Share of benefits with full means-testing
| Quick info | |
|---|---|
| Data type | Numeric |
| Scale | Metric |
| Value labels | Not Applicable |
| Technical name | health_ltc_gen_incl_full_means_share |
| Category | Health and long-term care |
| Label | Share of benefits with full means-testing |
| Related indicators | NA |
This indicator provides information on the share of long-term care benefits applying income-related and asset-related means-testing as an eligibility criterion. Means-testing as an eligibility conditionality refers to any control of the income or assets of the person in need of care or informal caregiver (potentially including household and/or family income) to determine eligibility. Income refers to a regular monetary payment received, such as a pension or income from employment. Assets refer to a financially valuable property such as money, land, buildings or bonds.
Coding rules
The indicator is calculated by counting the occurrences in single benefits of indicators on the eligibility criteria, focusing on income and assets testing, applied across all benefits in the country (regardless of whether it focused on caregivers or people in need), from which data were collected, and dividing the result by the total number of benefits identified. In this case, if both the means-testing criterion for assets and assets were applied, the benefit was included in the calculation. The minimum value of 0 indicates that no benefit in the country relies only on both income- and asset-related means-testing to define eligibility. The maximum value of 1 indicates that all benefits in the country rely on both income- and asset-related means-testing to determine eligibility. Benefits whose availability is known but for which no information on eligibility was available were not included in the calculation. Only benefits available based on legal regulations or valid sources were included in the calculation. Missing values coded in the following way: The code -888 is employed for countries which do not have a long-term care system (see Fischer, Sternkopf & Rothgang, 2023; de Carvalho & Fischer, 2020); these countries were excluded from data collection. The code -999 is employed for cases where information is missing. The code -777 is employed if a benefit type is not present in the country. Multiple data sources were employed and triangulated for constructing the indicator: national laws and regulations, academic publications and grey literature and websites such as report series from international organisations. The quality of each data point is rated by two quality ratings, plausibility and reliability assessment. Plausibility concerns are indicated if a) contradicting information was retrieved by stating “Yes, due to contradicting sources”; b) information was limited to single and/or unsound sources and values are thus uncertain stating “Yes, due to limited sources”. The reliability rating is based on two parameters: the type of sources and information triangulation between different sources. There are three levels of reliability as defined below:
- High reliability
- Information is contained in an official law or comparable legislative document in vigour during the analysed time-point. OR
- Information is consistent across at least three different sources, with two of them being either an independent, uncorrelated scientific publication (e.g., academic papers and chapters in books) and/or official government-related sources (e.g., ministry websites, government reports and bulletins).
- Medium reliability
- Information is consistent across at least three different sources, none of which is either a law, a scientific publication, or an official government-related source. OR
- Information is consistent across less than three different sources, with at least one of them being a scientific publication or an official government-related source.
- Low reliability
- Information is consistent across less than three different sources, none of which is either a law, a scientific publication, or an official government-related source.
The same ratings apply to the results of the calculation as follows. To reflect the impact that the data used, and their plausibility, have on the final result, plausibility concerns reflect the lowest quality rating among the data used in the calculation. That means that if at least one data presented some concerns due to contradicting or limited sources, this will be reflected in the plausibility assessment of the calculations. The same principle applies to reliability assessments for the result of calculations, that means that the lowest assessment among the data used for the calculation will be attributed to the results. Definitions and data collection procedures are outlined in detail in Viero & Fischer (2025).
Bibliographic info
Citation:- Viero, D., & Fischer, J. (2025). Comparative Assessment of Long-term Care System Generosity: Mapping Benefits and Inclusiveness Internationally. SOCIUM SFB 1342 WorkingPapers.
- Fischer, J., Sternkopf, M., & Rothgang, H. (2023). Covering a new social risk: The introduction of long-term care systems worldwide. In I. Mossig & H. Obinger (Eds.), SOCIUM SFB Working Papers: Vol. 25. Mapping Global Dynamics of Social Policy (pp. 32–35). Bremen: Collaborative Research Centre 1342. https://doi.org/10.26092/elib/2559
- De Carvalho, G., & Fischer, J. (2020). Health and long-term care system introduction and reform – concepts and operationalisations for global and historical comparative research. SFB 1342 Technical Paper Series, 3. https://doi.org/10.26092/ELIB/539
Misc
Project manager(s): Davide Viero and Johanna Fischer (on behalf of the A07 project)
- Version 0.001: Initial release.
Revisions: No revisions yet
Sources
- Please see Viero, D., & Fischer, J. (2025). Comparative Assessment of Long-term Care System Generosity: Mapping Benefits and Inclusiveness Internationally. SOCIUM SFB 1342 WorkingPapers.
