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In spite of a contribution of 481 million dollars in the form of American economic aid, our gold reserves, after increasing by 90 million dollars in 1950, fell in 1951 by 67 millions. Our foreign exchange holdings which in 1950 had increased by 67 millions, showed a drop of 158 millions in 1951. A credit balance of 10 million dollars in our bilateral payments agreements during 1950 was followed in 1951 by a trend in the opposite direction, to the tune of 29 million dollars. (...) Thus, Francels net cumulative position in the European Payments Union, after showing a debit of 197 million accounting units at 31 Docember 1951, rose to: - 300 million accounting units debit by the end of January - 429 million accounting units debit by the end of February - 458 million accounting units debit by the end of' March 14.
Language:English
Score: 397321.88 - https://www.wto.org/gatt_docs/English/SULPDF/91850229.pdf
Data Source: un
UNHCR 2020 Global Trends Report – key data: 82.4 million people forcibly displaced globally (79.5 million in 2019) – 4 per cent increase 26.44 million refugees (26.0 million in 2019) including: 20.7 million refugees under UNHCR’s mandate (20.4 million in 2019) 5.7 million Palestine refugees under UNRWA’s mandate (5.6 million in 2019) 48.0 million internally displaced people (45.7 million in 2019) 4.1 million asylum-seekers (4.1 million in 2019) 3.9 million Venezuelans displaced abroad (3.6 million in 2019) 2020 is the ninth year of uninterrupted rise in forced displacement worldwide. Today, one per cent of humanity is displaced and there are twice as many forcibly displaced people than in 2011 when the total was just under 40 million. More than two thirds of all people who fled abroad came from just five countries: Syria (6.7 million), Venezuela (4.0 million), Afghanistan (2.6 million), South Sudan (2.2 million) and Myanmar (1.1 million). (...) For the seventh year in a row, Turkey hosted the largest refugee population worldwide (3.7 million refugees), followed by Colombia (1.7 million, including Venezuelans displaced abroad), Pakistan (1.4 million), Uganda (1.4 million) and Germany (1.2 million).
Language:English
Score: 397285.6 - https://www.unhcr.org/neu/6129...d-of-soaring-displacement.html
Data Source: un
UNICEF estimates that more than 34 million children living through conflict and disaster lack access to child protection services, including 6.6 million children in Yemen, 5.5 million children in Syria and 4 million children in the Democratic Republic of the Congo (DRC). (...) The five largest individual appeals are for Syrian refugees and host communities in Egypt, Jordan, Lebanon, Iraq and Turkey (US$ 904 million); Yemen (US$ 542.3 million); The Democratic Republic of the Congo (US$ 326.1 million); Syria (US$ 319.8 million) and South Sudan (US$ 179.2 million). In East Asia and Pacific Region, UNICEF is seeking US$100.9 million for Myanmar (US$59.1 million); Democratic People’s Republic of Korea (US$19.5 million) and humanitarian support across the region (US$22.3 million). 
Language:English
Score: 397200.63 - https://www.unicef.org/eap/pre...ion-children-affected-conflict
Data Source: un
Outcome 2 Provisional programme expenditure, 2014-2016 Total: $1,568 million (13% of total) 2014: $606 million 2015: $529 million 2016:$433 million [VALUE]Million [PERCENTAGE] [VALUE]Million [PERCENTAGE] [VALUE]Million [PERCENTAGE] [VALUE]Million [PERCENTAGE] 2014-16 Regular resources 2014-16 Programme government 2014-16 Vertical funds 2014-16 Bilateral/Multilateral 218.41581800999995 238.20018325999999 183.93206640000008 927.21318669999994 Outcome 3 Provisional programme expenditure, 2014-2016 Total: $4,300 million (34% of total) 2014: $1,484 million 2015: $1,459 million 2016:$1,357 million [VALUE] Million [PERCENTAGE] [VALUE] Million [PERCENTAGE] [VALUE] Million [PERCENTAGE] [VALUE] Million [PERCENTAGE] 2014-16 Regular resources 2014-16 Programme government 2014-16 Vertical funds 2014-16 Bilateral/Multilateral 171.37423344999999 734.07373269000016 1193.9763703199999 2200.9258583199999 Outcome 4 Provisional programme expenditure, 2014-2016 Total: $83 million (1% of total) 2014: $31 million 2015: $33 million 2016:$19 million [VALUE] Million [PERCENTAGE] [VALUE] Million [PERCENTAGE] [VALUE] Million [PERCENTAGE] 2014-16 Regular resources 2014-16 Programme government 2014-16 Bilateral/Multilateral 26.612340239999998 2.8168740799999998 53.230876220000006 Outcome 5 Provisional programme expenditure, 2014-2016 Total: $724 million (6% of total) 2014: $252 million 2015: $256 million 2016:$216 million [VALUE] Million [PERCENTAGE] [VALUE] Million [PERCENTAGE] [VALUE] Million [PERCENTAGE] [VALUE] Million [PERCENTAGE] 2014-16 Regular resources 2014-16 Programme government 2014-16 Vertical funds 2014-16 Bilateral/Multilateral 116.97592483 59.738698159999998 79.015386610000007 467.88385419999997 Outcome 6 Provisional programme expenditure, 2014-2016 Total: $1,011 million (8% of total) 2014: $281 million 2015: $331 million 2016: $399 million [VALUE] Million [PERCENTAGE] [VALUE] Million [PERCENTAGE] [VALUE] Million [PERCENTAGE] 2014-16 Regular resources 2014-16 Programme government 2014-16 Bilateral/Multilateral 64.04682163999999 18.542371789999997 927.45670439999981 Outcome 7 Provisional programme expenditure, 2014-2016 Total: $569 million (5% of total) 2014: $215 million 2015: $228 million 2016:$127 million [VALUE] Million [PERCENTAGE] [VALUE] Million [PERCENTAGE] [VALUE] Million [PERCENTAGE] [VALUE] Million [PERCENTAGE] 2014-16 Regular resources 2014-16 Programme government 2014-16 Vertical funds 2014-16 Bilateral/Multilateral 151.20446884 252.79841791999996 12.914076250000001 152.51432421999999 Number of supported countries and 2014-2016 expenditure ($ US dollars millions) by Strategic Plan output Number of supported countries (Dec 2016) Output 1.1 Output 1.2 Output 1.3 Output 1.4 Output 1.5 Output 2.1 Output 2.2 Output 2.3 Output 2.4 Output 2.5 Output 2.6 Output 3.1 Output 3.2 Output 3.3 Output 3.4 Output 3.5 Output 4.1 Output 4.2 Output 4.3 Output 4.4 Output 5.1 Output 5.2 Output 5.3 Output 5.4 Output 5.5 Output 5.6 Output 6.1 Output 6.2 Output 6.3 Output 6.4 Output 7.1 Output 7.2 Output 7.3 Output 7.4 Output 7.5 Output 7.6 Output 7.7 Output 7.8 SP Outcome 1 SP Outcome 2 SP Outcome 3 SP Outcome 4 SP Outcome 5 SP Outcome 6 SP Outcome 7 126 62 113 116 81 90 60 63 72 76 21 30 80 63 52 33 13 20 11 26 43 60 15 45 27 24 27 27 8 22 14 30 32 25 21 20 27 21 Expenditure 2014-2016: Regular Resources Output 1.1 Output 1.2 Output 1.3 Output 1.4 Output 1.5 Output 2.1 Output 2.2 Output 2.3 Output 2.4 Output 2.5 Output 2.6 Output 3.1 Output 3.2 Output 3.3 Output 3.4 Output 3.5 Output 4.1 Output 4.2 Output 4.3 Output 4.4 Output 5.1 Output 5.2 Output 5.3 Output 5.4 Output 5.5 Output 5.6 Output 6.1 Output 6.2 Output 6.3 Output 6.4 Output 7.1 Output 7.2 Output 7.3 Output 7.4 Output 7.5 Output 7.6 Output 7.7 Output 7.8 SP Outcome 1 SP Outcome 2 SP Outcome 3 SP Outcome 4 SP Outcome 5 SP Outcome 6 SP Outcome 7 187.29868984000001 18.228668679999998 45.670637280000001 47.730034600000003 22.67868570000001 90.22598107999994 25.410372869999989 29.123813509999991 37.554936220000002 24.746787879999971 11.353926449999999 26.74468203 77.101817760000003 20.30433627 32.745694200000003 14.47770319 4.4011950199999976 2.6771527700000002 4.654822529999997 14.879169920000001 15.10806693 35.049411760000012 7.46555 08399999988 29.644297279999989 15.332666529999999 14.375931489999999 32.414833689999988 14.610851200000001 1.7530233200000001 15.26811343 5.3235226999999972 13.491002999999999 40.901036690000012 17.111116510000009 7.1965197199999968 14.76162021 42.303126409999997 10.116523600000001 Expenditure 2014-2016: Local Government Output 1.1 Output 1.2 Output 1.3 Output 1.4 Output 1.5 Output 2.1 Output 2.2 Output 2.3 Output 2.4 Output 2.5 Output 2.6 Output 3.1 Output 3.2 Output 3.3 Output 3.4 Output 3.5 Output 4.1 Output 4.2 Output 4.3 Output 4.4 Output 5.1 Output 5.2 Output 5.3 Output 5.4 Output 5.5 Output 5.6 Output 6.1 Output 6.2 Output 6.3 Output 6.4 Output 7.1 Output 7.2 Output 7.3 Output 7.4 Output 7.5 Output 7.6 Output 7.7 Output 7.8 SP Outcome 1 SP Outcome 2 SP Outcome 3 SP Outcome 4 SP Outcome 5 SP Outcome 6 SP Outcome 7 477.76890185000002 436.14465231000008 134.20468600999999 86.591426650000002 80.827831060000008 66.738139250000003 33.137009239999998 47.981837209999988 62.534695399999997 26.325800019999999 1.48270214 24.406329509999971 553.90593296000054 89.616637490000002 49.858436169999997 16.28639656 0.64409795000000003 0.64087611 0.93852964000000005 0.59337037999999998 7.5964160499999958 5.8671331399999938 3.453455329999997 5.9076897900000001 1.7667120199999999 35.14729183 3.3368921999999981 4.6477648199999937 6.0065266099999972 4.5511881600000006 2.0817218 26.978659029999999 12.87370868 52.716434030000002 55.132743670000004 37.715659289999998 30.268229209999969 35.031262210000001 Expenditure 2014-2016: Vertical Fund Output 1.1 Output 1.2 Output 1.3 Output 1.4 Output 1.5 Output 2.1 Output 2.2 Output 2.3 Output 2.4 Output 2.5 Output 2.6 Output 3.1 Output 3.2 Output 3.3 Output 3.4 Output 3.5 Output 4.1 Output 4.2 Output 4.3 Output 4.4 Output 5.1 Output 5.2 Output 5.3 Output 5.4 Output 5.5 Output 5.6 Output 6.1 Output 6.2 Output 6.3 Output 6.4 Output 7.1 Output 7.2 Output 7.3 Output 7.4 Output 7.5 Output 7.6 Output 7.7 Output 7.8 SP Outcome 1 SP Outcome 2 SP Outcome 3 SP Outcome 4 SP Outcome 5 SP Outcome 6 SP Outcome 7 67.722187669999983 2.7470286800000001 421.29589148000019 252.25258935000011 113.91779911 0.28405859999999999 5.8831274000000011 0 3.3755240099999999 174.3893563900001 0 0.86682073000000004 68.333358389999958 1120.2360559199999 0 4.5401352799999932 0 0 0 0 15.104581489999999 21.43513163999998 10.701448409999999 30.330490569999998 1.4437344999999999 0 0 0.44831695999999999 0 0 5.0133073600000007 0.11415599999999999 1.5089229500000001 2.5356118400000001 1.3764664799999999 2.0423380400000002 0.32327358 0 Expenditure 2014-2016: Bilateral/Multilateral Output 1.1 Output 1.2 Output 1.3 Output 1.4 Output 1.5 Output 2.1 Output 2.2 Output 2.3 Output 2.4 Output 2.5 Output 2.6 Output 3.1 Output 3.2 Output 3.3 Output 3.4 Output 3.5 Output 4.1 Output 4.2 Output 4.3 Output 4.4 Output 5.1 Output 5.2 Output 5.3 Output 5.4 Output 5.5 Output 5.6 Output 6.1 Output 6.2 Output 6.3 Output 6.4 Output 7.1 Output 7.2 Output 7.3 Output 7.4 Output 7.5 Output 7.6 Output 7.7 Output 7.8 SP Outcome 1 SP Outcome 2 SP Outcome 3 SP Outcome 4 SP Outcome 5 SP Outcome 6 SP Outcome 7 458.64261189999979 38.853485439999993 138.49180892000001 180.14019433000001 52.13320693 604.45682433999957 74.965009640000005 57.611997509999988 107.84909215 46.737928199999999 35.592334860000001 77.713505300000023 233.48433535999999 112.20318767000001 233.21325665000001 1544.31157334 8.3634397600000003 27.155694530000002 7.2529257399999967 10.45881619 107.0257610 7 70.515020919999998 15.198534520000001 55.79512625000001 100.30885024 119.0405612 604.17246098999988 154.58293456999999 13.296465230000001 155.40484361 21.349939759999991 11.71158236 31.167858320000001 26.617879430000009 12.275517000000001 18.658839530000002 16.37960293999998 14.35310488 Outcome 1 Provisional programme expenditure, 2014-2016 Total: $3,264 million (26% of total) 2014: $1,120 million 2015: $1,089 million 2016:$1,054 million [VALUE] Million [PERCENTAGE] [VALUE] Million [PERCENTAGE] [VALUE]Million [PERCENTAGE] [VALUE] Million [PERCENTAGE] 2014-16 Regular resources 2014-16 Programme government 2014-16 Vertical funds 2014-16 Bilateral/Multilateral 321.60671609999997 1215.53749788 857.93549629000017 868.26130751999995 2
Language:English
Score: 397119.38 - https://www.undp.org/sites/g/f...ssion/dp2017-15_Annex%203.docx
Data Source: un
Current Fertility in China 17 • Fertility policy - not always work • Social change - to encourage fewer • Tempo effect – period lower than cohort • Changes in attitude and behavior •Modern contraceptive services Reasons to Be So Low 18 • Jiangsu Study: 6 counties, 525 million • Choose one: 57 % • Choose two: 42 % • Average ideal: 1.44 • 2006 National survey: 1.73 Fertility Intention and Behavior 19 Among allowed for two in Jiangsu Study •Have two: 10 % • Consider for two: 1/3 • One as ideal: 55 % • Average ideal: 1.46 Fertility Intention and Behavior 20 Studies on Two-child Policy Areas Since mid-1980s, a pop of 8.4 million 21 • Uncertain future • Cost of having children • Unfriendly environment to reproduction • Rising demand for “human capital” • Retrenchment of public support • Concentrate for few but successful Reasons for Limiting to One Child 22 • Relatively low “unwanted fertility” • Son preference via sex-selective abortion • Infecundity and sub-fecundity • Delayed marriage and childbearing Low Fertility Proximate Determinants 23 Mean Age at First Marriage by Sex, China 1970-2000 20.00 21.00 22.00 23.00 24.00 25.00 26.00 1970 1975 1980 1985 1990 1995 2000 year ag e Male Female 24 Population aging: • By 2005, age 60+: 11%, 144 million • “Get old before get rich” By mid-century • 1/3 population aged 60+ • > 100 million aged 80+ • Less than 2 labors support 1 elder Implication of Low Fertility 25 Population Structure of China, 2000 (Shaded) and 2050 8000 6000 4000 2000 0 2000 4000 6000 8000 0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85+ Population in 00,000 Males Females 26 • Children for elderly support: unfeasible • Youths migrate to cities • Rural aging is higher than urban •More than an issue of elderly care • Overall transformation of society • Reconstruction of social structure Implication of Population Aging 27 Fragile families: • Single children: 160 million • Over 1/3 households with one child • 50 % women 60+ with one child • Tragedies seen in 2008 earthquake • Fragility of the family system Implication of Low Fertility 28 Population Decline: • Intrinsic growth rate: 20 ‰ (mid-1970s) to -20 ‰ (2005) • From doubling in 30 years to halving in 30 years • Births reached historically low in 2006 • Sharp drop in births in next decades Implication of Low Fertility 2929 Reported and Projected Number of Births, China 1980-2050 0 10 20 30 1980 1990 2000 2010 2020 2030 2040 2050 Year B irt hs in M ill io n reported Projected 1987, 25.3 million 2011, 17.3 million 2000, 17.7 million 2006, 15.9 million 30 Population Decline: • Continue to decline for 50+ years • Reduce by 220 to 300 million •Median age to 50 by mid-century • Reduce size by half at end-century Implication of Low Fertility 31 Labor shortage: • Economic boom due to large labor force • Demographic dividend: 15-25% growth • Sharp decline in labor supply • From 966 million in late 2020s to 761 million in mid-century • Reduce 100 million per decade, 10 million per year Implication of Low Fertility 32 Labor shortage: • From “abundant supply” to “limited surplus” • Young labor aged 20 to 24 • Recently educated, more innovative, and active consumers • Reduce from 125 million in 2010 to only 68 million in 2020 Implication of Low Fertility 3333 Projected Trends in Young Labor Force, China 2000-2050 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 2000 2010 2020 2030 2040 2050 Year La bo r f or ce in 1 00 m ill io n 0% 2% 4% 6% 8% 10% 12% 14% 16% Pr op or tio n New labor (of age 20-24) Proportion of new labor as of entire labor force 2010, 125 million 2009, 14.9% 2020, 68 million 2020, 8.3% 2046, 8.7% 2050, 54 million 34 To assess fertility in China: • Effect of government policy • Possible underreporting of births • Empirical studies by various scholars • Using various methods and data sets • Reach similar conclusion of around 1.5 Concluding Remarks 35 Reasons to be low: •Market oriented economy •Massive rural-urban migration • Changing attitude and behavior • Delayed marriage and childbearing •High prevalence of contraceptive use Concluding Remarks 36 Implication of low fertility: • Too new to be fully addressed • Certainly tremendous or revolutionary • Future will tell what discussed is only the tip of the iceberg • “Below replacement”: a new global demographic norm Concluding Remarks 37 End Fertility Prospects in China Slide Number 2 Slide Number 3 Slide Number 4 Slide Number 5 China’s Current Fertility Policy Slide Number 7 Slide Number 8 Slide Number 9 Slide Number 10 Slide Number 11 Slide Number 12 Slide Number 13 Slide Number 14 Slide Number 15 Slide Number 16 Slide Number 17 Slide Number 18 Slide Number 19 Slide Number 20 Slide Number 21 Slide Number 22 Slide Number 23 Slide Number 24 Slide Number 25 Slide Number 26 Slide Number 27 Slide Number 28 Slide Number 29 Slide Number 30 Slide Number 31 Slide Number 32 Slide Number 33 Slide Number 34 Slide Number 35 Slide Number 36 Slide Number 37
Language:English
Score: 397076.32 - https://www.un.org/development...s/200912_unpd_egm_baochang.pdf
Data Source: un
Between 2014 and 2018, the accumulated value of the reform and efficiency gains totaled some $58 million, including the redeployment of over 66 positions in the Professional category to strengthen technical work. (...) Overview of biennial efficiency savings 2020-21 Re-profiling and redeployments from the Management and Reform portfolio: US$1.9 million Re-profiling of staff development provision: US$ 1.4 million Removal of unassigned resources previously used for technical meetings: US$ 0.4 million Reductions in travel support costs: US$ 0.4 million Reductions in RBTC provisions within the Policy portfolio: US$ 0.3 million Re-profiling and grading of positions within the Policy portfolio: US$0.2 million Savings total: US$4.6 million (in constant 2018-19 US$) Source: Programme and Budget for 2020–21 - Programme of work and results framework , page 89; Programme and Budget for the biennium 2020-21 2018-19 Redeployment of resources from management, administrative and support services to front-line analytical and technical ones that directly deliver value to member States, including the creation of the equivalent of 26.5 new positions in the Professional category: US$15 million Savings total: US$15 million (in constant 2016-17 US$) Source: Programme and Budget for the biennium 2018-19 , pages  iii and 6. 2016-17 Conversion of managerial positions to technical positions: US$6 million Reductions in the number of administrative positions: US$3.1 million Reprofiled/redeployed positions/streamlining of General Service positions: US$3.7 million Conversion of general service positions to technical positions: US$3.7 million Redeployed non-staff expenditure: US$7.8 million Savings from new travel policy for Governing Body members: US$0.5 million Savings total: US$24.8 million (in constant 2014-15 US$) Source: Programme and Budget for the Biennium 2016-17 , pages 4-5. 2014-15 Reduction in the duration of the March programme and budget session of the Governing Body: US$0.5 million Rationalization of publications and their dissemination, including Century Project: US$0.5 million Consolidation of structures and reprofiling of positions resulting from HQ Reform: US$1.2 million Reductions/streamlining of administrative and management positions: US$1.2 million Savings total: US$3.4 million (in constant 2012-13 US$) Source: Programme and Budget for the Biennium 2014-15 , pages xv-xvi and paragraphs 14-15. 2012-13 Reduced budget for the International Labour Conference: US$0.78 million Reduced budget for the Governing Body: US$0.29 million Reduced budget for service to meetings (through paper smart strategy and efficient working method): US$1.8 million Reduced budget for support services (non-staff costs, administrative efficiencies and improved working methods): US$1.9 million Reductions Office-wide as a result of the new measures on travel: US$0.8 million Savings total: US$5.6 million (in constant 2010-11 US$) Source: Programme and Budget for the Biennium 2012-13 , pages 10-11. 2010-11 Reduced budget for management and support: US$2.8 million Reduced number of administrative personnel in technical programmes: US$1.2 million Reduced staff travel costs: US$1.1 million Reductions in the number and length of documents and other savings related to the Governing Body and the International Labour Conference: US$2.8 million Savings total: US$7.9 million Source: Programme and Budget for the Biennium 2010-11 , pages 5-6. 2008-09 Reduced budget for management services: US$2.2 million Reduced budget for support services: US$1.3 million Reduced budget for services to meetings: US$0.8 million Reduced budget for support personnel in technical programmes: approximately US$1 million. Savings total: US$5.3 million Source: Programme and Budget for the Biennium 2008-09 , page 4. 2006-07 Elimination of smaller units and subunits in technical programmes.
Language:English
Score: 397041.3 - https://www.ilo.org/global/abo.../efficiency/lang--en/index.htm
Data Source: un
Total income increased by 3 per cent, from $423 million in 2010 to $436 million in 2011. Total expenditures increased by 8 per cent, from $344 million to $373 million. (...) Total expenditures, including support costs, increased to $53 million, from $52 million in 2010. The resource balance available at the end of 2011 was $34 million, compared to $31 million in 2010 (and $38 million in 2009). (...) In 2011, UNDP spent $31 million ($33 million in 2010), including $15 million ($11 million in 2010) in other resources.
Language:English
Score: 396998.4 - https://www.undp.org/sites/g/f...-session/English/dp2012-17.doc
Data Source: un
On the basis of that study, the accrued liability estimates for UNCDF are $11 million; UNIFEM, $20 million; and UNDP, $430 million, totalling $461 million. (...) Total income increased by 7 per cent from $394 million in 2009 to $423 million. Total expenditures increased by 8 per cent from $318 million to $344 million. (...) In 2010, UNDP spent $33 million (2009: $39 million), including $11 million (2009: $10 million) in other resources.
Language:English
Score: 396899.85 - https://www.undp.org/sites/g/f...-session/english/dp2011-33.doc
Data Source: un
END   UNHCR 2020 Global Trends Report – key data: 82.4 million people forcibly displaced globally (79.5 million in 2019) – a 4 per cent increase 26.4 million refugees (26.0 million in 2019) including: 20.7 million refugees under UNHCR’s mandate (20.4 million in 2019) 5.7 million Palestine refugees under UNRWA’s mandate (5.6 million in 2019) 48.0 million internally displaced people (45.7 million in 2019) 4.1 million asylum-seekers (4.1 million in 2019) 3.9 million Venezuelans displaced abroad (3.6 million in 2019) 2020 is the ninth year of uninterrupted rise in forced displacement worldwide. Today, one per cent of humanity is displaced and there are twice as many forcibly displaced people than in 2011 when the total was just under 40 million. More than two thirds of all people who fled abroad came from just five countries: Syria (6.7 million), Venezuela (4.0 million), Afghanistan (2.6 million), South Sudan (2.2 million) and Myanmar (1.1 million). (...) For the seventh year in a row, Turkey hosted the largest refugee population worldwide (3.7 million refugees), followed by Colombia (1.7 million, including Venezuelans displaced abroad), Pakistan (1.4 million), Uganda (1.4 million) and Germany (1.2 million).
Language:English
Score: 396746.75 - https://www.unhcr.org/tr/en/29...d-of-soaring-displacement.html
Data Source: un
UNHCR 2020 Global Trends Report – key data: 82.4 million people forcibly displaced globally (79.5 million in 2019) – a 4 per cent increase 26.4 million refugees (26.0 million in 2019) including: 20.7 million refugees under UNHCR’s mandate (20.4 million in 2019) 5.7 million Palestine refugees under UNRWA’s mandate (5.6 million in 2019) 48.0 million internally displaced people (45.7 million in 2019) 4.1 million asylum-seekers (4.1 million in 2019) 3.9 million Venezuelans displaced abroad (3.6 million in 2019) 2020 is the ninth year of uninterrupted rise in forced displacement worldwide. Today, one per cent of humanity is displaced and there are twice as many forcibly displaced people than in 2011 when the total was just under 40 million. More than two thirds of all people who fled abroad came from just five countries: Syria (6.7 million), Venezuela (4.0 million), Afghanistan (2.6 million), South Sudan (2.2 million) and Myanmar (1.1 million). (...) For the seventh year in a row, Turkey hosted the largest refugee population worldwide (3.7 million refugees), followed by Colombia (1.7 million, including Venezuelans displaced abroad), Pakistan (1.4 million), Uganda (1.4 million) and Germany (1.2 million).
Language:English
Score: 396746.75 - https://www.unhcr.org/th/en/28...d-of-soaring-displacement.html
Data Source: un