This data collection contains basic demographic information for approximately 196 nations in 1973. Data are provided for the estimated number of population, births and deaths per 1,000 population in 1972, the number of infant deaths per 1,000 live births, the percentage rate of natural population increase, the number of years it took for the population to double, the percentage of the population aged 15 and under, life expectancy at birth in 1972, the median age of the mother, the median birth order, and the percentage of urban population.

This dataset merges 1972 data on social and military expenditures in 132 nations selected from WORLD MILITARY AND SOCIAL EXPENDITURES, 1974 (see Data Source) with information on demographic attributes of the same nations in 1972 obtained from WORLD POPULATION, 1973 (ICPSR 5032), collected by the United States Bureau of the Census. Military expenditures as well as international peacekeeping, public education, public health, and foreign economic aid expenditures are presented as both raw and per capita measures. Other information includes number of teachers, school age population per teacher, illiteracy rates, number of qualified physicians, population per physician, infant mortality rates, and population per soldier.

United States US: Population: Male: Ages 35-39: % of Male Population data was reported at 6.424 % in 2017. This records an increase from the previous number of 6.385 % for 2016. United States US: Population: Male: Ages 35-39: % of Male Population data is updated yearly, averaging 6.672 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 8.624 % in 1995 and a record low of 5.503 % in 1973. United States US: Population: Male: Ages 35-39: % of Male Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Population and Urbanization Statistics. Male population between the ages 35 to 39 as a percentage of the total male population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

United States US: Population: Female: Ages 35-39: % of Female Population data was reported at 6.270 % in 2017. This records an increase from the previous number of 6.243 % for 2016. United States US: Population: Female: Ages 35-39: % of Female Population data is updated yearly, averaging 6.577 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 8.241 % in 1995 and a record low of 5.233 % in 1973. United States US: Population: Female: Ages 35-39: % of Female Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Population and Urbanization Statistics. Female population between the ages 35 to 39 as a percentage of the total female population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

Switzerland Population: as % of Total: Aged 15-64 data was reported at 66.689 % in 2017. This records a decrease from the previous number of 66.942 % for 2016. Switzerland Population: as % of Total: Aged 15-64 data is updated yearly, averaging 67.307 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 68.450 % in 1988 and a record low of 64.779 % in 1973. Switzerland Population: as % of Total: Aged 15-64 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Switzerland – Table CH.World Bank: Population and Urbanization Statistics. Total population between the ages 15 to 64 as a percentage of the total population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average;

Jordan JO: Population: Male: Ages 55-59: % of Male Population data was reported at 2.655 % in 2017. This records an increase from the previous number of 2.525 % for 2016. Jordan JO: Population: Male: Ages 55-59: % of Male Population data is updated yearly, averaging 2.062 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 2.655 % in 2017 and a record low of 1.898 % in 1973. Jordan JO: Population: Male: Ages 55-59: % of Male Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Jordan – Table JO.World Bank.WDI: Population and Urbanization Statistics. Male population between the ages 55 to 59 as a percentage of the total male population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

San Marino Population: Growth data was reported at 0.592 % in 2017. This records a decrease from the previous number of 0.735 % for 2016. San Marino Population: Growth data is updated yearly, averaging 1.269 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 2.572 % in 1963 and a record low of 0.350 % in 1973. San Marino Population: Growth data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s San Marino – Table SM.World Bank.WDI: Population and Urbanization Statistics. Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage . Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; Derived from total population. Population source: (1) United Nations Population Division. World Population Prospects: 2017 Revision, (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

In 2021, there were **** births per 1,000 people in Northern Ireland, compared with eleven in the previous year. Between 2000 and 2008, Northern Ireland's birth rate increased from **** to **** but started to decline gradually until 2012 when it dropped from **** to **** in just one year. During this provided time period, the birth rate in Northern Ireland was highest in 1971, when it was **** and was at its lowest in 2020 when there were just eleven births per 1,000 people. Falling birth rates in the UK For the United Kingdom as a whole, the birth rate fell to **** births per 1,000 people in 2020, before a slight uptick to **** in 2021. After a postwar peak of **** births per 1,000 people in 1964, the UK birth rate fell sharply to just **** by 1977. Between 1977 and 2012 the birth rate fluctuated between **** and ****, but declined in every year between 2012 and 2020. In 2021, the UK's fertility rate (the number of births per women) fell to just ****, compared with **** in 1964. Since 1973, the UK has fallen below the minimum replacement level fertility rate of ***, and without immigration would likely see its population decline in the long term. Global demographic trends The considerable decline in the UK's fertility rate in recent decades is not an isolated phenomenon. As of 2024, Africa was, at ****, the only continent to have a fertility rate higher than the global average of ****. Several countries, mainly in East Asia and Europe, have far lower fertility rates than the UK or the global average, however. South Korea provides the most dramatic example of this trend, with its fertility rate falling from **** in 1960 to just **** by 2020. By the *****, it is expected that, as Africa's fertility rate converges with the rest of the world, the global population will peak at around **** billion and start to decline.

SV: Population: Male: Ages 25-29: % of Male Population data was reported at 8.365 % in 2017. This records an increase from the previous number of 8.079 % for 2016. SV: Population: Male: Ages 25-29: % of Male Population data is updated yearly, averaging 7.203 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 8.365 % in 2017 and a record low of 6.648 % in 1973. SV: Population: Male: Ages 25-29: % of Male Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s El Salvador – Table SV.World Bank: Population and Urbanization Statistics. Male population between the ages 25 to 29 as a percentage of the total male population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

The Second World War did not only cause many deaths but also leaded to broad changes in the population and settlement structure. This data compilation shows selected consequences of population movements in the context of the displacement of persons on the population structure in the Federal Republic of Germany and partly also in the German Democratic Republic. Under the command of the first federal minister for matters concerning displaced persons Hans Lukaschek the term ‘displaced persons’ was defined nationwide in the federal expellee law (find the legislative text attached).
The data compilation is passed on data published by the Federal Statistical Office and on data from selected scientific publications. The study in hand is subdivided in section A which is based on publications from the Federal Statistical Office and section B which is based on different individual scientific publications.

Subsection A1 contains selected data from censuses and extrapolations from censuses from sources of the Federal Statistical Office. Subsection A2 contains selected data from the micro census from sources of the Federal Statistical Office. Subsection B1 contains selected data from a publication by Heinz Günter Steinberg. Subsection B2 contains selected data from a publication by Gerhard Reichling. Subsection B2 contains selected data from a publication by Friedrich Edding and Eugen Lemberg.

Data tables in HISTAT:

A: Federal Statistical Office A1: Results and extrapolations from the censuses
A1.01 Resident population and displaced persons in 1000 by federal states, end-of-year values (1945-1966) A1.02 Displaced persons in 1000 by federal states, half-year values (1946-1956) A1.03 Influx of displaced persons by sex and federal state (1952-1960) A1.04a Displaced persons altogether in the federal territory by age in 1000 (1950-1953) A1.04b Male displaced persons in the federal territory by age in 1000 (1950-1953) A1.04c Female displaced persons in the federal territory by age in 1000 (1950-1953) A1.05 Displaced persons in the federal territory by age groups in 1000 (1950-1966) A1.06 Resettlement of displaced persons (1949-1962) A1.07 Marriages of displaced persons and the rest of the population in the FRG (1950-1960) A1.08 Marriages of displaced persons and the rest of the population in the FRG in absolute numbers in the different federal states (1950-1960)

A2: Results from the micro census A2.01 Displaced persons among the resident population by sex and federal state in 1000 (1958-1973) A2.02a Displaced persons among the resident population by sex and age group in the FRG in 1000 (1958-1973) A2.02b Displaced persons among the resident population by sex and age group in Schleswig-Holstein in 1000 (1958-1973) A2.02c Displaced persons among the resident population by sex and age group in Hamburg in 1000 (1958-1973) A2.02d Displaced persons among the resident population by sex and age group in Niedersachsen in 1000 (1958-1973) A2.02e Displaced persons among the resident population by sex and age group in Bremen in 1000 (1958-1973) A2.02f Displaced persons among the resident population by sex and age group in Nordrhein-Westfalen in 1000 (1958-1973) A2.02g Displaced persons among the resident population by sex and age group in Hessen in 1000 (1958-1973) A2.02h Displaced persons among the resident population by sex and age group in Rheinland-Pfalz in 1000 (1958-1973) A2.02i Displaced persons among the resident population by sex and age group in Baden-Württemberg in 1000 (1958-1973) A2.02j Displaced persons among the resident population by sex and age group in Bayern in 1000 (1958-1973) A2.02k Displaced persons among the resident population by sex and age group in West-Berlin in 1000 (1958-1973) A2.02l Displaced persons among the resident population by sex and age group in Saarland in 1000 (1958-1973) A2.03 Displaced persons among the resident population by federal sate and civil status in 1000 (1958-1973)

B: Scientific publications B1: Steinberg: Population development in Germany in the Second World War B1.01 Changes in population in German states (1939-1946) B1.02 Regional development of the civilian population in Germany (1939-1945) B1.03 Displaced persons in Germany by territory and date of displacement (1944-1955) B1.04 Arrival of displaced persons in Germany by territory of displacement (1944-1955) B1.05 Selected data on socio-economic development in Germany (1946-1987) B1.06 Regional development of population in the...

Abstract

This file contains data on Gini coefficients, cumulative quintile shares, explanations regarding the basis on which the Gini coefficient was computed, and the source of the information. There are two data-sets, one containing the "high quality" sample and the other one including all the information (of lower quality) that had been collected.

The database was constructed for the production of the following paper:

Deininger, Klaus and Lyn Squire, "A New Data Set Measuring Income Inequality", The World Bank Economic Review, 10(3): 565-91, 1996.

This article presents a new data set on inequality in the distribution of income. The authors explain the criteria they applied in selecting data on Gini coefficients and on individual quintile groups’ income shares. Comparison of the new data set with existing compilations reveals that the data assembled here represent an improvement in quality and a significant expansion in coverage, although differences in the definition of the underlying data might still affect intertemporal and international comparability. Based on this new data set, the authors do not find a systematic link between growth and changes in aggregate inequality. They do find a strong positive relationship between growth and reduction of poverty.

Geographic coverage

In what follows, we provide brief descriptions of main features for individual countries that are included in the data-base. Without being comprehensive, these notes are intended to indicate some of the considerations underlying our decision to include or exclude certain observations.

Argentina Various permanent household surveys, all covering urban centers only, have been regularly conducted since 1972 and are quoted in a wide variety of sources and years, e.g., for 1980 (World Bank 1992), 1985 (Altimir 1994), and 1989 (World Bank 1992). Estimates for 1963, 1965, 1969/70, 1970/71, 1974, 1975, 1980, and 1981 (Altimir 1987) are based only on Greater Buenos Aires. Estimates for 1961, 1963, 1970 (Jain 1975) and for 1970 (van Ginneken 1984) have only limited geographic coverage and do not satisfy our minimum criteria.

Despite the many urban surveys, there are no income distribution data that are representative of the population as a whole. References to national income distribution for the years 1953, 1959, and 1961(CEPAL 1968 in Altimir 1986 ) are based on extrapolation from national accounts and have therefore not been included. Data for 1953 and 1961 from Weisskoff (1970) , from Lecaillon (1984) , and from Cromwell (1977) are also excluded.

Australia Household surveys, the result of which is reported in the statistical yearbook, have been conducted in 1968/9, 1975/6, 1978/9, 1981, 1985, 1986, 1989, and 1990.

Data for 1962 (Cromwell, 1977) and 1966/67 (Sawyer 1976) were excluded as they covered only tax payers. Jain's data for 1970 was excluded because it covered income recipients only. Data from Podder (1972) for 1967/68, from Jain (1975) for the same year, from UN (1985) for 78/79, from Sunders and Hobbes (1993) for 1986 and for 1989 were excluded given the availability of the primary sources. Data from Bishop (1991) for 1981/82, from Buhman (1988) for 1981/82, from Kakwani (1986) for 1975/76, and from Sunders and Hobbes (1993) for 1986 were utilized to test for the effect of different definitions. The values for 1967 used by Persson and Tabellini and Alesina and Rodrik (based on Paukert and Jain) are close to the ones reported in the Statistical Yearbook for 1969.

Austria: In addition to data referring to the employed population (Guger 1989), national household surveys for 1987 and 1991 are included in the LIS data base. As these data do not include income from self-employment, we do not report them in our high quality data-set.

Bahamas Data for Ginis and shares are available for 1973, 1977, 1979, 1986, 1988, 1989, 1991, 1992, and 1993 in government reports on population censuses and household budget surveys, and for 1973 and 1975 from UN (1981). Estimates for 1970 (Jain 1975), 1973, 1975, 1977, and 1979 (Fields 1989) have been excluded given the availability of primary sources.

Bangladesh Data from household surveys for 1973/74, 1976/77, 1977/78, 1981/82, and 1985/86 are available from the Statistical Yearbook, complemented by household-survey based information from Chen (1995) and the World Development Report. Household surveys with rural coverage for 1959, 1960, 1963/64, 1965, 1966/67 and 1968/69, and with urban coverage for 1963/64, 1965, 1966/67, and 1968/69 are also available from the Statistical yearbook. Data for 1963/64 ,1964 and 1966/67, (Jain 1975) are not included due to limited geographic coverage, We also excluded secondary sources for 1973/74, 1976/77, 1981/82 (Fields 1989), 1977 (UN 1981), 1983 (Milanovic 1994), and 1985/86 due to availability of the primary source.

Barbados National household surveys have been conducted in 1951/52 and 1978/79 (Downs, 1988). Estimates based on personal tax returns, reported consistently for 1951-1981 (Holder and Prescott, 1989), had to be excluded as they exclude the non-wage earning population. Jain's figure (used by Alesina and Rodrik) is based on the same source.

Belgium Household surveys with national coverage are available for 1978/79 (UN 1985), and for 1985, 1988, and 1992 (LIS 1995). Earlier data for 1969, 1973, 1975, 1976 and 1977 (UN 1981) refer to taxable households only and are not included.

Bolivia The only survey with national coverage is the 1990 LSMS (World Development Report). Surveys for 1986 and 1989 cover the main cities only (Psacharopoulos et al. 1992) and are therefore not included. Data for 1968 (Cromwell 1977) do not refer to a clear definition and is therefore excluded.

Botswana The only survey with national coverage was conducted in 1985-1986 (Chen et al 1993); surveys in 74/75 and 85/86 included rural areas only (UN 1981). We excluded Gini estimates for 1971/72 that refer to the economically active population only (Jain 1975), as well as 1974/75 and 1985/86 (Valentine 1993) due to lack of national coverage or consistency in definition.

Brazil Data from 1960, 1970, 1974/75, 1976, 1977, 1978, 1980, 1982, 1983, 1985, 1987 and 1989 are available from the statistical yearbook, in addition to data for 1978 (Fields 1987) and for 1979 (Psacharopoulos et al. 1992). Other sources have been excluded as they were either not of national coverage, based on wage earners only, or because a more consistent source was available.

Bulgaria: Data from household surveys are available for 1963-69 (in two year intervals), for 1970-90 (on an annual basis) from the Statistical yearbook and for 1991 - 93 from household surveys by the World Bank (Milanovic and Ying).

Burkina Faso A priority survey has been undertaken in 1995.

Central African Republic: Except for a household survey conducted in 1992, no information was available.

Cameroon The only data are from a 1983/4 household budget survey (World Bank Poverty Assessment).

Canada Gini- and share data for the 1950-61 (in irregular intervals), 1961-81 (biennially), and 1981-91 (annually) are available from official sources (Statistical Yearbook for years before 1971 and Income Distributions by Size in Canada for years since 1973, various issues). All other references seem to be based on these primary sources.

Chad: An estimate for 1958 is available in the literature, and used by Alesina and Rodrik and Persson and Tabellini but was not included due to lack of primary sources.

Chile The first nation-wide survey that included not only employment income was carried out in 1968 (UN 1981). This is complemented by household survey-based data for 1971 (Fields 1989), 1989, and 1994. Other data that refer either only to part of the population or -as in the case of a long series available from World Bank country operations- are not clearly based on primary sources, are excluded.

China Annual household surveys from 1980 to 1992, conducted separately in rural and urban areas, were consolidated by Ying (1995), based on the statistical yearbook. Data from other secondary sources are excluded due to limited geographic and population coverage and data from Chen et al (1993) for 1985 and 1990 have not been included, to maintain consistency of sources..

Colombia The first household survey with national coverage was conducted in 1970 (DANE 1970). In addition, there are data for 1971, 1972, 1974 CEPAL (1986), and for 1978, 1988/89, and 1991 (World Bank Poverty Assessment 1992 and Chen et al. 1995). Data referring to years before 1970 -including the 1964 estimate used in Persson and Tabellini were excluded, as were estimates for the wage earning population only.

Costa Rica Data on Gini coefficients and quintile shares are available for 1961, 1971 (Cespedes 1973),1977 (OPNPE 1982), 1979 (Fields 1989), 1981 (Chen et al 1993), 1983 (Bourguignon and Morrison 1989), 1986 (Sauma-Fiatt 1990), and 1989 (Chen et al 1993). Gini coefficients for 1971 (Gonzalez-Vega and Cespedes in Rottenberg 1993), 1973 and 1985 (Bourguignon and Morrison 1989) cover urban areas only and were excluded.

Cote d'Ivoire: Data based on national-level household surveys (LSMS) are available for 1985, 1986, 1987, 1988, and 1995. Information for the 1970s (Schneider 1991) is based on national accounting information and therefore excluded

Cuba Official information on income distribution is limited. Data from secondary sources are available for 1953, 1962, 1973, and 1978, relying on personal wage income, i.e. excluding the population that is not economically active (Brundenius 1984).

Czech Republic Household surveys for 1993 and 1994 were obtained from Milanovic and Ying. While it is in principle possible to go back further, splitting national level surveys for the former Czechoslovakia into their independent parts, we decided not to do so as the same argument could be used to

Syria SY: Population: Female: Ages 25-29: % of Female Population data was reported at 6.601 % in 2017. This records a decrease from the previous number of 6.812 % for 2016. Syria SY: Population: Female: Ages 25-29: % of Female Population data is updated yearly, averaging 7.355 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 9.612 % in 2010 and a record low of 5.658 % in 1973. Syria SY: Population: Female: Ages 25-29: % of Female Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Syrian Arab Republic – Table SY.World Bank.WDI: Population and Urbanization Statistics. Female population between the ages 25 to 29 as a percentage of the total female population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

The statistic shows the number of unique mobile subscribers worldwide from 2010 to 2025. The number of global mobile connections is predicted to reach around **** billion by 2025.

Mobile connections - additional information

The first prototype of a handheld mobile phone was presented to the world in 1973, but it took more than ***** decades until mobile phones became accessible and affordable for almost everyone. In fact, figures show that there are about * billion mobile subscribers today worldwide, about *** thirds of the estimated global population. By 2020, the number of mobile subscriber is expected to increase to close to * billion, taking the global penetration rate to ** percent. Classic mobile phone use is on the decline however, with some ** percent of worldwide mobile phone users owning a smartphone as of 2015.

The world region with most mobile subscriptions is currently Asia Pacific, due to the area’s large population. As of 2016, Asia Pacific boasted over 4 billion cellular connections, ***** times more than both South and North America combined. In fact, no less than ***** Asian states (including transcontinental Russia) are present in a top 10 ranking of countries with the highest number of mobile- subscriptions. As of 2014, China is the largest market of mobile phone subscriptions in the world, home to some *** billion mobile-cellular users, the equivalent of about *** fifth of worldwide subscriptions. By 2019, this number is expected to increase to **** billion subscriptions.

Although the CIS (Commonwealth of Independent States), which includes some of the former member-states of the Soviet Union, ranks last in terms of number of mobile phone subscriptions, the region is first in terms of mobile phone penetration. As of 2016, there are an estimated ***** subscriptions per 100 inhabitants in the area, due to the fact that many users have multiple mobile phones at the same time.

The statistic shows the number of mobile connections worldwide from 2008 to 2020. The number of global mobile connections is predicted to reach around **** billion by 2017.

Mobile connections - additional information

The first prototype of a handheld mobile phone was presented to the world in 1973, but it took more than ***** decades until mobile phones became accessible and affordable for almost everyone. In fact, figures show that there are over *** billion worldwide mobile connections today, a number slightly higher than the estimated global population. By 2020, the number of active mobile phone subscriptions is expected to increase to over * billion. Classic mobile phone use is on the decline however, with some ** percent of worldwide mobile phone users owning a smartphone as of 2015.

The world region with most mobile subscriptions is currently Asia Pacific, due to the area’s large population. As of 2015, Asia Pacific boasted over *** billion cellular connections, three times more than both South and North America combined. In fact, no less than ***** Asian states (including transcontinental Russia) are present in a top 10 ranking of countries with the highest number of mobile- subscriptions. As of 2014, China is the largest market of mobile phone subscriptions in the world, home to some *** billion mobile-cellular users, the equivalent of about one fifth of worldwide subscriptions. By 2019, this number is expected to increase to **** billion subscriptions.

Although the CIS (Commonwealth of Independent States), which includes some of the former member-states of the Soviet Union, ranks last in terms of number of mobile phone subscriptions, the region is first in terms of mobile phone penetration. As of 2015, there are an estimated ***** subscriptions per 100 inhabitants in the area, due to the fact that many users have multiple mobile phones at the same time.

Switzerland Population: Female: Ages 35-39: % of Female Population data was reported at 6.763 % in 2017. This records an increase from the previous number of 6.646 % for 2016. Switzerland Population: Female: Ages 35-39: % of Female Population data is updated yearly, averaging 7.141 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 8.329 % in 2002 and a record low of 6.384 % in 1973. Switzerland Population: Female: Ages 35-39: % of Female Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Switzerland – Table CH.World Bank: Population and Urbanization Statistics. Female population between the ages 35 to 39 as a percentage of the total female population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

Guatemala GT: Population: Male: Ages 25-29: % of Male Population data was reported at 8.782 % in 2017. This records an increase from the previous number of 8.655 % for 2016. Guatemala GT: Population: Male: Ages 25-29: % of Male Population data is updated yearly, averaging 6.954 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 8.782 % in 2017 and a record low of 6.397 % in 1973. Guatemala GT: Population: Male: Ages 25-29: % of Male Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Guatemala – Table GT.World Bank: Population and Urbanization Statistics. Male population between the ages 25 to 29 as a percentage of the total male population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

France FR: Population: Male: Ages 30-34: % of Male Population data was reported at 6.441 % in 2017. This records a decrease from the previous number of 6.485 % for 2016. France FR: Population: Male: Ages 30-34: % of Male Population data is updated yearly, averaging 7.282 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 8.614 % in 1981 and a record low of 5.872 % in 1973. France FR: Population: Male: Ages 30-34: % of Male Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s France – Table FR.World Bank.WDI: Population and Urbanization Statistics. Male population between the ages 30 to 34 as a percentage of the total male population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

Luxembourg LU: Population: Male: Ages 30-34: % of Male Population data was reported at 7.636 % in 2017. This records a decrease from the previous number of 7.739 % for 2016. Luxembourg LU: Population: Male: Ages 30-34: % of Male Population data is updated yearly, averaging 7.881 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 9.137 % in 1995 and a record low of 7.148 % in 1973. Luxembourg LU: Population: Male: Ages 30-34: % of Male Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Luxembourg – Table LU.World Bank: Population and Urbanization Statistics. Male population between the ages 30 to 34 as a percentage of the total male population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

Turkey TR: Population: Male: Ages 25-29: % of Male Population data was reported at 8.027 % in 2017. This records a decrease from the previous number of 8.129 % for 2016. Turkey TR: Population: Male: Ages 25-29: % of Male Population data is updated yearly, averaging 8.118 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 8.923 % in 2007 and a record low of 6.820 % in 1973. Turkey TR: Population: Male: Ages 25-29: % of Male Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Turkey – Table TR.World Bank: Population and Urbanization Statistics. Male population between the ages 25 to 29 as a percentage of the total male population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

Switzerland Population: as % of Total: Female: Aged 15-64 data was reported at 65.440 % in 2017. This records a decrease from the previous number of 65.663 % for 2016. Switzerland Population: as % of Total: Female: Aged 15-64 data is updated yearly, averaging 65.727 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 66.828 % in 1987 and a record low of 63.892 % in 1973. Switzerland Population: as % of Total: Female: Aged 15-64 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Switzerland – Table CH.World Bank: Population and Urbanization Statistics. Female population between the ages 15 to 64 as a percentage of the total female population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average; Relevance to gender indicator: Knowing how many girls, adolescents and women there are in a population helps a country in determining its provision of services.