannheim (2005). • Brandt, M., Deindl, C., & Hank, K. “Tracing the origins of successful aging: The role of childhood conditions and societal context.” Social Science and Medicine 74(9) (2012): 1418–1425. DOI: 10.1016/j.socscimed.2012.01.004. • Brandt, M., & Deindl, C. “Intergenerational Transfers to Adult Children in Europe: Do Social Policies Matter?” Journal of Marriage and Family 75 (2013): 235-251. • Buber, I., & Engelhardt, H. “Children’s impact on the mental health of their older mothers and fathers: findings from the Survey of Health, Ageing and Retirement in Europe.” European Journal of Ageing 5(1) (2008): 31-45. • Buber, I. “Ageing in Austria: An overview of “Survey Health, Ageing and Retirement in Europe” (SHARE) with special focus on aspects of health.” Vienna Yearbook of Population Research (2007): 309-326. • D’Uva, T. B., O’Donnell, O., & van Doorslaer, E. “Differential health reporting by educational level and its impact on the measurement of health inequalities among older Europeans.” International Journal of Epidemiology 37 (2008): 1375-1383. • Deindl. C. “The influence of living conditions in early life on satisfaction in old age.” Advances in Life Course Research 18(1) (2013): 107-114. DOI: 10.1016/j.alcr.2012.10.008. • Dewey, M.E., & Prince, M.J. “Cognitive function.” In:Börsch-Supan, A., et al. ”Health, Ageing and Retirement in Europe - First Results from the Survey of Health, Ageing and Retirement in Europe” MEA, Mannheim (2005): 118-125. • Donfut-Attias, C., Ogg, J., & Wolff, F.-C. “European patterns of intergenerational financial and time transfers.” European Journal of Ageing 2 (2005):161-173. • Engelhardt, H. “Late careers in Europe: Effects of individual and institutional factors.” European Sociological Review 28(4) (2012): 550-563. DOI: 10.1093/esr/jcr024. • Erlinghagen, M., & Hank, K. “Participation of Older Europeans in Voluntary Work.” Ageing and Society 26(4) (2006): 657-584. • Gaymu, J., & Springer, S. “Living conditions and life satisfaction of older Europeans living alone: A gender and cross-country analysis.” Ageing and Society 30 (2010): 1153-1175. DOI: 10.1017/S0144686X10000231. • Gwozdz, W., & Sousa-Poza, A. “Ageing, health and life satisfaction of the oldest old: An analysis for Germany.” Social Indicators Research 97(3) (2010): 397-417. DOI: 10.1007/s11205-009-9508-8. • Hank, K., & Buber, I. “Grandparents Caring for Their Grandchildren Findings From the 2004 Survey of Health, Ageing, and Retirement in Europe.” Journal of Family Issues 30(1) (2009): 53-73. • Hochman, O., & Lewin-Epstein, N. “Determinants of early retirement preferences in Europe: The role of grandparenthood.” International Journal of Comparative Sociology 54(1) (2013): 29-47 DOI: 10.1177/0020715213480977. • Horner, E.M. “Subjective well-being and retirement: Analysis and policy recommendations.” Journal of Happiness Studies forthcoming. DOI: 10.1007/s10902-012-9399-2. • Jagger, C., et al. “The global Activity Limitation Index measured function and disability similarly across European countries.” Journal of Clinical Epidimiology 63 (2010): 892-899. • Jürges, H., & van Soest, A. “Comparing the wellbeing of older Europeans: Introduction.” Social Indicator Research 105 (2012): 187-190. • Jürges, H. “Healthy minds in healthy bodies: An international comparison of education-related inequality in physical health among older adults.” Scottish Journal of Political Economy 56(3) (2009): 296-320. DOI: 10.1111/j.1467-9485.2009.00485.x. • Kavé, G., Shrira, A., Palgi, Y., et al. “Formal education level versus self-rated literacy as predictors of cognitive aging.” Journals of Gerontology Series B: Psychological Sciences and Social Sciences 67(6) (2012): 697-704. DOI: 10.1093/geronb/gbs031. • Litwin, H., & Sapir, E.V. “Perceived income adequacy among older adults in 12 countries: Findings from the Survey of Health, Ageing, and Retirement in Europe.” The Gerontologist 49(3) (2009): 397-406. • Malter, F. and Börsch-Supan, A. (Eds). (2013). SHARE Wave 4: Innovations & Methodology. Munich: MEA, Max Planck Institute for Social Law and Social Policy. • Mazzonna, F. “The effect of education on old age health and cognitive abilities - does the instrument matter?” SHARE working paper 10-2012, Munich Center for the Economics of Aging (MEA) (2012). • Mazzonna, F., & Peracchi, F. “Ageing, cognitive abilities and retirement.” European Economic Review 56(4) (2012): 691-710. DOI: 10.1016/j.euroecorev.2012.03.004. • Mielck, A., Kiess, R., Knesebeck, O., et al. “Association between forgone care and household income among the elderly in five Western European countries – analyses based on survey data from the SHARE-study.” BMC Health Services Research 9(52) (2009). • Romero-Ortuno, R., Walsh, C. D., Lawor, B.I., & Kenny, R.A. “A Frailty Instrument for primary care: findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).” BMC Geriatrics 10(57) (2010). • Romero-Ortuno, R., et al. “A frailty instrument for primary care: findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).” BMC geriatrics 10(1) (2010): 57. • Schneeweis, N., Skirbekk, V., & Winter-Ebmer, R. “Does schooling improve cognitive functioning at older ages?” Economic Working Paper (1211), University of Linz (2012). • Schröder, M. (2011). Retrospective data collection in the Survey of Health, Ageing and Retirement in Europe. SHARELIFE Methodology. Mannheim: MEA. • Siegrist, J., & Wahrendorf, M. “Quality of work, health and retirement.” The Lancet 374 (2009): 1872-1873. DOI: 10.1016/S0140-6736(09)61666-4. • Siegrist, J., et al. “Quality of work, well-being, and intended early retirement of older employees—baseline results from the SHARE Study." The European Journal of Public Health 17(1) (2007): 62-68. • Sirven, N., & Debrand, N. “Promoting social participation for healthy ageing. An International Comparison of Europeans Aged Fifty and Over.” IRDES Working Paper 7 (2008): 1-21.

Coverage


Wave 1 SHARE baseline study: data collected in 2004/2005; sample size of 31,115 interviews (release 2.5.0). Wave 2: data collected in 2006/07; sample size of 34,415 Wave 2 interviews, 533 end-of-life interviews, and 18,742 longitudinal interviews (release 2.5.0). Wave 3 (SHARELIFE): data collected in 2008/09; sample size of 26,836 interviews, 1,139 end-of-life interviews, and 1,158 first interviews with new or previously non-cooperating spouses (release 1.0.0). Wave 4: data collected in 2010/11; sample size of 58,489 interviews, of which 21,566 were longitudinal, 1,110 end-of-life interviews (release 1.1.1). All respondents who were interviewed in any previous wave and their partners are part of the longitudinal sample.


2004


Based on age; in Germany and the Netherlands stratification is based on region.


Random (probability) sample, vignette samples, multi-stage sampling design. National sample frames are chosen to achieve full probability sampling. SHARE data is weighted in order to compensate for unequal selection probabilities in the various sample units. The sample excluded those individuals who were incarcerated, hospitalized or out of the country during the entire survey period, unable to speak the country’s language(s) or have moved to an unknown address. In addition, all respondents who were interviewed in any previous wave and their current partners are part of the longitudinal sample.


2004 SHARE baseline study: Austria, Belgium, Denmark, Spain, France, Germany, Greece, Israel, Italy, The Netherlands, Sweden, Switzerland. Wave 2: 15 countries (+ the Czech Republic, Ireland, and Poland). Wave 3 (SHARELIFE): 14 countries. Wave 4: 16 countries (+ Estonia, Hungary, Slovenia, and Portugal), excluding Greece, which could not take part in wave 4 due to the financial crisis. The Irish SHARE study was merged with TILDA – the Irish Longitudinal Study on Ageing - and there is no stand-alone SHARE in Ireland after wave 3.


Population aged 50+; Wave 1 SHARE baseline study: all individuals born in 1954 or earlier; Wave 2: all individuals born in 1956 or earlier; Wave 4: all individuals born in 1960 or earlier


The main goal of SHARE is to provide data to better understand the ageing process and how it affects individuals in the diverse cultural settings of Europe. The SHARE dataset includes cross-national information on economic circumstances, health, wellbeing, as well as integration into family and social networks. It also includes rich information on the socio-economic background of the surveyed individuals and their family members (parents and children), such as gender, age, marital status, educational level, current work, income, and living arrangements. SHARE data from Waves 1, 2 and 4 deal with respondents’ current living conditions, whereas Wave 3 (SHARELIFE) was conducted as retrospective survey and provides information about life histories. More specifically, SHARELIFE data provides information about childhood living circumstances, partners, children, accommodation, employment and wellbeing and health conditions. Thus, it allows for the study of ageing from a life-course perspective. Wave 4 data can also be used to disentangle the influences of the economic crisis on healthy ageing and intergenerational solidarity in different European countries. More specifically, the SHARE data covers: Wellbeing: Within this cross-cutting theme, SHARE provides data on subjective indicators of wellbeing, income and consumption, and satisfaction. The survey provides data on depressive symptoms and self-reported health, which are seen as good indicators of wellbeing. In this regard, SHARE provides the possibility to study, for example, the effect of objective or subjective variables of health on life satisfaction.


• Abuladze, L., & Sakkeus, L. “27 Social networks and everyday activity limitations.” In Börsch-Supan, A., Brandt, M., Litwin, H., / Weber, G. (eds.) “Active ageing and solidarity between generations in Europe” DE GRUYTER, Berlin, Boston (2013): 311-322. • Angelini, V., Brugiavini, A., & Weber, G. “Ageing and unused capacity in Europe: Is there an early retirement trap?” Economic Policy 24(7) (2009): 463-508. DOI: 10.1111/j.1468-0327.2009.00227.x. • Angelini, V., Cavapozzi, D., Corazzini, L., & Pacagnella, O. “Age, health and life satisfaction among older Europeans.” Social Indicators Research 105(2) (2012): 293-308 DOI: 10.1007/s11205-011-9882-x. • Angelini, V., Laferrere, A., & Weber, G.“ Home-ownership in Europe: How did it happen?” Advances in Life Course Research 18 (2013): 83-90. • Avendano, M., Jürges, H., & Mackenbach, J.P. “Educational level and changes in health across Europe: Longitudinal results from SHARE.” Journal of European Social Policy 19(4) (2009): 301-316. DOI: 10.1177/1350506809341512. • Ayalon, L., Heinik, J., & Litwin, H. “Population group differences in cognitive functioning in a national sample of Israelis fifty years and older.” Research on Aging 32(3) (2010): 304-322. DOI: 10.1177/0164027509356875. • Börsch-Supan, A., Hank, K., & Jürges, H. “A new comprehensive and international view on ageing: introducing the ‘Survey of Health, Ageing and Retirement in Europe’.” European Journal of Ageing 2(4) (2005): 245-253. • Börsch-Supan, A., Brandt, M. , Litwin, H., & Weber, G. (Eds). “Active ageing and solidarity between generations in Europe: First results from SHARE after the economic crisis.” De Gruyter, Berlin (2013). • Börsch-Supan, A., Brandt, M., Hank, K., & Schröder, M. (Eds). “The individual and the welfare state. Life histories in Europe.” Springer, Heidelberg (2011). • Börsch-Supan, A., Brugiavini, A., Jürges, H., et al. “First results from the Survey of Health, Ageing and Retirement in Europe (2004-2007). Starting the longitudinal dimension.” Mannheim Research Institute for the Economics of Aging (MEA), Mannheim (2008). • Börsch-Supan, A., Brugiavini, A., Jürges, H., et al. “Health, ageing and retirement in Europe – First results from the Survey of Health, Ageing and Retirement in Europe.” Mannheim Research Institute for the Economics of Aging (MEA), Mannheim (2005). • Borsch-Supan, A., Brandt, M., Hunkler, C., et al. „Data Resource Profile: The Survey of Health, Ageing and Retirement in Europe (SHARE).” International Journal of Epidemiology 1(10) (2013). DOI: 10.1093/ije/dyt088. • Börsch-Supan, A., & Jürges, H. (Eds). “The Survey of Health, Ageing and Retirement in Europe – Methodology.” MEA, Mannheim (2005). • Brandt, M., Deindl, C., & Hank, K. “Tracing the origins of successful aging: The role of childhood conditions and societal context.” Social Science and Medicine 74(9) (2012): 1418–1425. DOI: 10.1016/j.socscimed.2012.01.004. • Brandt, M., & Deindl, C. “Intergenerational Transfers to Adult Children in Europe: Do Social Policies Matter?” Journal of Marriage and Family 75 (2013): 235-251. • Buber, I., & Engelhardt, H. “Children’s impact on the mental health of their older mothers and fathers: findings from the Survey of Health, Ageing and Retirement in Europe.” European Journal of Ageing 5(1) (2008): 31-45. • Buber, I. “Ageing in Austria: An overview of “Survey Health, Ageing and Retirement in Europe” (SHARE) with special focus on aspects of health.” Vienna Yearbook of Population Research (2007): 309-326. • D’Uva, T. B., O’Donnell, O., & van Doorslaer, E. “Differential health reporting by educational level and its impact on the measurement of health inequalities among older Europeans.” International Journal of Epidemiology 37 (2008): 1375-1383. • Deindl. C. “The influence of living conditions in early life on satisfaction in old age.” Advances in Life Course Research 18(1) (2013): 107-114. DOI: 10.1016/j.alcr.2012.10.008. • Dewey, M.E., & Prince, M.J. “Cognitive function.” In:Börsch-Supan, A., et al. ”Health, Ageing and Retirement in Europe - First Results from the Survey of Health, Ageing and Retirement in Europe” MEA, Mannheim (2005): 118-125. • Donfut-Attias, C., Ogg, J., & Wolff, F.-C. “European patterns of intergenerational financial and time transfers.” European Journal of Ageing 2 (2005):161-173. • Engelhardt, H. “Late careers in Europe: Effects of individual and institutional factors.” European Sociological Review 28(4) (2012): 550-563. DOI: 10.1093/esr/jcr024. • Erlinghagen, M., & Hank, K. “Participation of Older Europeans in Voluntary Work.” Ageing and Society 26(4) (2006): 657-584. • Gaymu, J., & Springer, S. “Living conditions and life satisfaction of older Europeans living alone: A gender and cross-country analysis.” Ageing and Society 30 (2010): 1153-1175. DOI: 10.1017/S0144686X10000231. • Gwozdz, W., & Sousa-Poza, A. “Ageing, health and life satisfaction of the oldest old: An analysis for Germany.” Social Indicators Research 97(3) (2010): 397-417. DOI: 10.1007/s11205-009-9508-8. • Hank, K., & Buber, I. “Grandparents Caring for Their Grandchildren Findings From the 2004 Survey of Health, Ageing, and Retirement in Europe.” Journal of Family Issues 30(1) (2009): 53-73. • Hochman, O., & Lewin-Epstein, N. “Determinants of early retirement preferences in Europe: The role of grandparenthood.” International Journal of Comparative Sociology 54(1) (2013): 29-47 DOI: 10.1177/0020715213480977. • Horner, E.M. “Subjective well-being and retirement: Analysis and policy recommendations.” Journal of Happiness Studies forthcoming. DOI: 10.1007/s10902-012-9399-2. • Jagger, C., et al. “The global Activity Limitation Index measured function and disability similarly across European countries.” Journal of Clinical Epidimiology 63 (2010): 892-899. • Jürges, H., & van Soest, A. “Comparing the wellbeing of older Europeans: Introduction.” Social Indicator Research 105 (2012): 187-190. • Jürges, H. “Healthy minds in healthy bodies: An international comparison of education-related inequality in physical health among older adults.” Scottish Journal of Political Economy 56(3) (2009): 296-320. DOI: 10.1111/j.1467-9485.2009.00485.x. • Kavé, G., Shrira, A., Palgi, Y., et al. “Formal education level versus self-rated literacy as predictors of cognitive aging.” Journals of Gerontology Series B: Psychological Sciences and Social Sciences 67(6) (2012): 697-704. DOI: 10.1093/geronb/gbs031. • Litwin, H., & Sapir, E.V. “Perceived income adequacy among older adults in 12 countries: Findings from the Survey of Health, Ageing, and Retirement in Europe.” The Gerontologist 49(3) (2009): 397-406. • Malter, F. and Börsch-Supan, A. (Eds). (2013). SHARE Wave 4: Innovations & Methodology. Munich: MEA, Max Planck Institute for Social Law and Social Policy. • Mazzonna, F. “The effect of education on old age health and cognitive abilities - does the instrument matter?” SHARE working paper 10-2012, Munich Center for the Economics of Aging (MEA) (2012). • Mazzonna, F., & Peracchi, F. “Ageing, cognitive abilities and retirement.” European Economic Review 56(4) (2012): 691-710. DOI: 10.1016/j.euroecorev.2012.03.004. • Mielck, A., Kiess, R., Knesebeck, O., et al. “Association between forgone care and household income among the elderly in five Western European countries – analyses based on survey data from the SHARE-study.” BMC Health Services Research 9(52) (2009). • Romero-Ortuno, R., Walsh, C. D., Lawor, B.I., & Kenny, R.A. “A Frailty Instrument for primary care: findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).” BMC Geriatrics 10(57) (2010). • Romero-Ortuno, R., et al. “A frailty instrument for primary care: findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).” BMC geriatrics 10(1) (2010): 57. • Schneeweis, N., Skirbekk, V., & Winter-Ebmer, R. “Does schooling improve cognitive functioning at older ages?” Economic Working Paper (1211), University of Linz (2012). • Schröder, M. (2011). Retrospective data collection in the Survey of Health, Ageing and Retirement in Europe. SHARELIFE Methodology. Mannheim: MEA. • Siegrist, J., & Wahrendorf, M. “Quality of work, health and retirement.” The Lancet 374 (2009): 1872-1873. DOI: 10.1016/S0140-6736(09)61666-4. • Siegrist, J., et al. “Quality of work, well-being, and intended early retirement of older employees—baseline results from the SHARE Study." The European Journal of Public Health 17(1) (2007): 62-68. • Sirven, N., & Debrand, N. “Promoting social participation for healthy ageing. An International Comparison of Europeans Aged Fifty and Over.” IRDES Working Paper 7 (2008): 1-21.

Coverage


Wave 1 SHARE baseline study: data collected in 2004/2005; sample size of 31,115 interviews (release 2.5.0). Wave 2: data collected in 2006/07; sample size of 34,415 Wave 2 interviews, 533 end-of-life interviews, and 18,742 longitudinal interviews (release 2.5.0). Wave 3 (SHARELIFE): data collected in 2008/09; sample size of 26,836 interviews, 1,139 end-of-life interviews, and 1,158 first interviews with new or previously non-cooperating spouses (release 1.0.0). Wave 4: data collected in 2010/11; sample size of 58,489 interviews, of which 21,566 were longitudinal, 1,110 end-of-life interviews (release 1.1.1). All respondents who were interviewed in any previous wave and their partners are part of the longitudinal sample.


2004


Based on age; in Germany and the Netherlands stratification is based on region.


Random (probability) sample, vignette samples, multi-stage sampling design. National sample frames are chosen to achieve full probability sampling. SHARE data is weighted in order to compensate for unequal selection probabilities in the various sample units. The sample excluded those individuals who were incarcerated, hospitalized or out of the country during the entire survey period, unable to speak the country’s language(s) or have moved to an unknown address. In addition, all respondents who were interviewed in any previous wave and their current partners are part of the longitudinal sample.


2004 SHARE baseline study: Austria, Belgium, Denmark, Spain, France, Germany, Greece, Israel, Italy, The Netherlands, Sweden, Switzerland. Wave 2: 15 countries (+ the Czech Republic, Ireland, and Poland). Wave 3 (SHARELIFE): 14 countries. Wave 4: 16 countries (+ Estonia, Hungary, Slovenia, and Portugal), excluding Greece, which could not take part in wave 4 due to the financial crisis. The Irish SHARE study was merged with TILDA – the Irish Longitudinal Study on Ageing - and there is no stand-alone SHARE in Ireland after wave 3.


Population aged 50+; Wave 1 SHARE baseline study: all individuals born in 1954 or earlier; Wave 2: all individuals born in 1956 or earlier; Wave 4: all individuals born in 1960 or earlier


The main goal of SHARE is to provide data to better understand the ageing process and how it affects individuals in the diverse cultural settings of Europe. The SHARE dataset includes cross-national information on economic circumstances, health, wellbeing, as well as integration into family and social networks. It also includes rich information on the socio-economic background of the surveyed individuals and their family members (parents and children), such as gender, age, marital status, educational level, current work, income, and living arrangements. SHARE data from Waves 1, 2 and 4 deal with respondents’ current living conditions, whereas Wave 3 (SHARELIFE) was conducted as retrospective survey and provides information about life histories. More specifically, SHARELIFE data provides information about childhood living circumstances, partners, children, accommodation, employment and wellbeing and health conditions. Thus, it allows for the study of ageing from a life-course perspective. Wave 4 data can also be used to disentangle the influences of the economic crisis on healthy ageing and intergenerational solidarity in different European countries. More specifically, the SHARE data covers: Intergenerational Relations: SHARE provides data on household arrangements and proximity between family members, as well as exchange of support. In SHARE, accurate information on a child (martial status, partner, transition to adulthood, employment status, education, and frequency of contact) is available for up to four children. SHARE also provides information on practical (support with household tasks) and personal care (e.g. dressing, bathing, eating) and allows for the study of informal care.


• Abuladze, L., & Sakkeus, L. “27 Social networks and everyday activity limitations.” In Börsch-Supan, A., Brandt, M., Litwin, H., / Weber, G. (eds.) “Active ageing and solidarity between generations in Europe” DE GRUYTER, Berlin, Boston (2013): 311-322. • Angelini, V., Brugiavini, A., & Weber, G. “Ageing and unused capacity in Europe: Is there an early retirement trap?” Economic Policy 24(7) (2009): 463-508. DOI: 10.1111/j.1468-0327.2009.00227.x. • Angelini, V., Cavapozzi, D., Corazzini, L., & Pacagnella, O. “Age, health and life satisfaction among older Europeans.” Social Indicators Research 105(2) (2012): 293-308 DOI: 10.1007/s11205-011-9882-x. • Angelini, V., Laferrere, A., & Weber, G.“ Home-ownership in Europe: How did it happen?” Advances in Life Course Research 18 (2013): 83-90. • Avendano, M., Jürges, H., & Mackenbach, J.P. “Educational level and changes in health across Europe: Longitudinal results from SHARE.” Journal of European Social Policy 19(4) (2009): 301-316. DOI: 10.1177/1350506809341512. • Ayalon, L., Heinik, J., & Litwin, H. “Population group differences in cognitive functioning in a national sample of Israelis fifty years and older.” Research on Aging 32(3) (2010): 304-322. DOI: 10.1177/0164027509356875. • Börsch-Supan, A., Hank, K., & Jürges, H. “A new comprehensive and international view on ageing: introducing the ‘Survey of Health, Ageing and Retirement in Europe’.” European Journal of Ageing 2(4) (2005): 245-253. • Börsch-Supan, A., Brandt, M. , Litwin, H., & Weber, G. (Eds). “Active ageing and solidarity between generations in Europe: First results from SHARE after the economic crisis.” De Gruyter, Berlin (2013). • Börsch-Supan, A., Brandt, M., Hank, K., & Schröder, M. (Eds). “The individual and the welfare state. Life histories in Europe.” Springer, Heidelberg (2011). • Börsch-Supan, A., Brugiavini, A., Jürges, H., et al. “First results from the Survey of Health, Ageing and Retirement in Europe (2004-2007). Starting the longitudinal dimension.” Mannheim Research Institute for the Economics of Aging (MEA), Mannheim (2008). • Börsch-Supan, A., Brugiavini, A., Jürges, H., et al. “Health, ageing and retirement in Europe – First results from the Survey of Health, Ageing and Retirement in Europe.” Mannheim Research Institute for the Economics of Aging (MEA), Mannheim (2005). • Borsch-Supan, A., Brandt, M., Hunkler, C., et al. „Data Resource Profile: The Survey of Health, Ageing and Retirement in Europe (SHARE).” International Journal of Epidemiology 1(10) (2013). DOI: 10.1093/ije/dyt088. • Börsch-Supan, A., & Jürges, H. (Eds). “The Survey of Health, Ageing and Retirement in Europe – Methodology.” MEA, Mannheim (2005). • Brandt, M., Deindl, C., & Hank, K. “Tracing the origins of successful aging: The role of childhood conditions and societal context.” Social Science and Medicine 74(9) (2012): 1418–1425. DOI: 10.1016/j.socscimed.2012.01.004. • Brandt, M., & Deindl, C. “Intergenerational Transfers to Adult Children in Europe: Do Social Policies Matter?” Journal of Marriage and Family 75 (2013): 235-251. • Buber, I., & Engelhardt, H. “Children’s impact on the mental health of their older mothers and fathers: findings from the Survey of Health, Ageing and Retirement in Europe.” European Journal of Ageing 5(1) (2008): 31-45. • Buber, I. “Ageing in Austria: An overview of “Survey Health, Ageing and Retirement in Europe” (SHARE) with special focus on aspects of health.” Vienna Yearbook of Population Research (2007): 309-326. • D’Uva, T. B., O’Donnell, O., & van Doorslaer, E. “Differential health reporting by educational level and its impact on the measurement of health inequalities among older Europeans.” International Journal of Epidemiology 37 (2008): 1375-1383. • Deindl. C. “The influence of living conditions in early life on satisfaction in old age.” Advances in Life Course Research 18(1) (2013): 107-114. DOI: 10.1016/j.alcr.2012.10.008. • Dewey, M.E., & Prince, M.J. “Cognitive function.” In:Börsch-Supan, A., et al. ”Health, Ageing and Retirement in Europe - First Results from the Survey of Health, Ageing and Retirement in Europe” MEA, Mannheim (2005): 118-125. • Donfut-Attias, C., Ogg, J., & Wolff, F.-C. “European patterns of intergenerational financial and time transfers.” European Journal of Ageing 2 (2005):161-173. • Engelhardt, H. “Late careers in Europe: Effects of individual and institutional factors.” European Sociological Review 28(4) (2012): 550-563. DOI: 10.1093/esr/jcr024. • Erlinghagen, M., & Hank, K. “Participation of Older Europeans in Voluntary Work.” Ageing and Society 26(4) (2006): 657-584. • Gaymu, J., & Springer, S. “Living conditions and life satisfaction of older Europeans living alone: A gender and cross-country analysis.” Ageing and Society 30 (2010): 1153-1175. DOI: 10.1017/S0144686X10000231. • Gwozdz, W., & Sousa-Poza, A. “Ageing, health and life satisfaction of the oldest old: An analysis for Germany.” Social Indicators Research 97(3) (2010): 397-417. DOI: 10.1007/s11205-009-9508-8. • Hank, K., & Buber, I. “Grandparents Caring for Their Grandchildren Findings From the 2004 Survey of Health, Ageing, and Retirement in Europe.” Journal of Family Issues 30(1) (2009): 53-73. • Hochman, O., & Lewin-Epstein, N. “Determinants of early retirement preferences in Europe: The role of grandparenthood.” International Journal of Comparative Sociology 54(1) (2013): 29-47 DOI: 10.1177/0020715213480977. • Horner, E.M. “Subjective well-being and retirement: Analysis and policy recommendations.” Journal of Happiness Studies forthcoming. DOI: 10.1007/s10902-012-9399-2. • Jagger, C., et al. “The global Activity Limitation Index measured function and disability similarly across European countries.” Journal of Clinical Epidimiology 63 (2010): 892-899. • Jürges, H., & van Soest, A. “Comparing the wellbeing of older Europeans: Introduction.” Social Indicator Research 105 (2012): 187-190. • Jürges, H. “Healthy minds in healthy bodies: An international comparison of education-related inequality in physical health among older adults.” Scottish Journal of Political Economy 56(3) (2009): 296-320. DOI: 10.1111/j.1467-9485.2009.00485.x. • Kavé, G., Shrira, A., Palgi, Y., et al. “Formal education level versus self-rated literacy as predictors of cognitive aging.” Journals of Gerontology Series B: Psychological Sciences and Social Sciences 67(6) (2012): 697-704. DOI: 10.1093/geronb/gbs031. • Litwin, H., & Sapir, E.V. “Perceived income adequacy among older adults in 12 countries: Findings from the Survey of Health, Ageing, and Retirement in Europe.” The Gerontologist 49(3) (2009): 397-406. • Malter, F. and Börsch-Supan, A. (Eds). (2013). SHARE Wave 4: Innovations & Methodology. Munich: MEA, Max Planck Institute for Social Law and Social Policy. • Mazzonna, F. “The effect of education on old age health and cognitive abilities - does the instrument matter?” SHARE working paper 10-2012, Munich Center for the Economics of Aging (MEA) (2012). • Mazzonna, F., & Peracchi, F. “Ageing, cognitive abilities and retirement.” European Economic Review 56(4) (2012): 691-710. DOI: 10.1016/j.euroecorev.2012.03.004. • Mielck, A., Kiess, R., Knesebeck, O., et al. “Association between forgone care and household income among the elderly in five Western European countries – analyses based on survey data from the SHARE-study.” BMC Health Services Research 9(52) (2009). • Romero-Ortuno, R., Walsh, C. D., Lawor, B.I., & Kenny, R.A. “A Frailty Instrument for primary care: findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).” BMC Geriatrics 10(57) (2010). • Romero-Ortuno, R., et al. “A frailty instrument for primary care: findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).” BMC geriatrics 10(1) (2010): 57. • Schneeweis, N., Skirbekk, V., & Winter-Ebmer, R. “Does schooling improve cognitive functioning at older ages?” Economic Working Paper (1211), University of Linz (2012). • Schröder, M. (2011). Retrospective data collection in the Survey of Health, Ageing and Retirement in Europe. SHARELIFE Methodology. Mannheim: MEA. • Siegrist, J., & Wahrendorf, M. “Quality of work, health and retirement.” The Lancet 374 (2009): 1872-1873. DOI: 10.1016/S0140-6736(09)61666-4. • Siegrist, J., et al. “Quality of work, well-being, and intended early retirement of older employees—baseline results from the SHARE Study." The European Journal of Public Health 17(1) (2007): 62-68. • Sirven, N., & Debrand, N. “Promoting social participation for healthy ageing. An International Comparison of Europeans Aged Fifty and Over.” IRDES Working Paper 7 (2008): 1-21.


Linkage


Education variables are coded following ISCED. Occupation and economic activity follow ISCO and NACE codes respectively.


At this time, the linkage with administrative databases is only possible for Germany. SHARE cooperates with the German Pension Fund (DRV) and has linked the German survey data with administrative data held by the DRV in a pilot study in Wave 3 and Wave 4. The administrative data consists of two parts: the first part is longitudinal and includes socio-demographic characteristics (such as age, sex, number, and age of children) and detailed information about work history, as well as all activities, which generate public pension entitlements. These data is available for persons aged 14 and over. The second part is cross-sectional and includes information on the calculation of pension benefits. It is only available for retirees. The project of linking SHARE will continue in Wave 5 and will also be expanded to Austria, Estonia, the Netherlands, and Sweden. To get access to the administrative data of the German Pension Fund, which can be linked to SHARE survey data, researchers must submit an additional form that is also available at the SHARE web page (http://www.share-project.org/data-access-documentation/record-linkage.html). After successful registration, the data will be provided on a CD free of charge.

Linkage


Education variables are coded following ISCED. Occupation and economic activity follow ISCO and NACE codes respectively.


At this time, the linkage with administrative databases is only possible for Germany. SHARE cooperates with the German Pension Fund (DRV) and has linked the German survey data with administrative data held by the DRV in a pilot study in Wave 3 and Wave 4. The administrative data consists of two parts: the first part is longitudinal and includes socio-demographic characteristics (such as age, sex, number, and age of children) and detailed information about work history, as well as all activities, which generate public pension entitlements. These data is available for persons aged 14 and over. The second part is cross-sectional and includes information on the calculation of pension benefits. It is only available for retirees. The project of linking SHARE will continue in Wave 5 and will also be expanded to Austria, Estonia, the Netherlands, and Sweden. To get access to the administrative data of the German Pension Fund, which can be linked to SHARE survey data, researchers must submit an additional form that is also available at the SHARE web page (http://www.share-project.org/data-access-documentation/record-linkage.html). After successful registration, the data will be provided on a CD free of charge.

Linkage


Education variables are coded following ISCED. Occupation and economic activity follow ISCO and NACE codes respectively.


At this time, the linkage with administrative databases is only possible for Germany. SHARE cooperates with the German Pension Fund (DRV) and has linked the German survey data with administrative data held by the DRV in a pilot study in Wave 3 and Wave 4. The administrative data consists of two parts: the first part is longitudinal and includes socio-demographic characteristics (such as age, sex, number, and age of children) and detailed information about work history, as well as all activities, which generate public pension entitlements. These data is available for persons aged 14 and over. The second part is cross-sectional and includes information on the calculation of pension benefits. It is only available for retirees. The project of linking SHARE will continue in Wave 5 and will also be expanded to Austria, Estonia, the Netherlands, and Sweden. To get access to the administrative data of the German Pension Fund, which can be linked to SHARE survey data, researchers must submit an additional form that is also available at the SHARE web page (http://www.share-project.org/data-access-documentation/record-linkage.html). After successful registration, the data will be provided on a CD free of charge.

Linkage


Education variables are coded following ISCED. Occupation and economic activity follow ISCO and NACE codes respectively.


At this time, the linkage with administrative databases is only possible for Germany. SHARE cooperates with the German Pension Fund (DRV) and has linked the German survey data with administrative data held by the DRV in a pilot study in Wave 3 and Wave 4. The administrative data consists of two parts: the first part is longitudinal and includes socio-demographic characteristics (such as age, sex, number, and age of children) and detailed information about work history, as well as all activities, which generate public pension entitlements. These data is available for persons aged 14 and over. The second part is cross-sectional and includes information on the calculation of pension benefits. It is only available for retirees. The project of linking SHARE will continue in Wave 5 and will also be expanded to Austria, Estonia, the Netherlands, and Sweden. To get access to the administrative data of the German Pension Fund, which can be linked to SHARE survey data, researchers must submit an additional form that is also available at the SHARE web page (http://www.share-project.org/data-access-documentation/record-linkage.html). After successful registration, the data will be provided on a CD free of charge.

Linkage


Education variables are coded following ISCED. Occupation and economic activity follow ISCO and NACE codes respectively.


At this time, the linkage with administrative databases is only possible for Germany. SHARE cooperates with the German Pension Fund (DRV) and has linked the German survey data with administrative data held by the DRV in a pilot study in Wave 3 and Wave 4. The administrative data consists of two parts: the first part is longitudinal and includes socio-demographic characteristics (such as age, sex, number, and age of children) and detailed information about work history, as well as all activities, which generate public pension entitlements. These data is available for persons aged 14 and over. The second part is cross-sectional and includes information on the calculation of pension benefits. It is only available for retirees. The project of linking SHARE will continue in Wave 5 and will also be expanded to Austria, Estonia, the Netherlands, and Sweden. To get access to the administrative data of the German Pension Fund, which can be linked to SHARE survey data, researchers must submit an additional form that is also available at the SHARE web page (http://www.share-project.org/data-access-documentation/record-linkage.html). After successful registration, the data will be provided on a CD free of charge.

Linkage


Education variables are coded following ISCED. Occupation and economic activity follow ISCO and NACE codes respectively.


At this time, the linkage with administrative databases is only possible for Germany. SHARE cooperates with the German Pension Fund (DRV) and has linked the German survey data with administrative data held by the DRV in a pilot study in Wave 3 and Wave 4. The administrative data consists of two parts: the first part is longitudinal and includes socio-demographic characteristics (such as age, sex, number, and age of children) and detailed information about work history, as well as all activities, which generate public pension entitlements. These data is available for persons aged 14 and over. The second part is cross-sectional and includes information on the calculation of pension benefits. It is only available for retirees. The project of linking SHARE will continue in Wave 5 and will also be expanded to Austria, Estonia, the Netherlands, and Sweden. To get access to the administrative data of the German Pension Fund, which can be linked to SHARE survey data, researchers must submit an additional form that is also available at the SHARE web page (http://www.share-project.org/data-access-documentation/record-linkage.html). After successful registration, the data will be provided on a CD free of charge.

Linkage


Education variables are coded following ISCED. Occupation and economic activity follow ISCO and NACE codes respectively.


At this time, the linkage with administrative databases is only possible for Germany. SHARE cooperates with the German Pension Fund (DRV) and has linked the German survey data with administrative data held by the DRV in a pilot study in Wave 3 and Wave 4. The administrative data consists of two parts: the first part is longitudinal and includes socio-demographic characteristics (such as age, sex, number, and age of children) and detailed information about work history, as well as all activities, which generate public pension entitlements. These data is available for persons aged 14 and over. The second part is cross-sectional and includes information on the calculation of pension benefits. It is only available for retirees. The project of linking SHARE will continue in Wave 5 and will also be expanded to Austria, Estonia, the Netherlands, and Sweden. To get access to the administrative data of the German Pension Fund, which can be linked to SHARE survey data, researchers must submit an additional form that is also available at the SHARE web page (http://www.share-project.org/data-access-documentation/record-linkage.html). After successful registration, the data will be provided on a CD free of charge.

Linkage


Education variables are coded following ISCED. Occupation and economic activity follow ISCO and NACE codes respectively.


At this time, the linkage with administrative databases is only possible for Germany. SHARE cooperates with the German Pension Fund (DRV) and has linked the German survey data with administrative data held by the DRV in a pilot study in Wave 3 and Wave 4. The administrative data consists of two parts: the first part is longitudinal and includes socio-demographic characteristics (such as age, sex, number, and age of children) and detailed information about work history, as well as all activities, which generate public pension entitlements. These data is available for persons aged 14 and over. The second part is cross-sectional and includes information on the calculation of pension benefits. It is only available for retirees. The project of linking SHARE will continue in Wave 5 and will also be expanded to Austria, Estonia, the Netherlands, and Sweden. To get access to the administrative data of the German Pension Fund, which can be linked to SHARE survey data, researchers must submit an additional form that is also available at the SHARE web page (http://www.share-project.org/data-access-documentation/record-linkage.html). After successful registration, the data will be provided on a CD free of charge.

Linkage


Education variables are coded following ISCED. Occupation and economic activity follow ISCO and NACE codes respectively.


At this time, the linkage with administrative databases is only possible for Germany. SHARE cooperates with the German Pension Fund (DRV) and has linked the German survey data with administrative data held by the DRV in a pilot study in Wave 3 and Wave 4. The administrative data consists of two parts: the first part is longitudinal and includes socio-demographic characteristics (such as age, sex, number, and age of children) and detailed information about work history, as well as all activities, which generate public pension entitlements. These data is available for persons aged 14 and over. The second part is cross-sectional and includes information on the calculation of pension benefits. It is only available for retirees. The project of linking SHARE will continue in Wave 5 and will also be expanded to Austria, Estonia, the Netherlands, and Sweden. To get access to the administrative data of the German Pension Fund, which can be linked to SHARE survey data, researchers must submit an additional form that is also available at the SHARE web page (http://www.share-project.org/data-access-documentation/record-linkage.html). After successful registration, the data will be provided on a CD free of charge.

Linkage


Education variables are coded following ISCED. Occupation and economic activity follow ISCO and NACE codes respectively.


At this time, the linkage with administrative databases is only possible for Germany. SHARE cooperates with the German Pension Fund (DRV) and has linked the German survey data with administrative data held by the DRV in a pilot study in Wave 3 and Wave 4. The administrative data consists of two parts: the first part is longitudinal and includes socio-demographic characteristics (such as age, sex, number, and age of children) and detailed information about work history, as well as all activities, which generate public pension entitlements. These data is available for persons aged 14 and over. The second part is cross-sectional and includes information on the calculation of pension benefits. It is only available for retirees. The project of linking SHARE will continue in Wave 5 and will also be expanded to Austria, Estonia, the Netherlands, and Sweden. To get access to the administrative data of the German Pension Fund, which can be linked to SHARE survey data, researchers must submit an additional form that is also available at the SHARE web page (http://www.share-project.org/data-access-documentation/record-linkage.html). After successful registration, the data will be provided on a CD free of charge.


Data quality


Data is checked for entry errors and corrected if possible.


Even though SHARE is a panel survey with a core questionnaire stable over time, innovative research questions, physical measurements or modules have been added in each wave. For example, in Wave 2, two physical measurements – peak flow and chair stand – were added; whereas Wave 4 implemented a completely new module about social networks.


Consistent coding is used and well documented. The survey is harmonised ex-ante and uses a common generic questionnaire. SHARE also does some ex-post harmonisation in the areas of education (ISCED) and occupation (ISCO, NACE). The dataset provides further generated variables that ease cross-national analysis.

Data quality


Data is checked for entry errors and corrected if possible.


Even though SHARE is a panel survey with a core questionnaire stable over time, innovative research questions, physical measurements or modules have been added in each wave. For example, in Wave 2, two physical measurements – peak flow and chair stand – were added; whereas Wave 4 implemented a completely new module about social networks.


Consistent coding is used and well documented. The survey is harmonised ex-ante and uses a common generic questionnaire. SHARE also does some ex-post harmonisation in the areas of education (ISCED) and occupation (ISCO, NACE). The dataset provides further generated variables that ease cross-national analysis.

Data quality


Data is checked for entry errors and corrected if possible.


Even though SHARE is a panel survey with a core questionnaire stable over time, innovative research questions, physical measurements or modules have been added in each wave. For example, in Wave 2, two physical measurements – peak flow and chair stand – were added; whereas Wave 4 implemented a completely new module about social networks.


Consistent coding is used and well documented. The survey is harmonised ex-ante and uses a common generic questionnaire. SHARE also does some ex-post harmonisation in the areas of education (ISCED) and occupation (ISCO, NACE). The dataset provides further generated variables that ease cross-national analysis.

Data quality


Data is checked for entry errors and corrected if possible.


Even though SHARE is a panel survey with a core questionnaire stable over time, innovative research questions, physical measurements or modules have been added in each wave. For example, in Wave 2, two physical measurements – peak flow and chair stand – were added; whereas Wave 4 implemented a completely new module about social networks.


Consistent coding is used and well documented. The survey is harmonised ex-ante and uses a common generic questionnaire. SHARE also does some ex-post harmonisation in the areas of education (ISCED) and occupation (ISCO, NACE). The dataset provides further generated variables that ease cross-national analysis.

Data quality


Data is checked for entry errors and corrected if possible.


Even though SHARE is a panel survey with a core questionnaire stable over time, innovative research questions, physical measurements or modules have been added in each wave. For example, in Wave 2, two physical measurements – peak flow and chair stand – were added; whereas Wave 4 implemented a completely new module about social networks.


Consistent coding is used and well documented. The survey is harmonised ex-ante and uses a common generic questionnaire. SHARE also does some ex-post harmonisation in the areas of education (ISCED) and occupation (ISCO, NACE). The dataset provides further generated variables that ease cross-national analysis.

Data quality


Data is checked for entry errors and corrected if possible.


Even though SHARE is a panel survey with a core questionnaire stable over time, innovative research questions, physical measurements or modules have been added in each wave. For example, in Wave 2, two physical measurements – peak flow and chair stand – were added; whereas Wave 4 implemented a completely new module about social networks.


Consistent coding is used and well documented. The survey is harmonised ex-ante and uses a common generic questionnaire. SHARE also does some ex-post harmonisation in the areas of education (ISCED) and occupation (ISCO, NACE). The dataset provides further generated variables that ease cross-national analysis.

Data quality


Data is checked for entry errors and corrected if possible.


Even though SHARE is a panel survey with a core questionnaire stable over time, innovative research questions, physical measurements or modules have been added in each wave. For example, in Wave 2, two physical measurements – peak flow and chair stand – were added; whereas Wave 4 implemented a completely new module about social networks.


Consistent coding is used and well documented. The survey is harmonised ex-ante and uses a common generic questionnaire. SHARE also does some ex-post harmonisation in the areas of education (ISCED) and occupation (ISCO, NACE). The dataset provides further generated variables that ease cross-national analysis.

Data quality


Data is checked for entry errors and corrected if possible.


Even though SHARE is a panel survey with a core questionnaire stable over time, innovative research questions, physical measurements or modules have been added in each wave. For example, in Wave 2, two physical measurements – peak flow and chair stand – were added; whereas Wave 4 implemented a completely new module about social networks.


Consistent coding is used and well documented. The survey is harmonised ex-ante and uses a common generic questionnaire. SHARE also does some ex-post harmonisation in the areas of education (ISCED) and occupation (ISCO, NACE). The dataset provides further generated variables that ease cross-national analysis.

Data quality


Data is checked for entry errors and corrected if possible.


Even though SHARE is a panel survey with a core questionnaire stable over time, innovative research questions, physical measurements or modules have been added in each wave. For example, in Wave 2, two physical measurements – peak flow and chair stand – were added; whereas Wave 4 implemented a completely new module about social networks.


Consistent coding is used and well documented. The survey is harmonised ex-ante and uses a common generic questionnaire. SHARE also does some ex-post harmonisation in the areas of education (ISCED) and occupation (ISCO, NACE). The dataset provides further generated variables that ease cross-national analysis.

Data quality


Data is checked for entry errors and corrected if possible.


Even though SHARE is a panel survey with a core questionnaire stable over time, innovative research questions, physical measurements or modules have been added in each wave. For example, in Wave 2, two physical measurements – peak flow and chair stand – were added; whereas Wave 4 implemented a completely new module about social networks.


Consistent coding is used and well documented. The survey is harmonised ex-ante and uses a common generic questionnaire. SHARE also does some ex-post harmonisation in the areas of education (ISCED) and occupation (ISCO, NACE). The dataset provides further generated variables that ease cross-national analysis.


Applicability


SHARE is the first cross-national survey extensively and comparatively exploring topics related to working conditions, health and wellbeing, social engagement, and wellbeing status of the population 50+ in Europe. It is also the first survey that brings together harmonised data on financial and time transfers, given and received. It therefore allows for studying the ageing process and its consequences from different angles. A particular strength of the SHARE data is the broad set of health measures and biomarkers that enable researchers to validate respondents’ own perception of health. The core questionnaire of SHARE is stable over time, but its design allows for the inclusion of new modules and innovative research questions according to the circumstances of each wave. This has allowed for the inclusion of additional physical measurements in Wave 2 and a social connectedness module in Wave 4. In wave 5, the topic of uses in technology will be included and thus SHARE will allow for studying a rather neglected topic in ageing research. One of the main advantages of SHARE is the ex-ante harmonisation at all stages of the survey process. Therefore, the survey has one common generic questionnaire that is processed automatically in one common CAPI instrument. SHARE also does some ex-post harmonisation in the areas of education (ISCED) and occupation (ISCO, NACE). Furthermore, there are item specific differences, e.g. in answer categories, especially when it comes to institutional features. Regarding the international comparability of the results, SHARE was created to follow and is harmonised with the U.S. Health and Retirement Study (HRS) and the English Longitudinal Study of Ageing (ELSA). Moreover, SHARE has several sister studies: CHARLS (Chinese Health and Retirement Survey), ELSA-Brasil (Estudo Longitudinal de Saúde do Adulto), JSTAR (The Japanese Study of Aging and Retirement), KLoSA (The Korean Longitudinal Study of Aging), LASI (The Longitudinal Aging Study in India), MHAS (Mexican Health and Aging Study) and TILDA (The Irish Longitudinal Study on Ageing). A particular strength of the survey is based on the combination of SHARELIFE with SHARE and ELSA data. This operation allows for the analysis of the current status of the surveyed, as well as their life-course. Wave 3 SHARELIFE is that it collects detailed retrospective life-histories in 16 countries in 2008-09 and thus gives the possibility to researchers to study different themes in longitudinal perspective without having to wait for the cohorts to reach advanced age. Of course, it should be kept in mind that retrospective responses might be influenced by memory loss. Weaknesses: One of the main concerns regarding SHARE data is the generally decreasing survey participation rates and moderate levels of attrition, though in comparison with other European and recent US survey studies, the overall response rate of SHARE is rather high. SHARE’s main strategy to cope with attrition is the provision of ex-post calibrated weights following the procedure of Deville and Saerndal. The use of SHARE data requires a learning process by users in terms of meaningful data preparation and analysis. This is due to its cross-national and multidisciplinary nature, as well as the complexity of the phenomena covered by the survey. The SHARE team is making an effort to minimise these challenges by extensive data cleaning, provision of generated variables, a comprehensive documentation measures and intensive user support (by email, phone and in-person training). Moreover, a special training dataset for new users is in preparation. Public attitudes towards old age SHARE collects data on the individual expectations, plans to retire early, and financial expectations.

Applicability


SHARE is the first cross-national survey extensively and comparatively exploring topics related to working conditions, health and wellbeing, social engagement, and wellbeing status of the population 50+ in Europe. It is also the first survey that brings together harmonised data on financial and time transfers, given and received. It therefore allows for studying the ageing process and its consequences from different angles. A particular strength of the SHARE data is the broad set of health measures and biomarkers that enable researchers to validate respondents’ own perception of health. The core questionnaire of SHARE is stable over time, but its design allows for the inclusion of new modules and innovative research questions according to the circumstances of each wave. This has allowed for the inclusion of additional physical measurements in Wave 2 and a social connectedness module in Wave 4. In wave 5, the topic of uses in technology will be included and thus SHARE will allow for studying a rather neglected topic in ageing research. One of the main advantages of SHARE is the ex-ante harmonisation at all stages of the survey process. Therefore, the survey has one common generic questionnaire that is processed automatically in one common CAPI instrument. SHARE also does some ex-post harmonisation in the areas of education (ISCED) and occupation (ISCO, NACE). Furthermore, there are item specific differences, e.g. in answer categories, especially when it comes to institutional features. Regarding the international comparability of the results, SHARE was created to follow and is harmonised with the U.S. Health and Retirement Study (HRS) and the English Longitudinal Study of Ageing (ELSA). Moreover, SHARE has several sister studies: CHARLS (Chinese Health and Retirement Survey), ELSA-Brasil (Estudo Longitudinal de Saúde do Adulto), JSTAR (The Japanese Study of Aging and Retirement), KLoSA (The Korean Longitudinal Study of Aging), LASI (The Longitudinal Aging Study in India), MHAS (Mexican Health and Aging Study) and TILDA (The Irish Longitudinal Study on Ageing). A particular strength of the survey is based on the combination of SHARELIFE with SHARE and ELSA data. This operation allows for the analysis of the current status of the surveyed, as well as their life-course. Wave 3 SHARELIFE is that it collects detailed retrospective life-histories in 16 countries in 2008-09 and thus gives the possibility to researchers to study different themes in longitudinal perspective without having to wait for the cohorts to reach advanced age. Of course, it should be kept in mind that retrospective responses might be influenced by memory loss. Weaknesses: One of the main concerns regarding SHARE data is the generally decreasing survey participation rates and moderate levels of attrition, though in comparison with other European and recent US survey studies, the overall response rate of SHARE is rather high. SHARE’s main strategy to cope with attrition is the provision of ex-post calibrated weights following the procedure of Deville and Saerndal. The use of SHARE data requires a learning process by users in terms of meaningful data preparation and analysis. This is due to its cross-national and multidisciplinary nature, as well as the complexity of the phenomena covered by the survey. The SHARE team is making an effort to minimise these challenges by extensive data cleaning, provision of generated variables, a comprehensive documentation measures and intensive user support (by email, phone and in-person training). Moreover, a special training dataset for new users is in preparation. Health and Performance The greatest strength of SHARE is that it provides data on objective (walking speed, grip strength) as well as quasi-objective (daily activities, symptoms), measures of health (unlike most of the other longitudinal panels). Doing so is particularly important because health plays a central role in the quality of life of the oldest old. In addition to subjective health measures SHARE also collects objective health measures. Biomarkers enable researchers to validate respondents’ self-reports and therefore to study the amount and determinants of under-, over-, and misreporting in large scale population surveys. Furthermore, a combination of actual health measures and self-reported health status provides a unique possibility for an in-depth study of health. Finally, vignettes used in SHARE allow estimating a measure of health corrected for reporting heterogeneity.

Applicability


SHARE is the first cross-national survey extensively and comparatively exploring topics related to working conditions, health and wellbeing, social engagement, and wellbeing status of the population 50+ in Europe. It is also the first survey that brings together harmonised data on financial and time transfers, given and received. It therefore allows for studying the ageing process and its consequences from different angles. A particular strength of the SHARE data is the broad set of health measures and biomarkers that enable researchers to validate respondents’ own perception of health. The core questionnaire of SHARE is stable over time, but its design allows for the inclusion of new modules and innovative research questions according to the circumstances of each wave. This has allowed for the inclusion of additional physical measurements in Wave 2 and a social connectedness module in Wave 4. In wave 5, the topic of uses in technology will be included and thus SHARE will allow for studying a rather neglected topic in ageing research. One of the main advantages of SHARE is the ex-ante harmonisation at all stages of the survey process. Therefore, the survey has one common generic questionnaire that is processed automatically in one common CAPI instrument. SHARE also does some ex-post harmonisation in the areas of education (ISCED) and occupation (ISCO, NACE). Furthermore, there are item specific differences, e.g. in answer categories, especially when it comes to institutional features. Regarding the international comparability of the results, SHARE was created to follow and is harmonised with the U.S. Health and Retirement Study (HRS) and the English Longitudinal Study of Ageing (ELSA). Moreover, SHARE has several sister studies: CHARLS (Chinese Health and Retirement Survey), ELSA-Brasil (Estudo Longitudinal de Saúde do Adulto), JSTAR (The Japanese Study of Aging and Retirement), KLoSA (The Korean Longitudinal Study of Aging), LASI (The Longitudinal Aging Study in India), MHAS (Mexican Health and Aging Study) and TILDA (The Irish Longitudinal Study on Ageing). A particular strength of the survey is based on the combination of SHARELIFE with SHARE and ELSA data. This operation allows for the analysis of the current status of the surveyed, as well as their life-course. Wave 3 SHARELIFE is that it collects detailed retrospective life-histories in 16 countries in 2008-09 and thus gives the possibility to researchers to study different themes in longitudinal perspective without having to wait for the cohorts to reach advanced age. Of course, it should be kept in mind that retrospective responses might be influenced by memory loss. Weaknesses: One of the main concerns regarding SHARE data is the generally decreasing survey participation rates and moderate levels of attrition, though in comparison with other European and recent US survey studies, the overall response rate of SHARE is rather high. SHARE’s main strategy to cope with attrition is the provision of ex-post calibrated weights following the procedure of Deville and Saerndal. The use of SHARE data requires a learning process by users in terms of meaningful data preparation and analysis. This is due to its cross-national and multidisciplinary nature, as well as the complexity of the phenomena covered by the survey. The SHARE team is making an effort to minimise these challenges by extensive data cleaning, provision of generated variables, a comprehensive documentation measures and intensive user support (by email, phone and in-person training). Moreover, a special training dataset for new users is in preparation. Social systems and welfare The analysis of SHARE data allows for the study of the effects of welfare policies on health, socioeconomic status, and wellbeing on the population over 50. Such would be the case of health insurance coverage, maternity leave, early retirement, and disability benefits.

Applicability


SHARE is the first cross-national survey extensively and comparatively exploring topics related to working conditions, health and wellbeing, social engagement, and wellbeing status of the population 50+ in Europe. It is also the first survey that brings together harmonised data on financial and time transfers, given and received. It therefore allows for studying the ageing process and its consequences from different angles. A particular strength of the SHARE data is the broad set of health measures and biomarkers that enable researchers to validate respondents’ own perception of health. The core questionnaire of SHARE is stable over time, but its design allows for the inclusion of new modules and innovative research questions according to the circumstances of each wave. This has allowed for the inclusion of additional physical measurements in Wave 2 and a social connectedness module in Wave 4. In wave 5, the topic of uses in technology will be included and thus SHARE will allow for studying a rather neglected topic in ageing research. One of the main advantages of SHARE is the ex-ante harmonisation at all stages of the survey process. Therefore, the survey has one common generic questionnaire that is processed automatically in one common CAPI instrument. SHARE also does some ex-post harmonisation in the areas of education (ISCED) and occupation (ISCO, NACE). Furthermore, there are item specific differences, e.g. in answer categories, especially when it comes to institutional features. Regarding the international comparability of the results, SHARE was created to follow and is harmonised with the U.S. Health and Retirement Study (HRS) and the English Longitudinal Study of Ageing (ELSA). Moreover, SHARE has several sister studies: CHARLS (Chinese Health and Retirement Survey), ELSA-Brasil (Estudo Longitudinal de Saúde do Adulto), JSTAR (The Japanese Study of Aging and Retirement), KLoSA (The Korean Longitudinal Study of Aging), LASI (The Longitudinal Aging Study in India), MHAS (Mexican Health and Aging Study) and TILDA (The Irish Longitudinal Study on Ageing). A particular strength of the survey is based on the combination of SHARELIFE with SHARE and ELSA data. This operation allows for the analysis of the current status of the surveyed, as well as their life-course. Wave 3 SHARELIFE is that it collects detailed retrospective life-histories in 16 countries in 2008-09 and thus gives the possibility to researchers to study different themes in longitudinal perspective without having to wait for the cohorts to reach advanced age. Of course, it should be kept in mind that retrospective responses might be influenced by memory loss. Weaknesses: One of the main concerns regarding SHARE data is the generally decreasing survey participation rates and moderate levels of attrition, though in comparison with other European and recent US survey studies, the overall response rate of SHARE is rather high. SHARE’s main strategy to cope with attrition is the provision of ex-post calibrated weights following the procedure of Deville and Saerndal. The use of SHARE data requires a learning process by users in terms of meaningful data preparation and analysis. This is due to its cross-national and multidisciplinary nature, as well as the complexity of the phenomena covered by the survey. The SHARE team is making an effort to minimise these challenges by extensive data cleaning, provision of generated variables, a comprehensive documentation measures and intensive user support (by email, phone and in-person training). Moreover, a special training dataset for new users is in preparation. Work and Productivity Since SHARE covers the three stages of later life: pre-retirement, post-retirement and old age, it allows for an extensive study of the transition from work to retirement. Therefore, the use of SHARE and SHARELIFE data allows for the study of the distribution of work across the life-course, as well as the interaction with health, education, and cognitive function variables.

Applicability


SHARE is the first cross-national survey extensively and comparatively exploring topics related to working conditions, health and wellbeing, social engagement, and wellbeing status of the population 50+ in Europe. It is also the first survey that brings together harmonised data on financial and time transfers, given and received. It therefore allows for studying the ageing process and its consequences from different angles. A particular strength of the SHARE data is the broad set of health measures and biomarkers that enable researchers to validate respondents’ own perception of health. The core questionnaire of SHARE is stable over time, but its design allows for the inclusion of new modules and innovative research questions according to the circumstances of each wave. This has allowed for the inclusion of additional physical measurements in Wave 2 and a social connectedness module in Wave 4. In wave 5, the topic of uses in technology will be included and thus SHARE will allow for studying a rather neglected topic in ageing research. One of the main advantages of SHARE is the ex-ante harmonisation at all stages of the survey process. Therefore, the survey has one common generic questionnaire that is processed automatically in one common CAPI instrument. SHARE also does some ex-post harmonisation in the areas of education (ISCED) and occupation (ISCO, NACE). Furthermore, there are item specific differences, e.g. in answer categories, especially when it comes to institutional features. Regarding the international comparability of the results, SHARE was created to follow and is harmonised with the U.S. Health and Retirement Study (HRS) and the English Longitudinal Study of Ageing (ELSA). Moreover, SHARE has several sister studies: CHARLS (Chinese Health and Retirement Survey), ELSA-Brasil (Estudo Longitudinal de Saúde do Adulto), JSTAR (The Japanese Study of Aging and Retirement), KLoSA (The Korean Longitudinal Study of Aging), LASI (The Longitudinal Aging Study in India), MHAS (Mexican Health and Aging Study) and TILDA (The Irish Longitudinal Study on Ageing). A particular strength of the survey is based on the combination of SHARELIFE with SHARE and ELSA data. This operation allows for the analysis of the current status of the surveyed, as well as their life-course. Wave 3 SHARELIFE is that it collects detailed retrospective life-histories in 16 countries in 2008-09 and thus gives the possibility to researchers to study different themes in longitudinal perspective without having to wait for the cohorts to reach advanced age. Of course, it should be kept in mind that retrospective responses might be influenced by memory loss. Weaknesses: One of the main concerns regarding SHARE data is the generally decreasing survey participation rates and moderate levels of attrition, though in comparison with other European and recent US survey studies, the overall response rate of SHARE is rather high. SHARE’s main strategy to cope with attrition is the provision of ex-post calibrated weights following the procedure of Deville and Saerndal. The use of SHARE data requires a learning process by users in terms of meaningful data preparation and analysis. This is due to its cross-national and multidisciplinary nature, as well as the complexity of the phenomena covered by the survey. The SHARE team is making an effort to minimise these challenges by extensive data cleaning, provision of generated variables, a comprehensive documentation measures and intensive user support (by email, phone and in-person training). Moreover, a special training dataset for new users is in preparation. Education and learning Waves 1, 2, and 4 provide valuable information on the individual cognitive function, as well as the individual educational attainment. Moreover, SHARELIFE allows for the inclusion of childhood circumstances in the analysis.

Applicability


SHARE is the first cross-national survey extensively and comparatively exploring topics related to working conditions, health and wellbeing, social engagement, and wellbeing status of the population 50+ in Europe. It is also the first survey that brings together harmonised data on financial and time transfers, given and received. It therefore allows for studying the ageing process and its consequences from different angles. A particular strength of the SHARE data is the broad set of health measures and biomarkers that enable researchers to validate respondents’ own perception of health. The core questionnaire of SHARE is stable over time, but its design allows for the inclusion of new modules and innovative research questions according to the circumstances of each wave. This has allowed for the inclusion of additional physical measurements in Wave 2 and a social connectedness module in Wave 4. In wave 5, the topic of uses in technology will be included and thus SHARE will allow for studying a rather neglected topic in ageing research. One of the main advantages of SHARE is the ex-ante harmonisation at all stages of the survey process. Therefore, the survey has one common generic questionnaire that is processed automatically in one common CAPI instrument. SHARE also does some ex-post harmonisation in the areas of education (ISCED) and occupation (ISCO, NACE). Furthermore, there are item specific differences, e.g. in answer categories, especially when it comes to institutional features. Regarding the international comparability of the results, SHARE was created to follow and is harmonised with the U.S. Health and Retirement Study (HRS) and the English Longitudinal Study of Ageing (ELSA). Moreover, SHARE has several sister studies: CHARLS (Chinese Health and Retirement Survey), ELSA-Brasil (Estudo Longitudinal de Saúde do Adulto), JSTAR (The Japanese Study of Aging and Retirement), KLoSA (The Korean Longitudinal Study of Aging), LASI (The Longitudinal Aging Study in India), MHAS (Mexican Health and Aging Study) and TILDA (The Irish Longitudinal Study on Ageing). A particular strength of the survey is based on the combination of SHARELIFE with SHARE and ELSA data. This operation allows for the analysis of the current status of the surveyed, as well as their life-course. Wave 3 SHARELIFE is that it collects detailed retrospective life-histories in 16 countries in 2008-09 and thus gives the possibility to researchers to study different themes in longitudinal perspective without having to wait for the cohorts to reach advanced age. Of course, it should be kept in mind that retrospective responses might be influenced by memory loss. Weaknesses: One of the main concerns regarding SHARE data is the generally decreasing survey participation rates and moderate levels of attrition, though in comparison with other European and recent US survey studies, the overall response rate of SHARE is rather high. SHARE’s main strategy to cope with attrition is the provision of ex-post calibrated weights following the procedure of Deville and Saerndal. The use of SHARE data requires a learning process by users in terms of meaningful data preparation and analysis. This is due to its cross-national and multidisciplinary nature, as well as the complexity of the phenomena covered by the survey. The SHARE team is making an effort to minimise these challenges by extensive data cleaning, provision of generated variables, a comprehensive documentation measures and intensive user support (by email, phone and in-person training). Moreover, a special training dataset for new users is in preparation. Housing, Urban Development and Mobility In addition to the respondent, SHARE includes detailed information on household composition; that is everybody who is living in the same household: respondent’s partners, parents and parents-in-law, children, siblings, other relatives, or any other persons. Furthermore, SHARE is a unique survey in the way that it provides data on home ownership, accommodation history, and intentions to move as linked to life-course transitions, such as retirement.

Applicability


SHARE is the first cross-national survey extensively and comparatively exploring topics related to working conditions, health and wellbeing, social engagement, and wellbeing status of the population 50+ in Europe. It is also the first survey that brings together harmonised data on financial and time transfers, given and received. It therefore allows for studying the ageing process and its consequences from different angles. A particular strength of the SHARE data is the broad set of health measures and biomarkers that enable researchers to validate respondents’ own perception of health. The core questionnaire of SHARE is stable over time, but its design allows for the inclusion of new modules and innovative research questions according to the circumstances of each wave. This has allowed for the inclusion of additional physical measurements in Wave 2 and a social connectedness module in Wave 4. In wave 5, the topic of uses in technology will be included and thus SHARE will allow for studying a rather neglected topic in ageing research. One of the main advantages of SHARE is the ex-ante harmonisation at all stages of the survey process. Therefore, the survey has one common generic questionnaire that is processed automatically in one common CAPI instrument. SHARE also does some ex-post harmonisation in the areas of education (ISCED) and occupation (ISCO, NACE). Furthermore, there are item specific differences, e.g. in answer categories, especially when it comes to institutional features. Regarding the international comparability of the results, SHARE was created to follow and is harmonised with the U.S. Health and Retirement Study (HRS) and the English Longitudinal Study of Ageing (ELSA). Moreover, SHARE has several sister studies: CHARLS (Chinese Health and Retirement Survey), ELSA-Brasil (Estudo Longitudinal de Saúde do Adulto), JSTAR (The Japanese Study of Aging and Retirement), KLoSA (The Korean Longitudinal Study of Aging), LASI (The Longitudinal Aging Study in India), MHAS (Mexican Health and Aging Study) and TILDA (The Irish Longitudinal Study on Ageing). A particular strength of the survey is based on the combination of SHARELIFE with SHARE and ELSA data. This operation allows for the analysis of the current status of the surveyed, as well as their life-course. Wave 3 SHARELIFE is that it collects detailed retrospective life-histories in 16 countries in 2008-09 and thus gives the possibility to researchers to study different themes in longitudinal perspective without having to wait for the cohorts to reach advanced age. Of course, it should be kept in mind that retrospective responses might be influenced by memory loss. Weaknesses: One of the main concerns regarding SHARE data is the generally decreasing survey participation rates and moderate levels of attrition, though in comparison with other European and recent US survey studies, the overall response rate of SHARE is rather high. SHARE’s main strategy to cope with attrition is the provision of ex-post calibrated weights following the procedure of Deville and Saerndal. The use of SHARE data requires a learning process by users in terms of meaningful data preparation and analysis. This is due to its cross-national and multidisciplinary nature, as well as the complexity of the phenomena covered by the survey. The SHARE team is making an effort to minimise these challenges by extensive data cleaning, provision of generated variables, a comprehensive documentation measures and intensive user support (by email, phone and in-person training). Moreover, a special training dataset for new users is in preparation. Social, civic and cultural engagement The fourth wave of SHARE is unique in terms of social networks and thus allows for studying the social participation and environment of older people. However, researchers have reported a shortcoming with regard to voluntary work: Data is not very detailed and does now allow for distinguishing many types of voluntary work.

Applicability


SHARE is the first cross-national survey extensively and comparatively exploring topics related to working conditions, health and wellbeing, social engagement, and wellbeing status of the population 50+ in Europe. It is also the first survey that brings together harmonised data on financial and time transfers, given and received. It therefore allows for studying the ageing process and its consequences from different angles. A particular strength of the SHARE data is the broad set of health measures and biomarkers that enable researchers to validate respondents’ own perception of health. The core questionnaire of SHARE is stable over time, but its design allows for the inclusion of new modules and innovative research questions according to the circumstances of each wave. This has allowed for the inclusion of additional physical measurements in Wave 2 and a social connectedness module in Wave 4. In wave 5, the topic of uses in technology will be included and thus SHARE will allow for studying a rather neglected topic in ageing research. One of the main advantages of SHARE is the ex-ante harmonisation at all stages of the survey process. Therefore, the survey has one common generic questionnaire that is processed automatically in one common CAPI instrument. SHARE also does some ex-post harmonisation in the areas of education (ISCED) and occupation (ISCO, NACE). Furthermore, there are item specific differences, e.g. in answer categories, especially when it comes to institutional features. Regarding the international comparability of the results, SHARE was created to follow and is harmonised with the U.S. Health and Retirement Study (HRS) and the English Longitudinal Study of Ageing (ELSA). Moreover, SHARE has several sister studies: CHARLS (Chinese Health and Retirement Survey), ELSA-Brasil (Estudo Longitudinal de Saúde do Adulto), JSTAR (The Japanese Study of Aging and Retirement), KLoSA (The Korean Longitudinal Study of Aging), LASI (The Longitudinal Aging Study in India), MHAS (Mexican Health and Aging Study) and TILDA (The Irish Longitudinal Study on Ageing). A particular strength of the survey is based on the combination of SHARELIFE with SHARE and ELSA data. This operation allows for the analysis of the current status of the surveyed, as well as their life-course. Wave 3 SHARELIFE is that it collects detailed retrospective life-histories in 16 countries in 2008-09 and thus gives the possibility to researchers to study different themes in longitudinal perspective without having to wait for the cohorts to reach advanced age. Of course, it should be kept in mind that retrospective responses might be influenced by memory loss. Weaknesses: One of the main concerns regarding SHARE data is the generally decreasing survey participation rates and moderate levels of attrition, though in comparison with other European and recent US survey studies, the overall response rate of SHARE is rather high. SHARE’s main strategy to cope with attrition is the provision of ex-post calibrated weights following the procedure of Deville and Saerndal. The use of SHARE data requires a learning process by users in terms of meaningful data preparation and analysis. This is due to its cross-national and multidisciplinary nature, as well as the complexity of the phenomena covered by the survey. The SHARE team is making an effort to minimise these challenges by extensive data cleaning, provision of generated variables, a comprehensive documentation measures and intensive user support (by email, phone and in-person training). Moreover, a special training dataset for new users is in preparation. Uses of technology At this time, the survey collects a scarce number of variables regarding uses of technology and assisted living. Nevertheless, the Wave 5 questionnaire will include additional items on uses of technology.

Applicability


SHARE is the first cross-national survey extensively and comparatively exploring topics related to working conditions, health and wellbeing, social engagement, and wellbeing status of the population 50+ in Europe. It is also the first survey that brings together harmonised data on financial and time transfers, given and received. It therefore allows for studying the ageing process and its consequences from different angles. A particular strength of the SHARE data is the broad set of health measures and biomarkers that enable researchers to validate respondents’ own perception of health. The core questionnaire of SHARE is stable over time, but its design allows for the inclusion of new modules and innovative research questions according to the circumstances of each wave. This has allowed for the inclusion of additional physical measurements in Wave 2 and a social connectedness module in Wave 4. In wave 5, the topic of uses in technology will be included and thus SHARE will allow for studying a rather neglected topic in ageing research. One of the main advantages of SHARE is the ex-ante harmonisation at all stages of the survey process. Therefore, the survey has one common generic questionnaire that is processed automatically in one common CAPI instrument. SHARE also does some ex-post harmonisation in the areas of education (ISCED) and occupation (ISCO, NACE). Furthermore, there are item specific differences, e.g. in answer categories, especially when it comes to institutional features. Regarding the international comparability of the results, SHARE was created to follow and is harmonised with the U.S. Health and Retirement Study (HRS) and the English Longitudinal Study of Ageing (ELSA). Moreover, SHARE has several sister studies: CHARLS (Chinese Health and Retirement Survey), ELSA-Brasil (Estudo Longitudinal de Saúde do Adulto), JSTAR (The Japanese Study of Aging and Retirement), KLoSA (The Korean Longitudinal Study of Aging), LASI (The Longitudinal Aging Study in India), MHAS (Mexican Health and Aging Study) and TILDA (The Irish Longitudinal Study on Ageing). A particular strength of the survey is based on the combination of SHARELIFE with SHARE and ELSA data. This operation allows for the analysis of the current status of the surveyed, as well as their life-course. Wave 3 SHARELIFE is that it collects detailed retrospective life-histories in 16 countries in 2008-09 and thus gives the possibility to researchers to study different themes in longitudinal perspective without having to wait for the cohorts to reach advanced age. Of course, it should be kept in mind that retrospective responses might be influenced by memory loss. Weaknesses: One of the main concerns regarding SHARE data is the generally decreasing survey participation rates and moderate levels of attrition, though in comparison with other European and recent US survey studies, the overall response rate of SHARE is rather high. SHARE’s main strategy to cope with attrition is the provision of ex-post calibrated weights following the procedure of Deville and Saerndal. The use of SHARE data requires a learning process by users in terms of meaningful data preparation and analysis. This is due to its cross-national and multidisciplinary nature, as well as the complexity of the phenomena covered by the survey. The SHARE team is making an effort to minimise these challenges by extensive data cleaning, provision of generated variables, a comprehensive documentation measures and intensive user support (by email, phone and in-person training). Moreover, a special training dataset for new users is in preparation. Wellbeing SHARE data allow for the analysis of objective and subjective wellbeing indicators, whereas SHARELIFE provides insights on the influence of early life conditions and life-course events on wellbeing. Because SHARE Wave 1 and 2 make use of vignettes – short descriptions of a person or a social situation which contain precise references to what are thought to be the most important factors in the decision making or judgement-making process of respondents – it is a very useful dataset to study subjective wellbeing.

Applicability


SHARE is the first cross-national survey extensively and comparatively exploring topics related to working conditions, health and wellbeing, social engagement, and wellbeing status of the population 50+ in Europe. It is also the first survey that brings together harmonised data on financial and time transfers, given and received. It therefore allows for studying the ageing process and its consequences from different angles. A particular strength of the SHARE data is the broad set of health measures and biomarkers that enable researchers to validate respondents’ own perception of health. The core questionnaire of SHARE is stable over time, but its design allows for the inclusion of new modules and innovative research questions according to the circumstances of each wave. This has allowed for the inclusion of additional physical measurements in Wave 2 and a social connectedness module in Wave 4. In wave 5, the topic of uses in technology will be included and thus SHARE will allow for studying a rather neglected topic in ageing research. One of the main advantages of SHARE is the ex-ante harmonisation at all stages of the survey process. Therefore, the survey has one common generic questionnaire that is processed automatically in one common CAPI instrument. SHARE also does some ex-post harmonisation in the areas of education (ISCED) and occupation (ISCO, NACE). Furthermore, there are item specific differences, e.g. in answer categories, especially when it comes to institutional features. Regarding the international comparability of the results, SHARE was created to follow and is harmonised with the U.S. Health and Retirement Study (HRS) and the English Longitudinal Study of Ageing (ELSA). Moreover, SHARE has several sister studies: CHARLS (Chinese Health and Retirement Survey), ELSA-Brasil (Estudo Longitudinal de Saúde do Adulto), JSTAR (The Japanese Study of Aging and Retirement), KLoSA (The Korean Longitudinal Study of Aging), LASI (The Longitudinal Aging Study in India), MHAS (Mexican Health and Aging Study) and TILDA (The Irish Longitudinal Study on Ageing). A particular strength of the survey is based on the combination of SHARELIFE with SHARE and ELSA data. This operation allows for the analysis of the current status of the surveyed, as well as their life-course. Wave 3 SHARELIFE is that it collects detailed retrospective life-histories in 16 countries in 2008-09 and thus gives the possibility to researchers to study different themes in longitudinal perspective without having to wait for the cohorts to reach advanced age. Of course, it should be kept in mind that retrospective responses might be influenced by memory loss. Weaknesses: One of the main concerns regarding SHARE data is the generally decreasing survey participation rates and moderate levels of attrition, though in comparison with other European and recent US survey studies, the overall response rate of SHARE is rather high. SHARE’s main strategy to cope with attrition is the provision of ex-post calibrated weights following the procedure of Deville and Saerndal. The use of SHARE data requires a learning process by users in terms of meaningful data preparation and analysis. This is due to its cross-national and multidisciplinary nature, as well as the complexity of the phenomena covered by the survey. The SHARE team is making an effort to minimise these challenges by extensive data cleaning, provision of generated variables, a comprehensive documentation measures and intensive user support (by email, phone and in-person training). Moreover, a special training dataset for new users is in preparation. Intergenerational Solidarity A particular strength of SHARE is that it includes rich background information of respondents’ children. It is therefore possible to study how older Europeans today engage in intergenerational transfers and which individual and family characteristics influence the private transfers.


  • The information about this dataset was compiled by the author:
  • Diana Lopez-Falcon
  • (see Partners)