More than 100 years of improvements in living standards: the case of Colombia


We examine the long-term trends observed in the living standard of the Colombian population over more than 180 years. We construct a Historical Index of Human Development (HIHD) for Colombia for the nineteenth and twentieth centuries and find modest advances in the index during the nineteenth century, life expectancy being the dimension that contributed most to the Colombian Human Development Index in that century. In contrast, all HIHD components exhibited significant advances during the twentieth century. In particular, social dimensions were the main contributors to a growing Human Development Index in Colombia, and life expectancy was the main driver for both men and women. These achievements are mainly explained by the role of public policies aimed at the improvement of education and health. Next, since life expectancy was the dimension that most contributed to human development in the long run, we empirically examine the role of improvements in the provision of public utilities in the significant reduction of mortality. Our hypothesis is that the reduction of mortality was largely brought about by improvements in the provision of aqueducts and sewerage. To this end, we construct a new dataset using statistics reported by the Colombian government, which included annual information on the main diseases and causes of mortality during the 1916–2014 period disaggregated by departments. Econometric results show that the decline in mortality rates, especially those related to some waterborne diseases, was significantly related to the expansion of aqueducts and sewerage services in the country.

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Fig. 1

Source: Authors’ calculations. For a detailed explanation on the source of the original data and the methodology to transform it, see “Appendix 1

Fig. 2

Source: Authors’ calculations. For a detailed explanation on the source of the original data and the methodology to transform it, see “Appendix 1

Fig. 3

Source: Authors’ calculations. For a detailed explanation on the construction of the index, see “Appendix 1

Fig. 4

Source: Authors’ calculations. For a detailed explanation on the construction of the index, see “Appendix 1

Fig. 5

Sources: Flórez and Romero (2010), Flórez (2000) and DANE

Fig. 6

Sources: Flórez and Romero (2010), Flórez (2000) and DANE

Fig. 7

Sources: Database constructed by the authors based on Anuarios Generales de Estadística de la Contraloría (1924–1955), Anuarios Generales de Estadística (1950–1967), Estadísticas Vitales Nacimientos y Defunciones (2000–2010)

Fig. 8

Source: Database constructed by the authors based on the Colombian censuses, several years

Fig. 9

Source: Database constructed by the authors based on the Colombian censuses, several years

Fig. 10

Source: Registro de defunciones, Anuarios Generales de Estadística and DANE

Fig. 11

Sources: Authors’ elaboration. Note: Shaded departments represent the ones used for the analysis

Fig. 12

Sources: Database constructed by the authors based on Anuarios Generales de Estadística de la Contraloría (1924–1955), Anuarios Generales de Estadística (1950–1967), Estadísticas Vitales Nacimientos y Defunciones (2000–2010)

Fig. 13

Source: Database constructed by the authors based on the Colombian censuses, several years

Fig. 14

Source: Database constructed by the authors based on the Colombian censuses, several years


  1. 1.

    For estimations of the Historical Index of Human Development for other countries, see, for example, Crafts (1997, 2002) and Prados de la Escosura (2015a, b). For details on Latin-American countries’ HIHD, see Astorga et al. (2005), Prados de la Escosura (2015b) and Bértola and Ocampo (2012).

  2. 2.

    An update of Prados de la Escosura’s historical index for Colombia is in his Historical Index of Human Development database at Prados de la Escosura (2018)

  3. 3.

    We could also have used the average years of education, but this information is not distinguished by gender for all the years analysed. The information by sex is available for the 1950–2014 period by quinquennials (See Barro and Lee 2013); therefore, if we were to use this information, we would miss the analysis by gender for the first half of the twentieth century. Nevertheless, for comparative purposes, in Appendix 2, we present the HIHD for the total population, including as a proxy of education the average years of education for the total population aged 15 years and older, for the 1880–2010 period. We obtained this information from van Leeuwen and van Leeuwen-Li (2015). In general, the trend of the index during the analysed period is quite similar to the one presented in this paper.

  4. 4.

    It is only recently that the United Nations Development Programme (UNDP) began to calculate the Human Development Index (HDI) for several countries by gender, which includes life expectancy, education attainment, and per capita gross national income corresponding to women and men. The 2015 HDI value for women in Colombia is 0.731 and for men it is 0.728, which results in a Gender Development Index (ratio of female to male HDI) of 1.004, indicating that when income differences by gender are included in the calculation of the index, the gap between women and men closes (UNDP 2016).

  5. 5.

    It is important to mention that the comparisons must be interpreted with caution due to the different methodologies used by the authors to construct these indices. For example, Bértola and Ocampo (2012) present three different indices of human development, each one using different transformations on the variables. In addition, these authors include average years of education instead of an index of education based on school attendance and illiteracy, as carried out by Prados de la Escosura (2015a, b). Thus, our estimations are closer to those of Prados de la Escosura.

  6. 6.

    In Sect. 4, we will disaggregate and present the evolution of these diseases by gender.

  7. 7.

    In general, public policies were also important in reducing mortality rates in Latin American countries; see for example, Prados de la Escosura (2015a).

  8. 8.

    One of the main exponents of preventive medicine and hygiene in Colombia was Hector Abad Gómez. He was one of the first to develop projects in preventive health that were successfully taken to the country's rural communities (Zea 2017).

  9. 9.

    See Currie (1950).

  10. 10.

    The mission estimated that in 1950, the number of aqueducts that the country needed was close to 500 and the number of sewerage systems needed was 540 (Currie 1950, Table XII, page 346).

  11. 11.

    The degree of urbanization, which peaked in the 1950s and early 1960s, increased between 1951 and 1964 from 39% to 52% and the urbanization rate from 19.5 per thousand in 1951 to 26.1 per thousand in 1964 (Flórez 2000).

  12. 12.

    See Table 63 (p. 473) from Jiménez (2014).

  13. 13.

    For details on public health policies see, for example, Moya et al (2010).

  14. 14.

    In 1965, the Pro-Wellbeing Association for the Colombian Family (Profamilia) was founded as a private non-profit organization that promotes the respect and exercise of sexual and reproductive rights of the entire Colombian population. Its main programs and campaigns focus on family planning.

  15. 15.

    In Colombia, the fertility rate declined from about 6.4 children for every woman of reproductive age in 1905 to 4.6 children in 1975, to 3.4 in 1985, and to 2.5 by the end of the twentieth century.

  16. 16.

    When we use average years of education as a proxy for the education dimension, we find that social dimensions also are main drivers of long run human development in Colombia (See Appendix 2).

  17. 17.

    Horrell (2000) calculated a comprehensive gendered version of the human development index for the twentieth century in Britain, including indicators for income, leisure, inequality, wealth, health, education, and political rights. Unfortunately, for the Colombian case, we do not have that information disaggregated by gender for the period of analysis.

  18. 18.

    We also examined the role of public utilities on mortality rates, since health is one of the least studied dimension of the HIHD in the literature on Colombia's economic history. For a comprehensive analysis on the evolution of education in Colombia, see, among others, Ramírez and Salazar (2010), and Ramírez and Téllez (2007). For a complete analysis of Colombian historical series on income trends and economic growth, see, for instance, Kalmanovitz (2008), Kalmanovitz and López (2010), and GRECO (2002). For the evolution of demographic indicators, see Flórez (2000) and Flórez and Romero (2010).

  19. 19.

    On average, these departments accounted for 94% of the total population during the 1916–2014 period.

  20. 20.

    The values for the years for which we were not able to find information, were estimated by imputation.

  21. 21.

    For the years between censuses, we estimated the values by interpolation.

  22. 22.

    The data on causes of death by type of disease for each Colombian department are not presented here due to space limitations, but are included in our database.

  23. 23.

    See Appendix 2 for the definition of the disease groups used in this paper.

  24. 24.

    For a complete and detailed study on the epidemiological and demographic transition in Colombia for the 1946–2001 period, see Jiménez (2014). For an analysis on health transitions around the world see Riley (2005).

  25. 25.

    The aqueduct systems started to appear in the urban centres of greater economic dynamisms and population growth, under the modality of concession contracts granted to private entrepreneurs by the municipality. For example, in 1880, the Barranquilla aqueduct (Atlántico) was inaugurated; in 1886 the aqueduct of Bogotá; in 1891, the Medellin aqueduct (Antioquia). At the beginning of the twentieth century, a process of nationalization of public services began, and in 1928, the Congress declared the public utility of the aqueduct and sewerage services, so the state would be in charge of their provision (for details see Comisión de Regulación de Agua Potable y Saneamiento Básico 2001).

  26. 26.

    All rates are per 1000 inhabitants.

  27. 27.

    For a definition of the mortality measures used in this paper, see Appendix 3.

  28. 28.

    Despite the fact that Colombia is known as a violent country, the mortality rate caused by violent deaths is not as high as for other causes of mortality. For example, in 1991, the year with the highest level of violent deaths (79.64 deaths/100,000 inhabitants), the mortality rate from circulatory diseases was (99.71 deaths/100,000 inhabitants).

  29. 29.

    The goalposts for the coverage of aqueducts and sewerage were set at M = 100% and M0 = 0.

  30. 30.

    The education variable was also transformed using the Kakwani (1993) transformation. The relationship between education and health has been extensively examined in the literature; for example, by Lleras-Muney (2005), Cutler and Lleras-Muney (2010) and Cutler, Huang and Lleras-Muney (2015). These authors found that, in general, education is positively associated with health outcomes, but there are important differences across countries. Cutler, Huang and Lleras-Muney (2015) point out that recent studies that estimate the casual effect of education on reducing mortality rates are ambiguous. As the authors point out, some studies have found that, for instance, education, measured as compulsory schooling, reduces mortality in the USA, but not in England or France (see Cutler, Huang and Lleras-Muney (2015) and references therein). On the other hand, other studies such as Beach, Ferrie, Saavedra and Troesken (2016) examine how the declines of mortality rates due to new water purification technologies affected human capital formation.

  31. 31.

    Income is another possible variable that could be included in the regressions. However, we have not included it due to the lack of consistent data for departmental income for such a long period of time, and due to the problems of reverse causality between income and health found in the literature (for a complete discussion on this issue, see Deaton 2006). As in the case of education, the economic literature has found an ambiguous relationship between income and some health measures (infant mortality or the decline in the mortality rate). For example, Acemoglu and Johnson (2007) find that relative growth rates of GDP per capita show some decline in countries experiencing large increases in life expectancy. In contrast, Pritchett and Summers (1996) argue that child deaths in developing countries in 1990 could be attributed to poor economic performance in the 1980s.

  32. 32.

    We found similar results estimating Eq. (2) when the dependent variables (mortality measures) were specified by gender. Regressions by gender are available upon request.


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We thank an anonymous referee and the journal editor (Claude Diebolt) for their valuable comments. We also want to thank Laura Cristancho, Santiago Gómez, Alejandro Herrera, Juliana Gamboa, and Juan Sebastian Burgos for their excellent research assistance. We also thanks Hernando Baquero, dean of the faculty of Medicine of the Universidad del Norte, for his comments.

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Correspondence to María Teresa Ramírez-Giraldo.

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The opinions expressed herein are those of the authors and do not necessarily reflect the views of Banco de la República or its Board of Directors.


Appendix 1: The Historical Index of Human Development (HIHD) and its dimensions: methodology and sources

Following Prados de la Escosura’s (2015a, b) methodology, we calculated 3 yearly historical indices of human development for Colombia: one for the total population (HIHD) and the other two by gender (HIHD*). The first one covered the 1838–2014 period, since we have information available during the entire period under analysis for all its components: income, education, and health. Unfortunately, these data differentiated by gender are not available for the whole period. In the case of income, we do not have data on income by sex, thus we dropped income from the index and calculated a HIHD* in the same way as Crafts (1997) and Prados de la Escosura (2015b). In addition, data on secondary education and literacy rates are not disaggregated by gender for the nineteenth century, and the participation of women in tertiary education only begins at the end of the 1920s. Thus, we calculated the HIDH* by gender, for the 1915–2014 period for which data on all education variables are available differentiated by sex. To calculate the HIHD and the HIHD* by gender, their components are combined into a synthetic measure using a geometric average. All dimensions have equal weights in the index:

$${\text{HIHD}} = {\text{Income}}^{1/3} *{\text{Education}}^{1/3} *{\text{Health}}^{1/3}$$
$${\text{HIHD*}} = {\text{Education}}^{1/2} *{\text{Health}}^{1/2}$$

In particular, each dimension is calculated and transformed as follows:


We used the GDP per capita in Geary–Khamis (G–K) international dollars, at constant prices of 1990. From the Maddison Project Database version 2013, we obtained the information for the years 1820, 1850, and 1859, and for the period 1870–2010. For the missing years, we interpolate the values. A logarithmic transformation of per capita income is necessary because, as Anand and Sen (2000) point out, the function of capabilities is probably concave. In addition, as Prados de la Escosura (2015a, b), we adopted the following linear transformation of per capita income, using log values:

$$I = \left( {x - M_{o} } \right)/\left( {M - M_{o} } \right)$$

where x is the per capita income, M and Mo are the maximum and minimum values, respectively, or goalposts. The index (I) ranges between 0 and 1. We used the same goalposts for per capita income as Prados de la Escosura (2015a): M = $42.916 (G–K 1990 dollars) and Mo = $300 (G–K 1990 dollars).


For education attainment, we follow Prados de la Escosura (2015b) and Crafts (1997) by using an index based on two components: school attendance and literacy rate. In particular, a weight of 2/3 is given to literacy rate and 1/3 to a combined primary, secondary and tertiary enrolment rate.

Like Prados de la Escosura (2015a, b), we transformed each component using the approach proposed by Kakwani (1993). We constructed a normalized index in which an increase in the country’s education indicator at a higher level implies a greater achievement than if it would have happened at a lower level:

$$I = \frac{{\ln \left( {M - M_{o} } \right) - \ln \left( {M - x} \right)}}{{\ln \left( {M - M_{o} } \right)}}$$

where x is a component of the education dimension, M and Mo are the maximum and minimum values, respectively, or goalposts, and ln is the natural logarithm. The index (I) ranges between 0 and 1. The goalposts were set M = 100%, and Mo = 0. We used the same goalposts for men and women.

Data on adult literacy rates for the 1900–2010 period were taken from MOxLAD (2018), The World Bank Group (2018), and Colombian’ Censuses. However, for the nineteenth century there is no complete information on literacy rates, only Loy (1979) provides figures for 1860s. Thus, for the missing years, we interpolated the values. On the other hand, literacy rates by sex are only available for the twentieth century. Information was taken from Colombian’ Censuses, the World Bank Group (2018), and Barro and Lee (2013).

The number of students enrolled in primary education for the total population and by gender was obtained from Ramírez and Salazar (2010) for the 1838–1900 period, Ramírez and Téllez (2007) for the 1905–2000 period, and Ministerio de Educacion Nacional for 2000–2014. The gross enrolment rate for primary education by gender (the relation of students enrolled in primary education to the population aged 7–11) is only available from 1938 (Ramírez and Téllez 2007). Thus, to calculate the historical rates, we had to calculate the population aged between 7 and 11, that was not available for such a long period of time. To do this, we assume that the relationship between the population aged 7–11 and total population was stable over time. Data on the population were obtained from several Colombian censuses.

The number of students enrolled in secondary education for the total population during the nineteenth century was obtained from Informes que el Ministro de Instrucción Pública presenta al Congreso de Colombia en sus Sesiones Ordinarias (Ministerio de Instrucción Pública de Colombia 1904–1930). For the twentieth century, data on the number of students enrolled in secondary education for the total population and by gender were collected based on data recorded by Ministerio de Educacion Nacional (MEN 1930–1943), Anuarios Generales de Estadistica, and DANE (1950–1967). The gross enrolment rate for secondary education by gender (the relation of students enrolled in secondary education to the population aged 12–17) was calculated using information on population by age from Cepal/Celade (2000) for the 1950–2014 period, for the other years, we estimated the population aged between 12 and 17 based on several Colombian censuses.

Lastly, annual data for the number of students enrolled in higher education, at university level, for the total population, and by gender were collected from the Ministerio de Educacion Nacional (MEN 1930–1943), Anuarios Generales de Estadistica of the Departamento de la Contraloria (1905, 1915–1917, 1918–1922) and the Contraloria General de la Nación (1924–1955), and DANE (2000–2010) for the twentieth century. Thus, we calculated the gross enrolment rate of higher education as the ratio between students enrolled in higher education (universities) and the corresponding population aged 17–21. Information on population by age is from Cepal/Celade (2000) for the 1950–2014 period. For the other years, we estimated the population based on several Colombian censuses.


We used life expectancy at birth as a proxy for health. The information was obtained from Flórez (2000), Flórez and Romero (2010), and DANE. We also constructed a normalized index for life expectancy using Eq. (7). For life expectancy, the minimum goalpost (Mo) is set at 25 years for both men and women. Nonetheless, we assume different maximum values (M) of life expectancy goalposts for men and women, because women live longer than men. In this case, M are set at 81 years for men and at 85 years for women.

See Fig. 15.

Fig. 15

Sources: see “Appendix 1

Evolution of the original (no transformed) variables

Appendix 2

See Tables 9, 10, and 11.

Table 9 Average years of education: Colombia 1880–2010.
Table 10 HIHD and its dimensions with average years of education: Colombia 1880–2010.
Table 11 Contribution of the HIHD dimensions to HIHD growth: Colombia 1833–2010.

Appendix 3

See Table 12.

Table 12 Definition of disease groups.

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Jaramillo-Echeverri, J., Meisel-Roca, A. & Ramírez-Giraldo, M.T. More than 100 years of improvements in living standards: the case of Colombia. Cliometrica 13, 323–366 (2019).

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