Attempting to describe an individual’s welfare is no easy task. A psychologist might discuss a person’s neuroses. A physician could talk about cholesterol and lung function. A sociologist may explore a person’s relationships with friends and family. Human welfare is made up of mental, physical, and social health, but it’s also a person’s ability to provide for his or her needs, contribute to the society at large, and enjoy the freedoms provided by responsible political and economic governance. While psychologists, physicians, and sociologists use different terms and tools to measure human welfare, economists use terms like GDP1 and tools such as the United Nations Human Development Index to determine welfare. Economic measures alone are not perfect determinants of human welfare, but they do provide easily quantifiable metrics for comparing the effects of different circumstances on welfare. Things like immigration/ emigration, infant mortality, average lifespan, AIDS infection prevalence, and adult literacy can be determined, and impacts to a nation’s GDP (the standard of living) explored. Of course, a comprehensive exploration of each country’s circumstances and the impact upon GDP thereof is outside the scope of this essay. Instead, a small sample (three countries each) from the UN Human Development Index in the low-, medium-, and high-development categories will provide case studies from which generalizations can be made about the impacts of illiteracy, HIV/ AIDS rates, life expectancy, infant death, and net migration on GDP.
In high human development counties, positive net migration has a positive impact on GDP. The high (relative) GDP entices further immigration, creating continuous upward momentum in economic growth. As Bade and Parkin note in their economics textbook Foundations of Macroeconomics, “population growth is the only source of growth in the quantity of labor that can be sustained over long periods” (220). The medium development countries, however, face a continuous struggle with negative net migration putting downward pressure on GDP. As their citizens flock to other, more prosperous, countries, less labor is available and GDP suffers. In the low human development countries studied, net migration was also positive, which would normally help boost GDP growth. Unfortunately, any upward trend in GDP in these countries created by positive net migration is offset by other factors.
One of the major factors depressing GDP growth in low development countries is high infant mortality rates. Over nine percent (on average) of children born in the three low development countries studied will not survive to their first birthday. This dampens labor growth, which slows growth in the country’s GDP. The problem of infant mortality is not much better in the medium development countries studied. With rates well above 1%, these countries struggle to increase their populations – and thus the pool of available labor – and a smaller GDP is the result. The high human development countries, conversely, enjoy dramatically lower infant mortality rates. These low rates of infant death help ensure the population continues to expand: greater labor supply pushes GDP upward.
The upward trend in GDP enjoyed by the low infant mortality rate in the high human development countries studied continues into old age. With average lifespans around 80 years, workers in high development countries stay productive longer, further contributing to GDP growth. People in medium development countries enjoy life expectancies between 68 and 77 years; these workers also stay productive for a relatively long period of time. The average life expectancy in the low human development countries (less than 60 years) destroys GDP growth potential. Workers in these countries aren’t likely to see any form of retirement, and will have little incentive to invest in their own human capital.
Workers suffering from HIV/ AIDS are also unlikely to invest in their own future when that future seems so bleak. In the low development countries, average infection rates are well above 1%. Sick workers are unproductive workers. Unproductive workers drive down GDP. Further, the high incidence of AIDS infection seen in the low development countries spills over into higher numbers for infant mortality and a shorter average life expectancy. The medium and high development countries enjoy lower rates of HIV/ AIDS infection and higher GDP figures.
The lower incidence of HIV/ AIDS infection that helps bolster the GDP numbers of the medium and high development countries is in addition to, or perhaps because of, an adult literacy rate that’s dramatically higher than the ones seen in the low development countries studied. While medium development countries have rates around 90% or better, and 99% of the population in the high development countries is literate, 30% – 50% of adults in the low development countries cannot read their native language at a functional level. These low development workers are therefore unable to contribute to the economy in anything but the simplest, lowest-skill jobs. These jobs, of course, are also low-paying. The drag on GDP caused by this lack of human capital development is substantial.
As the previous paragraphs illustrate, low human development countries face significant challenges in growing their economies and promoting human welfare. These challenges are not insurmountable though; policies designed to target the core issues depressing economic activity can improve the lot of citizens in third-world countries. Many issues facing the developing world are important and should be addressed to improve the standard of living in the poorest nations. Two policy initiatives, however, are critical in improving economic conditions and human welfare: HIV mitigation and literacy improvement.
Lowering the incidence of HIV infection is imperative for low development countries as it dampens economic growth by increasing the infant mortality rate and lowering the average life expectancy. In the third world, medicines to extend the life of AIDS patients are not readily available, and infected mothers frequently pass the disease along to their newborn children. High rates of HIV/ AIDS disease also drive down human capital growth, because “as life expectancy shortens so does schooling inducing a lower growth rate of income” (Huang, Fulginiti, and Peterson).
Reducing HIV/ AIDS rates is facilitated by a literate populace: people who can read can be taught more easily than those who cannot. Those same literate workers can also acquire job skills more easily. As noted by Grant Johnston, in his work for the New Zealand Treasury, “people with better literacy skills are more likely to be employed, and to earn more, than people with poorer literacy skills.” Adult literacy also has non-economic benefits, such as increased appreciation of arts and culture, political and religious tolerance, and family stability.
1Throughout this essay, the acronym “GDP” is used to signify “real gross domestic product per capita.”
Country | Net | Infant | Life | HIV/AIDS | Literacy | GDP Composition | GDP | Unemployment | Population | Inflation | ||
Migration | Mortality | Expectancy | Prevalency | Rate | By Sector | Per | Rate | Below | Rate | |||
Rate | Rate | Rate | Agriculture | Industry | Services | Capita | Poverty | |||||
Canada | 5.65 | 4.92 | 81.38 | 0.30% | 99.00% | 2.00% | 20.00% | 78.00% | $39,600.00 | 8.00% | 9.40% | 1.60% |
Ireland | 0.86 | 3.85 | 80.19 | 0.20% | 99.00% | 2.00% | 29.00% | 70.00% | $37,600.00 | 13.70% | 5.50% | -1.60% |
United States | 4.18 | 6.06 | 78.37 | 0.60% | 99.00% | 1.20% | 22.20% | 76.70% | $47,400.00 | 9.70% | 12.00% | 1.40% |
Jamaica | -5.34 | 14.6 | 73.45 | 1.70% | 87.90% | 17.00% | 19.00% | 64.00% | $8,400.00 | 12.90% | 14.80% | 13.00% |
Georgia | -4.06 | 15.17 | 77.12 | 0.10% | 100.00% | 55.60% | 8.90% | 35.50% | $4,800.00 | 16.40% | 31.00% | 5.70% |
Mongolia | 0 | 37.26 | 68.31 | <0.1% | 97.80% | 21.20% | 29.50% | 49.30% | $3,300.00 | 2.80% | 36.10% | 4.20% |
Côte d’Ivoire | 0 | 64.78 | 56.78 | 3.40% | 48.70% | 28.20% | 21.30% | 50.60% | $1,800.00 | 40 – 50% | 42.00% | 1.40% |
Afghanistan | 3.31 | 149.2 | 45.02 | 0.01% | 28.10% | 31.00% | 26.00% | 43.00% | $1,000.00 | 35.00% | 36.00% | 13.30% |
Rwanda | 1.06 | 64.04 | 58.02 | 2.90% | 70.40% | 90.00% | 5.00% | 5.00% | $1,100.00 | N/A | 60.00% | 6.40% |
Works Cited
Bade, Robin, and Michael Parkin. Foundations of Macroeconomics. Boston: Pearson Addison-Wesley, 2010. Print.
Huang, Rui, Lilyan E. Fulginiti, and E. Wesley Peterson. The Impact of Life Expectancy in Human Capital Accumulation: AIDS. Rep. May 2003. Web. <http://ageconsearch.umn.edu/bitstream/22126/1/sp03hu05.pdf>.
Johnston, Grant. “Adult Literacy and Economic Growth.” National Adult Literacy Database. New Zealand Treasury, Dec. 2004. Web. 16 Apr. 2011. <http://www.nald.ca/library/research/aleg/page24.htm>.