WeSISpedia - User contributions [en]

Immigrant social rights

2026-08-18T14:51:25Z

Nils Duepont: Undo revision 13204 by Nils Duepont (talk)

{|class="wikitable sortable" border="1"
! Indicator name*
! Subcategory I
! Subcategory II
! Subcategory III
! Technical name*
! Scale*
! Short description
! Data origin*
|-
| | [[Access to social assistance for permanent residents]] || Direct restriction || Social assistance || Permanent residents || isr_permmig_socass_access_s || Metric || Measures if in the years of data collection, migrant workers who held a permanent residence permit had a legal claim to tax-funded social assistance || Original CRC Data
|-
| | [[Access to social assistance for temporary migrant workers]] || Direct restriction || Social assistance || Temporary migrant workers || isr_tempmig_socass_access_s || Metric || Measures if in the years of data collection, migrant workers who held a temporary residence permit had a legal claim to tax-funded social assistance || Original CRC Data
|-
| | [[Access to social assistance for recognized refugees]] || Direct restriction || Social assistance || Recognized refugees || isr_recoref_socass_access_s || Metric || Measures if in the years of data collection, recognized refugees had a legal claim to tax-funded social assistance || Original CRC Data
|-
| | [[Access to social assistance for asylum seekers]] || Direct restriction || Social assistance || Asylum seekers || isr_asylsee_socass_access_s || Metric || Measures if in the years of data collection, asylum seekers had a legal claim to tax-funded social assistance || Original CRC Data
|-
| | [[Unemployment insurance benefits for permanent residents]] || Direct restriction || Unemployment insurance benefits || Permanent residents || isr_permmig_uneins_access_s || Metric || Measures if in the years of data collection, permanent residents had a legal claim to contribution-based unemployment insurance benefits || Original CRC Data
|-
| | [[Unemployment insurance benefits for temporary migrant workers]] || Direct restriction || Unemployment insurance benefits || Temporary migrant workers || isr_tempmig_uneins_access_s || Metric || Measures if in the years of data collection, temporary migrant workers had a legal claim to contribution-based unemployment insurance benefits || Original CRC Data
|-
| | [[Consequences of social-welfare reliance for family reunification for citizens]] || Indirect restriction || Consequences of social-welfare reliance for family reunification || Citizens || isr_famicit_socben_conseq_s || Metric || Measures if sponsors who were citizens were required not to rely on social welfare for family reunification || Original CRC Data
|-
| | [[Consequences of social-welfare reliance for family reunification for third-country nationals]] || Indirect restriction || Consequences of social-welfare reliance for family reunification || Third-country nationals || isr_famitcn_socben_conseq_s || Metric || Measures if sponsors who were third-country nationals were required not to rely on social welfare for family reunification || Original CRC Data
|-
| | [[Income criterion for family reunification for citizens]] || Indirect restriction || Income requirement for family reunification || Citizens || isr_famicit_socben_prevme_s || Metric || Measures whether citizen sponsors had to meet an income or funds requirement for family reunification || Original CRC Data
|-
| | [[Income criterion for family reunification for third-country nationals]] || Indirect restriction || Income requirement for family reunification || Third-country nationals || isr_famitcn_socben_prevme_s || Metric || Measures whether third-country national sponsors had to meet an income or funds requirement for family reunification || Original CRC Data
|-
| | [[Consequences for dependence on social assistance for permanent residents]] || Indirect restriction || Consequences of dependency on social assistance || Permanent residents|| isr_permmig_socass_conseq_s || Metric || Measures whether reliance on social assistance led to consequences for the residence status of permanent residents || Original CRC Data
|-
| | [[Consequences for dependence on social assistance for temporary migrant workers]] || Indirect restriction || Consequences of dependency on social assistance || Temporary migrant workers || isr_tempmig_socass_conseq_s || Metric || Measures whether reliance on social assistance led to consequences for the residence status of temporary migrant workers || Original CRC Data
|-
| | [[Benefits for asylum seekers]] || Direct restriction || Benefits for asylum seekers || Asylum seekers || isr_asylsee_typben_access_s || Metric || Measures in what form (if at all) asylum seekers received support (cash or in kind) || Original CRC Data
|-
| | [[Consequences of loss of employment (perm_1) ]] || Indirect restriction || Consequences of loss of employment || Permanent entry tracks|| Isr_permmig1_socben_prevme_s || Metric || Measures whether loss of employment has consequences for a migrant worker’s residence permit || Original CRC Data
|-
| | [[Consequences of loss of employment (perm_1_name) ]] || Indirect restriction || Consequences of loss of employment || Permanent entry tracks|| Isr_permmig1_socben_prevme_name || String || Indicates the respective name of the entry track for which the consequence is measured|| Original CRC Data
|-
| | [[Consequences of loss of employment (perm_2)]] || Indirect restriction || Consequences of loss of employment || Permanent entry tracks|| Isr_permmig2_socben_prevme_s || Metric || Measures whether loss of employment has consequences for a migrant worker’s residence permit || Original CRC Data
|-
| | [[Consequences of loss of employment (perm_2_name)]] || Indirect restriction || Consequences of loss of employment || Permanent entry tracks|| Isr_permmig2_socben_prevme_name || String|| Indicates the respective name of the entry track for which the consequence is measured|| Original CRC Data
|-
| | [[Consequences of loss of employment (temp_1) ]] || Indirect restriction || Consequences of loss of employment || Temporary entry tracks|| Isr_tempmig1_socben_prevme_s || Metric || Measures whether loss of employment has consequences for a migrant worker’s residence permit || Original CRC Data
|-
| | [[Consequences of loss of employment (temp_1_name) ]] || Indirect restriction || Consequences of loss of employment || Temporary entry tracks|| Isr_tempmig1_socben_prevme_name || String || Indicates the respective name of the entry track for which the consequence is measured|| Original CRC Data
|-
| | [[Consequences of loss of employment (temp_2) ]] || Indirect restriction || Consequences of loss of employment || Temporary entry tracks|| Isr_tempmig2_socben_prevme_s || Metric || Measures whether loss of employment has consequences for a migrant worker’s residence permit || Original CRC Data
|-
| | [[Consequences of loss of employment (temp_2_name) ]] ||Indirect restriction || Consequences of loss of employment || Temporary entry tracks|| Isr_tempmig2_socben_prevme_name || String || Indicates the respective name of the entry track for which the consequence is measured|| Original CRC Data
|-
| | [[Consequences of loss of employment (temp_3) ]] || Indirect restriction || Consequences of loss of employment || Temporary entry tracks|| Isr_tempmig3_socben_prevme_s || Metric || Measures whether loss of employment has consequences for a migrant worker’s residence permit || Original CRC Data
|-
| | [[Consequences of loss of employment (temp_3_name) ]] || Indirect restriction || Consequences of loss of employment || Temporary entry tracks|| Isr_tempmig3_socben_prevme_name || String || Indicates the respective name of the entry track for which the consequence is measured|| Original CRC Data
|-
| | [[Consequences of loss of employment (temp_4) ]] || Indirect restriction || Consequences of loss of employment || Temporary entry tracks|| Isr_tempmig4_socben_prevme_s || Metric || Measures whether loss of employment has consequences for a migrant worker’s residence permit || Original CRC Data
|-
| | [[Consequences of loss of employment (temp_4_name) ]] || Indirect restriction || Consequences of loss of employment || Temporary entry tracks|| Isr_tempmig4_socben_prevme_name || String || Indicates the respective name of the entry track for which the consequence is measured|| Original CRC Data
|-
| | [[Consequences of loss of employment (temp_5) ]] || Indirect restriction || Consequences of loss of employment || Temporary entry tracks|| Isr_tempmig5_socben_prevme_s || Metric || Measures whether loss of employment has consequences for a migrant worker’s residence permit || Original CRC Data
|-
| | [[Consequences of loss of employment (temp_5_name) ]] || Indirect restriction || Consequences of loss of employment || Temporary entry tracks|| Isr_tempmig5_socben_prevme_name || String || Indicates the respective name of the entry track for which the consequence is measured|| Original CRC Data
|-
| | [[Consequences of loss of employment (temp_6) ]] || Indirect restriction || Consequences of loss of employment || Temporary entry tracks|| Isr_tempmig6_socben_prevme_s || Metric || Measures whether loss of employment has consequences for a migrant worker’s residence permit || Original CRC Data
|-
| | [[Consequences of loss of employment (temp_6_name) ]] || Indirect restriction || Consequences of loss of employment || Temporary entry tracks|| Isr_tempmig6_socben_prevme_name || String || Indicates the respective name of the entry track for which the consequence is measured|| Original CRC Data
|-
| | [[Consequences of loss of employment (seas_1) ]] || Indirect restriction || Consequences of loss of employment || Seasonal entry tracks|| Isr_seasmig1_socben_prevme_s || Metric || Measures whether loss of employment has consequences for a migrant worker’s residence permit || Original CRC Data
|-
| | [[Consequences of loss of employment (seas_1_name) ]] || Indirect restriction || Consequences of loss of employment || Seasonal entry tracks|| Isr_seasmig1_socben_prevme_name || String || Indicates the respective name of the entry track for which the consequence is measured|| Original CRC Data
|-
| | [[Consequences of loss of employment (seas_2) ]] || Indirect restriction || Consequences of loss of employment || Seasonal entry tracks|| Isr_seasmig2_socben_prevme_s || Metric || Measures whether loss of employment has consequences for a migrant worker’s residence permit || Original CRC Data
|-
| | [[Consequences of loss of employment (seas_2_name) ]] || Indirect restriction || Consequences of loss of employment || Seasonal entry tracks|| Isr_seasmig2_socben_prevme_name || String || Indicates the respective name of the entry track for which the consequence is measured|| Original CRC Data
|-
| | [[Consequences of loss of employment (EU Blue Card) ]] || Indirect restriction || Consequences of loss of employment || EU Blue Card Holders|| Isr_EUblue_socben_prevme_s || Metric || Measures whether loss of employment has consequences for a migrant worker’s residence permit || Original CRC Data
|-
| | [[Consequences of loss of employment (EU Blue Card_name) ]] || Indirect restriction || Consequences of loss of employment || EU Blue Card Holders|| Isr_EUblue_socben_prevme_name || String || Indicates the respective name of the entry track for which the consequence is measured|| Original CRC Data
|-
|}

Immigrant social rights

2026-08-18T14:28:46Z

Nils Duepont: Test indicators added again for testing the master branch on the new server, i.e. prod.wesis.org

Food waste per capita (kg)

2026-07-06T09:26:15Z

Nils Duepont:

{{IndicatorForm
|datatype = Numeric
|scale = Metric
|valuelabels = Not applicable
|techname = sdg_12_31a_food_was_capi
|category= Sustainable development goals|Sustainable development goals
|label = Food waste per capita (kg)
|relatedindicators = Not applicable
|description = This indicator measures the food waste per capita in kg. It is part of monitoring the achievement and progress towards the UN Sustainable Development Goals.
|codingrules =
<ul>
<li>For detailed information and coding rules see https://unstats.un.org/wiki/spaces/SDGeHandbook/pages/34505092/Home.</li>
</ul>
|citation = United Nations Department of Economic and Social Affairs. 2024. ''SDG Indicators Database''. https://unstats.un.org/sdgs/dataportal/database.
|relatedpublications =
<ul>
<li>United Nations Department of Economic and Social Affairs. 2025. ''The Sustainable Development Goals Report 2025''. New York: United Nations Publications. https://unstats.un.org/sdgs/report/2025/.</li>
</ul>
|projectmanagers = Marius Bode, Hannes Salzmann, Carmen Cordes, Nils Düpont (INF)
|datarelease =
<ul>
<li>Version 0.001: Initial release</li>
</ul>
|revisions = No revisions yet
|sources =
<ul>
<li>United Nations Department of Economic and Social Affairs. 2024. ''SDG Indicators Database''. https://unstats.un.org/sdgs/dataportal/database.</li>
<li>United Nations Department of Economic and Social Affairs. 2026. ''SDG Indicators Database''. https://unstats.un.org/sdgs/dataportal/database.</li>
</ul>
}}

Sustainable development goals

2026-07-06T09:24:25Z

Nils Duepont:

{|class="wikitable sortable" border="1"
|-
! Indicator name*
! Subcategory I
! Subcategory II
! Technical name*
! Scale*
! Short description
! Data origin*
|-
|[[Proportion of population below international poverty line, bothsex]]
|Goal 01: No poverty
|Target 1: Eradicate extreme poverty
|sdg_01_11a_prop_pop_below_int_povline_bothsex
|Metric
|A measure of the proportion of the population living below the international poverty line in percent
|3rd Party Data
|-
|[[Proportion of population below international poverty line, female]]
|Goal 01: No poverty
|Target 1: Eradicate extreme poverty
|sdg_01_11a_prop_pop_below_int_povline_female
|Metric
|A measure of the proportion of the female population living below the international poverty line in percent
|3rd Party Data
|-
|[[Proportion of population below international poverty line, male]]
|Goal 01: No poverty
|Target 1: Eradicate extreme poverty
|sdg_01_11a_prop_pop_below_int_povline_male
|Metric
|A measure of the proportion of the male population living below the international poverty line in percent
|3rd Party Data
|-
|[[Proportion of population living below the national poverty line]]
|Goal 01: No poverty
|Target 2: Reduce poverty by at least 50%
|sdg_01_21_prop_pop_below_nat_povline
|Metric
|A measure of the proportion of the population living below the national poverty line in percent
|3rd Party Data
|-
|[[Proportion of population living in multidimensional poverty, bothsex]]
|Goal 01: No poverty
|Target 2: Reduce poverty by at least 50%
|sdg_01_22a_prop_pop_in_multidim_pov_bothsex
|Metric
|A measure of the proportion of the population living in multidimensional poverty in percent
|3rd Party Data
|-
|[[Proportion of population living in multidimensional poverty, female]]
|Goal 01: No poverty
|Target 2: Reduce poverty by at least 50%
|sdg_01_22a_prop_pop_in_multidim_pov_female
|Metric
|A measure of the proportion of the female population living in multidimensional poverty in percent
|3rd Party Data
|-
|[[Proportion of population living in multidimensional poverty, male]]
|Goal 01: No poverty
|Target 2: Reduce poverty by at least 50%
|sdg_01_22a_prop_pop_in_multidim_pov_male
|Metric
|A measure of the proportion of the male population living in multidimensional poverty in percent
|3rd Party Data
|-
|[[ILO Proportion of mothers with newborns receiving maternity cash benefit]]
|Goal 01: No poverty
|Target 3: Implement nationally appropriate social protection systems
|sdg_01_31a_prop_moth_newb_mat_cash
|Metric
|A measure of the proportion of mothers with newborns receiving maternity cash benefit in percent
|3rd Party Data
|-
|[[World Bank Proportion of population covered by social assistance programs]]
|Goal 01: No poverty
|Target 3: Implement nationally appropriate social protection systems
|sdg_01_31c_prop_pop_soc_asst_pro
|Metric
|A measure of the proportion of the population covered by social assistance programs in percent
|3rd Party Data
|-
|[[ILO Proportion of unemployed persons receiving unemployment cash benefit, bothsex]]
|Goal 01: No poverty
|Target 3: Implement nationally appropriate social protection systems
|sdg_01_31f_prop_unemp_rec_cash_bothsex
|Metric
|A measure of the proportion of the unemployed persons receiving unemployment cash benefit in percent
|3rd Party Data
|-
|[[ILO Proportion of unemployed persons receiving unemployment cash benefit, female]]
|Goal 01: No poverty
|Target 3: Implement nationally appropriate social protection systems
|sdg_01_31f_prop_unemp_rec_cash_female
|Metric
|A measure of the proportion of the unemployed female persons receiving unemployment cash benefit in percent
|3rd Party Data
|-
|[[ILO Proportion of unemployed persons receiving unemployment cash benefit, male]]
|Goal 01: No poverty
|Target 3: Implement nationally appropriate social protection systems
|sdg_01_31f_prop_unemp_rec_cash_male
|Metric
|A measure of the proportion of the unemployed male persons receiving unemployment cash benefit in percent
|3rd Party Data
|-
|[[Proportion of population using basic drinking water services, by location]]
|Goal 01: No poverty
|Target 4: Equal rights to ownership, basic services, technology, and economic resources
|sdg_01_41a_prop_pop_bas_dri_wat
|Metric
|A measure of the proportion of the population using basic drinking water services in percent
|3rd Party Data
|-
|[[Proportion of total government spending on essential services, health]]
|Goal 01: No poverty
|Target a: Mobilization of resources to end poverty
|sdg_01_a2b_prop_tot_gov_spend_ess_serv_heal
|Metric
|A measure of the proportion of the total government spending on essential services (health) in percent
|3rd Party Data
|-
|[[Proportion of total government spending on essential services, social protection]]
|Goal 01: No poverty
|Target a: Mobilization of resources to end poverty
|sdg_01_a2c_prop_tot_gov_spend_ess_serv_soc_prot
|Metric
|A measure of the proportion of the total government spending on essential services (social protection) in percent
|3rd Party Data
|-
|[[Prevalence of undernourishment]]
|Goal 02: Zero hunger
|Target 1: Universal access to safe and nutritious food
|sdg_02_11a_prev_undernou
|Metric
|A measure of the proportion of the prevalence of undernourishment in percent
|3rd Party Data
|-
|[[Proportion of children moderately or severely stunted]]
|Goal 02: Zero hunger
|Target 2: End all forms of malnutrition
|sdg_02_21a_prop_ch_mod_sev_stun
|Metric
|A measure of the proportion of the children moderately or severely stunted in percent
|3rd Party Data
|-
|[[Proportion of children moderately or severely wasted]]
|Goal 02: Zero hunger
|Target 2: End all forms of malnutrition
|sdg_02_22a_prop_ch_mod_sev_wast
|Metric
|A measure of the proportion of the children moderately or severely wasted in percent
|3rd Party Data
|-
|[[Productivity of large-scale food producers (agricultural output per labour day, PPP) (constant 2017 international $)]]
|Goal 02: Zero hunger
|Target 3: Double the productivity and incomes of small-scale food producers
|sdg_02_31b_prod_lar_food_produ_bothsex
|Metric
|A measure of the productivity of large-scale food producers in constant 2017 international $
|3rd Party Data
|-
|[[Proportion of local breeds classified as being at risk of extinction as a share of local breeds with known level of extinction risk]]
|Goal 02: Zero hunger
|Target 5: Maintain the genetic diversity in food production
|sdg_02_52b_prop_loc_bre_class_risk_exti_sha_loc_bre_know_lvl_exti_risk
|Metric
|A measure of the proportion of local breeds classified as being at risk of extinction as a share of local breeds with known level of extinction risk in percent
|3rd Party Data
|-
|[[Agriculture orientation index for government expenditures]]
|Goal 02: Zero hunger
|Target a: Invest in rural infrastructure, agricultural research, technology and gene banks
|sdg_02_a1a_agricul_ori_index_gov_expen
|Metric
|A measure of the agriculture orientation index for government expenditures
|3rd Party Data
|-
|[[Agricultural export subsidies (millions of current USD)]]
|Goal 02: Zero hunger
|Target b: Prevent agricultural trade restrictions, market distortions and export subsidies
|sdg_02_b1_agricul_exp_subsi
|Metric
|A measure of the agricultural export subsidies in millions of current USD
|3rd Party Data
|-
|[[Maternal mortality ratio]]
|Goal 03: Good health and well-being
|Target 1: Reduce maternal mortality
|sdg_03_11_mat_mor_ratio_female
|Metric
|A measure of the maternal mortality ratio in deaths per 1,000 live births
|3rd Party Data
|-
|[[Under-five mortality rate, bothsex (deaths per 1,000 live births)]]
|Goal 03: Good health and well-being
|Target 2: End all preventable deaths under five years of age
|sdg_03_21b_ufive_mor_rate_bothsex
|Metric
|A measure of the under-five mortality ratio (bothsex) in deaths per 1,000 live births
|3rd Party Data
|-
|[[Under-five mortality rate, female (deaths per 1,000 live births)]]
|Goal 03: Good health and well-being
|Target 2: End all preventable deaths under five years of age
|sdg_03_21b_ufive_mor_rate_female
|Metric
|A measure of the under-five mortality ratio (female) in deaths per 1,000 live births
|3rd Party Data
|-
|[[Under-five mortality rate, male (deaths per 1,000 live births)]]
|Goal 03: Good health and well-being
|Target 2: End all preventable deaths under five years of age
|sdg_03_21b_ufive_mor_rate_male
|Metric
|A measure of the under-five mortality ratio (male) in deaths per 1,000 live births
|3rd Party Data
|-
|[[Infant mortality rate (deaths per 1,000 live births)]]
|Goal 03: Good health and well-being
|Target 2: End all preventable deaths under five years of age
|sdg_03_21c_inf_mor_rate_bothsex
|Metric
|A measure of the infant mortality ratio (bothsex) in deaths per 1,000 live births
|3rd Party Data
|-
|[[Infant mortality rate, female (deaths per 1,000 live births)]]
|Goal 03: Good health and well-being
|Target 2: End all preventable deaths under five years of age
|sdg_03_21c_inf_mor_rate_female
|Metric
|A measure of the infant mortality ratio (female) in deaths per 1,000 live births
|3rd Party Data
|-
|[[Infant mortality rate, male (deaths per 1,000 live births)]]
|Goal 03: Good health and well-being
|Target 2: End all preventable deaths under five years of age
|sdg_03_21c_inf_mor_rate_male
|Metric
|A measure of the infant mortality ratio (male) in deaths per 1,000 live births
|3rd Party Data
|-
|[[Neonatal mortality rate (deaths per 1,000 live births)]]
|Goal 03: Good health and well-being
|Target 2: End all preventable deaths under five years of age
|sdg_03_22b_neona_mor_rate_bothsex
|Metric
|A measure of the neonatal mortality ratio in deaths per 1,000 live births
|3rd Party Data
|-
|[[Tuberculosis incidence (per 100,000 population)]]
|Goal 03: Good health and well-being
|Target 3: Fight communicable diseases
|sdg_03_32_tub_inci
|Metric
|A measure of the tuberculosis incidence per 100,000 population
|3rd Party Data
|-
|[[Mortality rate attributed to cardiovascular disease, cancer, diabetes or chronic respiratory disease (probability), bothsex]]
|Goal 03: Good health and well-being
|Target 4: Reduce mortality from non-communicable diseases and promote mental health
|sdg_03_41a_mor_rate_att_card_dis_can_dia_chr_dis_bothsex
|Metric
|A measure of the mortality rate (bothsex) attributed to cardiovascular disease, cancer, diabetes or chronic respiratory disease in percent
|3rd Party Data
|-
|[[Mortality rate attributed to cardiovascular disease, cancer, diabetes or chronic respiratory disease (probability), female]]
|Goal 03: Good health and well-being
|Target 4: Reduce mortality from non-communicable diseases and promote mental health
|sdg_03_41a_mor_rate_att_card_dis_can_dia_chr_dis_female
|Metric
|A measure of the mortality rate (female) attributed to cardiovascular disease, cancer, diabetes or chronic respiratory disease in percent
|3rd Party Data
|-
|[[Mortality rate attributed to cardiovascular disease, cancer, diabetes or chronic respiratory disease (probability), male]]
|Goal 03: Good health and well-being
|Target 4: Reduce mortality from non-communicable diseases and promote mental health
|sdg_03_41a_mor_rate_att_card_dis_can_dia_chr_dis_male
|Metric
|A measure of the mortality rate (male) attributed to cardiovascular disease, cancer, diabetes or chronic respiratory disease in percent
|3rd Party Data
|-
|[[Suicide mortality rate, bothsex (deaths per 100,000 population)]]
|Goal 03: Good health and well-being
|Target 4: Reduce mortality from non-communicable diseases and promote mental health
|sdg_03_42a_sui_mor_rate_bothsex
|Metric
|A measure of the suicide mortality rate (bothsex) in deaths per 100,000 population
|3rd Party Data
|-
|[[Suicide mortality rate, female (deaths per 100,000 population)]]
|Goal 03: Good health and well-being
|Target 4: Reduce mortality from non-communicable diseases and promote mental health
|sdg_03_42a_sui_mor_rate_female
|Metric
|A measure of the suicide female mortality rate in deaths per 100,000 population
|3rd Party Data
|-
|[[Suicide mortality rate, male (deaths per 100,000 population)]]
|Goal 03: Good health and well-being
|Target 4: Reduce mortality from non-communicable diseases and promote mental health
|sdg_03_42a_sui_mor_rate_male
|Metric
|A measure of the suicide male mortality rate in deaths per 100,000 population
|3rd Party Data
|-
|[[Proportion of women of reproductive age (aged 15-49 years) who have their need for family planning satisfied with modern methods ( of women aged 15-49 years)]]
|Goal 03: Good health and well-being
|Taget 7: Universal access to sexual and reproductive care, family planning and education
|sdg_03_71_prop_wom_repro_age_need_fam_plan_sat_mod_meth_female
|Metric
|A measure of the proportion of women of reproductive age (aged 15-49 years) who have their need for family planning satisfied with modern methods in percent
|3rd Party Data
|-
|[[Universal health coverage (UHC) service coverage index]]
|Goal 03: Good health and well-being
|Target 8: Achieve universal health coverage
|sdg_03_81_uni_heal_cov_serv_cov_index
|Metric
|A measure of the universal health coverage service coverage (index)
|3rd Party Data
|-
|[[Proportion of population with large household expenditures on health (greater than 25) as a share of total household expenditure or income]]
|Goal 03: Good health and well-being
|Target 8: Achieve universal health coverage
|sdg_03_82a_prop_pop_lar_hh_expen_heal_grtwenfive_sha_tot_hh_expen_inco
|Metric
|A measure of the proportion of population with large household expenditures on health (greater than 25%) as a share of total household expenditure or income in percent
|3rd Party Data
|-
|[[Age-standardized mortality rate attributed to household air pollution (deaths per 100,000 population)]]
|Goal 03: Good health and well-being
|Target 9: Reduce illnesses and deaths from hazardous chemicals and pollution
|sdg_03_91b_agestand_mor_rate_att_hh_amb_air_poll
|Metric
|A measure of the age-standardized mortality rate attributed to household air pollution in deaths per 100,000 population
|3rd Party Data
|-
|[[Total official development assistance to medical research and basic health sectors, net disbursement, by recipient countries (millions of constant 2022 USD)]]
|Goal 03: Good health and well-being
|Target b: Support research, development and universal access to affordable vaccines and medicines
|sdg_03_b2a_tot_off_dev_ass_med_res_bas_heal_net_dis_rec_coun
|Metric
|A measure of the total official development assistance to medical research and basic health sectors in millions of constant 2022 USD
|3rd Party Data
|-
|[[Proportion of children aged 36-59 months who are developmentally on track in at least three of the following domains: literacy-numeracy, physical development, social-emotional development, and learning ( of children aged 36-59 months), bothsex]]
|Goal 04: Quality education
|Target 2: Equal access to quality pre-primary education
|sdg_04_21_prop_ch_dev_on_track_bothsex
|Metric
|A measure of the proportion of children aged 36-59 months (bothsex) who are developmentally on track in at least three of the following domains: literacy-numeracy, physical development, social-emotional development, and learning in percent
|3rd Party Data
|-
|[[Proportion of children aged 36-59 months who are developmentally on track in at least three of the following domains: literacy-numeracy, physical development, social-emotional development, and learning ( of children aged 36-59 months), female]]
|Goal 04: Quality education
|Target 2: Equal access to quality pre-primary education
|sdg_04_21_prop_ch_dev_on_track_female
|Metric
|A measure of the proportion of female children aged 36-59 months who are developmentally on track in at least three of the following domains: literacy-numeracy, physical development, social-emotional development, and learning in percent
|3rd Party Data
|-
|[[Proportion of children aged 36-59 months who are developmentally on track in at least three of the following domains: literacy-numeracy, physical development, social-emotional development, and learning ( of children aged 36-59 months), male]]
|Goal 04: Quality education
|Target 2: Equal access to quality pre-primary education
|sdg_04_21_prop_ch_dev_on_track_male
|Metric
|A measure of the proportion of male children aged 36-59 months who are developmentally on track in at least three of the following domains: literacy-numeracy, physical development, social-emotional development, and learning in percent
|3rd Party Data
|-
|[[Adjusted gender parity index for participation rate in organized learning (one year before the official primary entry age), (ratio)]]
|Goal 04: Quality education
|Target 5: Eliminate all discrimination in education
|sdg_04_51a_adju_gen_par_index_part_rate_org_lear
|Metric
|A measure of the adjusted gender parity index for participation rate in organized learning (one year before the official primary entry age) as a ratio percent
|3rd Party Data
|-
|[[Total official flows for scholarships, by recipient countries (millions of constant 2022 USD)]]
|Goal 04: Quality education
|Target b: Expand higher education scholarships for developing countries
|sdg_04_b1_tot_off_flow_schoshi_rec_coun
|Metric
|A measure of the total official flows for scholarships in millions of constant 2022 USD
|3rd Party Data
|-
|[[Proportion of ever-partnered women and girls subjected to physical and/or sexual violence by a current or former intimate partner in the previous 12 months, by age]]
|Goal 05: Gender equality
|Target 2: End all violence against and exploitation of women and girls
|sdg_05_21_prop_evpat_wom_gi_sub_phy_sexu_vio_part_female
|Metric
|A measure of the proportion of ever-partnered women and girls subjected to physical and/or sexual violence by a current or former intimate partner in the previous 12 months in percent
|3rd Party Data
|-
|[[Proportion of seats held by women in national parliaments ( of total number of seats)]]
|Goal 05: Gender equality
|Target 5: Ensure full participation in leadership and decision-making
|sdg_05_51c_prop_seat_wom_nat_parli_female
|Metric
|A measure of the proportion of seats held by women in national parliaments in percent of total number of seats
|3rd Party Data
|-
|[[Proportion of population using safely managed drinking water services, by urban/rural]]
|Goal 06: Clean water and sanitation
|Target 1: Safe and affordable drinking water
|sdg_06_11_prop_pop_safe_mana_dri_wat_serv
|Metric
|A measure of the proportion of population using safely managed drinking water services in percent
|3rd Party Data
|-
|[[Proportion of population using safely managed sanitation services, by urban/rural]]
|Goal 06: Clean water and sanitation
|Target 2: End open defecation and provide access to sanitation and hygiene
|sdg_06_21b_prop_pop_safe_mana_san_serv
|Metric
|A measure of the proportion of population using safely managed sanitation service in percent
|3rd Party Data
|-
|[[Water Use Efficiency (United States dollars per cubic meter)]]
|Goal 06: Clean water and sanitation
|Target 4: Increase water-use efficiency and ensure freshwater supplies
|sdg_06_41_wat_use_eff
|Metric
|A measure of the water use efficiency in USD per cubic meter
|3rd Party Data
|-
|[[Level of water stress: freshwater withdrawal as a proportion of available freshwater resources]]
|Goal 06: Clean water and sanitation
|Target 4: Increase water-use efficiency and ensure freshwater supplies
|sdg_06_42_lvl_wat_str_frewat_wdra_prop_ava_frewat_res
|Metric
|A measure of the level of water stress: freshwater withdrawal as a proportion of available freshwater resource in percent
|3rd Party Data
|-
|[[Proportion of transboundary basins (river and lake basins and aquifers) with an operational arrangement for water cooperation]]
|Goal 06: Clean water and sanitation
|Target 5: Implement IWRM
|sdg_06_52a_prop_trabou_bas_oper_arr_wat_coop
|Metric
|A measure of the proportion of transboundary basins (river and lake basins and aquifers) with an operational arrangement for water cooperation in percent
|3rd Party Data
|-
|[[Total official development assistance (gross disbursement) for water supply and sanitation, by recipient countries (millions of constant 2022 USD)]]
|Goal 06: Clean water and sanitation
|Target a: Expand water and sanitation support to developing countries
|sdg_06_a1_tot_off_dev_ass_wat_sup_san
|Metric
|A measure of the total official development assistance (gross disbursement) for water supply and sanitation in millions of constant 2022 USD
|3rd Party Data.
|-
|[[Proportion of population with access to electricity, by urban/rural]]
|Goal 07: Affordable and clean energy
|Target 1: Universal access to modern energy
|sdg_07_11_prop_pop_acc_elec
|Metric
|A measure of the proportion of population with access to electricity in percent
|3rd Party Data
|-
|[[Renewable energy share in the total final energy consumption]]
|Goal 07: Affordable and clean energy
|Target 2: Increase global percentage of renewable energy
|sdg_07_21b_renew_ene_sha_tot_fin_ene_consu
|Metric
|A measure of the renewable energy share in the total final energy consumption in percent
|3rd Party Data
|-
|[[International financial flows to developing countries in support of clean energy research and development and renewable energy production, including in hybrid systems (millions of constant 2021 USD)]]
|Goal 07: Affordable and clean energy
|Target a: Promote access to research, technology and investments in clean energy
|sdg_07_a1_int_fin_flow_dev_coun_sup_clea_ene_res_dev_renew_ene_pro
|Metric
|A measure of the international financial flows to developing countries in support of clean energy research and development and renewable energy production, including in hybrid systems in millions of constant 2021 USD
|3rd Party Data
|-
|[[Annual growth rate of real GDP per capita]]
|Goal 08: Decent work and economic growth
|Target 1: Sustainable economic growth
|sdg_08_11_annu_grow_rate_real_gdp_capi
|Metric
|A measure of the annual growth rate of real GDP per capita in percent
|3rd Party Data
|-
|[[Annual growth rate of real GDP per employed person]]
|Goal 08: Decent work and economic growth
|Target 2: Diversify, innovate and upgrade for economic productivity
|sdg_08_21_annu_grow_rate_real_gdp_empl_per
|Metric
|A measure of the annual growth rate of real GDP per employed person in percent
|3rd Party Data
|-
|[[Unemployment rate, by sex and age - 19th ICLS]]
|Goal 08: Decent work and economic growth
|Target 5: Full employment and decent work with equal pay
|sdg_08_52c_unempl_rate_sex_age_nineteen_bothsex
|Metric
|A measure of the unemployment rate in percent.
|3rd Party Data
|-
|[[Level of national compliance with labour rights (freedom of association and collective bargaining) based on International Labour Organization (ILO) textual sources and national legislation]]
|Goal 08: Decent work and economic growth
|Target 8: Protect labour rights and promote safe working environments
|sdg_08_82_lvl_nat_compl_lab_righ_bas_ilo
|Metric
|A measure of the level of national compliance with labour rights (freedom of association and collective bargaining) based on International Labour Organization (ILO) textual sources and national legislation
|3rd Party Data
|-
|[[Number of automated teller machines (ATMs) per 100,000 adults]]
|Goal 08: Decent work and economic growth
|Target 10: Universal access to banking, insurance and financial services
|sdg_08_101a_num_atm
|Metric
|A measure of the number of automated teller machines (ATMs) per 100,000 adults
|3rd Party Data
|-
|[[Total official flows (commitments) for Aid for Trade, by donor countries (millions of constant 2022 USD)]]
|Goal 08: Decent work and economic growth
|Target a: Increase aid for trade support
|sdg_08_a1a_tot_off_flow_comm_aid_tra_don_coun
|Metric
|A measure of the total official flows (commitments) for Aid for Trade, by donor countries in millions of constant 2022 USD
|3rd Party Data
|-
|[[Total official flows (commitments) for Aid for Trade, by recipient countries (millions of constant 2022 USD)]]
|Goal 08: Decent work and economic growth
|Target a: Increase aid for trade support
|sdg_08_a1d_tot_off_flow_comm_aid_tra_rec_coun
|Metric
|A measure of the total official flows (commitments) for Aid for Trade, by recipient countries in millions of constant 2022 USD
|3rd Party Data
|-
|[[Manufacturing value added per capita (constant 2015 USD)]]
|Goal 09: Industry, innovation, technology and infrastructure
|Target 2: Promote inclusive and sustainable industrialization
|sdg_09_21a_manu_val_add_capi
|Metric
|A measure of the manufacturing value added per capita in constant 2015 USD
|3rd Party Data
|-
|[[Manufacturing employment as a proportion of total employment - 19th ICLS]]
|Goal 09: Industry, innovation, technology and infrastructure
|Target 2: Promote inclusive and sustainable industrialization
|sdg_09_22b_manu_empl_prop_tot_empl_nineteen
|Metric
|A measure of the manufacturing employment as a proportion of total employment in percent
|3rd Party Data
|-
|[[Proportion of small-scale manufacturing industries in total manufacturing value added]]
|Goal 09: Industry, innovation, technology and infrastructure
|Target 3: Increase access to financial services and markets
|sdg_09_31_prop_smasca_manu_ind_tot_manu_val_add
|Metric
|A measure of the proportion of small-scale manufacturing industries in total manufacturing value added in percent
|3rd Party Data
|-
|[[Carbon dioxide emissions from fuel combustion (millions of tonnes)]]
|Goal 09: Industry, innovation, technology and infrastructure
|Target 4: Upgrade all industries and infrastructures for sustainability
|sdg_09_41a_car_dio_emi_fuel_comb
|Metric
|A measure of the carbon dioxide emissions from fuel combustion in millions of tonnes
|3rd Party Data
|-
|[[Research and development expenditure as a proportion of GDP]]
|Goal 09: Industry, innovation, technology and infrastructure
|Target 5: Enhance research and upgrade industrial technologies
|sdg_09_51_res_dev_expen_prop_gdp
|Metric
|A measure of the research and development expenditure as a proportion of GDP in percent
|3rd Party Data
|-
|[[Total official flows for infrastructure, by recipient countries (millions of constant 2022 USD)]]
|Goal 09: Industry, innovation, technology and infrastructure
|Target a: Facilitate sustainable infrastructure development for developing countries
|sdg_09_a1_tot_off_flow_infra_rec_coun
|Metric
|A measure of the total official flows for infrastructure, by recipient countries in millions of constant 2022 USD
|3rd Party Data
|-
|[[Proportion of population covered by at least a 2G mobile network]]
|Goal 09: Industry, innovation, technology and infrastructure
|Target c: Universal access to information and communications technology
|sdg_09_c1a_prop_pop_cov_lea_twog_mob_netw
|Metric
|A measure of the proportion of population covered by at least a 2G mobile network in percent
|3rd Party Data
|-
|[[Proportion of population covered by at least a 4G mobile network]]
|Goal 09: Industry, innovation, technology and infrastructure
|Target c: Universal access to information and communications technology
|sdg_09_c1c_prop_pop_cov_lea_fourg_mob_netw
|Metric
|A measure of the proportion of population covered by at least a 4G mobile network in percent
|3rd Party Data
|-
|[[Proportion of people living below 50 percent of median income]]
|Goal 10: Reduced inequality
|Target 2: Promote universal social, economic and political inclusion
|sdg_10_21_prop_peo_below_fiftyper_med_inco
|Metric
|A measure of the proportion of people living below 50 percent of median income in percent
|3rd Party Data
|-
|[[Labour share of GDP]]
|Goal 10: Reduced inequality
|Target 4: Adopt fiscal and social policies that promote equality
|sdg_10_41_lab_gdp
|Metric
|A measure of the labour share of GDP in percent
|3rd Party Data
|-
|[[Non-performing loans to total gross loans]]
|Goal 10: Reduced inequality
|Target 5: Improved regulation of global financial markets and institutions
|sdg_10_51a_nonperf_loa_tot_gro_loa
|Metric
|A measure of the non-performing loans to total gross loans in percent
|3rd Party Data
|-
|[[Total deaths and disappearances recorded during migration (number)]]
|Goal 10: Reduced inequality
|Target 7: Responsible and well-managed migration policies
|sdg_10_73_num_tot_dea_disapp_rec_dur_migr
|Metric
|A measure of the number of total deaths and disappearances recorded during migration
|3rd Party Data
|-
|[[Average remittance costs of sending $200 to a receiving country as a proportion of the amount remitted]]
|Goal 10: Reduced inequality
|Target c: Reduce transaction costs for migrant remittances
|sdg_10_c1a_avg_rem_cost_send_twohun_rec_coun_prop_amou_rem
|Metric
|A measure of the average remittance costs of sending $200 to a receiving country as a proportion of the amount remitted in percent
|3rd Party Data
|-
|[[Average remittance costs of sending $200 for a sending country as a proportion of the amount remitted]]
|Goal 10: Reduced inequality
|Target c: Reduce transaction costs for migrant remittances
|sdg_10_c1d_avg_rem_cost_send_twohun_send_coun_prop_amou_rem
|Metric
|A measure of the average remittance costs of sending $200 for a sending country as a proportion of the amount remitted in percent
|3rd Party Data
|-
|[[Number of damaged critical infrastructure attributed to disasters (number)]]
|Goal 11: Sustainable cities and communities
|Target 5: Reduce the adverse effects of natural disasters
|sdg_11_53a_num_dam_crit_infstr_att_dis
|Metric
|A measure of the number of damaged critical infrastructure attributed to disasters
|3rd Party Data
|-
|[[Number of disruptions to basic services attributed to disasters (number)]]
|Goal 11: Sustainable cities and communities
|Target 5: Reduce the adverse effects of natural disasters
|sdg_11_53e_num_disrup_bas_serv_att_dis
|Metric
|A measure of the number of disruptions to basic services attributed to disasters
|3rd Party Data
|-
|[[Food waste per capita (kg)]]
|Goal 12: Responsible consumption and production
|Target 3: Halve global per capita food waste
|sdg_12_31a_food_was_capi
|Metric
|A measure of the food waste per capita in kg
|3rd Party Data
|-
|[[Parties meeting their commitments and obligations in transmitting information as required by Montreal Protocol on hazardous waste, and other chemicals]]
|Goal 12: Responsible consumption and production
|Target 4: Responsible management of chemicals and waste
|sdg_12_41a_par_comm_obli_transm_info_req_by_mont_proto_haz_was_chem
|Metric
|A measure of the parties meeting their commitments and obligations in transmitting information as required by Montreal Protocol on hazardous waste, and other chemicals in percent
|3rd Party Data
|-
|[[Electronic waste generated, per capita (kg)]]
|Goal 12: Responsible consumption and production
|Target 4: Responsible management of chemicals and waste
|sdg_12_42b_elec_was_gen_capi
|Metric
|A measure of the electronic waste generated per capita in kg
|3rd Party Data
|-
|[[Hazardous waste generated, per capita (kg)]]
|Goal 12: Responsible consumption and production
|Target 4: Responsible management of chemicals and waste
|sdg_12_42d_haz_was_gen_capi
|Metric
|A measure of the hazardous waste generated per capita in kg
|3rd Party Data
|-
|[[Hazardous waste treated or disposed (tonnes)]]
|Goal 12: Responsible consumption and production
|Target 4: Responsible management of chemicals and waste
|sdg_12_42h_haz_was_trea_disp
|Metric
|A measure of the hazardous waste treated or disposed in tonnes
|3rd Party Data
|-
|[[Municipal waste generated (tonnes)]]
|Goal 12: Responsible consumption and production
|Target 4: Responsible management of chemicals and waste
|sdg_12_42k_muni_was_gen
|Metric
|A measure of the municipal waste generated in tonnes
|3rd Party Data
|-
|[[Total waste generation, by activity (tonnes)]]
|Goal 12: Responsible consumption and production
|Target 4: Responsible management of chemicals and waste
|sdg_12_42o_tot_was_gen
|Metric
|A measure of the total waste generation in tonnes
|3rd Party Data
|-
|[[Electronic waste recycled (tonnes)]]
|Goal 12: Responsible consumption and production
|Target 5: Substantially reduce waste generation
|sdg_12_51a_elec_was_recy
|Metric
|A measure of the electronic waste recycled in tonnes
|3rd Party Data
|-
|[[Municipal waste recycled (tonnes)]]
|Goal 12: Responsible consumption and production
|Target 5: Substantially reduce waste generation
|sdg_12_51e_muni_was_recy
|Metric
|A measure of the municipal waste recycled in tonnes
|3rd Party Data
|-
|[[Number of companies publishing sustainability reports with disclosure by dimension, by level of requirement (number)]]
|Goal 12: Responsible consumption and production
|Target 6: Encourage companies to adopt sustainable practices and sustainability reporting
|sdg_12_61_num_comp_pub_sust_rep_discl
|Metric
|A measure of the number of companies publishing sustainability reports with disclosure
|3rd Party Data
|-
|[[Implementation of standard accounting tools to monitor the economic and environmental aspects of tourism (number of tables)]]
|Goal 12: Responsible consumption and production
|Target b: Develop and implement tools to monitor sustainable tourism
|sdg_12_b1a_impl_stan_acc_tool_mon_eco_envi_asp_tour_num
|Metric
|A measure of the implementation of standard accounting tools to monitor the economic and environmental aspects of tourism in number of tables
|3rd Party Data
|-
|[[Fossil-fuel subsidies (consumption and production) as a proportion of total GDP]]
|Goal 12: Responsible consumption and production
|Target c: Remove market distortions that encourage wasteful consumption
|sdg_12_c1a_fossfue_subsi_prop_tot_gdp
|Metric
|A measure of the fossil-fuel subsidies (consumption and production) as a proportion of total GDP in percent
|3rd Party Data
|-
|[[Total greenhouse gas emissions without LULUCF for Annex I Parties (Mt CO2 equivalent)]]
|Goal 13: Climate action
|Target 2: Integrate climate change measures into policy and planning
|sdg_13_22a_tot_greenh_gas_emi_witou_lulucf_ann
|Metric
|A measure of the total greenhouse gas emissions without LULUCF for Annex I Parties in Mt CO2 equivalent
|3rd Party Data
|-
|[[Total greenhouse gas emissions without LULUCF for non-Annex I Parties (Mt CO2 equivalent)]]
|Goal 13: Climate action
|Target 2: Integrate climate change measures into policy and planning
|sdg_13_22b_tot_greenh_gas_emi_witou_lulucf_nonann
|Metric
|A measure of the total greenhouse gas emissions without LULUCF for non-Annex I Parties in Mt CO2 equivalent
|3rd Party Data
|-
|[[Beach litter originating from national land-based sources that ends in the ocean]]
|Goal 14: Life below water
|Target 1: Reduce marine pollution
|sdg_14_11h_bea_lit_orig_nat_landbas_sou_end_oce_per
|Metric
|A measure of the beach litter originating from national land-based sources that ends in the ocean in percent
|3rd Party Data
|-
|[[Beach litter originating from national land-based sources that ends in the ocean (tonnes)]]
|Goal 14: Life below water
|Target 1: Reduce marine pollution
|sdg_14_11i_bea_lit_orig_nat_landbas_sou_end_oce_ton
|Metric
|A measure of the beach litter originating from national land-based sources that ends in the ocean in tonnes
|3rd Party Data
|-
|[[Proportion of fish stocks within biologically sustainable levels (not overexploited)]]
|Goal 14: Life below water
|Target 4: Sustainable fishing
|sdg_14_41_prop_fish_stock_bio_susta_lvl_not_overexpl
|Metric
|A measure of the proportion of fish stocks within biologically sustainable levels (not overexploited) in percent
|3rd Party Data
|-
|[[Average proportion of Marine Key Biodiversity Areas (KBAs) covered by protected areas]]
|Goal 14: Life below water
|Target 5: Conserve coastal and marine areas
|sdg_14_51_avg_prop_mar_kba_cov_prot_area
|Metric
|A measure of the average proportion of Marine Key Biodiversity Areas (KBAs) covered by protected areas in percent
|3rd Party Data
|-
|[[Progress by countries in the degree of implementation of international instruments aiming to combat illegal, unreported and unregulated fishing (level of implementation: 1 lowest to 5 highest)]]
|Goal 14: Life below water
|Target 6: End subsidies contributing to overfishing
|sdg_14_61_pro_coun_impl_int_instr_aim_comb_ill_unrep_unregu_fish
|Ordinal
|A measure of the progress by countries in the degree of implementation of international instruments aiming to combat illegal, unreported and unregulated fishing
|3rd Party Data
|-
|[[National ocean science expenditure as a share of total research and development funding]]
|Goal 14: Life below water
|Target a: Increase scientific knowledge, research and technology for ocean health
|sdg_14_a1_nat_oce_sci_expen_sh_tot_rea_dev_fund
|Metric
|A measure of the national ocean science expenditure as a share of total research and development funding in percent
|3rd Party Data
|-
|[[Land area (thousands of hectares)]]
|Goal 15: Life on land
|Target 1: Conserve and restore terrestrial and freshwater ecosystems
|sdg_15_11a_land_area
|Metric
|A measure of the land area in thousands of hectares
|3rd Party Data
|-
|[[Forest area as a proportion of total land area]]
|Goal 15: Life on land
|Target 1: Conserve and restore terrestrial and freshwater ecosystems
|sdg_15_11c_for_area_prop_tot_land_area
|Metric
|A measure of the forest area as a proportion of total land area in percent
|3rd Party Data
|-
|[[Average proportion of Freshwater Key Biodiversity Areas (KBAs) covered by protected areas]]
|Goal 15: Life on land
|Target 1: Conserve and restore terrestrial and freshwater ecosystems
|sdg_15_12a_avg_prop_frewat_kba_cov_prot_area
|Metric
|A measure of the average proportion of Freshwater Key Biodiversity Areas (KBAs) covered by protected areas in percent.
|3rd Party Data
|-
|[[Average proportion of Terrestrial Key Biodiversity Areas (KBAs) covered by protected areas]]
|Goal 15: Life on land
|Target 1: Conserve and restore terrestrial and freshwater ecosystems
|sdg_15_12b_avg_prop_terre_kba_cov_prot_area
|Metric
|A measure of the average proportion of Terrestrial Key Biodiversity Areas (KBAs) covered by protected areas in percent
|3rd Party Data
|-
|[[Forest area certified under an independently verified certification scheme (thousands of hectares)]]
|Goal 15: Life on land
|Target 2: End deforestation and restore degraded forests
|sdg_15_21b_for_area_cert_indep_ver_cert_sche
|Metric
|A measure of the forest area certified under an independently verified certification scheme in thousands of hectares
|3rd Party Data
|-
|[[Proportion of land that is degraded over total land area]]
|Goal 15: Life on land
|Target 3: End desertification and restore degraded land
|sdg_15_31_prop_land_degra_over_tot_land_area
|Metric
|A measure of the proportion of land that is degraded over total land area in percent
|3rd Party Data
|-
|[[Average proportion of Mountain Key Biodiversity Areas (KBAs) covered by protected areas]]
|Goal 15: Life on land
|Target 4: Ensure conservation of mountain ecosystems
|sdg_15_41_avg_prop_mount_kba_cov_prot_area
|Metric
|A measure of the average proportion of Mountain Key Biodiversity Areas (KBAs) covered by protected areas in percent
|3rd Party Data
|-
|[[Red List Index]]
|Goal 15: Life on land
|Target 5: Protect biodiversity and natural habitats
|sdg_15_51_red_list_index
|Metric
|A measure of the Red List Index from the SDG database by the UN
|3rd Party Data
|-
|[[Total reported number of Standard Material Transfer Agreements (SMTAs) transferring plant genetic resources for food and agriculture to the country (number)]]
|Goal 15: Life on land
|Target 6: Protect access to genetic resources and fair sharing of the benefits
|sdg_15_61a_tot_rep_num_smta_transf_plan_gen_res_food_agricul_coun
|Metric
|A measure of the total reported number of Standard Material Transfer Agreements (SMTAs) transferring plant genetic resources for food and agriculture to the country
|3rd Party Data
|-
|[[Legislation, Regulation, Act related to the prevention of introduction and management of Invasive Alien Species (1 = YES, 0 = NO)]]
|Goal 15: Life on land
|Target 8: Prevent invasive alien species on land and in water ecosystems
|sdg_15_81a_leg_regu_act_rela_prev_intro_mana_inv_ali_spec
|Binary
|A measure of the Legislation, Regulation, Act related to the prevention of introduction and management of Invasive Alien Species
|3rd Party Data
|-
|[[National Biodiversity Strategy and Action Plan (NBSAP) targets alignment to Aichi Biodiversity target 9 set out in the Strategic Plan for Biodiversity 2011-2020 (1 = YES, 0 = NO)]]
|Goal 15: Life on land
|Target 8: Prevent invasive alien species on land and in water ecosystems
|sdg_15_81b_nbsap_tar_ali_aichi_biodiv_tar_nine_stra_plan_biodiv
|Binary
|A measure of the National Biodiversity Strategy and Action Plan (NBSAP) targets alignment to Aichi Biodiversity target 9 set out in the Strategic Plan for Biodiversity 2011-2020
|3rd Party Data
|-
|[[Number of victims of intentional homicide per 100,000 population, bothsex (victims per 100,000 population)]]
|Goal 16: Peace, justice and strong institutions
|Target 1: Reduce violence everywhere
|sdg_16_11a_num_vic_int_homi_pop_bothsex
|Metric
|A measure of the number of victims of intentional homicide per 100,000 population (bothsex) in victims per 100,000 population
|3rd Party Data
|-
|[[Number of victims of intentional homicide per 100,000 population, female (victims per 100,000 population)]]
|Goal 16: Peace, justice and strong institutions
|Target 1: Reduce violence everywhere
|sdg_16_11a_num_vic_int_homi_pop_female
|Metric
|A measure of the number of victims of intentional homicide per 100,000 population (female) in victims per 100,000 population
|3rd Party Data
|-
|[[Number of victims of intentional homicide per 100,000 population, male (victims per 100,000 population)]]
|Goal 16: Peace, justice and strong institutions
|Target 1: Reduce violence everywhere
|sdg_16_11a_num_vic_int_homi_pop_male
|Metric
|A measure of the number of victims of intentional homicide per 100,000 population (male) in victims per 100,000 population.
|3rd Party Data
|-
|[[Proportion of population subjected to physical violence in the previous 12 months, bothsex]]
|Goal 16: Peace, justice and strong institutions
|Target 1: Reduce violence everywhere
|sdg_16_13a_prop_pop_subj_phy_vio_prev_twelvemon_bothsex
|Metric
|A measure of the proportion of population subjected to physical violence in the previous 12 months in percent
|3rd Party Data
|-
|[[Proportion of population subjected to physical violence in the previous 12 months, female]]
|Goal 16: Peace, justice and strong institutions
|Target 1: Reduce violence everywhere
|sdg_16_13a_prop_pop_subj_phy_vio_prev_twelvemon_female
|Metric
|A measure of the proportion of the female population subjected to physical violence in the previous 12 months in percent
|3rd Party Data
|-
|[[Proportion of population subjected to physical violence in the previous 12 months, male]]
|Goal 16: Peace, justice and strong institutions
|Target 1: Reduce violence everywhere
|sdg_16_13a_prop_pop_subj_phy_vio_prev_twelvemon_male
|Metric
|A measure of the proportion of the male population subjected to physical violence in the previous 12 months in percent
|3rd Party Data
|-
|[[Proportion of population subjected to robbery in the previous 12 months, bothsex]]
|Goal 16: Peace, justice and strong institutions
|Target 1: Reduce violence everywhere
|sdg_16_13b_prop_pop_subj_robb_prev_twelvemon_bothsex
|Metric
|A measure of the proportion of population subjected to robbery in the previous 12 months in percent
|3rd Party Data
|-
|[[Proportion of population subjected to robbery in the previous 12 months, female]]
|Goal 16: Peace, justice and strong institutions
|Target 1: Reduce violence everywhere
|sdg_16_13b_prop_pop_subj_robb_prev_twelvemon_female
|Metric
|A measure of the female proportion of population subjected to robbery in the previous 12 months in percent
|3rd Party Data
|-
|[[Proportion of population subjected to robbery in the previous 12 months, male]]
|Goal 16: Peace, justice and strong institutions
|Target 1: Reduce violence everywhere
|sdg_16_13b_prop_pop_subj_robb_prev_twelvemon_male
|Metric
|A measure of the male proportion of population subjected to robbery in the previous 12 months in percent
|3rd Party Data
|-
|[[Detected victims of human trafficking, by age and sex (number), bothsex]]
|Goal 16: Peace, justice and strong institutions
|Target 2: Protect children from abuse, exploitation, trafficking and violence
|sdg_16_22e_det_vic_hum_traff_bothsex
|Metric
|A measure of the number of detected victims of human trafficking
|3rd Party Data
|-
|[[Detected victims of human trafficking, by age and sex (number), female]]
|Goal 16: Peace, justice and strong institutions
|Target 2: Protect children from abuse, exploitation, trafficking and violence
|sdg_16_22e_det_vic_hum_traff_female
|Metric
|A measure of the number of detected female victims of human trafficking
|3rd Party Data
|-
|[[Detected victims of human trafficking, by age and sex (number), male]]
|Goal 16: Peace, justice and strong institutions
|Target 2: Protect children from abuse, exploitation, trafficking and violence
|sdg_16_22e_det_vic_hum_traff_male
|Metric
|A measure of the number of detected male victims of human trafficking
|3rd Party Data
|-
|[[Police reporting rate for physical assault in the previous 12 months, bothsex]]
|Goal 16: Peace, justice and strong institutions
|Target 3: Equal access to justice
|sdg_16_31a_pol_rep_rate_phy_ass_prev_twelve_mon_bothsex
|Metric
|A measure of the police reporting rate for physical assault (bothsex) in the previous 12 months in percent
|3rd Party Data
|-
|[[Police reporting rate for physical assault in the previous 12 months, female]]
|Goal 16: Peace, justice and strong institutions
|Target 3: Equal access to justice
|sdg_16_31a_pol_rep_rate_phy_ass_prev_twelve_mon_female
|Metric
|A measure of the police reporting rate for physical assault (female) in the previous 12 months in percent
|3rd Party Data
|-
|[[Police reporting rate for physical assault in the previous 12 months, male]]
|Goal 16: Peace, justice and strong institutions
|Target 3: Equal access to justice
|sdg_16_31a_pol_rep_rate_phy_ass_prev_twelve_mon_male
|Metric
|A measure of the police reporting rate for physical assault (male) in the previous 12 months in percent
|3rd Party Data
|-
|[[Police reporting rate for sexual assault in the previous 12 months, bothsex]]
|Goal 16: Peace, justice and strong institutions
|Target 3: Equal access to justice
|sdg_16_31b_pol_rep_rate_sex_ass_prev_twelve_mon_bothsex
|Metric
|A measure of the police reporting rate for sexual assault (bothsex) in the previous 12 months in percent
|3rd Party Data
|-
|[[Police reporting rate for robbery in the previous 12 months, bothsex]]
|Goal 16: Peace, justice and strong institutions
|Target 3: Equal access to justice
|sdg_16_31c_pol_rep_rate_robb_prev_twelve_mon_bothsex
|Metric
|A measure of the police reporting rate for sexual assault (bothsex) in the previous 12 months in percent
|3rd Party Data
|-
|[[Unsentenced detainees as a proportion of overall prison population, bothsex]]
|Goal 16: Peace, justice and strong institutions
|Target 3: Equal access to justice
|sdg_16_32_unsent_deta_prop_ovall_pri_pop_bothsex
|Metric
|A measure of the unsentenced detainees as a proportion of overall prison population (bothsex) in percent
|3rd Party Data
|-
|[[Unsentenced detainees as a proportion of overall prison population, female]]
|Goal 16: Peace, justice and strong institutions
|Target 3: Equal access to justice
|sdg_16_32_unsent_deta_prop_ovall_pri_pop_female
|Metric
|A measure of the unsentenced detainees as a proportion of overall prison population (female) in percent
|3rd Party Data
|-
|[[Unsentenced detainees as a proportion of overall prison population, male]]
|Goal 16: Peace, justice and strong institutions
|Target 3: Equal access to justice
|sdg_16_32_unsent_deta_prop_ovall_pri_pop_male
|Metric
|A measure of the unsentenced detainees as a proportion of overall prison population (male) in percent
|3rd Party Data
|-
|[[Prevalence rate of bribery, bothsex]]
|Goal 16: Peace, justice and strong institutions
|Target 5: Substantially reduce corruption and bribery
|sdg_16_51_prev_rate_bri_bothsex
|Metric
|A measure of the prevalence rate of bribery (bothsex) in percent
|3rd Party Data
|-
|[[Primary government expenditures as a proportion of original approved budget]]
|Goal 16: Peace, justice and strong institutions
|Target 6: Develop effective, accountable and transparent institutions
|sdg_16_61_pri_gov_expen_prop_orig_app_bud
|Metric
|A measure of the primary government expenditures as a proportion of original approved budget in percent
|3rd Party Data
|-
|[[Total government revenue (budgetary central government) as a proportion of GDP]]
|Goal 17: Partnerships for the goals
|Target 1: Mobilize resources to improve domestic revenue collection
|sdg_17_11a_tot_gov_rev_prop_gdp
|Metric
|A measure of the total government revenue (budgetary central government) as a proportion of GDP in percent
|3rd Party Data
|-
|[[Net official development assistance (ODA) to small island states (SIDS) as a percentage of OECD-DAC donors' GNI, by donor countries]]
|Goal 17: Partnerships for the goals
|Target 2: Implement all development assistance commitments
|sdg_17_21a_net_oda_sids_per_oecddac_don_gni_don_coun
|Metric
|A measure of the net official development assistance (ODA) to small island states (SIDS) as a percentage of OECD-DAC donors' GNI (by donor countries) in percent
|3rd Party Data
|-
|[[Foreign direct investment (FDI) inflows (millions of USD)]]
|Goal 17: Partnerships for the goals
|Target 3: Mobilize financial resources for developing countries
|sdg_17_31a_fdi_inflow
|Metric
|A measure of the foreign direct investment (FDI) inflows in millions of USD
|3rd Party Data
|-
|[[Debt service as a proportion of exports of goods and services]]
|Goal 17: Partnerships for the goals
|Target 4: Assist developing countries in attaining debt sustainability
|sdg_17_41_deb_serv_prop_exp_goo_serv
|Metric
|A measure of the debt service as a proportion of exports of goods and services in percent
|3rd Party Data
|-
|[[Number of fixed broadband subscriptions, by speed (number)]]
|Goal 17: Partnerships for the goals
|Target 6: Knowledge sharing and cooperation for access to science, technology and innovation
|sdg_17_61a_num_fix_broa_sub_spe
|Metric
|A measure of the number of fixed broadband subscriptions
|3rd Party Data
|-
|[[Amount of tracked exported environmentally sound technologies (current USD)]]
|Goal 17: Partnerships for the goals
|Target 7: Promote sustainable technologies to developing countries
|sdg_17_71a_amo_tra_exp_enviro_sou_tech
|Metric
|A measure of the amount of tracked exported environmentally sound technologies in current USD
|3rd Party Data
|-
|[[Amount of tracked imported environmentally sound technologies (current USD)]]
|Goal 17: Partnerships for the goals
|Target 7: Promote sustainable technologies to developing countries
|sdg_17_71b_amo_tra_imp_enviro_sou_tech
|Metric
|A measure of the amount of tracked imported environmentally sound technologies in current USD
|3rd Party Data
|-
|[[Proportion of individuals using the internet, bothsex]]
|Goal 17: Partnerships for the goals
|Target 8: Strengthen the science, technology and innovation capacity for least-developed countries
|sdg_17_81_prop_indi_us_int_bothsex
|Metric
|A measure of the proportion of individuals (bothsex) using the internet in percent
|3rd Party Data
|-
|[[Proportion of individuals using the internet, female]]
|Goal 17: Partnerships for the goals
|Target 8: Strengthen the science, technology and innovation capacity for least-developed countries
|sdg_17_81_prop_indi_us_int_female
|Metric
|A measure of the proportion of female individuals using the internet in percent
|3rd Party Data
|-
|[[Proportion of individuals using the internet, male]]
|Goal 17: Partnerships for the goals
|Target 8: Strengthen the science, technology and innovation capacity for least-developed countries
|sdg_17_81_prop_indi_us_int_male
|Metric
|A measure of the proportion of male individuals using the internet in percent
|3rd Party Data
|-
|[[Total official development assistance (gross disbursement) for technical cooperation (millions of 2022 USD)]]
|Goal 17: Partnerships for the goals
|Target 9: Enhanced SDG capacity in developing countries
|sdg_17_91_tot_off_dev_ass_tech_coop
|Metric
|A measure of the total official development assistance (gross disbursement) for technical cooperation in millions of 2022 USD
|3rd Party Data
|-
|[[Developing countries’ and least developed countries’ share of global merchandise imports]]
|Goal 17: Partnerships for the goals
|Target 11: Increase the exports of developing countries
|sdg_17_111a_dev_coun_lea_dev_coun_sh_glo_mech_imp
|Metric
|A measure of the developing countries’ and least developed countries’ share of global merchandise imports in percent
|3rd Party Data
|-
|[[Developing countries’ and least developed countries’ share of global merchandise exports]]
|Goal 17: Partnerships for the goals
|Target 11: Increase the exports of developing countries
|sdg_17_111b_dev_coun_lea_dev_coun_sh_glo_mech_exp
|Metric
|A measure of the developing countries’ and least developed countries’ share of global merchandise exports in percent
|3rd Party Data
|-
|[[Bank capital to assets ratio]]
|Goal 17: Partnerships for the goals
|Target 13: Enhance global macroeconomic stability
|sdg_17_131a_bank_cap_ass_rat
|Metric
|A measure of the bank capital to assets ratio in percent
|3rd Party Data
|-
|[[Gross public sector debt, central government, as a proportion of GDP]]
|Goal 17: Partnerships for the goals
|Target 13: Enhance global macroeconomic stability
|sdg_17_131t_gro_pub_sec_debt_cen_gov_prop_gdp
|Metric
|A measure of the gross public sector debt, central government, as a proportion of GDP in percent
|3rd Party Data
|-
|[[Number of countries reporting progress in multi-stakeholder development effectiveness monitoring frameworks that support the achievement of the sustainable development goals, recipient ( 0 = no; 1 = yes)]]
|Goal 17: Partnerships for the goals
|Target 16: Enhance the global partnership for sustainable development
|sdg_17_161b_num_coun_rep_pro_multisth_dev_eff_mon_frwork_supp_ach_susta_dev_goal_rec
|Binary
|A measure of the number of countries reporting progress in multi-stakeholder development effectiveness monitoring frameworks that support the achievement of the sustainable development goals (Recipient) in percent
|3rd Party Data
|-
|[[Amount of USD committed to public-private partnerships for infrastructure, million USD nominal]]
|Goal 17: Partnerships for the goals
|Target 17: Encourage effective partnerships
|sdg_17_171a_amo_usd_comm_pubpri_partshi_infra_usd_nom
|Metric
|A measure of the amount of USD committed to public-private partnerships for infrastructure in million USD nominal
|3rd Party Data
|-
|[[Data Sources performance index (Statistical Performance Indicators Pillar 4) (Index)]]
|Goal 17: Partnerships for the goals
|Target 18: Enhance availability of reliable data
|sdg_17_181a_data_sou_per_index_spip_four
|Metric
|A measure of the Data Sources performance index (Statistical Performance Indicators Pillar 4) (Index)
|3rd Party Data
|-
|[[Dollar value of all resources made available to strengthen statistical capacity in developing countries (current USD)]]
|Goal 17: Partnerships for the goals
|Target 19: Further develop measurements of progress
|sdg_17_191_dol_val_res_ava_stre_stat_capa_dev_coun
|Metric
|A measure of the dollar value of all resources made available to strengthen statistical capacity in developing countries in current USD
|3rd Party Data
|-
|}

Immigrant social rights

2026-06-24T10:19:02Z

Nils Duepont: Reverted edits by Nils Duepont (talk) to last revision by Hannes Salzmann

Immigrant social rights

2026-06-24T08:08:59Z

Nils Duepont: Test indicators added again for testing the master branch on the new server, i.e. prod.wesis.org

Economic and financial factors

2026-06-23T09:11:57Z

Nils Duepont:

{|class="wikitable sortable" border="1"
|-
! Indicator name*
! Subcategory I
! Subcategory II
! Subcategory III
! Technical name*
! Scale*
! Short description
! Data origin*<br />
|-
| [[GDP per Capita in 1990 US-$, Maddison Data Project]]
| Economics
|
|
| econnat_economics_gdppercap_1990usd_mdp
| Metric
| GDP per Capita in 1990 US-Dollar, Maddison Project Database, version 2018
| 3rd Party Data
|-
| [[GDP in current USD (WB)]]
| Economics
|
|
| econnat_economics_gdp_cusd_wb
| Metric
| GDP in current US-Dollar, World Bank national accounts data
| 3rd Party Data
|-
| [[Agricultural employment in percent of total employment, ILO]]
| Labour Market
|
|
| econnat_economics_agricempl_perctot_ilo
| Metric
| Employment in the agricultural sector in percent of total employment
| 3rd Party Data
|-
| [[Central government debt in percent of GDP, IMF]]
| Finance
|
|
| econnat_economics_cgovdebt_pergdp_imf
| Metric
| Central government debt in percent of GDP
| 3rd Party Data
|-
| [[Employment in the industrial sector as percentage of total employment, ILO]]
| Labour Market
|
|
| econnat_economics_industryempl_perctotal_ilo
| Metric
| Employment in the industrial sector (mining and quarrying, manufacturing, construction, and public utilities) as a percentage of total employment based on ILO estimates
| 3rd Party Data
|-
| [[GDP in current NCU, World Bank]]
| Economics
|
|
| econnat_economics_gdp_cncu_wb
| Metric
| Nominal GDP in current national currency units
| 3rd Party Data
|-
| [[Annual real GDP growth in percent, World Bank]]
| Economics
|
|
| econnat_economics_gdp_percgrowth_wb
| Metric
| Annual real GDP growth in percent
| 3rd Party Data
|-
| [[Real GDP in 2010 US-$, World Bank]]
| Economics
|
|
| econnat_economics_gdp_real2010usd_wb
| Metric
| Real GDP in 2010 US-Dollars
| 3rd Party Data
|-
| [[Real GDP in NCU, World Bank]]
| Economics
|
|
| econnat_economics_gdp_realncu_wb
| Metric
| Real GDP in national currency units. Base year for constant national currency unit varies by country
| 3rd Party Data
|-
| [[Annual inflation in percent using GDP deflators, World Bank]]
| Economics
|
|
| econnat_economics_gdpdefl_percgrowth_wb
| Metric
| Annual inflation in percent using GDP deflators
| 3rd Party Data
|-
| [[GDP deflator index, World Bank]]
| Economics
|
|
| econnat_economics_gdpdefl_indexvby_wb
| Metric
| GDP deflator index with varying base year by country
| 3rd Party Data
|-
| [[GDP per capita in current PPP-$, World Bank]]
| Economics
|
|
| econnat_economics_gdppercap_cpppd_wb
| Metric
| GDP per capita in current purchasing power parity international Dollars
| 3rd Party Data
|-
| [[GDP per capita in current NCU, World Bank]]
| Economics
|
|
| econnat_economics_gdppercap_cncu_wb
| Metric
| GDP per capita in current national currency units
| 3rd Party Data
|-
| [[GDP per capita in current US-$, World Bank]]
| Economics
|
|
| econnat_economics_gdppercap_cusd_wb
| Metric
| GDP per capita in current US-Dollars.
| 3rd Party Data
|-
| [[Annual real GDP growth per capita, World Bank]]
| Economics
|
|
| econnat_economics_gdppercap_percgrowth_wb
| Metric
| Annual real GDP growth per capita
| 3rd Party Data
|-
| [[Real GDP per capita in 2017 PPP-$, World Bank]]
| Economics
|
|
| econnat_economics_gdppercap_real2017pppd_wb
| Metric
| Real GDP per capita in purchasing power parity international Dollars. Base year: 2017
| 3rd Party Data
|-
| [[Real GDP per capita in constant 2010 US-$, World Bank]]
| Economics
|
|
| econnat_economics_gdppercap_real2010usd_wb
| Metric
| Real GDP per capita in constant US-Dollars. Base year: 2010
| 3rd Party Data
|-
| [[Real GDP per capita in constant NCU, World Bank]]
| Economics
|
|
| econnat_economics_gdppercap_realncu_wb
| Metric
| Real GDP per capita in constant national currency units. Base year varies by country
| 3rd Party Data
|-
| [[Informal employment in percent of total non-agricultural employment, ILO]]
| Labour Market
|
|
| econnat_economics_tinformalempl_percnaempl_ilo
| Metric
| Informal employment in percent of total non-agricultural employment
| 3rd Party Data
|-
| [[Service employment in percent of total employment, ILO]]
| Labour Market
|
|
| econnat_economics_servempl_perctot_ilo
| Metric
| Employment in the service sector in percent of total employment
| 3rd Party Data
|-
| [[Value added in the agricultural sector as a percentage of GDP, World Bank]]
| Economics
|
|
| econnat_economics_agricva_pergdp_wb
| Metric
| Value added in the agricultural sector as a percentage of GDP
| 3rd Party Data
|-
| [[Value added in the industrial sector as a percentage of GDP, World Bank]]
| Economics
|
|
| econnat_economics_industryva_pergdp_wb
| Metric
| Value added in the industrial sector (mining, manufacturing, construction, electricity, water and gas) as a percentage of GDP
| 3rd Party Data
|-
| [[Value added in the manufacturing sector in percent of GDP, World Bank]]
| Economics
|
|
| econnat_economics_manufava_pergdp_wb
| Metric
| Value added in the manufacturing sector in percent of GDP
| 3rd Party Data
|-
| [[Value added in the service sector in percent of GDP, World Bank]]
| Economics
|
|
| econnat_economics_servva_pergdp_wb
| Metric
| Value added in the service sector in percent of GDP.
| 3rd Party Data
|-
| [[Public Social Spending as a % of GDP, OECD]]
| Finance
| Social Spending
|
| socx_public_oecd
| Metric
| Total public spending on social protection and assistance as a percentage of GDP
| 3rd Party Data
|-
| [[Private Social Spending as a % of GDP, OECD]]
| Finance
| Social Spending
|
| socx_private_oecd
| Metric
| Total voluntary and mandatory private spending on social protection and assistance as a percentage of GDP
| 3rd Party Data
|-
| [[Public Social Spending as a % of GDP, ILO]]
| Finance
| Social Spending
|
| socx_public_ilo
| Metric
| Total public spending on social protection and assistance as a percentage of GDP
| 3rd Party Data
|-
| [[GDP per Capita in 2011 US-$, Maddison Data Project]]
| Economics
|
|
| econnat_economics_gdppercap_2011usd_mdp
| Metric
| GDP per Capita in 2011 US-Dollar, Maddison Project Database
| 3rd Party Data
|}

GDP in current US-$, World Bank

2026-06-23T09:10:32Z

Nils Duepont: Nils Duepont moved page GDP in current US-$, World Bank to GDP in current USD (WB)

#REDIRECT [[GDP in current USD (WB)]]

GDP in current USD (WB)

2026-06-23T09:10:31Z

Nils Duepont: Nils Duepont moved page GDP in current US-$, World Bank to GDP in current USD (WB)

GDP in current USD (WB)

2026-06-23T09:04:53Z

Nils Duepont:

GDP in current USD (WB)

2026-06-23T09:04:28Z

Nils Duepont:

GDP in current USD (WB)

2026-06-23T08:57:34Z

Nils Duepont:

GDP in current USD (WB)

2026-06-23T08:57:04Z

Nils Duepont:

{{IndicatorForm
|datatype = Numeric
|scale = Metric
|valuelabels = Not applicable
|techname = econnat_economics_gdp_cusd_wb
|category= Economic and financial factors
|label = Current GDP in USD (World Bank)
|relatedindicators = tbd
|description = This indicator captures the current Gross Domestic Product (GDP) in USD.
|codingrules =
<ul>
<li>GDP at purchaser's prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources.</li>
<li>Data are in current U.S. dollars. Dollar figures for GDP are converted from domestic currencies using single year official exchange rates. For a few countries where the official exchange rate does not reflect the rate effectively applied to actual foreign exchange transactions, an alternative conversion factor is used.</li>
<li>For detailed information and coding rules see https://data.worldbank.org/indicator/NY.GDP.MKTP.CD</li>
</ul>
|citation =
|relatedpublications =
|projectmanagers = Nils Düpont, Carmen Cordes, Marius Bode (INF)
|datarelease =
<ul><li>Version 0.001: Initial release</li>
<li>Version 0.002: Update based on World Bank data published 2025.04.15</li></ul>
|revisions = Update based on World Bank data published 2025.04.15
|sources =
<ul>
<li>World Bank national accounts data, and OECD National Accounts data files. https://data.worldbank.org/indicator/NY.GDP.MKTP.CD</li>
</ul>
}}

Election date lower legislative chamber

2026-06-23T08:48:26Z

Nils Duepont:

{{IndicatorForm
|datatype=Date
|scale=Date
|valuelabels=Not applicable
|techname=polnat_polity_election_date_low
|category=Political factors
|label=Date of election to lower legislative chamber
|relatedindicators=<ul>
<li>[[Election dummy lower legislative chamber]]</li>
</ul>
|description=Date of an election to the 1st or lower legislative chamber.
|codingrules=<ul>
<li>Only elections to 1st or "lower" legislative chambers are considered. Presidential elections and elections to 2nd chambers are not included in Elections Global.</li>
<li>Data is reported valid as of December 31st of a given year. In rare cases where more than one election took place in a given year, earlier elections are not included.</li>
<li>Whenever possible, the exact date is reported. In some cases only the year and month could be identified, while in a few cases only the year could be determined.</li>
</ul>
For further coding rules see the codebook of Döring and Düpont 2020.
|citation=Döring, Holger, and Nils Düpont. 2020. ''Elections Global: Election results in 207 countries, 1880–2015''. Harvard Dataverse, V2. https://doi.org/10.7910/DVN/OGOURC.
|relatedpublications=
|projectmanagers=Nils Düpont (A01), Paul Bederke
|datarelease=<ul><li>Version 0.001: Initial release</li></ul>
|revisions=No revisions yet
|sources=<ul>
<li>Döring, Holger, and Nils Düpont. 2020. ''Elections Global: Election results in 207 countries, 1880–2015''. Harvard Dataverse, V2. https://doi.org/10.7910/DVN/OGOURC.</li>
</ul>
}}

Election dummy lower legislative chamber

2026-06-23T08:47:59Z

Nils Duepont:

{{IndicatorForm
|datatype=Numeric
|scale=Binary
|valuelabels=<ul>
<li>0 = No election</li>
<li>1 = Yes, election took place</li>
</ul>
|techname=polnat_polity_election_dummy
|category=Political factors
|label=Election dummy lower legislative chamber
|relatedindicators=<ul>
<li>[[Election date lower legislative chamber]]</li>
</ul>
|description=Dichotomous indicator whether an election to the 1st or lower legislative chamber took place in a given year (=1), or not (=0).
|codingrules=<ul>
<li>Based on WeSIS' [[Country_codes|entity list]], the indicator represents a time-series for each entity ranging from the first to the last year a country either was "independent" or "related to" (columns "independence" and "relation_year" respectively). For some entities the time-series may therefore largely consist of "zeros".</li>
<li>Only elections to 1st or "lower" chambers are considered. Presidential elections and elections to 2nd chambers are not included in Elections Global.</li>
<li>Data is reported valid as of December 31st of a given year. In rare cases where more than one election took place in a given year, earlier elections are not included.</li>
</ul>
For further coding rules see the codebook of Döring and Düpont 2020.
|citation=Döring, Holger, and Nils Düpont. 2020. ''Elections Global: Election results in 207 countries, 1880–2015''. Harvard Dataverse, V2. https://doi.org/10.7910/DVN/OGOURC.
|relatedpublications=
|projectmanagers=Nils Düpont (A01), Paul Bederke
|datarelease=<ul><li>Version 0.001: Initial release</li></ul>
|revisions=No revisions yet
|sources=<ul>
<li>Döring, Holger, and Nils Düpont. 2020. ''Elections Global: Election results in 207 countries, 1880–2015''. Harvard Dataverse, V2. https://doi.org/10.7910/DVN/OGOURC.</li>
</ul>
}}

Election dummy lower legislative chamber

2026-06-23T08:46:51Z

Nils Duepont:

{{IndicatorForm
|datatype=Numeric
|scale=Binary
|valuelabels=<ul>
<li>0 = No election</li>
<li>1 = Yes, election took place</li>
</ul>
|techname=polnat_polity_election_dummy
|category=Political factors
|label=Election dummy lower legislative chamber
|relatedindicators=<ul>
<li>[[Election date lower legislative chamber]]</li>
</ul>
|description=Dichotomous indicator whether an election to the 1st or lower legislative chamber took place in a given year (=1), or not (=0).
|codingrules=<ul>
<li>Based on WeSIS' [[Country_codes|entity list]], the indicator represents a time-series for each entity ranging from the first to the last year a country either was "independent" or "related to" (columns "independence" and "relation_year" respectively). For some entities the time-series may therefore largely consist of "zeros".</li>
<li>Only elections to 1st or "lower" chambers are considered. Presidential elections and elections to 2nd chambers are not included in Elections Global.</li>
<li>Data is reported valid as of December 31st of a given year. In rare cases where more than one election took place in a given year, earlier elections are not included.</li>
</ul>
For further coding rules see the codebook of Döring and Düpont 2020.
|citation=Döring, Holger, and Nils Düpont. 2020. "Elections Global: Election results in 207 countries, 1880–2015". Harvard Dataverse, V2. [https://doi.org/10.7910/DVN/OGOURC https://doi.org/10.7910/DVN/OGOURC]
|relatedpublications=
|projectmanagers=Nils Düpont (A01), Paul Bederke
|datarelease=<ul><li>Version 0.001: Initial release</li></ul>
|revisions=No revisions yet
|sources=<ul>
<li>Döring, Holger, and Nils Düpont. 2020. "Elections Global: Election results in 207 countries, 1880–2015". Harvard Dataverse, V2. [https://doi.org/10.7910/DVN/OGOURC https://doi.org/10.7910/DVN/OGOURC]</li>
</ul>
}}

Election dummy lower legislative chamber

2026-06-23T08:46:12Z

Nils Duepont:

{{IndicatorForm
|datatype=Numeric
|scale=Binary
|valuelabels=<ul>
<li>0 = No</li>
<li>1 = Yes</li>
</ul>
|techname=polnat_polity_election_dummy
|category=Political factors
|label=Election dummy lower legislative chamber
|relatedindicators=<ul>
<li>[[Election date lower legislative chamber]]</li>
</ul>
|description=Dichotomous indicator whether an election to the 1st or lower legislative chamber took place in a given year.
|codingrules=<ul>
<li>Based on WeSIS' [[Country_codes|entity list]], the indicator represents a time-series for each entity ranging from the first to the last year a country either was "independent" or "related to" (columns "independence" and "relation_year" respectively). For some entities the time-series may therefore largely consist of "zeros".</li>
<li>Only elections to 1st or "lower" chambers are considered. Presidential elections and elections to 2nd chambers are not included in Elections Global.</li>
<li>Data is reported valid as of December 31st of a given year. In rare cases where more than one election took place in a given year, earlier elections are not included.</li>
</ul>
For further coding rules see the codebook of Döring and Düpont 2020.
|citation=Döring, Holger, and Nils Düpont. 2020. "Elections Global: Election results in 207 countries, 1880–2015". Harvard Dataverse, V2. [https://doi.org/10.7910/DVN/OGOURC https://doi.org/10.7910/DVN/OGOURC]
|relatedpublications=
|projectmanagers=Nils Düpont (A01), Paul Bederke
|datarelease=<ul><li>Version 0.001: Initial release</li></ul>
|revisions=No revisions yet
|sources=<ul>
<li>Döring, Holger, and Nils Düpont. 2020. "Elections Global: Election results in 207 countries, 1880–2015". Harvard Dataverse, V2. [https://doi.org/10.7910/DVN/OGOURC https://doi.org/10.7910/DVN/OGOURC]</li>
</ul>
}}

International student mobility

2026-06-23T08:38:36Z

Nils Duepont:

{{IndicatorForm
|datatype = Numeric
|scale = Metric
|valuelabels = Not applicable
|techname = edu_internat_student
|category= Migration
|label = Inbound international students
|relatedindicators =
<ul>
<li>[[International Student Mobility - normalized on the nr. of tertiary students in destination country]]</li>
<li>[[International Student Mobility - normalized on the nr. of tertiary students in origin country]]</li>
<li>[[International Student Mobility - normalized on the nr. of tertiary students sent]]</li>
<li>[[International Student Mobility - normalized on the nr. of tertiary students received]]</li>
</ul>
|description = The data source for the student mobility network consists of all independent countries acknowledged as such by the United Nations (UN) at the time of 31st of January 2019, which have a higher education sector in place. We use data on degree mobility and refer to the one provided by the UNESCO Institute for Statistics (UIS).
|codingrules =
<ul>
<li>UNESCO defines transnational students as "[s]tudents who have crossed a national or territorial border for the purposes of education and are now enrolled outside their country of origin" (2010, 264).</li>
<li>UIS asks countries to submit data annually on the numbers and origins of transnational students enrolled in their tertiary education institutions for at least a year. We use this data for the years 1998-2019. However, there is a large amount of missing data and in many cases, it is hard to distinguish whether a) the number of outgoing students is so small that none have been reported, or b) there actually have not been any incoming students from a particular country, or c) whether the data is simply missing. We assume that if there were a high number of students from country O (country of origin) studying in country D (destination country), the UIS would have at least an approximate figure. We thus decided to replace all missing data with the value of zero, since there was no case in which actually zero international students have been reported.</li>
</ul>
|citation = Vögtle, Eva M., and Michael Windzio. 2019. "Looking for freedom? Networks of international student mobility and countries’ levels of democracy." ''The Geographical Journal'' 186 (1): 103–115. http://dx.doi.org/10.1111/geoj.12329.
|relatedpublications =
|projectmanagers = Fabian Besche-Truthe, Michael Windzio, Helen Seitzer (A05)
|datarelease = <ul><li>Version 0.001: Initial release</li></ul>
|revisions = No revisions yet
|sources = <ul>
<li>
UNESCO Institute for Statistics (UIS)</li>
</ul>
}}

International student mobility

2026-06-23T08:36:00Z

Nils Duepont:

{{IndicatorForm
|datatype = Numeric
|scale = Metric
|valuelabels = Not applicable
|techname = edu_internat_student
|category= Migration
|label = Inbound international students
|relatedindicators =
<ul>
<li>[[International Student Mobility - normalized on the nr. of tertiary students in destination country]]</li>
<li>[[International Student Mobility - normalized on the nr. of tertiary students in origin country]]</li>
<li>[[International Student Mobility - normalized on the nr. of tertiary students sent]]</li>
<li>[[International Student Mobility - normalized on the nr. of tertiary students received]]</li>
</ul>
|description = The data source for the student mobility network consists of all independent countries acknowledged as such by the United Nations (UN) at the time of 31st of January 2019, which have a higher education sector in place. We use data on degree mobility and refer to the one provided by the UNESCO Institute for Statistics (UIS).
|codingrules =
<ul>
<li>UNESCO defines transnational students as "[s]tudents who have crossed a national or territorial border for the purposes of education and are now enrolled outside their country of origin" (2010, p. 264).</li>
<li>UIS asks countries to submit data annually on the numbers and origins of transnational students enrolled in their tertiary education institutions for at least a year. We use this data for the years 1998-2019. However, there is a large amount of missing data and in many cases, it is hard to distinguish whether a) the number of outgoing students is so small that none have been reported, or b) there actually have not been any incoming students from a particular country, or c) whether the data is simply missing. We assume that if there were a high number of students from country O (country of origin) studying in country D (destination country), the UIS would have at least an approximate figure. We thus decided to replace all missing data with the value of zero, since there was no case in which actually zero international students have been reported.</li>
</ul>
|citation = Vögtle, Eva M., and Michael Windzio. 2019. "Looking for freedom? Networks of international student mobility and countries’ levels of democracy." ''The Geographical Journal'' 186 (1): 103–115. http://dx.doi.org/10.1111/geoj.12329.
|relatedpublications =
|projectmanagers = Fabian Besche-Truthe, Michael Windzio, Helen Seitzer (A05)
|datarelease = <ul><li>Version 0.001: Initial release</li></ul>
|revisions = No revisions yet
|sources = <ul>
<li>
UNESCO Institute for Statistics (UIS)</li>
</ul>
}}

International student mobility

2026-06-23T08:34:21Z

Nils Duepont:

{{IndicatorForm
|datatype = Numeric
|scale = Metric
|valuelabels = Not applicable
|techname = edu_internat_student
|category= Migration
|label = Inbound international students
|relatedindicators =
<ul>
<li>[[International Student Mobility - normalized on the nr. of tertiary students in destination country]]</li>
<li>[[International Student Mobility - normalized on the nr. of tertiary students in origin country]]</li>
<li>[[International Student Mobility - normalized on the nr. of tertiary students sent]]</li>
<li>[[International Student Mobility - normalized on the nr. of tertiary students received]]</li>
</ul>
|description = The data source for the student mobility network consists of all independent countries acknowledged as such by the United Nations (UN) at the time of 31st of January 2019, which have a higher education sector in place. We use data on degree mobility and refer to the one provided by the UNESCO Institute for Statistics (UIS).
|codingrules =
<ul>
<li>UNESCO defines transnational students as "[s]tudents who have crossed a national or territorial border for the purposes of education and are now enrolled outside their country of origin" (2010, p. 264).</li>
<li>UIS asks countries to submit data annually on the numbers and origins of transnational students enrolled in their tertiary education institutions for at least a year. We use this data for the years 1998-2019. However, there is a large amount of missing data and in many cases, it is hard to distinguish whether a) the number of outgoing students is so small that none have been reported, or b) there actually have not been any incoming students from a particular country, or c) whether the data is simply missing. We assume that if there were a high number of students from country O (country of origin) studying in country D (destination country), the UIS would have at least an approximate figure. We thus decided to replace all missing data with the value of zero, since there was no case in which actually zero international students have been reported.</li>
</ul>
|citation =
|relatedpublications = Vögtle, Eva M., and Michael Windzio. 2019. "Looking for freedom? Networks of international student mobility and countries’ levels of democracy." ''The Geographical Journal'' 186 (1): 103–115. http://dx.doi.org/10.1111/geoj.12329.
|projectmanagers = Fabian Besche-Truthe, Michael Windzio, Helen Seitzer (A05)
|datarelease = <ul><li>Version 0.001: Initial release</li></ul>
|revisions = No revisions yet
|sources = <ul>
<li>
UNESCO Institute for Statistics (UIS)</li>
</ul>
}}

International student mobility

2026-06-23T08:33:57Z

Nils Duepont:

{{IndicatorForm
|datatype = Numeric
|scale = Metric
|valuelabels = Not applicable
|techname = edu_internat_student
|category= Migration
|label = Inbound international students
|relatedindicators =
<ul>
<li>[[International Student Mobility - normalized on the nr. of tertiary students in destination country]]</li>
<li>[[International Student Mobility - normalized on the nr. of tertiary students in origin country]]</li>
<li>[[International Student Mobility - normalized on the nr. of tertiary students sent]]</li>
<li>[[International Student Mobility - normalized on the nr. of tertiary students received]]</li>
</ul>
|description = The data source for the student mobility network consists of all independent countries acknowledged as such by the United Nations (UN) at the time of 31st of January 2019, which have a higher education sector in place. We use data on degree mobility and refer to the one provided by the UNESCO Institute for Statistics (UIS).
|codingrules =
<ul>
<li>UNESCO defines transnational students as "[s]tudents who have crossed a national or territorial border for the purposes of education and are now enrolled outside their country of origin" (2010, p. 264).</li>
<li>UIS asks countries to submit data annually on the numbers and origins of transnational students enrolled in their tertiary education institutions for at least a year. We use this data for the years 1998-2019. However, there is a large amount of missing data and in many cases, it is hard to distinguish whether a) the number of outgoing students is so small that none have been reported, or b) there actually have not been any incoming students from a particular country, or c) whether the data is simply missing. We assume that if there were a high number of students from country O (country of origin) studying in country D (destination country), the UIS would have at least an approximate figure. We thus decided to replace all missing data with the value of zero, since there was no case in which actually zero international students have been reported.</li>
</ul>
|citation =
|relatedpublications = Vögtle, Eva M., and Michael Windzio. 2019. "Looking for freedom? Networks of international student mobility and countries’ levels of democracy." ''The Geographical Journal'' 186 (1): 103–1[[File:Example.jpg]]15. http://dx.doi.org/10.1111/geoj.12329.
|projectmanagers = Fabian Besche-Truthe, Michael Windzio, Helen Seitzer (A05)
|datarelease = <ul><li>Version 0.001: Initial release</li></ul>
|revisions = No revisions yet
|sources = <ul>
<li>
UNESCO Institute for Statistics (UIS)</li>
</ul>

}}

Colony of Belgium, ever

2026-06-23T08:04:29Z

Nils Duepont:

{{IndicatorForm
|datatype = Numeric
|scale = Binary
|valuelabels = <ul><li>0 = Never a Belgian colony</li><li>1 = Was a Belgian colony</li></ul>
|techname = col_ever_belgium
|category= Violent conflicts and colonial dependencies|Violent conflicts and colonial dependencies
|subcategory = Colonialism
|label = Colony of Belgium, ever
|relatedindicators =
<ul>
<li>[[Colony of Britain, ever]]</li>
<li>[[Colony of France, ever]]</li>
<li>[[Colony of Germany, ever]]</li>
<li>[[Colony of Italy, ever]]</li>
<li>[[Colony of Netherlands, ever]]</li>
<li>[[Colony of Portugal, ever]]</li>
<li>[[Colony of Spain, ever]]</li>
</ul>
|description = This indicator captures if at any point in the focal country's history it was a colony of Belgium (=1), or not (=0).
|codingrules = For detailed coding rules see the codebook of Becker 2019.
|citation = Becker, Bastian. 2019. ''Introducing COLDAT: The Colonial Dates Dataset.'' Bremen: SOCIUM SFB 1342. SOCIUM SFB 1342 Working Papers, 2/2019. https://doi.org/10.26092/elib/4395.
|relatedpublications =
|projectmanagers = Bastian Becker, Nils Düpont, Carmen Cordes, Marius Bode (INF)
|datarelease = <ul><li>Version 0.001: Initial release</li></ul>
|revisions = No revisions yet
|sources = <ul><li>Becker, Bastian. 2019. ''Colonial Dates Dataset (COLDAT)''. Harvard Dataverse, V2. https://doi.org/10.7910/DVN/T9SDEW.</li></ul>
}}

Proportion of population below international poverty line, bothsex

2026-06-23T07:51:22Z

Nils Duepont:

{{IndicatorForm
|datatype = Numeric
|scale = Metric
|valuelabels = Not applicable
|techname = sdg_01_11a_prop_pop_below_int_povline_bothsex
|category = Sustainable development goals|Sustainable development goals
|label = Proportion of population below international poverty line, bothsex
|relatedindicators = Not applicable
|description = This indicator measures the proportion of the population living below the international poverty line in percent. It is part of monitoring the achievement and progress towards the UN Sustainable Development Goals.
|codingrules =
<ul>
<li>For detailed information and coding rules see https://unstats.un.org/wiki/spaces/SDGeHandbook/pages/34505092/Home.</li>
</ul>
|citation = United Nations Department of Economic and Social Affairs. 2024. ''SDG Indicators Database''. https://unstats.un.org/sdgs/dataportal/database.
|relatedpublications =
<ul>
<li>United Nations Department of Economic and Social Affairs. 2025. ''The Sustainable Development Goals Report 2025''. New York: United Nations Publications. https://unstats.un.org/sdgs/report/2025/.</li>
</ul>
|projectmanagers = Marius Bode, Hannes Salzmann, Carmen Cordes, Nils Düpont (INF)
|datarelease =
<ul>
<li>Version 0.001: Initial release</li>
</ul>
|revisions = No revisions yet
|sources =
<ul>
<li>United Nations Department of Economic and Social Affairs. 2024. ''SDG Indicators Database''. https://unstats.un.org/sdgs/dataportal/database.</li>
<li>United Nations Department of Economic and Social Affairs. 2026. ''SDG Indicators Database''. https://unstats.un.org/sdgs/dataportal/database.</li>
</ul>
}}

Main page

2026-06-19T09:36:01Z

Nils Duepont:

Welcome to WeSISpedia, the collaborative codebook accompanying [https://wesis.org WeSIS] -- the '''We'''lfare '''S'''tate '''I'''nformation '''S'''ystem. The aim of WeSIS is to provide a comprehensive database on social policies throughout the world since 1880. WeSIS includes monadic data on social policies and (explanatory) variables capturing domestic conditions like policy legacies, economic, financial and political factors, information about the social structure, culture, and geography. Reflecting different forms of interdependencies and relations among states, WeSIS further includes dyadic data about (flows of) communication, political institutional linkages, economic relations, migration, colonial dependencies, and violent conflicts.

Every indicator is documented here in WeSISpedia, and the information is parsed and displayed in WeSIS. Indicator tables (see the corresponding boxes below) provide basic information about all indicators of each policy field or topic, and further link to dedicated indicator pages where each indicator is documented in a structured and detailed manner. Alongside common [[Coding_rules|coding rules]] and harmonized [[Country_codes|country and IO codes]], WeSISpedia provides useful information when preparing data for WeSIS, and records additional aspects (e.g. on [[Data quality|data quality]]) affecting the data collection and documentation.

WeSIS and WeSISpedia are key research data components of the Collaborative Research Center 1342 on [http://www.socialpolicydynamics.de/en/ Global Dynamics of Social Policy] funded by the German Research Foundation.

----

'''If you are filling an indicator page''', please follow the [[Coding_rules|coding rules]] and the instructions of either the [[Template:Indicator|indicator template]] ''or'' the [[Form:IndicatorForm|indicator form]] for creating new pages.

'''If you are preparing a file to upload in WeSIS''', please follow the instructions of the [[File_formats|file formats]] and make sure you are using the correct [[Country codes|country and IO names and codes]].
The [[File_upload_guide|file upload guide]] is work in progress.

----


__NOTOC__


{| role="presentation" id="mp-upper" style="width: 100%; margin-top:4px; border-spacing: 10px;"

| id="mp-left" class="indicator-type" style="width:34%; border:1px solid #f2cedd; padding:0; background:#fff5fa; vertical-align:top; color:#000;" |
<h2 id="mp-tfa-h2" style="margin:0.5em; background:#f2cedd; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #bfa3af; color:#000; padding:0.2em 0.4em;">Social policies<span style="font-size:85%; font-weight:normal;"></span></h2>

<div id="indicator-links" style="padding:0.1em 0.6em;">
<ul>
<li>[[Old age and survivors]]</li>
<li>[[Labour and labour market]]</li>
<li>[[Health and long-term care]]</li>
<li>[[Education and training]]</li>
<li>[[Family and gender policies]]</li>
<li>[[Immigrant social rights]]</li>
<li>[[Social assistance rights]]</li>
<li>[[Social expenditures]]</li>
</ul>
</div>


| id="mp-right" class="indicator-type" style="width:33%; border:1px solid #cef2e0; padding:0; background:#f5fffa; vertical-align:top; color:#000;" |
<h2 id="mp-tfa-h2" style="margin:0.5em; background:#cef2e0; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3bfb1; color:#000; padding:0.2em 0.4em;">National attributes<span style="font-size:85%; font-weight:normal;"></span></h2>

<div id="indicator-links" style="padding:0.1em 0.6em;">
<ul>
<li>[[Policy legacies]]</li>
<li>[[Economic and financial factors]]</li>
<li>[[Political factors]]</li>
<li>[[Social structure]]</li>
<li>[[Culture]]</li>
<li>[[Geography]]</li>
<li>[[Sustainable development goals]]</li>
</ul>
</div>


| id="mp-left" class="indicator-type" style="width:33%; border:1px solid #cef2e0; padding:0; background:#f5fffa; vertical-align:top; color:#000;" |
<h2 id="mp-tfa-h2" style="margin:0.5em; background:#cef2e0; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3bfb1; color:#000; padding:0.2em 0.4em;">Global linkages<span style="font-size:85%; font-weight:normal;"></span></h2>

<div id="indicator-links" style="padding:0.1em 0.6em;">
<ul>
<li>[[Communication]]</li>
<li>[[Political institutional linkages]]</li>
<li>[[Economic relations]]</li>
<li>[[Migration]]</li>
<li>[[Violent conflicts and colonial dependencies]]</li>
</ul>
</div>
|}


{| role="presentation" id="mp-upper" style="width: 100%; margin-top:4px; border-spacing: 10px;"
| id="mp-right" class="MainPageBG" style="width:34%; border:1px solid #cedff2; padding:0; background:#f5faff; vertical-align:top;"|
<h2 id="mp-itn-h2" style="margin:0.5em; background:#cedff2; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3b0bf; color:#000; padding:0.2em 0.4em;">Data preparation</h2>

<div id="mp-tfa" style="padding:0.1em 0.6em;">
<ul>
<li>[[Coding_rules|Coding rules and conceptual agreements]]</li>
<li>[[File_upload_guide|File upload guide]]</li>
<li>[[File_formats|File formats]]</li>
<li>[[Country codes|Country and IO codes]]</li>
<li>[[Optional_column_names|Optional column names]]</li>
<li>[[Abbreviations|Abbreviations]]</li>
</ul>
</div>


| id="mp-right" class="MainPageBG" style="width:33%; border:1px solid #cedff2; padding:0; background:#f5faff; vertical-align:top;"|
<h2 id="mp-itn-h2" style="margin:0.5em; background:#cedff2; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3b0bf; color:#000; padding:0.2em 0.4em;">Data documentation</h2>

<div id="mp-tfa" style="padding:0.1em 0.6em;">
<ul>
<li>[[Form:IndicatorForm|Indicator form]]</li>
<li>[[Template:Indicator|Indicator template]]</li>
<li>[[Example:_Example_indicator|Example page using the template]]</li>
<li>[[Data quality|Data quality in WeSIS]]</li>
</ul>
</div>


| id="mp-right" class="MainPageBG" style="width:33%; border:1px solid #cedff2; padding:0; background:#f5faff; vertical-align:top;"|
<h2 id="mp-itn-h2" style="margin:0.5em; background:#cedff2; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3b0bf; color:#000; padding:0.2em 0.4em;">Further resources</h2>

<div id="mp-tfa" style="padding:0.1em 0.6em;">
<ul>
<li>[[Country related documents]]</li>
<li>[[Help:Tutorials|WeSISpedia help page]]</li>
<li>[[Copyright_issues|Collection of copyright issues]]</li>
</ul>
</div>
|}

Main page

2026-06-19T09:33:45Z

Nils Duepont:

Welcome to WeSISpedia, the collaborative codebook accompanying [https://wesis.org WeSIS] -- the '''We'''lfare '''S'''tate '''I'''nformation '''S'''ystem. The aim of WeSIS is to provide a comprehensive database on social policies throughout the world since 1880. WeSIS includes monadic data on social policies and (explanatory) variables capturing domestic conditions like policy legacies, economic, financial and political factors, information about the social structure, culture, and geography. Reflecting different forms of interdependencies and relations among states, WeSIS further includes dyadic data about (flows of) communication, political institutional linkages, economic relations, migration, colonial dependencies, and violent conflicts.

Every indicator is documented here in WeSISpedia, and the information is parsed and displayed in WeSIS. Indicator tables (see the corresponding boxes below) provide basic information about all indicators of each policy field or topic, and further link to dedicated indicator pages where each indicator is documented in a structured and detailed manner. Alongside common [[Coding_rules|coding rules]] and harmonized [[Country_codes|country and IO codes]], WeSISpedia provides useful information when preparing data for WeSIS, and records additional aspects affecting the data collection and documentation.

WeSIS and WeSISpedia are key research data components of the Collaborative Research Center 1342 on [http://www.socialpolicydynamics.de/en/ Global Dynamics of Social Policy] funded by the German Research Foundation.

----

'''If you are filling an indicator page''', please follow the [[Coding_rules|coding rules]] and the instructions of either the [[Template:Indicator|indicator template]] ''or'' the [[Form:IndicatorForm|indicator form]] for creating new pages.

'''If you are preparing a file to upload in WeSIS''', please follow the instructions of the [[File_formats|file formats]] and make sure you are using the correct [[Country codes|country and IO names and codes]].
The [[File_upload_guide|file upload guide]] is work in progress.

----


__NOTOC__


{| role="presentation" id="mp-upper" style="width: 100%; margin-top:4px; border-spacing: 10px;"

| id="mp-left" class="indicator-type" style="width:34%; border:1px solid #f2cedd; padding:0; background:#fff5fa; vertical-align:top; color:#000;" |
<h2 id="mp-tfa-h2" style="margin:0.5em; background:#f2cedd; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #bfa3af; color:#000; padding:0.2em 0.4em;">Social policies<span style="font-size:85%; font-weight:normal;"></span></h2>

<div id="indicator-links" style="padding:0.1em 0.6em;">
<ul>
<li>[[Old age and survivors]]</li>
<li>[[Labour and labour market]]</li>
<li>[[Health and long-term care]]</li>
<li>[[Education and training]]</li>
<li>[[Family and gender policies]]</li>
<li>[[Immigrant social rights]]</li>
<li>[[Social assistance rights]]</li>
<li>[[Social expenditures]]</li>
</ul>
</div>


| id="mp-right" class="indicator-type" style="width:33%; border:1px solid #cef2e0; padding:0; background:#f5fffa; vertical-align:top; color:#000;" |
<h2 id="mp-tfa-h2" style="margin:0.5em; background:#cef2e0; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3bfb1; color:#000; padding:0.2em 0.4em;">National attributes<span style="font-size:85%; font-weight:normal;"></span></h2>

<div id="indicator-links" style="padding:0.1em 0.6em;">
<ul>
<li>[[Policy legacies]]</li>
<li>[[Economic and financial factors]]</li>
<li>[[Political factors]]</li>
<li>[[Social structure]]</li>
<li>[[Culture]]</li>
<li>[[Geography]]</li>
<li>[[Sustainable development goals]]</li>
</ul>
</div>


| id="mp-left" class="indicator-type" style="width:33%; border:1px solid #cef2e0; padding:0; background:#f5fffa; vertical-align:top; color:#000;" |
<h2 id="mp-tfa-h2" style="margin:0.5em; background:#cef2e0; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3bfb1; color:#000; padding:0.2em 0.4em;">Global linkages<span style="font-size:85%; font-weight:normal;"></span></h2>

<div id="indicator-links" style="padding:0.1em 0.6em;">
<ul>
<li>[[Communication]]</li>
<li>[[Political institutional linkages]]</li>
<li>[[Economic relations]]</li>
<li>[[Migration]]</li>
<li>[[Violent conflicts and colonial dependencies]]</li>
</ul>
</div>
|}


{| role="presentation" id="mp-upper" style="width: 100%; margin-top:4px; border-spacing: 10px;"
| id="mp-right" class="MainPageBG" style="width:34%; border:1px solid #cedff2; padding:0; background:#f5faff; vertical-align:top;"|
<h2 id="mp-itn-h2" style="margin:0.5em; background:#cedff2; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3b0bf; color:#000; padding:0.2em 0.4em;">Data preparation</h2>

<div id="mp-tfa" style="padding:0.1em 0.6em;">
<ul>
<li>[[Coding_rules|Coding rules and conceptual agreements]]</li>
<li>[[File_upload_guide|File upload guide]]</li>
<li>[[File_formats|File formats]]</li>
<li>[[Country codes|Country and IO codes]]</li>
<li>[[Optional_column_names|Optional column names]]</li>
<li>[[Abbreviations|Abbreviations]]</li>
</ul>
</div>


| id="mp-right" class="MainPageBG" style="width:33%; border:1px solid #cedff2; padding:0; background:#f5faff; vertical-align:top;"|
<h2 id="mp-itn-h2" style="margin:0.5em; background:#cedff2; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3b0bf; color:#000; padding:0.2em 0.4em;">Data documentation</h2>

<div id="mp-tfa" style="padding:0.1em 0.6em;">
<ul>
<li>[[Form:IndicatorForm|Indicator form]]</li>
<li>[[Template:Indicator|Indicator template]]</li>
<li>[[Example:_Example_indicator|Example page using the template]]</li>
<li>[[Data quality|Data quality in WeSIS]]</li>
</ul>
</div>


| id="mp-right" class="MainPageBG" style="width:33%; border:1px solid #cedff2; padding:0; background:#f5faff; vertical-align:top;"|
<h2 id="mp-itn-h2" style="margin:0.5em; background:#cedff2; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3b0bf; color:#000; padding:0.2em 0.4em;">Further resources</h2>

<div id="mp-tfa" style="padding:0.1em 0.6em;">
<ul>
<li>[[Country related documents]]</li>
<li>[[Help:Tutorials|WeSISpedia help page]]</li>
<li>[[Copyright_issues|Collection of copyright issues]]</li>
</ul>
</div>
|}

Global economic competition in export-sectors

2026-06-19T09:30:00Z

Nils Duepont:

{{IndicatorForm
|datatype = Numeric
|scale = Metric
|valuelabels = Not applicable
|techname = comp_sector
|category= Economic relations
|label = Competition on export-marktes
|relatedindicators =
<ul>
<li>[[Global economic competition on export-markets]]</li>
</ul>
|description = This indicator captures economic competition between countries by using export data. Competition on export-markets of two countries A and B is defined in terms of the distribution of their exports among the respective export partners. If the trade volumes of A and B are similarly distributed among the sales markets, then there is a high degree of competition.
|codingrules = We used export data of the United Nations Comtrade dataset (https://comtrade.un.org/) for 164 countries from 1962 to 2018. The country sample and the calculation of the indicator (including the Phyton script) is described in detail in Mossig et al. 2021.
|citation = Mossig, Ivo, Hendrik Heuer, Michael Lischka, and Fabian Besche-Truthe. 2021. "Measuring global competition in export markets and export sectors." SFB 1342 Technical Paper Series 8/2021. Bremen: SFB 1342. http://dx.doi.org/10.26092/elib/1533
|relatedpublications =
|projectmanagers = Ivo Mossig, Hendrik Heuer, Michael Lischka (A01), Fabian Besche-Truhe (A05)
|datarelease = <ul><li>Version 0.001: Initial release</li></ul>
|revisions = No revisions yet
|sources =
<ul>
<li>https://comtrade.un.org/</li>
</ul>
}}

Global economic competition on export-markets

2026-06-19T09:29:46Z

Nils Duepont:

{{IndicatorForm
|datatype = Numeric
|scale = Metric
|valuelabels = Not applicable
|techname = comp_exportmarkets
|category= Economic relations
|label = Competition on export-marktes
|relatedindicators =
<ul>
<li>[[Global economic competition in export-sectors]]</li>
</ul>
|description = This indicator captures economic competition between countries by using export data. Competition on export-markets of two countries A and B is defined in terms of the distribution of their exports among the respective export partners. If the trade volumes of A and B are similarly distributed among the sales markets, then there is a high degree of competition.

|codingrules = We used export data of the United Nations Comtrade dataset (https://comtrade.un.org/) for 164 countries from 1962 to 2018. The country sample and the calculation of the indicator (including the Phyton script) is described in detail in Mossig et al. 2021.

|citation = Mossig, Ivo, Hendrik Heuer, Michael Lischka, and Fabian Besche-Truthe. 2021. "Measuring global competition in export markets and export sectors." SFB 1342 Technical Paper Series 8/2021. Bremen: SFB 1342. http://dx.doi.org/10.26092/elib/1533
|relatedpublications =
|projectmanagers = Ivo Mossig, Hendrik Heuer, Michael Lischka (A01), Fabian Besche-Truhe (A05)
|datarelease = <ul><li>Version 0.001: Initial release</li></ul>
|revisions = No revisions yet
|sources =
<ul>
<li>https://comtrade.un.org/</li>
</ul>
}}

Global economic competition on export-markets

2026-06-19T09:29:10Z

Nils Duepont:

{{IndicatorForm
|datatype = Numeric
|scale = Metric
|valuelabels = Not applicable
|techname = comp_exportmarkets
|category= Economic relations
|label = Competition on export-marktes
|relatedindicators =
<ul>
<li>[[Global economic competition in export-sectors]]</li>
</ul>
|description = This indicator captures economic competition between countries by using export data. Competition on export-markets of two countries A and B is defined in terms of the distribution of their exports among the respective export partners. If the trade volumes of A and B are similarly distributed among the sales markets, then there is a high degree of competition.

|codingrules = We used export data of the United Nations Comtrade dataset (https://comtrade.un.org/) for 164 countries from 1962 to 2018. The country sample and the calculation of the indicator (including the Phyton script) is described in detail in Mossig et al. 2021.

|citation = Mossig, Ivo, Hendrik Heuer, Michael Lischka, and Fabian Besche-Truthe. 2021. "Measuring global competition in export markets and export sectors." SFB 1342 Technical Paper Series 8/2021. Bremen: SFB 1342. http://dx.doi.org/10.26092/elib/1533
|relatedpublications =
|projectmanagers = Ivo Mossig (A01), Hendrik Heuer (A01), Michael Lischka (A01), Fabian Besche-Truhe (A05)
|datarelease = <ul><li>Version 0.001: Initial release</li></ul>
|revisions = No revisions yet
|sources =
<ul>
<li>https://comtrade.un.org/</li>
</ul>
}}

Global economic competition in export-sectors

2026-06-19T09:28:36Z

Nils Duepont:

{{IndicatorForm
|datatype = Numeric
|scale = Metric
|valuelabels = Not applicable
|techname = comp_sector
|category= Economic relations
|label = Competition on export-marktes
|relatedindicators =
<ul>
<li>[[Global economic competition on export-markets]]</li>
</ul>
|description = This indicator captures economic competition between countries by using export data. Competition on export-markets of two countries A and B is defined in terms of the distribution of their exports among the respective export partners. If the trade volumes of A and B are similarly distributed among the sales markets, then there is a high degree of competition.
|codingrules = We used export data of the United Nations Comtrade dataset (https://comtrade.un.org/) for 164 countries from 1962 to 2018. The country sample and the calculation of the indicator (including the Phyton script) is described in detail in Mossig et al. 2021.
|citation = Mossig, Ivo, Hendrik Heuer, Michael Lischka, and Fabian Besche-Truthe. 2021. "Measuring global competition in export markets and export sectors." SFB 1342 Technical Paper Series 8/2021. Bremen: SFB 1342. http://dx.doi.org/10.26092/elib/1533
|relatedpublications =
|projectmanagers = Ivo Mossig (A01), Hendrik Heuer (A01), Michael Lischka (A01), Fabian Besche-Truhe (A05)
|datarelease = <ul><li>Version 0.001: Initial release</li></ul>
|revisions = No revisions yet
|sources =
<ul>
<li>https://comtrade.un.org/</li>
</ul>
}}

Global economic competition in export-sectors

2026-06-19T09:27:19Z

Nils Duepont:

{{Indicator
|datatype = Numeric
|scale = Metric
|valuelabels = Not applicable
|techname = comp_sector
|category= [[Economic relations]]
|label = Competition on export-marktes
|relatedindicators =
<ul>
<li>[[Global economic competition on export-markets]]</li>
</ul>

|description = This indicator captures economic competition between countries by using export data. Competition on export-markets of two countries A and B is defined in terms of the distribution of their exports among the respective export partners. If the trade volumes of A and B are similarly distributed among the sales markets, then there is a high degree of competition.

|codingrules = We used export data of the United Nations Comtrade dataset (https://comtrade.un.org/) for 164 countries from 1962 to 2018. The country sample and the calculation of the indicator (including the Phyton script) is described in detail in Mossig et al. 2021.

|citation = Mossig, Ivo, Hendrik Heuer, Michael Lischka, and Fabian Besche-Truthe. 2021. "Measuring global competition in export markets and export sectors." SFB 1342 Technical Paper Series 8/2021. Bremen: SFB 1342. http://dx.doi.org/10.26092/elib/1533
|relatedpublications =
|projectmanagers = Ivo Mossig (A01), Hendrik Heuer (A01), Michael Lischka (A01), Fabian Besche-Truhe (A05)
|datarelease = <ul><li>Version 0.001: Initial release</li></ul>
|revisions = No revisions yet
|sources = https://comtrade.un.org/
}}

Global economic competition in export-sectors

2026-06-19T09:27:05Z

Nils Duepont:

{{Indicator
|datatype = Numeric
|scale = Metric
|valuelabels = Not applicable
|techname = comp_sector
|category= [[Economic relations]]
|label = Competition on export-marktes
|relatedindicators =
<ul>
<li>[[Global economic competition on export-markets]]</li>
</ul>

|description = This indicator captures economic competition between countries by using export data. Competition on export-markets of two countries A and B is defined in terms of the distribution of their exports among the respective export partners. If the trade volumes of A and B are similarly distributed among the sales markets, then there is a high degree of competition.

|codingrules = We used export data of the United Nations Comtrade dataset (https://comtrade.un.org/) for 164 countries from 1962 to 2018. The country sample and the calculation of the indicator (including the Phyton script) is described in detail in Mossig et al. 2021.

|citation = Mossig, Ivo, Hendrik Heuer, Michael Lischka, and Fabian Besche-Truthe. 2021. "Measuring global competition in export markets and export sectors." SFB 1342 Technical Paper Series/8/2021. Bremen: SFB 1342. http://dx.doi.org/10.26092/elib/1533
|relatedpublications =
|projectmanagers = Ivo Mossig (A01), Hendrik Heuer (A01), Michael Lischka (A01), Fabian Besche-Truhe (A05)
|datarelease = <ul><li>Version 0.001: Initial release</li></ul>
|revisions = No revisions yet
|sources = https://comtrade.un.org/
}}

Global economic competition in export-sectors

2026-06-19T09:26:05Z

Nils Duepont:

{{Indicator
|datatype = Numeric
|scale = Metric
|valuelabels = Not applicable
|techname = comp_sector
|category= [[Economic relations]]
|label = Competition on export-marktes
|relatedindicators =
<ul>
<li>[[Global economic competition on export-markets]]</li>
</ul>

|description = This indicator captures economic competition between countries by using export data. Competition on export-markets of two countries A and B is defined in terms of the distribution of their exports among the respective export partners. If the trade volumes of A and B are similarly distributed among the sales markets, then there is a high degree of competition.

|codingrules = We used export data of the United Nations Comtrade dataset (https://comtrade.un.org/) for 164 countries from 1962 to 2018. The country sample and the calculation of the indicator (including the Phyton script) is described in detail in Mossig et al. 2021.

|citation = Mossig, Ivo, Hendrik Heuer, Michael Lischka, and Fabian Besche-Truthe. 2021. "Measuring global competition in export markets and export sectors." Bremen: SFB 1342. http://dx.doi.org/10.26092/elib/1533
|relatedpublications =
|projectmanagers = Ivo Mossig (A01), Hendrik Heuer (A01), Michael Lischka (A01), Fabian Besche-Truhe (A05)
|datarelease = <ul><li>Version 0.001: Initial release</li></ul>
|revisions = No revisions yet
|sources = https://comtrade.un.org/
}}

Colony of Belgium, ever

2026-06-19T09:18:57Z

Nils Duepont:

{{IndicatorForm
|datatype = Numeric
|scale = Binary
|valuelabels = <ul><li>0 = Never a Belgian colony</li><li>1 = Was a Belgian colony</li></ul>
|techname = col_ever_belgium
|category= Violent conflicts and colonial dependencies|Violent conflicts and colonial dependencies
|subcategory = Colonialism
|label = Colony of Belgium, ever
|relatedindicators =
<ul>
<li>[[Colony of Britain, ever]]</li>
</ul>
|description = This indicator catpures if at any point in the focal country's history it was a colony of Belgium (=1), or not (=0).
|codingrules = For detailed coding rules see the codebook of Becker 2019.
|citation = Becker, Bastian. 2019. "Introducing COLDAT: The Colonial Dates Dataset." SOCIUM SFB 1342 Working Papers/2/2019. Bremen: SOCIUM, SFB 1342. https://doi.org/10.7910/DVN/T9SDEW.
|relatedpublications = related publications
|projectmanagers = Bastian Becker
|datarelease = <ul><li>Version 0.001: Initial release</li></ul>
|revisions = No revisions yet
|sources = <ul><li>Becker, Bastian. 2019. ''Colonial Dates Dataset (COLDAT)''. Harvard Dataverse, V2. https://doi.org/10.7910/DVN/T9SDEW</li></ul>
}}

Colony of Belgium, ever

2026-06-19T09:16:47Z

Nils Duepont:

{{IndicatorForm
|datatype = Numeric
|scale = Binary
|valuelabels = <ul><li>0 = Never a Belgian colony</li><li>1 = Was a Belgian colony</li></ul>
|techname = col_ever_belgium
|category= Violent conflicts and colonial dependencies|Violent conflicts and colonial dependencies
|subcategory = Colonialism
|label = Colony of Belgium, ever
|relatedindicators =
<ul>
<li>[[Colony of Britain, ever]]</li>
</ul>
|description = This indicator catpures if at any point in the focal country's history it was a colony of Belgium.
|codingrules = For detailed coding rules see the codebook of Becker 2019.
|citation = Becker, Bastian. 2019. "Introducing COLDAT: The Colonial Dates Dataset." SOCIUM SFB 1342 Working Papers/2/2019. Bremen: SOCIUM, SFB 1342. https://doi.org/10.7910/DVN/T9SDEW.
|relatedpublications = related publications
|projectmanagers = Bastian Becker
|datarelease = <ul><li>Version 0.001: Initial release</li></ul>
|revisions = No revisions yet
|sources = <ul><li>Becker, Bastian. 2019. ''Colonial Dates Dataset (COLDAT)''. Harvard Dataverse, V2. https://doi.org/10.7910/DVN/T9SDEW</li></ul>
}}

Colony of Belgium, ever

2026-06-19T09:15:41Z

Nils Duepont:

{{IndicatorForm
|datatype = Numeric
|scale = Binary
|valuelabels = <ul><li>0 = Never a Belgian colony</li><li>1 = Was a Belgian colony</li></ul>
|techname = col_ever_belgium
|category= Violent conflicts and colonial dependencies|Violent conflicts and colonial dependencies
|subcategory = Colonialism
|label = Colony of Belgium, ever
|relatedindicators =
<ul>
<li>Colony of Britain, ever</li>
</ul>
|description = This indicator catpures if at any point in the focal country's history it was a colony of Belgium.
|codingrules = For detailed coding rules see the codebook of Becker 2019.
|citation = Becker, Bastian. 2019. "Introducing COLDAT: The Colonial Dates Dataset." SOCIUM SFB 1342 Working Papers/2/2019. Bremen: SOCIUM, SFB 1342. https://doi.org/10.7910/DVN/T9SDEW.
|relatedpublications = related publications
|projectmanagers = Bastian Becker
|datarelease = <ul><li>Version 0.001: Initial release</li></ul>
|revisions = No revisions yet
|sources = <ul><li>Becker, Bastian. 2019. ''Colonial Dates Dataset (COLDAT)''. Harvard Dataverse, V2. https://doi.org/10.7910/DVN/T9SDEW</li></ul>
}}

First Year of Belgian Colonial Rule

2026-06-19T09:15:02Z

Nils Duepont:

{{Indicator
|datatype = Numeric
|scale = Date
|valuelabels = <ul><li>YYYY = First year under Belgian colonialism </li><li>NA = Never a Belgian colony</li></ul>
|techname = col_start_belgium_max
|category= [[Violent conflicts and colonial dependencies|Violent conflicts and colonial dependencies]]
|subcategory = Colonialism
|label = First Year of Belgian Colonial Rule, last date version
|relatedindicators =
|description = First year during which country was colonized by Belgium. Based on last date aggregation.
|codingrules = year, YYYY format. As there are many sources aggregation here "...is the last date mentioned
across all sources, i.e. all sources agree that a certain territory has become/ceased to be a European colony." (Becker 2019, 9).
|citation = Becker, Bastian. 2019. "Introducing COLDAT: The Colonial Dates Dataset." SOCIUM SFB 1342 Working Papers/2/2019. Bremen: SOCIUM, SFB 1342. https://doi.org/10.7910/DVN/T9SDEW.
|relatedpublications = related publications
|projectmanagers = project managers
|datarelease = <ul><li>Version 0.001: Initial release</li></ul>
|revisions = No revisions yet
|sources = sources
}}

Colony of Belgium, ever

2026-06-19T09:12:25Z

Nils Duepont:

{{IndicatorForm
|datatype = Numeric
|scale = Binary
|valuelabels = <ul><li>0 = Never a Belgian colony</li><li>1 = Was a Belgian colony</li></ul>
|techname = col_ever_belgium
|category= Violent conflicts and colonial dependencies|Violent conflicts and colonial dependencies
|subcategory = Colonialism
|label = Colony of Belgium, ever
|relatedindicators =
|description = This indicator catpures if at any point in the focal country's history it was a colony of Belgium.
|codingrules = For detailed coding rules see the codebook of Becker 2019.
|citation = Becker, Bastian. 2019. ''Colonial Dates Dataset (COLDAT)''. Harvard Dataverse, V2. https://doi.org/10.7910/DVN/T9SDEW
|relatedpublications = related publications
|projectmanagers = Bastian Becker
|datarelease = <ul><li>Version 0.001: Initial release</li></ul>
|revisions = No revisions yet
|sources = <ul><li>Becker, Bastian. 2019. ''Colonial Dates Dataset (COLDAT)''. https://doi.org/10.7910/DVN/T9SDEW, Harvard Dataverse, V2</li></ul>
}}

Colony of Belgium, ever

2026-06-19T09:11:19Z

Nils Duepont:

{{IndicatorForm
|datatype = Numeric
|scale = Binary
|valuelabels = <ul><li>0 = Never a Belgian colony</li><li>1 = Was a Belgian colony</li></ul>
|techname = col_ever_belgium
|category= Violent conflicts and colonial dependencies|Violent conflicts and colonial dependencies
|subcategory = Colonialism
|label = Colony of Belgium, ever
|relatedindicators =
|description = This indicator catpures if at any point in the focal country's history it was a colony of Belgium.
|codingrules = For detailed coding rules see the codebook of Becker 2019.
|citation = Becker, Bastian. 2019. ''Colonial Dates Dataset (COLDAT)''. https://doi.org/10.7910/DVN/T9SDEW, Harvard Dataverse, V2
|relatedpublications = related publications
|projectmanagers = Bastian Becker
|datarelease = <ul><li>Version 0.001: Initial release</li></ul>
|revisions = No revisions yet
|sources = <ul><li>Becker, Bastian. 2019. ''Colonial Dates Dataset (COLDAT)''. https://doi.org/10.7910/DVN/T9SDEW, Harvard Dataverse, V2</li></ul>
}}

Colony of Belgium, ever

2026-06-19T09:11:05Z

Nils Duepont:

{{IndicatorForm
|datatype = Numeric
|scale = Binary
|valuelabels = <ul><li>0 = Never a Belgian colony</li><li>1 = Was a Belgian colony</li></ul>
|techname = col_ever_belgium
|category= [[Violent conflicts and colonial dependencies|Violent conflicts and colonial dependencies]]
|subcategory = Colonialism
|label = Colony of Belgium, ever
|relatedindicators =
|description = This indicator catpures if at any point in the focal country's history it was a colony of Belgium.
|codingrules = For detailed coding rules see the codebook of Becker 2019.
|citation = Becker, Bastian. 2019. ''Colonial Dates Dataset (COLDAT)''. https://doi.org/10.7910/DVN/T9SDEW, Harvard Dataverse, V2
|relatedpublications = related publications
|projectmanagers = Bastian Becker
|datarelease = <ul><li>Version 0.001: Initial release</li></ul>
|revisions = No revisions yet
|sources = <ul><li>Becker, Bastian. 2019. ''Colonial Dates Dataset (COLDAT)''. https://doi.org/10.7910/DVN/T9SDEW, Harvard Dataverse, V2</li></ul>
}}

Proportion of population below international poverty line, bothsex

2026-06-19T08:54:55Z

Nils Duepont:

{{IndicatorForm
|datatype = Numeric
|scale = Metric
|valuelabels = Not applicable
|techname = sdg_01_11a_prop_pop_below_int_povline_bothsex
|category = Sustainable development goals|Sustainable development goals
|label = Proportion of population below international poverty line, bothsex
|relatedindicators = Not applicable
|description = This indicator measures the proportion of the population living below the international poverty line in percent. It is part of monitoring the achivement and progress towards the UN Sustainable Development Goals.
|codingrules =
<ul>
<li>For detailed information and coding rules see https://unstats.un.org/wiki/spaces/SDGeHandbook/pages/34505092/Home</li>
</ul>
|citation = United Nations Department of Economic and Social Affairs. 2024. ''SDG Indicators Database''. https://unstats.un.org/sdgs/dataportal/database.
|relatedpublications =
<ul>
<li>United Nations Department of Economic and Social Affairs. 2025. ''The Sustainable Development Goals Report 2025''. New York. https://unstats.un.org/sdgs/report/2025/</li>
</ul>
|projectmanagers = Marius Bode, Hannes Salzmann, Carmen Cordes, Nils Düpont (INF)
|datarelease =
<ul>
<li>Version 0.001: Initial release</li>
</ul>
|revisions = No revisions yet
|sources =
<ul>
<li>United Nations Department of Economic and Social Affairs. 2024. ''SDG Indicators Database''. https://unstats.un.org/sdgs/dataportal/database.</li>
<li>United Nations Department of Economic and Social Affairs. 2026. ''SDG Indicators Database''. https://unstats.un.org/sdgs/dataportal/database.</li>
</ul>
}}

Proportion of population below international poverty line, bothsex

2026-06-19T08:50:53Z

Nils Duepont:

{{IndicatorForm
|datatype = Numeric
|scale = Metric
|valuelabels = Not applicable
|techname = sdg_01_11a_prop_pop_below_int_povline_bothsex
|category= [[Sustainable development goals|Sustainable development goals]]
|label = Proportion of population below international poverty line, bothsex
|relatedindicators = Not applicable
|description = This indicator measures the proportion of the population living below the international poverty line in percent. It is part of monitoring the achivement and progress towards the UN Sustainable Development Goals.
|codingrules =
<ul>
<li>For detailed information and coding rules see https://unstats.un.org/wiki/spaces/SDGeHandbook/pages/34505092/Home</li>
</ul>
|citation = United Nations Department of Economic and Social Affairs. 2024. ''SDG Indicators Database''. https://unstats.un.org/sdgs/dataportal/database.
|relatedpublications =
<ul>
<li>United Nations Department of Economic and Social Affairs. 2025. ''The Sustainable Development Goals Report 2025''. New York. https://unstats.un.org/sdgs/report/2025/</li>
</ul>
|projectmanagers = Marius Bode, Hannes Salzmann, Carmen Cordes, Nils Düpont (INF)
|datarelease =
<ul>
<li>Version 0.001: Initial release</li>
</ul>
|revisions = No revisions yet
|sources =
<ul>
<li>United Nations Department of Economic and Social Affairs. 2024. ''SDG Indicators Database''. https://unstats.un.org/sdgs/dataportal/database.</li>
<li>United Nations Department of Economic and Social Affairs. 2026. ''SDG Indicators Database''. https://unstats.un.org/sdgs/dataportal/database.</li>
</ul>
}}

Proportion of population below international poverty line, bothsex

2026-06-19T08:47:54Z

Nils Duepont:

{{Indicator
|datatype = Numeric
|scale = Metric
|valuelabels = Not applicable
|techname = sdg_01_11a_prop_pop_below_int_povline_bothsex
|category= [[Sustainable development goals|Sustainable development goals]]
|label = Proportion of population below international poverty line, bothsex
|relatedindicators = Not applicable
|description = This indicator measures the proportion of the population living below the international poverty line in percent. It is part of monitoring the achivement and progress towards the UN Sustainable Development Goals.
|codingrules =
<ul>
<li>For detailed information and coding rules see https://unstats.un.org/wiki/spaces/SDGeHandbook/pages/34505092/Home</li>
</ul>
|citation = United Nations Department of Economic and Social Affairs. 2024. ''SDG Indicators Database''. https://unstats.un.org/sdgs/dataportal/database.
|relatedpublications =
<ul>
<li> United Nations Department of Economic and Social Affairs. 2025. ''The Sustainable Development Goals Report 2025''. New York. https://unstats.un.org/sdgs/report/2025/</li>
</ul>
|projectmanagers = Marius Bode, Hannes Salzmann, Carmen Cordes, Nils Düpont (INF)
|datarelease = Version 0.001: Initial release.
|revisions = No revisions yet
|sources =
<ul>
<li>United Nations Department of Economic and Social Affairs. 2024. ''SDG Indicators Database''. https://unstats.un.org/sdgs/dataportal/database.</li>
<li>United Nations Department of Economic and Social Affairs. 2026. ''SDG Indicators Database''. https://unstats.un.org/sdgs/dataportal/database.</li>
</ul>
}}

Education IO membership network

2026-06-15T09:19:48Z

Nils Duepont:

{{IndicatorForm
|datatype=Numeric
|scale=Ordinal
|valuelabels=<ul><li>0 = No membership</li><li>1 = Full membership</li><li>99 = IGO not in existence</li></ul>
|techname=polilink_igo_mem_edu_nw
|category=Political institutional linkages
|label=Education IO Membership Network
|relatedindicators=<ul>
<li>[[UN membership]]</li>
<li>[[ILO membership]]</li>
<li>[[IMF membership]]</li>
<li>[[WHO membership]]</li>
</ul>
|description=This dyadic network captures the membership of countries in international and intergovernmental organizations that are active in education. Included are the following 28 organisations:

* Arab Bureau of Education for the Gulf States (ABEGS),
* Asian Development Bank (ADB),
* Arab League of Educational, Cultural and Scientific Organisation (ALECSO),
* Asia-Pacific Economic Cooperation (APEC),
* Association of Southeast Asian Nations (ASEAN),
* African Union (AU),
* Caribbean Community (CARICOM),
* Asia-Europe Foundation (ASEF),
* Council of the Baltic Sea States (CBSS),
* Commonwealth of Independent States (CIS),
* Economic Community of Central African States (ECCAS),
* European Free Trade Association (EFTA),
* European Union (EU),
* Southeast Asian Ministers of Education Organization (SEAMEO),
* South Asian Association for Regional Cooperation (SAARC),
* Intergovernmental Foundation for Educational, Scientific and Cultural Cooperation (IFESCCO),
* Organization of American States (OAS),
* Union of South American Nations (UNASUR),
* Southern Common Market (Mercado Común del Sur) (Mercosur),
* Organisation of Eastern Caribbean States (OECS),
* Inter-American Development Bank (IADB),
* African Development Bank (AfDB),
* Islamic World Educational, Scientific and Cultural Organization (ICESCO),
* Organization of Ibero-American States for Education, Science and Culture (OEI),
* International Labour Organization (ILO),
* Organization for Economic Cooperation and Development (OECD),
* World Bank (WB),
* United Nations Educational, Scientific and Cultural Organization (UNESCO)
|codingrules=<ul>
<li>The dyadic, ordinal indicator captures whether (=1) or not (=0) a country shares a tie with the intergovernmental organization in the focal year.</li>
<li>Years in which the intergovernmental organization was not existent/not yet founded are coded as <code>99</code>.</li>
<li>Unless noted otherwise, membership is reported valid as of December 31st of a given year.</li>
</ul>
|citation=Niemann, Dennis, and Kerstin Martens. 2021. "Global discourses, regional framings and individual showcasing: Analyzing the world of education IOs." In ''International Organizations in Global Social Governance'', eds. Kerstin Martens, Dennis Niemann, and Alexandra Kaasch. Basingstoke: Palgrave Macmillan, 163–186. https://doi.org/10.1007/978-3-030-65439-9_7
|relatedpublications=
|projectmanagers=Kerstin Martens, Dennis Niemann, Michael Windzio, Helen Seitzer, Fabian Besche-Truthe (A05), Nils Düpont, Carmen Cordes, Marius Bode (INF)
|datarelease=
<ul>
<li>Version 0.001: Initial release</li>
</ul>
|revisions=No revisions yet
|sources=
<ul>
<li>Union of International Associations. Various years. ''Yearbook of International Organizations''. Brussels: Union of International Associations Publishing.</li>
<li>Pevehouse, Jon C.W., Timothy Nordstron, Roseanne W. McManus, and Anne Spencer Jamison. 2019. "Correlates of War Intergovernmental Organizations (v3) [Dataset]". https://correlatesofwar.org/data-sets/igos/</li>
</ul>
}}

Education IO membership network

2026-06-15T09:16:57Z

Nils Duepont:

{{IndicatorForm
|datatype=Numeric
|scale=Ordinal
|valuelabels=<ul><li>0 = No membership</li><li>1 = Full membership</li><li>99 = IGO not in existence</li></ul>
|techname=polilink_igo_mem_edu_nw
|category=Political institutional linkages
|label=Education IO Membership Network
|relatedindicators=<ul>
<li>[[UN membership]]</li>
<li>[[ILO membership]]</li>
<li>[[IMF membership]]</li>
<li>[[WHO membership]]</li>
</ul>
|description=This network entails the membership of countries in international and intergovernmental organizations that are active in education. Included are the following 28 organisations:

* Arab Bureau of Education for the Gulf States (ABEGS),
* Asian Development Bank (ADB),
* Arab League of Educational, Cultural and Scientific Organisation (ALECSO),
* Asia-Pacific Economic Cooperation (APEC),
* Association of Southeast Asian Nations (ASEAN),
* African Union (AU),
* Caribbean Community (CARICOM),
* Asia-Europe Foundation (ASEF),
* Council of the Baltic Sea States (CBSS),
* Commonwealth of Independent States (CIS),
* Economic Community of Central African States (ECCAS),
* European Free Trade Association (EFTA),
* European Union (EU),
* Southeast Asian Ministers of Education Organization (SEAMEO),
* South Asian Association for Regional Cooperation (SAARC),
* Intergovernmental Foundation for Educational, Scientific and Cultural Cooperation (IFESCCO),
* Organization of American States (OAS),
* Union of South American Nations (UNASUR),
* Southern Common Market (Mercado Común del Sur) (Mercosur),
* Organisation of Eastern Caribbean States (OECS),
* Inter-American Development Bank (IADB),
* African Development Bank (AfDB),
* Islamic World Educational, Scientific and Cultural Organization (ICESCO),
* Organization of Ibero-American States for Education, Science and Culture (OEI),
* International Labour Organization (ILO),
* Organization for Economic Cooperation and Development (OECD),
* World Bank (WB),
* United Nations Educational, Scientific and Cultural Organization (UNESCO)
|codingrules=<ul>
<li>The ordinal indicator captures whether (=1) or not (=0) a country shares a tie to the intergovernmental organization in the focal year.</li>
<li>Years in which the intergovernmental organization was not existent/not yet founded are coded as <code>99</code>.</li>
<li>Unless noted otherwise, membership is reported valid as of December 31st of a given year.</li>
</ul>
|citation=Niemann, Dennis, and Kerstin Martens. 2021. "Global discourses, regional framings and individual showcasing: Analyzing the world of education IOs." In ''International Organizations in Global Social Governance'', eds. Kerstin Martens, Dennis Niemann, and Alexandra Kaasch. Basingstoke: Palgrave Macmillan, 163–186. https://doi.org/10.1007/978-3-030-65439-9_7
|relatedpublications=
|projectmanagers=Kerstin Martens, Dennis Niemann, Michael Windzio, Helen Seitzer, Fabian Besche-Truthe (A05), Nils Düpont, Carmen Cordes, Marius Bode (INF)
|datarelease=
<ul>
<li>Version 0.001: Initial release</li>
</ul>
|revisions=No revisions yet
|sources=
<ul>
<li>Union of International Associations. Various years. ''Yearbook of International Organizations''. Brussels: Union of International Associations Publishing.</li>
<li>Pevehouse, Jon C.W., Timothy Nordstron, Roseanne W. McManus, and Anne Spencer Jamison. 2019. "Correlates of War Intergovernmental Organizations (v3) [Dataset]". https://correlatesofwar.org/data-sets/igos/</li>
</ul>
}}

AfDB membership

2026-06-15T09:05:57Z

Nils Duepont:

SAARC membership

2026-06-15T09:05:50Z

Nils Duepont:

OEI membership

2026-06-15T09:05:41Z

Nils Duepont:

OECS membership

2026-06-15T09:05:34Z

Nils Duepont:

OAS membership

2026-06-15T09:05:23Z

Nils Duepont:

Mercosur membership

2026-06-15T09:05:11Z

Nils Duepont: