Historical Index of Human Development
Life Expectancy at birth
Life expectancy is defined as “the average number of years of life which would remain for males and females reaching the ages specified if they continued to be subjected to the same mortality experienced in the year(s) to which these life expectancies refer” (United Nations, 2000). Data for the period 1980-2015 come from the Human Development Reports (UNDP, 2010 and 2016) while the World Bank (World Development Indicators) provides that data for 1960-1975 (exceptionally completed with data from UNESCO) and the United Nations” Demographic Yearbook Historical Supplement (United Nations, 2000) for the 1950s. Pre-1950 estimates come mostly from Riley (2005b), Flora (1983), and the OxLAD database for Latin America (Astorga et al., 2003), which were completed with the national sources listed below.
Dearth of data forced me occasionally to introduce some assumptions for the period before the epidemiological or health transition that, in developing regions, particularly those of South Asia and Sub-Saharan Africa, often started during the Interwar years (Omran, 1971; Riley 2005b, 2005c). I have accepted Riley’s (2005a, p. 539) assumption that “the average of all life expectancy estimates of acceptable quality for countries in a region provides the best available gauge of the pretransition average for the entire region”.
Maximum and the minimum values for the life expectancy index were established at 85 and 20 years, respectively. A “floor” of 25 years has been accepted as the minimum historical value for life expectancy at birth. Such a “floor” precludes a zero value for the transformed life expectancy index and, consequently, for the HIHD.
North Africa. Algeria, 1900-1929, inferred from the infant survival rate (ISR, that is, 400 –as the maximum infant mortality rate per thousand- less the country’s infant mortality rate). Egypt, 1929-1938, from Fargues (1986); 1913, assumed to be as Tunisia’s; and 1900, as Algeria’s. Libya, 1900-1938, assumed to be identical to Egypt’s. Morocco, 1900-1938, assumed to be as Algeria’s, except 1913, as Tunisia’s. Tunisia, 1900, 1929-1938, assumed to be the same as Algeria’s.
Central Africa. Estimates for CAR, Chad, Congo, Congo D.R., and Gabon over 1870-1929, and for Cameroon (1870-1913) inferred from heights.
West Africa. Figures for 1938 are backwards projected with estimates inferred from heights and infant survival rates (ISR), for Benin, Burkina Faso, Côte d’Ivoire, Gambia, Ghana (but for 1913), Guinea, Guinea-Bissau, Liberia, Mali, Nigeria (but for 1929, from Ayeni 1976), Senegal (but for 1929), and Sierra Leone (but for 1929). Mauritania’s and Niger’s assumed to identical to Mali’s. Togo’s assumed to be as Benin’s, but Benin in 1913, as Ghana’s.
East Africa. Data for 1938 backwards projected with estimates inferred from heights and ISR, for Burundi, Ethiopia, Rwanda, Somalia, and Tanzania. Djibouti’s assumed to be as Ethiopia’s. Riley (2005b) provides estimates of 23.9 years for Kenya and Uganda in the 1930s, so I assigned the minimum historical value of 25 years to these countries over 1870-1929. Sudan’s was assumed to be as Kenya’s.
Southern Africa. Data for 1938 backwards projected with estimates inferred from heights and ISR, for Angola, Botswana (1913), Malawi, Mauritius (1870-1913), Namibia (1870-1880), South Africa (1870), Swaziland (1929), and Zambia. Namibia, 1890-1900, assumed to be the same as for blacks in Cape Colony, from Simkins et al. (1989); 1929-1938, from Notkola et al. (2000), estimated from Northern Namibia’s figures adjusted with the ratio all Namibia to Northern Namibia c. 1960. South Africa, 1880-1913, estimates from Simkins et al. (1989). For Zimbabwe, Riley (2005b), following Condé (1973), assigned 26.4 to the 1930s, so I have assigned the minimum goalpost over 1870-1929. Botswana’s (but for 1913), Lesotho’s, and Swaziland’s (but for 1929), were assumed to be identical to Namibia’s. Madagascar’s, assumed to as Mauritius’s and Mozambique’s as Malawi’s.
Most data come from Arriaga (1968) and the MOxLAD database for Latin America (Astorga et al. 2003) (supplemented with the working sheets prepared by Shane and Barbara Hunt which have been kindly provided by Pablo Astorga). In addition, national sources used are:
Argentina, 1870-1890, Recchini de Lattes and Lattes (1975).
Chile, 1890-1900, and Uruguay, 1870-1900, assumed to have evolved along Argentina.
Uruguay, 1900-1938, Ministerio de Salud Pública (2001),
Life expectancy for Colombia, 1870-1900, Cuba, 1870-1900, Panama, 1880-1900, Honduras, 1890-1900, Puerto Rico, 1870-1890, and Venezuela, 1880-1900, has been assumed to evolve along Costa Rica’s.
Peru, 1913-1938, assumed to evolve along Bolivia’s.
Puerto Rico, 1900-1938, UN (1993); 1890, Riley (2005b); 1870-1890, assumed it evolves along Costa Rica.
Jamaica, 1880-1938, Riley (2005a: 198); 1870-1880, assumed it evolves along Costa Rica.
Trinidad-Tobago, 1860-1900, assumed to evolve along Jamaica’s.
U.S.A., 1870-1890, Haines (1994).
In the absence of life expectancy estimates for early years projecting the available figures with infant survival rates (ISR) has derived them for Panama, 1900-1929 and Guyana, 1950-1960. Such a procedure was also used to distribute the average life expectancy estimate for Argentina, 1869-1894.
Most pre-1950 estimates come from Riley (2005b) who claims that the earliest health transition started in the 1870/1890s when mean and median values were 27.5 and 25.1 years, respectively. Lower bound estimates for 1950 or 1940s levels were used for 1938. In the absence data, pre-1929 life expectancy at birth was assumed to be 25 years.
Cambodia, 1938, Siampos (1970), cited in Riley (2005b); 1929 assumed it evolved along China as they had similar levels in 1938.
China, 1938 is proxied by upper bound in 1936 (2005b); 1929, Caldwell et al. (1986), cited in Lavely and Wong (1998).
Hong Kong SAR, 1900-1938, assumed to have evolved at the same rate of variation as Taiwan’s.
India, 1890-1938, McAlpin (1983) extrapolated to 1880 with Visaria and Visaria (1982).
Indonesia, 1929, Riley (2005b).
Japan, 1890-1900, Johansson and Mosk (1987); 1880, Janetta and Preston (1991); 1870, Riley (2005b).
Korea, 1938, United Nations (1993). 1913, Riley (2005b) provides a figure of 23.5 years for 1915. Since the historical lower bound was assumed to be 25 years, this value was assigned to the pre-1913 era. 1929, derived by increasing the figure for 1915 by 0.87 yearly, as suggested by Riley (2005b).
Lao PDR, 1929, assumed to evolve as Vietnam’s.
Malaysia, 1929-1938 figures obtained by projecting 1950 level backwards with the infant survival rate.
Nepal, 1925, assumed to evolve as India.
Singapore, 1929-1938 figures obtained by projecting 1950 level backwards with the infant survival rate; 1870-1925, assumed to evolve at the same pace as Malaysia’s.
Sri Lanka, 1890-1913, 1938, Langford and Storey (1993); 1929, Sarkar (1951)
Taiwan, 1955 onwards, Taiwan national statistics; 1950, Glass and Grebenik (1967); 1890-1938, Cha and Wu (2002). The level assumed for 1890 by Cha and Wu, 25 years, accepted for 1870-1880.
Thailand, 1938, Vallin (1976).
Turkey, 1938, Shorter and Macura (1982); 1913, Pamuk (2007). Pre-1913, and 1929, assumed to evolve at the same yearly rate of change as Greece’s.
Australia, 1870-1900, Whitwell et al. (1997).
New Zealand (adjusted for Maori population), 1880-1890, Glass and Grebenik (1967); 1870, Riley (2005b).
Austria, 1870, Helczmanovski (1979); 1880-1890, interpolated from data in Helczmanovski (1979), Glass and Grebenik (1967: 82), and the United Nations (1993).
Belgium, 1929-1950, United Nations (1993); 1913, Crafts (1997); 1880-1900, Flora (1983); 1870, Deprez (1979).
Bulgaria, 1870-1890, assumed to move along Greece’s.
Cyprus, since life expectancy levels in Cyprus and Greece in 1890 were identical and those for 1938, very close, I assumed they were the same up to 1929. Figures for 1890 and 1938 come from Riley (2005b).
Czechoslovakia, 1870-1913, Sbr (1962); 1890, Riley (2005b).
Finland, 1870-1990, Kannisto et al. (1999).
France, 1870-1900, Flora (1983).
Germany, 1870-1890, Flora (1983).
Greece, 1870-1913, Valaoras (1960).
Hungary, 1870-1900, assumed to evolve along Austria’s.
Ireland, 1850-1900, assumed to evolve along the U.K.’s
Italy, 1881, and 1901, Zamagni (1990); 1870-1938, Conte et al. (2007).
Poland, 1870-1913, assuming it evolved as Czechoslovakia’s.
Portugal, 1850-1913, Leite (2005); 1929, Veiga (2005); 1938, United Nations (1993).
Romania, assumed to evolve along Greece, 1870-1890, and along Bulgaria’s, 1890-1929.
Russia, Pressat (1985) for European Russia, 1870-1913, and European Soviet Union, 1929-1938.
Spain, 1950s, Nicolau (2005) and Goerlich and Pinilla (2005); 1870-1938, Dopico and Reher (1998).
Sweden, 1870-1965, Keyfitz and Fleiger (1968), reproduced in Sandberg and Steckel (1997).
Yugoslavia, assumed to evolve along Greece’s, 1870-1890, and along Bulgaria’s, 1890-1929. For 1929 and 1938 life expectancy was estimated by projecting the available figures with infant survival rates for 1950.
United Kingdom, 1850-1900, Floud and Harris (1997).
The rate of adult literacy is defined as the percentage of the population aged 15 years or over who is able to read and write. Unfortunately, in empirical terms, adult literacy is a far from uniform concept. While, from a conceptual point of view, there are no objections to the UNESCO definition of a literate person, namely, “who can, with understanding, both read and write a short simple statement on his everyday life” (quoted in Nilsson, 1999, p. 278), assessing a person’s literacy is quite a different issue.
Reading and writing do not necessarily go together in developing societies and prior to the diffusion of the schooling system the lag between acquiring the ability to read and to write can be as wide as a century or more (Markussen, 1990; Nilsson, 1999). Hence, the literacy rate would vary wildly depending on whether a wide (read ability only) or a narrow (reading and writing skills) definition of literacy is used, and how it is actually measured (with marriage signatures being particularly misleading in pre-industrial societies). Moreover, becoming literate is far more difficult and time-intensive in countries which languages employ Chinese characters (Taira, 1971; Honda, 1997). In practice, although classifying a person as truly literate should imply that she is able to read and write, it not always possible to make such a precise distinction for the past (Nilsson, 1999). Unfortunately, historical data are far from homogeneous and, therefore, the results will suffer from biases, which, nonetheless, will not condition decisively long run trends.
Most of the data on literacy for 1980-2015 comes from UNESCO http://data.uis.unesco.org, completed with the 2009 Human Development Report (UNDP, 2009). For 1950-1975 data come from UNESCO (1970, 2002) and the World Bank (2010), completed with data from Banks (2010), Hayami and Ruttan (1985), and Easterly (1999). UNESCO (1953, 1957), Flora (1973), OxLAD database for Latin America, plus national sources, provide data for the pre-1950 era. Data for Guinea, Madagascar, Mali, Mauritius, Niger, Senegal, and Togo, 1970-80, come from Ouane and Amon-Tanoh (1990).
In the absence of historical data on literacy, available literacy rates were projected backwards with the rate of primary enrolment. Also, occasionally, available literacy rates have been projected backwards with years of primary education (from Morrisson and Murtin, 2009). In the post-1960 period, the literacy rate has been, in a few cases, derived by assuming that the illiteracy rate was identical to the share of population with no schooling provided by Barro and Lee (2002, 2010) and Cohen and Soto (2007).
Goalposts [M=100, Mo=0] have been kept but the highest and lowest historical values have been set at 99 and 1 per cent, respectively. This “ceiling” prevents index values above one, while “floor” precludes a zero value for the transformed literacy index and, consequently, for the HIHD.
Literacy rates have been projected backwards with the rate of primary enrolment for Algeria (1870-1880, 1938), Burkina Faso (1929-1938), Burundi (1929-1938), Cape Verde (1929-1938), Chad (1925-1938), Congo (1929-1938), Congo D. R. (1929-1938), Djibouti (1938), Ethiopia (1938), The Gambia (1929), Ghana (1870-1938), Guinea-Bissau (1938), Guinea (1913-1938), Kenya (1929-1938), Lesotho (1890-1938), Liberia (1890-1938), Mauritius (1870-1933), Namibia (1913-1938), Nigeria (1900-1938), Rwanda (1929-1938), Sierra Leone (1870-1938), South Africa (1929), Sudan (1913-1938), Swaziland (1938), Tanzania (1929-1938), Togo (1929-1938), Tunisia (1900-1913), Uganda (1900-1938), Zambia (1900-1938), and Zimbabwe (1900-1938).
Also, in the absence of estimates for the pre-1938 period, available literacy rates were projected backwards with years of primary education for the population above 15 years (Morrisson and Murtin 2009) for Angola (1870-1938), Benin (1870-1938), Botswana (1900-1938), Cameroon (1870-1938), Côte d’Ivoire (1870-1938), Ethiopia (1870-1933), Kenya (1870-1913), Lesotho (1870-1880), Madagascar (1870-1938), Malawi (1870-1938), Mali (1870-1938), Mozambique (1870-1880), Morocco (1870-1900), Senegal (1870-1880), and Tunisia (1870-1890).
Botswana (1870-1900) and Namibia (1870-1900) have been assumed to evolve along South Africa, and Swaziland (1870-1929), as Lesotho’s. Libya (1870-1900) is assumed to be as Egypt’s. Djibouti (1870-1929) was assumed to evolve along Sudan.
Newland (1991) and MOxLAD database (Astorga et al. 2003) (plus the working sheets prepared by Shane and Barbara Hunt and kindly provided by Pablo Astorga) provide most of the data. Otherwise, the sources are:
Chile, 1870, Braun et al. (2000)
Nicaragua, 1900, Núñez (2005)
Literacy rates have been backwards projected with the rate of primary enrolment for Bolivia, 1870-1890, and Puerto Rico, 1870-1890.
U.S., 1870-1890, 1960-1970, Costa and Steckel (1997).
Literacy rates have been backwards projected with years of primary education for the population above 15 years (Morrisson and Murtin (2009) for Dominican Republic, 1870-1900; El Salvador, 1870-1890; Uruguay, 1870-1890, and Venezuela, 1870-1880.
China, 1870, 1913, Morrisson and Murtin (2007).
India, 1890, 1938, Tomlinson (1993).
Japan, 1870, Steckel and Floud (1997); 1880-1890 (by assuming that the rate of primary enrolment was a good approximation), Hanley (1990); 1900-1938, Honda (1997).
Korea, 1929, Kimura (1990).
Literacy rates have been projected backwards with the rate of primary enrolment for Cambodia and Laos, 1913-1938; China, 1929; Hong Kong, 1870-1913; India, 1870-1880, 1929; Indonesia, Taiwan, and Vietnam, 1900-1938; Iran, Jordan, Malaysia and Myanmar, 1929; Israel, Lebanon, Sri Lanka, and Syria, 1920-1938; Korea, 1913; Fiji, 1900-1913, 1929-38.
Literacy rates have been backwards projected with years of primary education for the population above 15 years from Morrisson and Murtin (2009) for Iraq, 1870-1938; Malaysia, 1870-1900; Myanmar, 1870-80; Philippines, 1870-1913; Syria, 1870-1900; Thailand, 1880-1913, 1929.
Australia, 1870, Vamplew (1987); 1890-1900, Steckel and Foud (1997b).
Austria, 1880-1913, Flora (1983).
Belgium, 1938, Banks (2010).
Czechoslovakia, 1880-1900, Flora (1983); 1938, Banks (2010).
Finland, 1870, Crafts (1997); 1880-90, Myllantaus (1990); 1900, Flora (1983); 1929-60, Banks (2010).
Germany, 1950, Banks (2010).
Greece, 1929-1950, Banks (2010).
Ireland, 1870-1900, Flora (1983); 1913, Crafts (1997).
Italy, 1870-80, Flora (1983); 1890, 1960, Conte et al. (2007); 1938, Banks (2010).
Poland, 1870-90, assumed to evolve along Hungary’s; 1900, Flora (1983); 1929-1960, Banks (2010).
Portugal, 1880, Reis (1993); 1880-1890, 1913-1938, Nunes (1993).
Romania, 1929-1960, Banks (2010).
Russia, 1870-1960, Mironov (1991, 1993).
Spain, 1870-1880, Núñez (2005); 1890-1930, Reher (personal communication); Viñao (1990).
Sweden, 1870-1960, Banks (2010).
Yugoslavia, 1929-1990, Banks (2010).
U.K., 1870-1960, Banks (2010).
Literacy rates have been backwards projected with the rate of primary enrolment for Albania, 1920-1938; Cyprus, 1880-1900.
Literacy rates have been backwards projected with years of primary education from Morrisson and Murtin (2009) for Bulgaria, 1870-1880.
Figures on enrolment rates, apparently straightforward, present difficulties of interpretation. The usual measurement procedure is to divide the number of students by the relevant school-age population cohort. For example, primary enrolment rate defined as the share of children receiving primary education over population aged 5 to 14 years, keeping this yardstick fixed over time. This way the unadjusted (primary) enrolment rate is obtained. Such age span is, however, longer than primary schooling, leading to an under-estimate. Even worse, comparability is fraught with difficulties as the length of primary or secondary schooling changes across countries and over time, and, therefore, biases of an unknown sign are introduced (Benavot and Riddle, 1988; Nilsson, 1999). Alas, up to the mid-twentieth century, the only kind of enrolment rate that can be easily computed for a large number of countries and over a long time-span is the unadjusted one. Then, UNESCO, OECD, and the World Bank provide gross enrolment rates, in which the denominator is adjusted to the age bracket for each type of schooling (primary, secondary, tertiary) for the present. In our case, since the rate of unadjusted all or total enrolment includes primary, secondary, and tertiary enrolment numbers in the numerator and the population aged 5-24 in the denominator, differences between gross and net rates are negligible.
Most of the data on gross enrolment rates for 1970-2015 comes from UNESCO http://data.uis.unesco.org, completed with the 2009 Human Development Report (UNDP, 2009). For the pre-1970 period, enrolment figures come mostly from UNESCO (2010), Banks (2010), Mitchell (2003a, 2003b, 2003c), Flora (1983), and MOxLAD database for Latin America, supplemented with national sources.
Occasionally, for nineteenth and early twentieth century countries (mostly African and Asian) the total -that is, primary, secondary, and tertiary- enrolment rate has been obtained by adjusting the primary or primary and secondary enrolment ratio with the ratio resulting from dividing the share of population aged 5-14 years of age by the share of population aged 5-24. This crude procedure implies the assumption that secondary and tertiary enrolment numbers represent a negligible proportion of the relevant population cohort. For those countries for which no evidence on enrolment was available at given dates, the closer enrolment rates have been projected backwards with the average years of schooling among the population above 15 (Morrisson and Murtin 2009). The relevant population was derived as follows. Firstly, I computed the share of population aged 5-24 (and 5-14) over total population at census years from Mitchell (2003a, 2003b, 2003c) that was, then, interpolated log-linearly to derive yearly series and, finally, its result multiplied by total population figures.
Goalposts [M=100, Mo=0] have been kept but the highest and lowest historical values have been set at 99 and 1 per cent, respectively. This “ceiling” prevents index values above one, while “floor” precludes a zero value for the transformed enrolment index and, consequently, for the HIHD.
For missing countries the population share of those aged 5-24 years of age has been replaced with that of a neighbour country with a similar demographic transition. Thus, Nigeria’s shares have been accepted for Benin, Cameroon, Equatorial Guinea, and Togo. South Africa’s were adopted for Botswana, Lesotho, Namibia, and Swaziland. Mali’s shares have been used, in turn, for Burkina Faso, CAR, Chad, Congo, The Gambia, Guinea, Guinea-Bissau, Mauritania, Niger, and Senegal. Uganda’s are used for Burundi, Congo D.R., and Rwanda. Then, Ghana’s are employed for Cape Verde, Côte d’Ivoire, Gabon, Liberia, and Sierra Leone, and Kenya’s for Somalia. Lastly, Mozambique’s were accepted for Comoros and Madagascar, Egypt’s for Djibouti, Ethiopia, and Sudan, Algeria’s for Libya, and Tanzania’s for Malawi.
All enrolment rates have been derived according to the procedure explained above with primary enrolment rates provided by UNESCO (1953, 1957) [U], Benavot and Riddle (1988) B&R] and Frankema (2012) [F], for the following countries and years: for Angola (F), 1890-1929; Benin (B&R,F), 1890-1938; Botswana (F,U), 1890-1938, 1960; Burkina Faso (B&R,F), 1913-1950; Burundi (F,U) 1929-1950; Cameroon (B&R), 1890-1929; CAR (B&R,F), 1900-1950; Chad (B&R), 1900-1938; Congo (B&R,F), 1900-1950; Congo, D.R. (U), 1929-1950; Côte d’Ivoire, (B&R,F), 1900-1950, 1960; Djibouti (F), 1938-1960; Egypt (B&R), 1890-1900; Equatorial Guinea (F), 1960; Ethiopia (F), 1938; Gabon (B&R,F), 1900-1950; The Gambia (B&R,F), 1900-1938, 1960; Ghana (F), 1870, 1890; Guinea (B&R,F), 1913-1950, 1960; Guinea-Bissau (F), 1938-1960; Kenya (B&R), 1938; Lesotho (B&R,F) 1890-1938, 1960; Madagascar (B&R,U), 1929-1938; Malawi (F), 1900-1938; Mali (B&R), 1913-1929; Mauritania (B&R), 1913-1938; Mauritius (B&R), 1870-1900, 1929, 1938; Mozambique (B&R), 1938; Namibia (B&R,F), 1913-1960; Niger (B&R,F), 1913-1938; Nigeria (B&R,F), 1929-1950, 1960; Rwanda (U,F), 1929-1950; Senegal (B&R,F), 1913-1960; Sierra Leone (F), 1870-1890, 1950; Sudan (B&R), 1913-1929; Swaziland (F,U), 1938-1955; Tanzania (B&R,F), 1938, 1960; Togo (B&R,U) 1913-1950; Uganda (F,B&R,U), 1900-1950; Zambia (F), 1900-1950; Zimbabwe (F), 1900, 1938-1960.
For those countries for which no evidence on enrolment was available for a given benchmark, the closest enrolment rates were projected backwards with average years of schooling among the population above 15 (Morrisson and Murtin 2009). This procedure was applied to Egypt (1870-1880), Kenya (1870-1913), Madagascar (1870-1900), Malawi (1870-1890), Mozambique (1870-1913), and Tunisia (1870-1890).
In the absence of enrolment data for particular countries, I have assumed all enrolment rates evolved as those of a neighbouring country or one with similar features. Thus, Djibouti’s (1913-1929) was assumed to move along Sudan’s, and Libya’s (1870-1938) as Egypt’s. Enrolment rates for Botswana (1870-1890), Lesotho (1870-1880) and Namibia (1870-1900) have been derived with the rate of variation of South Africa over the relevant period, and Swaziland’s (1870-1929) with Lesotho’s. Also, it was assumed that Guinea-Bissau’s (1965-1970) moved along Senegal’s, The Gambia’s (1870-1890) as Ghana’s, and Tanzania’s (1890-1913) as Uganda’s.
Most data come from MOxLAD database (Astorga et al. 2003), supplemented it with the working sheets prepared by Shane and Barbara Hunt. Otherwise, the sources are:
Puerto Rico, 1870-1880, and Venezuela, 1870-1890, Newland (1991).
All enrolment derived with primary enrolment in Benavot and Riddle (1988), adjusted with the ratio of those aged 5-14 years to those aged 5-24 years, for Dominican Rep., 1870-1913; Ecuador, 1870-1880.
All enrolment rates have been backwards projected with years of primary education for the population above 15 years (Morrisson and Murtin (2009) for Cuba, 1870-1890; Honduras, 1870-1880; Panama, 1870-1890, and Paraguay, 1870-1880.
China, 1890-1913, assumed to evolve as Hong Kong’s. Hong-Kong assumed to have evolved as China, 1960-1980, and Kuwait as Iraq, 1950-1960. Bahrein, 1950-1970, and Brunei-Darassalam, Oman, Qatar, and UAE, 1950-1980, assumed to evolve along Kuwait’s.
All enrolment derived with primary enrolment in Benavot and Riddle (1988), adjusted to all enrolment with the ratio of those aged 5-14 years to those aged 5-24 years, for Cambodia, 1929 and 1938; Iraq, 1913; Israel and Laos, 1920-38 1929 and 1938; Philippines, Taiwan, and Fiji, 1900; Syria, 1900-1913.
All enrolment rates have been backwards projected with years of primary education for the population above 15 years from Morrisson and Murtin (2009) for India and Myanmar, 1870; Iran and Iraq, 1870-1900; Philippines and Syria, 1870-1890; Thailand, 1800-1900; Turkey, 1870-1880.
Population aged 5-24 (and 5-14) share in total population in Syria accepted for Lebanon and that of China for Nepal.
Italy, 1870, 1913, 1929, Conte et al. (2007); Portugal, 1880-1913, Reis (1993), primary enrolment; Spain, 1870-1980, Núñez (2005).
Population aged 5-24 (and 5-14) share in total population for Cyprus derived from Turkey’s and Greece’s, weighted by the Turkish and Greek shares in total population.
All enrolment derived with primary enrolment in Benavot and Riddle (1988), adjusted to all enrolment with the ratio of those aged 5-14 years to those aged 5-24 years, for Czechoslovakia, 1913; Denmark, 1870; Romania, 1870.
All enrolment derived with primary and secondary enrolment in Lindert (2004), adjusted to all enrolment with the ratio of those aged 5-14 years to those aged 5-24 years (Mitchell 2003c), for Ireland, 1870-1900; Italy, 1870; Switzerland, 1870; UK, 1870-1900.
All enrolment rates have been backwards projected with years of primary education for the population above 15 years from Morrisson and Murtin (2009) for Bulgaria, 1870-1880.
Per Capita GDP
GDP per head is expressed in 1990 Geary-Khamis dollars. Unless stated below, post-1950 GDP per head data come from the Maddison Project (2013), completed with Maddison (2006, 2010) and, since 1995, with Conference Board (2016). Occasionally, Conference Board estimates have been accepted for the entire post-1950 period, as it is the case of China, for which the “alternative” series have been accepted. Otherwise, for specific countries shown below, per capita GDP levels for (usually) 1950 have been projected backwards with volume indices of real per capita GDP taken from historical national accounts.
Similarly to the cases of social indicators, I have assumed a lower bound for per capita GDP that has been set at G-K 1990 $ 300, which represents a basic level of physiological subsistence (Sagar and Najam, 1998; Milanovic et al., 2011), below both the World Bank’s extreme poverty threshold of G-K 1990 $ 1 a day per person and Maddison’s (2006) G-K 1990 $ 400 per capita.
Most estimates pre-1950 come from Prados de la Escosura (2012). The GDP data set for Africa was with the available estimates for the northern region and South Africa. In North Africa, 1870-1950, estimates come from Maddison (2006: 577-580) completed with some interpolations on the basis of my own indirect estimates. For Algeria, I interpolated the levels for 1890 and 1900. For Tunisia, I accepted Maddison estimates for 1913 and interpolated the rest of the benchmarks. In the case of Morocco I found Maddison’s level for 1913 too low relative to Tunisia, and used my own estimates. For Egypt, Maddison figures were also used but re-scaled by accepting Pamuk (2006) level for 1950. In the case of South Africa, I deflated Stadler (1963) nominal GDP estimates for 1913-1950 with Alvaredo and Atkinson (2010) price index, and used population figures from Feinstein (2005: 257-8) to derive per capita GDP. Then, the estimates for 1913 were projected backwards to 1870 with my own indirect estimates.
Further assumptions were needed to fill missing values of GDP per head for some Sub-Saharan countries. Following Maddison’s approach, I assumed that growth trends for missing countries were similar to those of their neighbours. Thus, in the case of French Equatorial Africa (CAR, Congo, Gabon, and Chad), over 1870-1929, I assumed they grew as similar countries (coastal or landlocked, resource abundant or scarce) in French West Africa. Similarly, during the same period, Cameroon, Guinea-Bissau, and Togo were assumed to grow at the same rate of similar countries in West French Africa. Liberia was assumed to evolve as Sierra Leone over 1900-1913. In East Africa, I accepted Uganda’s pace of growth for Rwanda and Burundi (1913-1929) while Kenya’s pace of growth during 1870-1913 was assumed to be similar to Tanzania’s. Also, Ethiopia and Sudan were assumed to evolve as Egypt over 1870-1913. In southern Africa, Mozambique was accepted to evolve as Angola (1870-1900), and Zambia and Malawi (1913-1929) as Zimbabwe. Lastly, in the cases of Botswana, Lesotho, and Swaziland (1913-1938), and Namibia (1870-1913), I accepted the growth rate for South Africa.
Data for 1950-2015 comes CEPAL (2009) and (2017) http://interwp.cepal.org/, except in the case of Cuba for 1950-1990. For the pre-1950 period, estimates derive from the Maddison Project Dataset (2013), Astorga and Fitzgerald (1998) and MOxLAD database (Astorga et al. 2003). Otherwise national sources have been used. GDP per head is expressed in 1990 Geary-Khamis dollars.
Argentina, Della Paolera et al. (2003), 1884-1950, assuming the rate of growth over 1870-84 was identical to that for 1884-90. The alternative option of projecting backwards the level for 1884 to 1875 with Cortés Conde (1997) casts too low a figure. I assumed the level for 1870 was identical to that of 1875.
Brazil, 1870-1950, Goldsmith, (1986).
Bolivia, 1870-1950, Herranz-Loncán and Peres Cajías (2016). Figures for 1870 and 1880 interpolated from those for 1850 and 1883.
Chile, 1870-1950, Díaz, Lüders and Wagner (2007).
Colombia, 1870-1905, Kalmanovitz Krauter and López Rivera (2009) and data kindly provided by Salomon Kalmanovitz in private communication; 1905-1950, GRECO (2002).
Cuba, up to 1902, Santamaría (2005); 1902-1958, Ward and Devereux (2012); 1958-1990, Maddison Project (2013).
An important caveat in the case of Cuba is that Maddison’s (and Maddison Project’s) level for 1990 has not been accepted. The reason is that, given the lack of PPPs for Cuba in 1990, Maddison (2006: 192) assumed Cuban per capita GDP was 15 per cent below the Latin American average. Since this is an arbitrary assumption, I started from Brundenius and Zimbalist’s (1989) estimate of Cuba’s GDP per head relative to six major Latin American countries (Argentina, Brazil, Chile, Colombia, Mexico, and Venezuela, LA6) in 1980 (provided in Astorga and Fitzgerald 1998) and applied this ratio to the average per capita income of LA6 in 1980 Geary-Khamis dollars to derive Cuba’s level in 1980. Then, following Maddison (1995: 166), I derived the level for 1990 with the growth rate of real per capita GDP at national prices over 1980-1990 and reflated the result with the US implicit GDP deflator in order to arrive to an estimate of per capita GDP in 1990 at 1990 Geary-Khamis dollars. Interestingly, Cuba’s position relative to the US in 1929 and 1955 is very close to the one Ward and Devereux (2012) estimated using a different approach.
Ecuador, 1870-1890, I assumed it evolved as Peru over 1880-1900, yielding $447 for 1880, and I arbitrarily assumed a per capita GDP of $400 for 1870.
Jamaica, 1870-1929, Eisner (1961).
Mexico, 1870-1900, Coatsworth (1989: 41); 1896-1950, INEGI (1995)
Puerto Rico, 1900-1940, Devereux (2017); 1940-1950, Anuario Estadístico de Puerto Rico (1955).
Peru, 1870-1950, Seminario (2011)
Uruguay, 1870-1950, Bértola (1998)
Venezuela, 1870-1950, Batista (1997).
Central America (Costa Rica, El Salvador, Guatemala, Honduras, and Nicaragua), I derived the level for 1913 by assuming the growth over 1913-20 was identical to that of 1920-25, the latter derived from OxLAD database (Astorga et al. 2003).
Caribbean. Bahamas, Barbados, Belize, Guyana, since 1950, Trinidad-Tobago, 1950-1970, and St. Kitts and Nevis, St. Vincent and the Grenadines, from 1990, Maddison (2006, 2010), Conference Board (2016), and Bulmer-Thomas (personal communication)
Canada, 1870-1926, Urquhart (1993); 1926-1950, Statistics Canada (2004).
U.S., Gallman (Rhode, 2002), 1870-1890; 1890-1950, Kendrik (1961).
Middle East (Iran, Iraq, Jordan, Lebanon, Palestine (Israel), Saudi Arabia, Syria, Yemen, and the Gulf -Bahrain, Kuwait, Oman, Qatar, UAE-), 1870-1913, Pamuk (2006)
Bhutan, Brunei, and Maldives, Maddison (2006).
Korea, 1913-1938, Cha and Kim (2006); 1890, Bourguignon and Morrisson (2002).
Myanmar, 1880-1890, assumed to evolve along India.
Philippines, 1890, Bourguignon and Morrisson (2002).
Turkey, 1880, Altug et al. (2008); 1890, Bourguignon and Morrisson (2002).
Taiwan, 1880-1890, assumed to evolve as China’s; 1900, Cha and Wu (2002).
New Zealand, 1870-1938, Greasley and Oxley (2000a, 2000b).
Austria, 1870-1913, Maddison (2010) level for 1913 projected backwards with Schulze (2000) estimates for Imperial Austria under the assumption that real output per head in Modern Austria moved along Imperial Austria’s.
Belgium, 1870-1913, Horlings (1997); 1929-1938, average of GDP estimates of income and expenditure approaches in Buyst (1997), and output in Horlings (1997).
Czechoslovakia, Poland, Romania, Yugoslavia, 1880, computed with Good (1994) ratio of 1880 GDP per head to the average GDP per head of 1870 and 1890 applied to Maddison’s (2010) average levels for 1870 and 1890.
Cyprus, 1913-2007, Apostolides (2011). I assumed the level for 1913 was identical to that for 1921.
Denmark, 1850-1938, Hansen (1974).
France, 1870-1950, Toutain (1997).
Finland, 1870-1990, Hjerppe (1996).
Germany, Nominal GDP, 1950-2000, IMF (2010); 1901-1913, 1925-1949, Spoerer and Ritschl (1997); 1901 level backwards projected to 1870 with Hoffmann et al. (1965). Real GDP derived by deflating Nominal GDP. The deflator comes from IMF (2010), 1960-2000; Spoerer and Ritschl (1997), 1901-1960; Hoffmann et al. (1965), 1870-1901.
Greece, 1870-1938, Kostelenos et al. (2007) moving base series.
Hungary, 1870-1913, Maddison (2009) level for 1913 projected backwards to 1870 with Schulze (2000) estimates for Imperial Hungary, under the assumption that movements in real output per head in Modern Hungary reflected those in Imperial Hungary; 1913-1938, Eckstein (1955: 175) for Modern (Republic of) Hungary, as defined by the Treaty of Trianon (1919).
Netherlands, 1870-1913, Smits et al. (2000), average of income, output and expenditure estimates; 1921-1938, Bakker et al. (1990).
Norway, 1870-2000, Grytten (2004).
Portugal, 1850-1910, Lains (2006); 1910-1950, Batista et al. (1997).
Russia, 1870-1885, Imperial Russia, Goldsmith (1961), agricultural and industrial output weighted with Gregory (1982) weights for 1883-87; 1885-1913, Gregory (1982), Table 3.1; 1913-1928, Markevich and Harrison (2011).
Spain, 1870-2015, Prados de la Escosura (2017).
Sweden, 1870-2000, Krantz and Schön (2007).
United Kingdom, 1850-1985, Mitchell (1988).
All figures are adjusted to refer to mid-year and to take into account the territorial changes and are derived from UNESCO, http://data.uis.unesco.org/, for 1970-2015, Maddison (2010), and Mitchell (2003a, 2003b, 2003c), completed for Latin America and the Caribbean with CEPAL (2009 and 2016), 1950-2015, and OxLAD database (Astorga et al., 2003), 1900-1938. Otherwise, national sources were used.
Cyprus, 1929-1938, Apostolides (2011).
Spain, 1870-2015, Prados de la Escosura (2017).
Turkey, 1870-1913, Pamuk (2006, 2007).
Algeria and Tunisia, 1870-1950, Fargues (1986).
South Africa, 1870-2000, Feinstein (2005).
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