Graph and download economic data for Life Expectancy at Birth, Total for Developing Countries in Latin America and Caribbean (SPDYNLE00INLAC) from 1960 to 2023 about Caribbean Economies, Latin America, life expectancy, life, and birth.

Dataset built merging different datasets. The goal of the dataset is to be useful for data analysis.

Columns explanation: - Country: 119 countries names. The list is available here. - Year: from 2000 to 2015 (both included). Longitudinal format. - Continent: names of the different continents (6 continets: Europe, Asia, Africa, North America, South America, Oceania). Data taken from this link. - Least Developed: if the value is TRUE, the country is classified as "Least Developed", if it is FALSE, the country isn't classified as "Least Developed". Data of Least Developed countries taken from this link. - Life Expectancy: data taken from this link. - Population: data taken from this link. - CO2 emissions: data taken from this link. - Health expenditure: data taken from this link. - Electric power consumption: data taken from this link. - Forest area: data taken from this link. - GDP per capita: data taken from this link. - Individuals using the Internet: data taken from this link. - Military expenditure: data taken from this link. - People practicing open defecation: data taken from this link. - People using at least basic drinking water services: data taken from this link. - Obesity among adults: data taken from this link. - Beer consumption per capita: data taken from this link.

Columns explanation: • Country. • Year: from 2000 to 2020 • Continent: names of the different continents (6 continets: Europe, Asia, Africa, North America, South America, Oceania). • Life Expectancy • Population. • CO2 emissions. • Health expenditure. • Electric power consumption. • Forest area. • GDP per capita. • Individuals using the Internet. • Military expenditure. • People practicing open defecation. • People using at least basic drinking water services. • Obesity among adults. • Beer consumption per capita. Source for the data is https://data.worldbank.org/

Context

Life expectancy at birth is defined as the average number of years that a newborn could expect to live if he or she were to pass through life subject to the age-specific mortality rates of a given period. The years are from 1950 to 2018.

Content

For regional- and global-level data pre-1950, data from a study by Riley was used, which draws from over 700 sources to estimate life expectancy at birth from 1800 to 2001.

Riley estimated life expectancy before 1800, which he calls "the pre-health transition period". "Health transitions began in different countries in different periods, as early as the 1770s in Denmark and as late as the 1970s in some countries of sub-Saharan Africa". As such, for the sake of consistency, we have assigned the period before the health transition to the year 1770. "The life expectancy values employed are averages of estimates for the period before the beginning of the transitions for countries within that region. ... This period has presumably the weakest basis, the largest margin of error, and the simplest method of deriving an estimate."

For country-level data pre-1950, Clio Infra's dataset was used, compiled by Zijdeman and Ribeira da Silva (2015).

For country-, regional- and global-level data post-1950, data published by the United Nations Population Division was used, since they are updated every year. This is possible because Riley writes that "for 1950-2001, I have drawn life expectancy estimates chiefly from various sources provided by the United Nations, the World Bank’s World Development Indicators, and the Human Mortality Database".

For the Americas from 1950-2015, the population-weighted average of Northern America and Latin America and the Caribbean was taken, using UN Population Division estimates of population size.

Acknowledgements

Life expectancy:

Data publisher's source: https://www.lifetable.de/RileyBib.pdf Data published by: James C. Riley (2005) – Estimates of Regional and Global Life Expectancy, 1800–2001. Issue Population and Development Review. Population and Development Review. Volume 31, Issue 3, pages 537–543, September 2005., Zijdeman, Richard; Ribeira da Silva, Filipa, 2015, "Life Expectancy at Birth (Total)", http://hdl.handle.net/10622/LKYT53, IISH Dataverse, V1, and UN Population Division (2019) Link: https://datasets.socialhistory.org/dataset.xhtml?persistentId=hdl:10622/LKYT53, http://onlinelibrary.wiley.com/doi/10.1111/j.1728-4457.2005.00083.x/epdf, https://population.un.org/wpp/Download/Standard/Population/ Dataset: https://ourworldindata.org/life-expectancy

GDP per capita:

Data publisher's source: The Maddison Project Database is based on the work of many researchers that have produced estimates of economic growth for individual countries. Data published by: Bolt, Jutta and Jan Luiten van Zanden (2020), “Maddison style estimates of the evolution of the world economy. A new 2020 update”. Link: https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-project-database-2020 Dataset: https://ourworldindata.org/life-expectancy

Inspiration

The life expectancy vs GDP per capita analysis.

In 2025, Luxembourg was the country with the highest gross domestic product per capita in the world. Of the 20 listed countries, 13 are in Europe and five are in Asia, alongside the U.S. and Australia. There are no African or Latin American countries among the top 20. Correlation with high living standards While GDP is a useful indicator for measuring the size or strength of an economy, GDP per capita is much more reflective of living standards. For example, when compared to life expectancy or indices such as the Human Development Index or the World Happiness Report, there is a strong overlap - 14 of the 20 countries on this list are also ranked among the 20 happiest countries in 2024, and all 20 have "very high" HDIs. Misleading metrics? GDP per capita figures, however, can be misleading, and to paint a fuller picture of a country's living standards then one must look at multiple metrics. GDP per capita figures can be skewed by inequalities in wealth distribution, and in countries such as those in the Middle East, a relatively large share of the population lives in poverty while a smaller number live affluent lifestyles.