WRITTEN SUBMISSION BY THE STATE OF PALESTINE: INDEPENDENT COMMISSION FOR HUMAN RIGHTS - NOTE BY THE SECRETARIAT
The occupation authorities refuse to register or grant residency to hundreds of
thousands of Palestinians because they were outside the Palestinian territories at the
beginning of the occupation in 1967 or spent periods abroad between 1967 and 1994. While
Israelis consider Jews living in the West Bank to be Israeli citizens, they do not lose that
status regardless of the number of years they spend abroad.
Israel, the occupying power, also violates the right of Palestinians to marry and form families,
with policies and laws related to nationality and residency. (...) Forced displacement in occupied Jerusalem
In occupied East Jerusalem, Israel subjects the vast majority of the hundreds of thousands of
Palestinians who live there, to a legal status that undermines their right to reside there, in a
systematic discriminatory manner aimed at Judaizing and controlling the city.
Idioma:Español
Puntuación: 1583956.6
-
https://daccess-ods.un.org/acc...t?open&DS=A/HRC/47/NI/3&Lang=S
Fuente de datos: ods
Notable Media Coverage: Women Deliver Conference
Updated June 8 2010, 5:00pm ET
German
Globaler Aufruf von Melinda Gates zur Rettung des Lebens von Frauen und Kindern, N/A, news aktuell (Translated Press release)
Gates-Stiftung spendet 1,5 Mrd, N/A, BILD
1,5 Mrd. Dollar Spende durch die Stiftung von Bill und Melinda Gates, N/A , ShortNews.de Spende-durch-die- Stiftung-von-Bill-und-Melinda-Gates>
French
The UN’s boss calls for an improvement of maternal health, Agence France Presse (AFP)
o Les Echos.fr
o Ma Santé Facile.com
o News.Fr.Msn.com
o TV5.org
o Dernières Nouvelles d’Alsace.fr
Melinda Gates Calls for Global Action to Save Women's and Children's Lives, Capital.fr
o Le Point.fr
o Euroinvestor.fr
o Generation NT.com
o Zebulon.fr
Spanish
El Objetivo son los tratamientos a medida para cada paciente, Rafael P. Ybarra, El País
Los Gates donan 1.200 millones para mejorar la salud materno-infantil, El País.com
Fundación Gates dona 1.500 millones de dólares para salud materno-infantil, ABC.es
Fundación Gates dona 1.500 millones de dólares para salud de muejres y niños, ADN.es
La Fundación Gates dona 1.200 millones de eruos para proteger la salud maternal e infantile, Yo Dona.com
La Fundación Gates destina 1.200 millones euros al desarrollo de programas integrals de salud materna e infantile, Europa Press
o Diario Vasco.com
o El Comercio Digital.com
o El Correo Vizcaya.com
http://www.presseportal.de/pm/16536/1627111/bill_melinda_gates_foundation
http://www.bild.de/BILD/news/telegramm/news-ticker,rendertext=12815880.html
http://www.shortnews.de/id/835181/1-5-Mrd-Dollar-Spende-durch-die-Stiftung-von-Bill-und-Melinda-Gates
http://www.google.com/hostednews/afp/article/ALeqM5h0oD9L6MJKNZbu51BiyjEx84kxtA
http://www.capital.fr/bourse/communiques/melinda-gates-demande-une-action-mondiale-pour-sauver-la-vie-de-femmes-et-d-enfants-507343
o El Diario Montañés.es
o Hoy.es
o Ideal.es
o La Rioja.com
o La Verdad de Murcia.es
o La Voz de Galicia.es
o La Voz Digital.es
o Norte de Castilla.es
o Sur.es
Italian
Melinda Gates fa appello a un’azione globale per salvare la vita a donne e bambin, Adnkronos/IGN
Swedish
Kvinnor fokus för nytt välgörenhetsprojekt (Women are the focus for new charity project), E24
http://www.adnkronos.com/IGN/News/Aziende_Informano/Melinda-Gates-fa-appello-a-un%E2%80%99azione-globale-per-salvare-la-vita-a-donne-e-bambini_504158162.html
http://www.e24.se/ego/senastenytt_s189/http:/www.e24.se/kvinna/pengar/melinda-gates-satsar-pa-valgorenhet-for-kvinnor_2109553.e24
Idioma:Español
Puntuación: 1466519.1
-
https://www.who.int/pmnch/acti..._wdmediacoverage_otherlang.pdf
Fuente de datos: un
According to these data, women in the region spend between one fifth and one third of their time each day or each week on unpaid domestic and care work, while men spend about 10% of their time on this work. (...) Data on how boys, girls and adolescents spend their time also allows the measurement of their well-being. (...) In rural areas of Peru, data show that 57.3% of women spend time fetching water, and in Guatemala women spend six hours per week on this activity, which is almost two hours more than men.
Idioma:Español
Puntuación: 1397025.7
-
https://www.cepal.org/sites/de...ial_de_america_latina_2016.pdf
Fuente de datos: un
WRITTEN SUBMISSION BY THE PHILIPPINES: COMMISSION ON HUMAN RIGHTS - NOTE BY THE SECRETARIAT
The
IOM also reported that with their termination, nearly 16% of all Filipino migrant workers
were forced to spend their own money to return home, adding that 70% of OFWs did not
receive support from their employers before returning to the Philippines. (...) Although the government has already initiated the release of special risk allowance
to frontliners, thousands have yet received their benefits. Last August 30, and September 1,
2021, healthcare workers staged protests calling for the immediate release of their benefits .8
In a statement, the Commission urged the government to make the processing of claims as
easy and efficient as possible.
Idioma:Español
Puntuación: 1344001.8
-
https://daccess-ods.un.org/acc...t?open&DS=A/HRC/48/NI/1&Lang=S
Fuente de datos: ods
REPORT OF THE SPECIAL RAPPORTEUR ON THE HUMAN RIGHTS OF MIGRANTS, JORGE BUSTAMANTE : ADDENDUM
Asylum-seekers
granted refugee status, spend an average of 10 months in detention, with the longest period in
one case being three and a half years. (...) According to Government sources,
hundreds of thousands of persons have been deported since these laws went into effect in 1996.
47. (...) To make matters worse, the Department of Homeland Security often
transfers detainees hundreds or thousands of miles away from their home cities without any
notice to their attorneys or family members, which violates the agency’s own administrative
regulations on detention and transfer of detainees.
Idioma:Español
Puntuación: 1290737.3
-
daccess-ods.un.org/acce...pen&DS=A/HRC/7/12/ADD.2&Lang=S
Fuente de datos: ods
THE RIGHT TO FOOD : REPORT OF THE SPECIAL RAPPORTEUR ON THE RIGHT TO FOOD, JEAN ZIEGLER : ADDENDUM
Other natural
disasters are common, including earthquakes such as the terrible quake that devastated
India-administered Kashmir killing thousands of people in October 2005 and the tsunami
of December 2004 that killed at least 11,000 people, injuring and displacing thousands more
across the south-eastern coastal areas of the country.
5. (...) According to
FAO, India is home to the largest share of the worlds undernourished population, and more
than 200 million Indian children, women and men eat less than the daily minimum calorie
requirement.7 Official Indian statistics suggest that this situation may be even worse, with
more than half (53 per cent) of the population estimated to be undernourished in the
Governments own report on progress towards achieving the MDGs.8 It is estimated that the
poorest 30 per cent of households eat less than 1,700 kilocalories per day per person (well below
the international minimum standard of 2,100 kilocalories per day)9 even if they spend 70 per cent
of their income on food.10 Average calorie consumption has been falling over recent decades -
but while this is explained as a shift away from basic staple food amongst higher income
families, it is also a sign of increasing food insecurity amongst the poorest.
Idioma:Español
Puntuación: 1280413.7
-
daccess-ods.un.org/acce...DS=E/CN.4/2006/44/ADD.2&Lang=S
Fuente de datos: ods
El modelo a estimar es:
IDH como factor de la migración
m = ln( Emigrantesj hacia i / Emigrantesi hacia j )2000 = β0 + β1populationDensityi95 +β2populationDensityj95+ β3loggdp_pci95 + β4loggdp_pcj95 + β5 propPob_15_24i95 + β6 propPob_15_24j95 + β7propWomeni95+ β8propWomenj95 + β9avgHHsizei95+ β10avgHHsizej95+ β11schoolingi95+ β12schoolingj95+ β13prop_L_secondaryi95 + β14prop_L_secondaryj95+ β15prop_L_servicesi95 + β16prop_L_servicesj95+ β17AGRIgrowth_ratei95+ β18AGRIgrowth_ratej95 + β19TOTALgrowth_ratei95+ β20TOTALgrowth_ratej95+ β21DummyCHIHi + β22DummyCHIHj+ β23DummyCOAHi + β24DummyCOAHj + β25DummyTAMPSi + β26DummyTAMPSj + β27DummyBCi + β28DummyBCj+ β29DummyDFi + β30DummyDFj + β31DummyEDOMEXi +β32DummyEDOMEXj + β33DummySINALOAi + β34DummySINALOAj + β35DummyOAXACAi + β36DummyOAXACAj + β37distancei_j + β38lifeexpectancyi95 + β39lifeexpectancyj95 + β40Networkj_i95 + β41Networki_j95 + β42logpopulationi95 + β43logpopulationj95 + εij
Resultados del modelo Gravitacional – Nivel Estatal (1)
INT
Model 1 Model 2 Population density (thousands)- Destination -1.280*** 1.196 Population density (thousands) - Origin 1.663*** 7.352** Perc. people between 15 and 24 y/o - Destination 12.281 11.658 Perc. people between 15 and 24 y/o - Origin -15.461* -21.374 Women rate - Destination 25.137*** 24.730*** Women rate - Origin -26.448*** -22.404*** Avg. household size - Destination 0.332 0.287 Avg. household size - Origin -0.313* -0.499** Log GDP per capita - Destination 0.267*** 2.186 Log GDP per capita - Origin -0.380*** 3.177** Avg. level of education - Destination 0.087 -0.629 Avg. level of education - Origin -0.190* -3.981*** Life expectancy - Destination 0.061 0.042 Life expectancy - Origin -0.156*** -0.302*** Perc. secondary sector - Destination -0.384 -1.108 Perc. secondary sector - Origin -0.286 -1.205 Perc. services sector - Destination 1.493*** 1.079** Perc. services sector - Origin -0.793** -1.960*** Agr. sector growth rate - Destination 0.004 -0.007 Agr. sector growth rate - Origin 0.011* -0.019* Total growth rate - Destination -0.021 -0.01 Total growth rate - Origin 0.021** 0.048***
INT
Resultados del modelo Gravitacional – Nivel Estatal (2)
Model 1 Model 2 Immigrants stock - Destination 1.569 2.24 Immigrants stock - Origin 3.597*** 3.408*** Dummy DF - Destination 5.786** 249.709 Dummy DF - Origin -7.636*** 564.110* Dummy Edo MEX - Destination 0.336 1.593 Dummy Edo MEX - Origin -0.227 2.549 Dummy Baja California - Destination 0.458*** 0.381* Dummy Baja California - Origin -0.292 -0.5 Dummy Sonora - Destination 0.307** 0.138 Dummy Sonora - Origin -0.134 -0.654*** Dummy Chihuahua - Destination 0.649*** 0.629*** Dummy Chihuahua - Origin -0.203 -0.275 Dummy Coahuila - Destination 0.719** 0.569 Dummy Coahuila - Origin -0.556*** -1.409*** Dummy Tamaulipas - Destination 0.500*** 0.359** Dummy Tamaulipas - Origin -0.456*** -0.877*** Dummy Sinaloa - Destination 0.286** 0.032 Dummy Sinaloa - Origin 0.259** -0.138 Dummy Oaxaca - Destination -0.287 -0.225 Dummy Oaxaca - Origin -0.172* -0.401*** Distance between states (thousands km) 0.090*** 0.044
INT
Resultados del modelo Gravitacional – Nivel Estatal (3)
Model 1 Model 2 Population density squared (thousands)- Destination -7.893 Population density squared (thousands)- Origin -18.516* Log GDP per capita squared - Destination -0.384 Log GDP per capita squared - Origin -0.701** Avg. level of education squared - Destination 0.076 Avg. level of education squared - Origin 0.374*** Distance between states squared (thousands km) 0.016 Log total population - Destination -0.253*** 3.024 Log total population - Origin 0.127*** 6.490* Log total population squared - Destination -0.112 Log total population squared - Origin -0.218* Constant 10.556 -41.423 Observations 496 496 Adjusted R-squared 0.488 0.496 * Significant at 10% level, ** Significant at 5%, *** Significant at 1%
Controlando por los otros factores, un estado de la frontera norte tiene una tasa de inmigración neta entre 105% (Coahuila) y 58% (BC) mayor que el promedio. (...) IDH como factor de la migración
INT
Resultados del modelo Gravitacional – Nivel Municipal (1)
Model 1 Model 2 Population density (thousands)- Destination -0.004 0.002 Population density (thousands) - Origin 0.008*** 0.030*** Perc. people between 15 and 24 y/o - Destination 4.524*** 4.363*** Perc. people between 15 and 24 y/o - Origin 0.021 0.493 Women rate - Destination -1.219 -0.854 Women rate - Origin 1.428* -0.292 Avg. household size - Destination 0.095*** 0.102*** Avg. household size - Origin -0.062** -0.054* Log GDP per capita - Destination 0.393*** -0.763 Log GDP per capita - Origin -0.278*** 0.195 Avg. level of education - Destination -0.055*** 0.115 Avg. level of education - Origin -0.027* -0.099 Life expectancy - Destination 0.042*** 0.043*** Life expectancy - Origin -0.002 -0.003 Perc. secondary sector - Destination 1.239*** 1.270*** Perc. secondary sector - Origin -0.011 -0.03 Perc. services sector - Destination 0.509*** 0.552*** Perc. services sector - Origin -0.342*** -0.319** Agr. sector growth rate - Destination 0 0 Agr. sector growth rate - Origin 0.002 0.002 Total growth rate - Destination -0.006** -0.006** Total growth rate - Origin 0.010*** 0.008***
INT
Resultados del modelo Gravitacional – Nivel Municipal (2)
Model 1 Model 2 Immigrants stock - Destination -1.511*** -1.559*** Immigrants stock - Origin 0.468** 0.603*** Dummy DF - Destination -0.334*** -0.373*** Dummy DF - Origin 0.327*** 0.284*** Dummy Edo MEX - Destination -0.071** -0.076** Dummy Edo MEX - Origin -0.032 -0.089*** Dummy Baja California - Destination 0.399*** 0.419*** Dummy Baja California - Origin -0.282*** -0.265*** Dummy Sonora - Destination 0.234*** 0.244*** Dummy Sonora - Origin -0.067* -0.064* Dummy Chihuahua - Destination 0.209*** 0.217*** Dummy Chihuahua - Origin -0.015 0.011 Dummy Coahuila - Destination -0.023 -0.016 Dummy Coahuila - Origin -0.094** -0.075* Dummy Tamaulipas - Destination 0.265*** 0.273*** Dummy Tamaulipas - Origin -0.130*** -0.156*** Dummy Sinaloa - Destination 0.200*** 0.210*** Dummy Sinaloa - Origin 0.209*** 0.194*** Dummy Oaxaca - Destination 0.031 0.035 Dummy Oaxaca - Origin 0.187*** 0.181*** Distance between states (thousands km) 0.141** 0.435***
INT
Resultados del modelo Gravitacional – Nivel Municipal (3)
Model 1 Model 2 Log GDP per capita squared - Destination 0.065* Log GDP per capita squared - Origin -0.027 Population density squared (thousands)- Destination 0 Population density squared (thousands)- Origin -0.001** Avg. level of education squared - Destination -0.014** Avg. level of education squared - Origin 0.006 Distance between states squared (thousands km) -0.147*** Log total population - Destination -0.133*** -0.025 Log total population - Origin 0.005 0.713*** Log total population squared - Destination -0.005 Log total population squared - Origin -0.029*** Constant -2.610*** -4.146 Observations 14608 14608 Adjusted R-squared 0.1 0.103 * Significant at 10% level, ** Significant at 5%, *** Significant at 1%
La mayoría de los factores son pull factors: PARA AMBAS REGIONES
PIB per capita Tamaño del hogar promedio Porcentaje de la fuerza laboral en el sector servicios Stock (redes) de inmigrantes
REGIÓN DE DESTINO Porcentaje de personas entre 15 y 24 años de edad Esperanza de vida Porcentaje de la fuerza laboral en el sector secundario
IDH como factor de la migración
Los factores push son: PARA AMBAS REGIONES
Tasa de crecimiento de la economía estatal Dummy para el DF
REGIÓN DE DESTINO Dummy para el Estado de México Total de la población en el estado
REGIÓN DE ORIGEN Densidad de población estatal Porcentaje de mujeres en el estado
IDH como factor de la migración
La densidad poblacional en el Distrito Federal es en efecto un factor de atracción de emigrantes, una vez que se han controlado otros factores.
Idioma:Español
Puntuación: 1183411.1
-
https://www.cepal.org/sites/de...s/courses/files/isoloaga_p.pdf
Fuente de datos: un
THE RIGHT TO FOOD : REPORT OF THE SPECIAL RAPPORTEUR ON THE RIGHT TO FOOD, JEAN ZIEGLER : ADDENDUM
More than 3.5 million animals were killed in 2000 and another 4.7 million
in 2001.3 Over 10,000 herders were left without any livestock and thousands more Mongolian
families lost most of their herd.
7. (...) It is important to understand that during the early 1990s, there was a return to the land,
with many families driven back to rural areas to escape escalating urban poverty. Thousands of
people lost their jobs in urban areas as the economy collapsed and State industry was dismantled
during the brutal economic transition, and many turned to herding as the only alternative. (...) Residents of the urban ger
districts (urban shantytown districts surrounding Ulaanbaatar made up of the traditional
Mongolian white felt tents, or gers) face severe problems of access to safe water and pay far
more for water from kiosks than apartment residents for running water.14 Poor families now
spend over 70 per cent of their income on food,15 and therefore have to make difficult choices
between food, water, health, education or winter heating.
Idioma:Español
Puntuación: 1162924.4
-
daccess-ods.un.org/acce...DS=E/CN.4/2005/47/ADD.2&Lang=S
Fuente de datos: ods
ISSN 0378-5386
Bo
(Por »il)
Ambos Sexos
Hombres
Mujeres
51.82 54.63 57.08 59.02 61.17
50.14 52.82 55.18 56.99 58.90
53.58 56.53 59.07 61.16 63.54
125.13 111.85 99.97 90.42 80.49
133.79 120.34 108.03 98.28 89.29
116.03 102.93 91.50 82.18 71.26
Expectation of life at
birth: Both sexes
Males
Females
Infant mortality rate
(per thousands)
Both sexes
Males
Females
CRECIMIENTO NATURAL
Crecimiento anual:
B-D (En miles)
Tasa de crecimiento
natural (Por mil)
4 648 5 537 6 575 7 031 7 595
27.17 28.14 29.02 27.06 25.67
NATURAL INCREASE
Annual natural increase:
B-D (in thousands)
Natural increase rate
(per thousands)
MIGRACIÓN
Higracion anual:
M (En miles)
Tasa de migración
m (Por mil)
100 -47 -163 -194 -201
0.61 -0.23 -0.71 -0.74 -0.67
MIGRATION
Annual migration
M (in thousands)
Migration rate
ni (per thousands)
CRECIMIENTO TOTAL
Creciaiento anual:
B-D+(-)M (En miles
Tasa de crecimiento
total: r (Por mil)
4 748 5 490 6 412 6 843 7 395
27.78 27.91 28.31 26.33 25.01
TOTAL INCREASE
Annual increase
B-D+(-)M (in thousands)
Total increase rate
r (per thousands)
18
(Continua)/(continued)
CUADRO 2 b (continuación) / TABLE 2 b (continued)
AMERICA LATINA: INDICADORES DEMOGRÁFICOS ESTIMADOS ENTRE 1950-1955 Y 2020-2025
LATÍN AMERICA: DEHOGRAPHIC INDEXES ESTIMATED FOR 1950-1955 AND 2020-2025
AMERICA LATINA
DUINQUENIOS/OUINQUENNIA
Indicadores Demographic
demográficos 1975- 1980- 1985- 1990- 1995- indexes
1980 1985 1990 1995 2000
FECUNDIDAD
Nacimientos anuales:
B (En Miles)
Tasa bruta de nata-
lidad b (Por Mil)
Tasa global de
fecundidad
Tasa bruta de
reproducción
10 839 11 577 12 141 12 475 12 660
32.49 30.99 29.16 27.05 25.00
4.40 4.00 3.64 3.32 3.06
2.15 1.95 1.78 1.62 1.49
EERTITILY
Annual birth:
B (in thousands)
Crude birth rate
b (per thousands)
Total fertility
rate
Gross reproduction
rate
HORTALIDAD
Muertes anuales
D (En niles)
Tasa bruta de Morta-
lidad: d (Por Mil)
Esperanza de vida al
nacer: Anbos sexos
Hombres
Mujeres
Tasa de Mortalidad
infantil. (Por Mil)
AMbos Sexos
HoMbres
Mujeres
2 894 2 995 3 116 3 239
8.69 8.04 7.S2 7.06
63.20 64.87 66.32 67.70
60.74 62.23 63.63 64.96
65.78 67.65 69.14 70.57
391
6.74
8 90
6.12
1.82
70.05 62.10 55.06 48.58 43.00
78.22 69.85 62.31 55.36 49.38
61.48 53.95 47.45 41.45 36.31
H0RTALITY
Annual death:
D (in thousands)
Crude death rate
d (per thousands)
Expectation of lifa at
birth: Both sexes
Hales
fetales
Infant Mortality rate
(per thousands)
Both sexes
Males
Fetales
CRECIMIENTO NATURAL
CreciMiento anual:
B-D (En Miles)
Tasa de creciMiento
natural (Por Mil)
7 946 8 S82 9 025 9 235 9 269
23.80 22.95 21.64 19.99 18.26
NATURAL INCREASE
Annual natural increase:
B-D (in thousands)
Natural increase rate
(per thousands)
MIGRACIÓN
Migración anual:
M (En niles)
Tasa de Migración
m (Por Mil)
-249 -328 -264 -219 -210
-0.71 -0.88 -0.64 -0.48 -0.42
MIGRATI0N
Annual Migration
M (in thousands)
Migration rate
M (per thousands)
CRECIMIENTO TOTAL
CreciMiento anual:
B-D+(-)M (En Miles
Tasa de creciMiento
total: r (Por Mil)
7 697 8 255 8 761 9 016 9 059
23.09 22.07 21.00 19.51 17.84
TOTAL INCREASE
Annual increase
B-D*(-)M (in thousands)
Total increase rate
r (per thousands)
(Continua)/(Continued)
19
CUADRO 2 b (conclulion) / TABLE 2 b (concluded)
AMERICA LATINA: INDICADORES DEM0GRAFIC08 ESTIMADOS ENTRE 1950-1955 Y 2020-2025
LATÍN AMERICA: DEMOGRAPHIC INDEXES ESTIHATED FOR 1950-1955 AND 2020-2025
AMERICA LATINA
QUINQUENIOS/OUINQUENNIA
Indicadores Deaographic
demográficos 2000- 2005- 2010- 2015- 2020- indexes
2005 2010 2015 2020 2025
FECUNDIDAD
Naciaientos anuales:
B (En alies)
Tasa bruta de nata-
lidad b (Por ail)
Tasa global de
fecundidad
Tasa bruta de
reproducción
12 841 13 053 13 250 13 386 13 473
23.27 21.87 20.66 19.55 18.54
2.86 2.70 2.58 2.48 2.40
1.39 1.32 1.26 1.21 1.17
FERTITILY
Annual birth:
B (in thousands)
Crude birth rate
b (per thousands)
Total fertility
rate
Gross reproduction
rate
MORTALIDAD
Muertes anuales
D (En ailes) 3 606 3 879 4 203 4 606 5 098
MORTALITY
Annual death:
D (in thousands)
Tasa bruta da aorta-
lidad: d (Por ail)
Esperanza da vida al
nacer: Aabos sexos
Hoabres
Mujeres
Tasa da mortalidad
infantil. (Por ail)
Aabot Sexos
Hoabres
Mujeres
6.58 6.54 6.60 6.77 7.06
69.94 70.83 71.62 72.28 72.83
67.11 67.97 68.72 69.36 69.90
72.90 73.84 74.66 75.34 75.90
38.33 34.38 30.98 28.16 25.85
44.32 40.04 36.34 33.21 30.63
32.04 28.43 25.34 22.84 20.84
Crude death rate
d (per thousands)
Expactation of Ufa at
birth: Both saxas
Males
Feaales
Infant aortality rate
(per thousands)
Both saxas
Hales
Feaales
CRECIMIENTO NATURAL
Creciaiento anual:
B-D (En ailes)
Tasa de creciaiento
natural (Por ail)
9 234 9 174 9 047 8 780 8 375
16.69 15 .33 14.07 12.78 11.49
NATURAL INCREASE
Annual natural increase:
B-D (in thousands)
Natural increase rate
(per thousands)
MIGRACIÓN
Migración anual:
M (En ailes)
Tasa de aigracion
a (Por ail)
-203 -198 -193 -188
-0.37 -0.33 -0.30 -0.28 -0.26
MIGRATION
Annual aigration
M (in thousands)
Migration rate
a (per thousands)
CRECIMIENTO TOTAL
Creciaiento anual:
B-D+(-)N (En ailes
Tasa de creciaiento
total: r (Por ail)
9 031 8 976 8 854 8 592 8 191
16.32 14.99 13.76 12.50 11.23
TOTAL INCREASE
Annual increase
B-D+(-)M (in thousands)
Total increase rate
r (per thousands)
20
CUADRO 3 a / IABLE 3 a
AMERICA LATINA: PROYECCIÓN DE LA POBLACIÓN TOTAL SEGÚN SEXO Y GRUPOS
QUINQUENALES DE EDADES. 1950-2025
LATÍN AHERICA: PROJECIION OF THE TOTAL POPULATION BY SEX AND
QUINQUENNIAL AGE GKOUPS. 1950-2025
ARGENTINA
Sexo y grupos POBLACION/POPULATION
de edad/
Sex and age Artos/Years
groups
1950 1955 1960 1965 1970 1975
AMBOS SEXOS/BOIH SEXES
Total 17 150 336 18 927 821 20 616 009 22 2B3 100 23 962 313 26 051 685
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 y +
1
1
1
1
1
1
1
1
1
947
709
578
567
578
469
320
240
127
973
797
632
485
328
201
109
81
133
551
744
966
761
111
361
851
382
966
166
135
838
945
228
510
688
2
1
1
1
1
1
1
1
1
1
158
940
724
616
611
599
473
314
224
098
931
744
570
416
262
143
93
225
611
874
565
847
448
442
565
856
295
572
461
066
525
631
953
885
2
2
1
1
1
1
1
1
1
1
1
261
140
943
738
632
613
592
459
294
193
053
873
676
494
337
191
119
102
220
295
229
219
550
006
985
781
577
346
829
450
223
776
489
930
2
2
2
1
1
1
1
1
1
1
1
342
245
142
954
750
634
606
577
439
265
148
992
796
588
401
247
149
581
297
099
768
241
226
661
780
517
401
956
088
452
554
297
920
261
2
2
2
2
1
1
1
1
1
1
1
1
460
328
247
153
966
752
627
592
553
405
218
083
906
695
482
297
191
686
264
553
313
241
047
790
035
888
647
988
207
267
443
207
340
398
2
2
2
2
2
1
1
1
1
1
1
1
801 575
462 373
343 826
2B5 996
196 394
988 748
758 649
622 650
575 202
522 035
357 681
155 202
998 301
800 673
577 557
364 230
240 593
HOMBRES/MALES
Iotal
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 y +
8 826
992
Q67
800
796
802
748
673
638
593
525
430
344
259
169
99
50
32
955
312
028
669
290
248
906
247
996
736
530
811
570
692
979
030
996
915
9 666
1 095
988
874
817
814
809
749
668
627
573
496
395
303
215
130
66
38
371
977
459
451
727
735
866
030
205
731
854
772
290
280
659
273
908
152
10 469
1 148
1 086
989
881
825
815
805
741
656
607
543
457
350
254
168
89
48
900
359
319
344
675
104
525
626
153
071
585
791
647
287
632
086
846
851
11 244
1 188
1 139
1 086
994
887
825
810
796
728
636
577
502
405
292
195
115
61
313
852
870
734
861
178
143
836
744
064
845
762
027
084
010
622
501
181
12
1
1
1
1
018
248
181
140
091
999
886
820
801
781
705
605
533
444
338
226
136
78
838
560
035
438
916
722
882
518
323
016
304
328
065
011
430
716
187
388
13
1
1
1
1
1
1
006 250
422 136
248 895
188 412
159 792
113 087
009 994
888 966
816 005
789 396
759 065
672 253
561 759
476 128
375 651
266 379
160 845
97 486
MUJERES/EEMALES
Total
0- 4
5- 9
10-14
1S-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 y+
8 323
954
842
778
771
776
720
647
601
533
448
366
287
226
158
102
58
48
381
821
523
075
67,6
513
205
114
855
646
436
355
565
146
966
198
514
773
9 261
1 062
952
850
800
797
789
724
646
597
524
434
349
266
200
132
77
55
450
248
151
423
838
112
582
413
360
125
441
799
172
786
866
358
045
732
10 146
1 112
1 053
953
856
807
798
786
718
«38
585
509
416
326
239
169
101
71
109
743
901
951
554
115
025
381
833
711
992
555
182
163
591
690
643
079
11 038
1 153
1 105
1 055
959
863
809
795
781
711
628
571
490
391
296
205
132
88
786
729
428
366
908
063
083
825
036
453
556
194
061
368
544
675
419
080
11
1
1
1
1
943
212
147
107
061
966
865
807
790
772
700
613
550
462
357
255
161
113
475
126
229
115
397
519
165
272
712
872
343
660
142
256
013
491
153
010
13
1
1
1
1
1
045 435
379 439
213 478
155 414
126 204
083 307
978 754
869 683
806 644
785 806
762 970
685 428
593 443
522 174
425 022
311 178
203 385
143 107
(continua)/(continued)
21
CUADRO 3 a (continuación) / TABLE 3 a (continued)
AMERICA LATINA:
LATÍN AMERICA:
PROYECCIÓN DE LA POBLACIÓN TOTAL SEGÚN SEXO Y GRUPOS
QUINQUENALES DE EDADES. 1950-2025
P80JECTI0N OF THE TOTAL FOPULATION BY SEX AND
QUINQUENNIAL ASE GROUPS. 1 •350-2025
ARGENTINA
Sexo y grupos POBLACION/POPULATION
de edad/
Sex and age Aflos/Years
Sroups
1980 1985 1990 1995 2000
AMBOS SEXOS/BOTH SEXES
Total 28 237 149
0 - 4
5 - 9
10 -14
15 -19
2 0 - 2 4
25 -29
3 0 - 3 4
3 5 - 3 9
4 0 - 4 4
45 -49
5 0 - 5 4
5 5 - 5 9
6 0 - 6 4
6 5 - 6 9
7 0 - 7 4
7 5 - 7 9
80 y +
HOMBRES/MALES
3
2
2
2
2
2
1
1
1
1
1
1
1
241
783
455
334
272
180
971
737
594
535
466
287
069
888
672
442
303
127
516
686
978
473
134
053
575
845
904
401
045
204
873
442
598
295
30
3
3
2
2
2
2
2
1
1
1
1
1
1
331
240
223
776
447
322
257
162
949
709
557
483
394
195
957
752
521
379
283
084
845
709
327
527
199
398
263
938
734
267
398
786
260
G31
475
443
32
3
3
3
2
2
2
2
2
1
1
1
1
1
1
321
229
224
216
768
435
308
240
140
920
672
507
414
299
075
815
589
464
887
187
866
719
145
478
283
283
245
302
561
347
030
840
280
675
349
296
34
3
3
3
3
2
2
2
2
2
1
1
1
1
1
264
271
215
218
207
755
421
292
218
110
880
621
440
321
173
920
643
549
112
795
764
399
684
921
773
281
902
472
668
200
155
850
424
929
682
212
6
3
3
3
3
3
2
2
2
2
2
I
1
1
1
1
237
394
259
209
210
194
741
406
271
189
069
825
551
349
196
009
731
627
533
122
620
863
0B4
643
556
075
706
713
120
402
589
290
988
316
030
416
Iotal
o- 4
5 - 9
10 -14
15 -19
2 0 - 2 4
2 5 - 2 9
3 0 - 3 4
35 -39
4 0 - 4 4
4 5 - 4 9
5 0 - 5 4
5 5 - 5 9
6 0 - 6 4
6 5 - 6 9
7 0 - 7 4
7 5 - 7 9
80 y +
MUJERES/EEMALES
Total
O- 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
BO y +
14 045
1 645
1 412
1 245
1 183
1 151
1 102
999
876
798
763
721
624
504
406
298
191
119
14 191
1 595
1 371
1 210
1 151
1 121
1 077
971
861
796
772
744
662
564
482
373
250
183
471
984
423
024
111
326
980
248
050
412
582
689
496
561
442
729
764
651
678
143
093
662
867
147
154
805
526
432
322
712
548
643
431
714
834
644
15
1
1
1
1
1
1
1
15
1
1
1
1
1
1
1
045
645
636
408
239
175
141
092
985
858
773
728
673
563
433
325
217
146
285
594
587
368
207
147
115
070
963
851
783
755
721
632
523
426
304
233
534
921
470
454
982
279
770
138
738
388
901
129
025
7
Idioma:Español
Puntuación: 1162612.2
-
daccess-ods.un.org/acce...get?open&DS=LC/DEM/G.58&Lang=S
Fuente de datos: ods
Brasil y Regiones.
(Thousands of people)
Unity 2004 2007 2009 2011 2014
Rate (% per
year)
Var. (1000
people)
Brazil 18.030 16.842 16.035 14.888 14.466 -2,8 *** -3.564
North Region 1.963 1.620 1.619 1.855 1.691 0,0 -272
Northeast Region 8.254 7.798 7.214 6.665 6.529 -3,3 *** -1.725
Southeast Region 3.562 3.456 3.520 3.155 3.065 -2,1 *** -497
South Region 3.180 2.868 2.607 2.339 2.248 -4,2 *** -933
Midwest Region 1.070 1.099 1.075 874 934 -2,5 *** -137
Source: PNAD/IBGE special tabs. 2016, February. (...) Brasil y Regiones.
(Thousands of people)
Unity 2004 2007 2009 2011 2014
Rate (% per
year)
Var. (1000
people)
Brazil 5.763 5.413 4.917 4.477 4.569 -3,7 *** -1.193
North Region 574 490 461 521 474 -0,9 -100
Northeast Region 2.633 2.490 2.166 2.068 2.180 -3,8 *** -453
Southeast Region 1.060 1.033 1.057 880 902 -2,8 *** -158
South Region 1.234 1.115 967 834 807 -5,3 *** -427
Midwest Region 262 284 267 173 205 -5,3 *** -56
Source: PNAD/IBGE special tabs. 2016, February. (...) Brasil y
Regiones.
(Thousands of people)
Unity 2004 2007 2009 2011 2014
Rate 04/09 (%
per year)
Rate 11/14 (%
per year)
Var. (1000
people)
Brazil 4.279 5.079 5.352 4.563 5.511 4,0 ** 6,3 ** 1.232
North Region 631 795 830 643 737 3,9 4,8 * 106
Northeast Region 1.486 1.814 1.873 1.823 2.280 4,2 ** 7,6 ** 794
Southeast Region 1.175 1.386 1.452 1.103 1.281 3,9 *** 4,6 * 107
South Region 732 811 890 782 929 4,4 *** 5,6 * 197
Midwest Region 255 272 307 212 283 2,2 10,9 ** 28
Source: PNAD/IBGE special tabs. 2016, February.
Idioma:Español
Puntuación: 1092895.4
-
https://www.cepal.org/sites/de..._cepal_chile_novembro_2016.pdf
Fuente de datos: un
