Econometrics Term Paper - Life Expectancy

Michael Daubert

Econometrics

Professor Tebaldi

4/29/16

Econometrics Term Paper

Introduction:

        Life expectancy is an extremely significant subject in today’s society and I believe more people need to take the time to understand and examine the topic. As a result, I decided to focus my paper on life expectancy because it is the most important measure of health and helps determine how long a typical person can expect to live. While conducting my research, I discovered the variable improved water sources and I immediately decided to make it my dependent variable. From here I was able to create the research question of, how does improved water sources effect people’s life expectancy. I expanded my research by examining life expectancy in developed countries as well as developing countries.

We are very lucky to live in the United States because their life expectancy is 75-80 years old, which is high considering variables like health care, doctors, and medicine all contribute to this rate. However this is not the case for developing countries because they have very low life expectancy rate, which ranges anywhere between a persons’ high forty’s to their low sixty’s. I was not aware of this before conducting my research and it was truly sickened to read. It became clear to me that variables such as access to health care and doctors also have a huge impact on life expectancy and you can’t assume that all countries are the same. In addition, almost all of these developing countries did not have access to improved water sources, which remained the most significant variable. This subject is so important because I have always taken for granted how easy I can get clean water whenever I wanted. This is not the case for many people in developing countries because they do not have this resource and struggle to find access to a clean water source. In addition, I am going to present this model by running several regressions to see how each variable is correlated with one another.

Economic Theory/Literature Review:

        The first paper I used for my research addressed the question of if increasing environmental stress or pollution levels reduces the health status of a country? This study used data from eighty countries during four different years; 1990, 1995, 2000, and 2005. This study informed me that I should consider analyzing the relationship between environmental variables and health indicators because countries with low prevention levels suffer from higher impacts of pollution emissions. In addition this researched discussed three dependent variables; life expectancy, child mortality rates, and infant mortality rates. However, the study decided to separate the independent variables into two categories; environmental factors and socio-economic factors. The first socio-economic variable is population density and it is measured by midyear population divided by the land area in square kilometers. The second socio-economic variable is urban population density and it is measured by the midyear population of the area defined as a percent of the population that is within the urban area of each country. The first environmental independent variable the study discussed was particulate matter concentration, which are small particles that can enter the respiratory system and cause harmful health effects. In addition, the study continues to examine independent variables that fall are categorized as prevention factors. The first prevention factors is improved water sanitation source and it measures the percentage of the population with access to excreta disposal facilities, which prevents human, animal, and insect contact with excreta. As a result, the regression showed that life expectancy has a positive correlation with both child mortality and infant mortality rates and a negative correlation with particle matter. In addition the author found that improved water sources had a positive correlation with life expectancy, but a negative correlation with both infant mortality and child mortality rates. As a result, this study was very useful and provided my research with key information to further my study.

        The next study I decided to use for my research examined the gap between life expectancy in well-developed countries compared to underdeveloped third world countries. This study explained that these third world countries have a life expectancy of forty-five to fifty-fix years old, which is very low compared to develop countries life expectancy of 70 years old. The study continues to explain that the author used two models to help further his study. The first model included seven explanatory variables; education index, access to essential drugs, number of physicians, population of adults with aids, access to improved source, aids squared, and GDP per capita. The second model included five more explanatory variables; cigarette consumption, urban population, sanitation facilities, public health care expenditure, and Gini coefficient. However, the second model did not provided significant data and the author decided to use the first model. The first model results showed that there was a positive correlation to life expectancy, when increased by ten percent, with every variable besides AIDS. The author expected AIDs to be negatively correlated and with a ten percent increase in AIDs, life expectancy decreases by 1.06 years. However, a population with improved water sources increased life expectancy by 0.51 years, GDP per capita increased it by 0.26 years, the number of physicians increased it by 0.093 years, education increased in by 0.92 years, and essential drugs increased it by 0.22 years. As a conclusion, the author strongly believed focusing on improved water sources is an issue that developing countries should address immediate.

        The final study I used for my research collected data from 194 countries and helps to find the key determinants in the creation of a higher life expectancy nationally. The dependent variable of this study was life expectancy and the author decided to break the independent variables down into five categories. The first section is economic determinants and used it as a dummy variable to determine if a country was developed or not. The country was given a 1 if they were developed and 0 if the country was not developed. The author then uses another variable of Gross National Income per capita and is measured by purchasing power. In addition, the author also uses inflation as a variable it measures the annual percent change in the cost to the average consumer of acquiring a pre-standardized basket of goods.

 The authors’ next section begins discussing independent variables and the cultural as well as social determinants. The author breaks this down into five variables; literacy rate as a ratio of literate population to the illiterate population in each country, mobile phones per 100 people, internet access per 100 people, school enrollment, and telephone lines per 100 people. Health is the next section and the author includes seven independent variables; HIV, tuberculosis, water, undernourishment, smoking, immunization, and health expenditure. Demographic is the next section the author uses and includes five independent variables. This variable are urban population growth, urban population, population growth, mortality rate, and fertility rate. The last section of independent variables the author uses is environment. This section includes five variable, which are CO2 capita, CO2 GDP, electric power consumption, forest, and electricity produced by nuclear power plants.  

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