Median Age Is Key to Development Metrics- DRAFT v2

Poverty Rate

Poverty Rate is measured using a relatively ambitious poverty line of $5.00 per day, in purchasing power parity (PPP) terms. This indicator measures the percentage of a country’s population living on less than $5.00 a day, standardized across countries using PPP exchange rates.

The quintiles probability line graph featuring the logistic regression analysis illustrates how a country’s probability of being in the top two quintiles of the lowest poverty rate increases as median age increases. The threshold for having a 50% probability of being in the top two quintiles of the lowest poverty rate is a median age of 33.

This scatterplot illustrates the relationship between median age and poverty rate in the countries included for analysis. The map allows users to visualize the geographic patterns behind country poverty rate values. The findings illustrate a statistically significant linear relationship: As the median age of the population increases, the poverty rate tends to decrease. Almost all countries with a median age less than 20 years have poverty rates above 70%. Examples of countries in this category include Ethiopia and Malawi, with median ages of 18.3 years and 17.7 years, respectively. Conversely, almost all countries with median ages within the demographic window of opportunity (between ages 26 and 40) have poverty rates below 50%. In countries where the median age has surpassed 30 years, the poverty rate tends to fall more consistently at 40% and below. An example is Colombia, with a median age of 30.9 and a poverty rate of 28%. Only when countries reach a median age of 40 years are they likely to attain a poverty rate below 10%. For instance, Belgium and the Czech Republic both have a median age above 40 years and a poverty rate at or below 0.5%.  To illustrate the connection between median age and poverty rate: No country with a median age less than 25 years has a poverty rate less than 20%, while no country with a median age of 30 or greater has a poverty rate greater than 50%.

Source: World Bank, “PovcalNet” World Bank Data.

Child Health

The Child Health metric in this analysis is measured using the child mortality rate from the Center for International Earth Science Information Network’s child health indicators. The child mortality rate is the probability of a child dying between the age 1 and his or her fifth birthday, expressed as deaths per 1,000 live births.

The quintiles probability line graph featuring the logistic regression analysis illustrates how a country’s probability of being in the top two quintiles of child health (low child mortality rate) increases as median age increases. The threshold for having a 50% probability of being in the top two quintiles of child health is a median age of 29.

This scatterplot illustrates the statistical relationship between median age and child mortality in the countries included for analysis. The map allows users to visualize the geographic patterns behind country child health values. The findings demonstrate a statistically significant linear relationship: As the median age of the population increases, child mortality tends to decrease. Almost all countries with a median age of fewer than 20 years have a high infant and neonatal mortality rates. Countries in this category include the Democratic Republic of Congo, Liberia, Mali, and Nigeria, with median ages 16.9, 19.3, 16.3, and 18 years. In all these three countries, child mortality spans between 20 and 46.5 deaths per 1,000 live births. Conversely, almost all countries with median ages within the demographic window of opportunity (between the ages of 26 and 40) have child mortality rates lower than ten deaths per 1,000 live births. In countries where median age surpassed 30 years, child mortality rates fall significantly below ten deaths per 1,000 live births. Only when countries reach 40 years and above that child mortality fall to two deaths or less per 1,000 live births. For instance, Cuba has a median age of more than 40 years and a child mortality rate is 1.3 deaths per 1,000 live births. To illustrate the connection between median age and child health: No country with a median age less than 25 years has a child mortality rate below 10 deaths per 1,000 live births, while no country with a median age of 26 years or greater has a child mortality rate above ten deaths per 1,000 live births.

Source: Center for International Earth Science Information Network (CIESIN), Columbia University, “Natural Resource Protection and Child Health Indicators, 2019 Release (2010-2019),” (Palisades, NY: National Aeronautics and Space Administration (NASA) Socioeconomic Data and Applications Center (SEDAC), 2019).

Education Quality

Education Quality is measured using the Learning-Adjusted Years of Schooling (LAYS) indicator. This indicator includes two parts:

1. Expected years of schooling, which is the average number of years of schooling a child born today can expect to receive by age 18.
2. Harmonized test scores from major international and regional student achievement testing programs, as a marker of the quality of the education system.

This scatterplot illustrates the relationship between median age and LAYS in the countries included for analysis. The map allows users to visualize the geographic patterns behind country education quality values. The findings illustrate a statistically significant linear relationship: As the median age of the population increases, education quality (measured by LAYS) also tends to increase. Almost all countries with a median age less than 20 years have average education quality scores less than six LAYS. Examples of countries in this category include Ethiopia and Malawi, with median ages of 19.5 years and 18 years, respectively. Conversely, almost all countries with median ages within the demographic window of opportunity (between ages 26 and 40) have education quality scores greater than six LAYS. In countries where the median age has surpassed 30 years, education quality scores often reach seven LAYS or above. An example is Brazil, with a median age of 33.5 and nearly eight LAYS. Only when countries reach median age of 40 years are they likely to attain an education quality score above 10 LAYS. For instance, Sweden and South Korea both have a median age above 40 years and an education quality score approaching 12 LAYS. To illustrate the connection between median age and education quality: No country with a median age less than 30 years has an education quality score greater than nine LAYS, while no country with a median age of 30 years or greater has a score less than six LAYS.

Source: World Bank, “Human Capital Index, Learning-Adjusted Years of Schooling Indicator.”

Liberal Democracy Index

Liberal Democracy is measured using the freedom of expression and association indicator. This indicator includes two main components:

1. Electoral democracy component (measured on five indices): Freedom of association, clean elections, freedom of expression and alternative sources of information, elected officials, and suffrage.
2. Liberal democracy (focused on three components): Equality before the law and individual rights, judicial constraints on the executive branch, and legislative constraints on the branch.

The quintiles probability line graph featuring the logistic regression analysis illustrates how a country’s probability of being in the top two quintiles of liberal democracy increases as median age increases. The threshold for having a 50% probability of being in the top two quintiles of liberal democracy is a median age of 28.

This scatterplot illustrates the statistical relationship between median age and liberal democracy in the countries included for analysis. The map allows users to visualize the geographic patterns behind country liberal democracy values. The findings illustrate a statistically significant linear relationship: As the median age of the population increases, liberal democracy (measured by V-Dems) also tends to increase. Almost all the priority countries with a median age of less than 20 years have average liberal democracy scores lower than 0.6. Examples of countries in this category include South Sudan, the Democratic Republic of Congo, Ethiopia, and Nigeria, with median ages of 19.0 years, 17.0 years, 19.5 years, and 18.1 years. In all four countries, liberal democracy falls between 0 and 0.45 as the median age reaches 30; the liberal democracy index is more consistently above 0.4. This is the case with Brazil, with a median age of 33.5 and a liberal democracy index of 0.51. An exception is Turkey, where the median age is 31.5, but the V-Dems score is 0.10. Only when countries reach the median age of 40 or greater are they likely to have a liberal democracy score above 0.6. Examples are Germany and France, each with median ages above 40 and a liberal democracy index above 0.7. To illustrate the connection between median age and liberal democracy: Almost all countries with a median age below 25 years have a V-Dems score below 0.6. No country with a median age of 45 years or greater has a score less than 0.7.

Source: Varieties of Democracy (V-Dem) project, V-Dem Institute of the University of Gothenburg.

Safety and Security

Safety and Security is measured using the Legatum’s safety and security pillar. This pillar measures the degree to which individuals and communities are free from:

• War and civil conflicts.
• Terrorism.
• Politically related terror.
• Violent crimes.
• Property crime.

The pillar gauges whether these forms of violence and crime have destabilized the security of individuals both immediately and through longer-lasting effects.

The quintiles probability line graph featuring the logistic regression analysis illustrates how a country’s probability of being in the top two quintiles of safety and security increases as median age increases. The threshold for having a 50% probability of being in the top two quintiles of safety and security is a median age of 28.

This scatterplot illustrates the relationship between median age and Legatum Prosperity Index score in the countries included in the analysis. The map allows users to visualize the geographic patterns behind country safety and security values. The findings demonstrate a statistically significant linear relationship: As median age increases, so does the safety and security index. Almost all countries with a median age of less than 20 years have average Legatum’s scores lower than 40. Examples of countries in this category include the Democratic Republic of Congo and South Sudan, with median ages of 16.9 years and 18.9 years. In both countries, the Legatum’s scores fall below 40, with both countries scoring 33.3 and 19.2 correspondingly. Conversely, almost all countries with median ages within the demographic window of opportunity (between the ages of 26 and 40) have a safety and security score close to 80 or greater. Only when countries reach a median age of 40 years are they likely to attain safety and security. For instance, countries like Denmark and Switzerland, with median ages of 42.2 and 42.9, respectively, score 92.9 and 94 on the Legatum safety and security index. To illustrate the connection between median age and safety and security: No country with a median age less than 30 years has a Legatum safety and security score above 80.

Source: Legatum Institute, Legatum Prosperity Index.

Government Effectiveness

The Government Effectiveness metric is drawn from nearly 50 indicators across 16 sources. Issue areas range from the quality of bureaucracy, public administration, and fiscal management; to coverage of and satisfaction with education, health, water, telecommunications, power, and transportation systems; to government policy and decision-making coherence, stability, and responsiveness.

The quintiles probability line graph featuring the logistic regression analysis illustrates how a country’s probability of being in the top two quintiles of government effectiveness increases as median age increases. The threshold for having a 50% probability of being in the top two quintiles of government effectiveness is a median age of 31.

This scatterplot illustrates the statistical relationship between median age and government effectiveness in the countries included for analysis. The map allows users to visualize the geographic patterns behind country government effectiveness values. The findings illustrate a statistically significant linear relationship: As the median age of the population increases, government effectiveness also tends to increase. Almost all countries with a median age less than 20 years have government effectiveness scores less than 0, and many have scores less than -1. Examples of countries in this category include Afghanistan and Madagascar, with median ages of 18.4 years and 19.6 years, respectively. Conversely, countries with median ages within the demographic window of opportunity (between the ages of 26 and 40) almost all have a government effectiveness score greater than -1. In countries where the median age has surpassed 35 years, the government effectiveness score often reaches 0 or above. An example is India, with a median age of 28.4 and a government effectiveness score of 0.3. Only when countries reach a median age of 40 years are they likely to attain a government effectiveness score above 1. For instance, Finland and the United Kingdom both have a median age above 40 years and government effectiveness scores above 1. To illustrate the connection between median age and government effectiveness: No country with a median age less than 25 years has a government effectiveness score greater than 0.5, while no country with a median age of 35 years or greater has a score less than -1.

Source: World Bank, Worldwide Governance Indicators.

Economic Gender Gap

The Economic Gender Gap metric discussed in this analysis focuses on one piece of the advancement gap that women face, specifically the ratio of women to men among professional and technical workers.

The quintiles probability line graph featuring the logistic regression analysis illustrates how a country’s probability of being in the top two quintiles of a low economic gender gap increases as median age increases. The threshold for having a 50% probability of being in the top two quintiles of a low economic gender gap in terms of the ratio of women to men among professional and technical workers is a median age of 34.

This scatterplot illustrates the statistical relationship between median age and the economic gender in the countries included for analysis. The map allows users to visualize the geographic patterns behind country economic gender gap values. The findings illustrate a statistically significant linear relationship: As the median age of the population increases, the female-to-male ratio in the professional workforce also tends to increase. Almost all countries with a median age less than 20 years have a female-to-male ratio in the professional workforce less than 0.75, and for many countries, the ratio is less than 0.5. Examples of countries in this category include the Democratic Republic of the Congo and Liberia, with median ages of 17 years and 19.4 years, respectively. Conversely, countries with median ages within the demographic window of opportunity (between the ages of 26 and 40) almost all have a female-to-male ratio in the professional workforce greater than 0.5.  In countries where the median age has surpassed 30 years, the female-to-male ratio in the professional workforce often reaches 1 or above. An example is Panama, with a median age of 29.7 and a female-to-male ratio in the professional workforce of 1.2. Only when countries a median age of 40 years are they likely to attain a female-to-male ratio in the professional workforce above 1.25. For instance, Poland and Canada both have a median age above 40 years and a female-to-male ratio in the professional workforce above 1.25. To illustrate the connection between median age and education quality: Only three countries with a median age less than 25 years have a female-to-male ratio in the professional workforce greater than 1.5, while no country with a median age of 30 years or greater has a ratio less than 0.5.

Source: International Labour Organization, ILOSTAT database as featured in the World Economic Forum’s Global Gender Gap Report.