National average life expectancies of developing countries remain significantly below the attainable levels of their more developed counterparts. Utilizing data from the current 135 developing countries from 1985-2010, this paper evaluates the effectiveness of various health interventions in terms of promoting human capital formation through improvements in life expectancy. Subsequently, the impact of life expectancy is applied to a production function in order to quantify the impact of its increasing levels on promoting per capita economic growth. While inconsistent in magnitude, the results show a tangible positive effect of increasing life expectancy on promoting economic growth that is consistent within existing literature. Ultimately, the analysis demonstrates the plausible impact of various health interventions on increasing human capital proxied by life expectancy and thereby increasing both the national economic activity and standard of living for citizens of developing countries, advocating for public health interventions by government officials or private aid organizations.
Ending extreme poverty is one of the United Nation’s 8 Millennium Development Goals; a goal hoped to be reached by 2015. In this study I attempt to determine the factors most influential on a country’s poverty level. I observe 10 of the 12 countries in South America over 3 time periods, 1998, 2003, and 2005, making 30 total observations of panel data. Variables that correlated positively in my model with poverty were population growth and the age dependency ratio. Variables that correlated negatively in my model with poverty were health expenditure, trade, government effectiveness and GDP growth rate. The most influential variables I found to be population growth and government effectiveness.
Over the past half century, the world experienced incredible and unprecedented economic growth without a proportional increase in individual life satisfaction and happiness. Despite high GDP and levels of personal and household incomes, the United States falls short of many human development indicators. This paper seeks to address the geographic and economic factors of happiness within the United States using the Centers for Disease Control’s Behavioral Risk Factor Surveillance Survey (BRFSS). Models use two dependent variables, life satisfaction and mental health, as proxies for happiness. Geography is statistically relevant with defined variation across the country. Personal income is important for overall life satisfaction but has little effect on mental health. Most interestingly, states with higher per capita economic growth also have better mental health.
The pattern of stagnating growth and underdevelopment remains an all too common phenomenon for countries with a colonial past, regardless of efforts by developmental economists and international organizations. In order to increase our understanding of what factors lead to this pattern, this study investigates the link between colonization and growth by examining trade characteristics of prior colonies. Using data from the World Bank, the IMF and the OECD, this study utilizes simultaneous equation modeling to determine how trade patterns can provide the link between colonization and the current state of underdevelopment in Africa, the Middle East, and Latin America. This leads to a more refined understanding of why economic development fails to occur even in a period of booming international trade and globalization. Probing into the trade patterns of these nations, this paper answers the following question: Does colonial identity impact trade and growth patterns today? This study finds that history plays a role in determining how countries trade and grow, but the results are varied depending on the analysis utilized. Furthermore, there is a link between the types of goods traded and the growth of a nation, but trade in primary products does not necessarily limit a country’s growth potential.
In the last few centuries, the world has seen unprecedented stratification between economic growth of countries. This study takes a quantitative approach to the role that nationalism and colonial history may play in the economic growth rates of countries. It explains the factors that are linked to nationalism and colonial background and explores the intersection between the two. The effect of these variables on economic growth is measured using cross-sectional data from 74 former European colonies that gained independence after the Second World War, or the year 1945. Using an Ordinary Least Squares (OLS) regression, it was found that region, form of government, and imports have significant effects on economic growth.