This table provides metadata for the actual indicator available from Turkey statistics closest to the corresponding global SDG indicator. Please note that even when the global SDG indicator is fully available from Turkey statistics, this table should be consulted for information on national methodology and other Turkey-specific metadata information.
| Target name | Adopt policies, especially fiscal, wage and social protection policies, and progressively achieve greater equality |
|---|---|
| Indicator name | Redistributive impact of fiscal policy |
| Global / Proxy indicator | Proxy indicator |
| Description of indicator |
a) Gini coefficient of disposable income, post taxes and transfers: Disposable income is used in the calculation of the Gini coefficient of disposable income, post taxes and transfers. Disposable income deducts from gross income the value of taxes on income and wealth paid and of contributions paid by households to public social security schemes b) Gini coefficient of market income, before taxes and transfers: Market income is used in the calculation of the Gini coefficient of market income, before taxes and transfers. Market income adds to primary income the value of employment-related social insurance transfers received by households. |
| Unit | Number |
| Available disaggregation | - |
| Calculation | - |
| Comparability | Comparable over time. Since it is a proxy indicator, it differs from global metadata in some way. |
| Revision | - |
| Other information | The Redistributive Impact of Fiscal Policy indicator is defined as the Gini coefficient of prefiscal per capita (or equivalized) income less the Gini coefficient of postfiscal per capita (or equivalized) income. Prefiscal income is defined as the cumulative income accruing to an individual (or a household) from market and private sources only. Postfiscal income is prefiscal income minus direct and indirect taxes plus transfers and indirect subsidies. For example, if the Redistributive Impact of Fiscal Policy is positive, that indicates that the net effect of Fiscal Policy is to reduce the Gini Coefficient, from what it otherwise would be without Fiscal Policy (in an accounting sense, not as an economic counterfactual). |
| Data source | OECD (TurkStat, Income and Living Conditions Survey) |
| Data source link | https://www.oecd.org/social/income-distribution-database.htm |
Income and Living Conditions Survey
| Sample coverage | The sampling frame is based on Address Based Population Register System and National Address Database which was established in 2007. From this linked system, clusters (blocks) involving approximately 100 dwelling addresses (between 80 and 120) are constructed and this blocked list is defined as the sampling frame of EU SILC survey. The register system is updated twice in the year. Addresses of the institutional population are not included in the sampling frame. |
|---|---|
| Sample size |
In the 2019 Income and Living Conditions Survey, a total of 26 732 households were visited. Of these households; A survey was conducted with 24 924 of them, and the remaining 1 808 households could not be surveyed for various reasons.
In the 2020 Income and Living Conditions Survey, a total of 27 437 households were visited. Of these households; A survey was conducted with 25 706 of them, and the remaining 1 731 households could not be surveyed for various reasons. In the 2021 Income and Living Conditions Survey, a total of 28 064 households were visited. Of these households; A survey was conducted with 26 289 of them, and the remaining 1 775 households could not be surveyed for various reasons. In the 2022 Income and Living Conditions Survey, a total of 27 918 households were visited. Of these households; A survey was conducted with 26 436 of them, and the remaining 1 482 households could not be surveyed for various reasons. In the 2023 Income and Living Conditions Survey, a total of 27 825 households were visited. Of these households; A survey was conducted with 24 932 of them, and the remaining 2 893 households could not be surveyed for various reasons. |
| Interview method |
Computer asisted personal interview (CAPI) method is applied in 2019. Telephone asisted personal interview (CATI) method is applied in 2020. Computer asisted personal interview (CAPI) method is applied in 2021. Computer asisted personal interview (CAPI) method is applied in 2022. Computer asisted personal interview (CAPI) method is applied in 2023. |
| Reference period for application of survey |
The reference period for income information is "the previous calendar year". So, the income information in the 2019 application is for 2018.
|
| Field survey time and duration | March - July period of the related year |