Introduction
Health insurance coverage is a sensitive issue in the USA. A case in point is the recently enacted Obamacare in the USA. The law intended to widen coverage of health insurance to all American citizens including the vulnerable groups that are often disadvantaged in market-driven health insurance schemes. The reason that is always given for government provision of health insurance and health services is that the very poor cannot afford to pay market premiums for health insurance since they can barely meet their basic needs. Therefore, there is a need to subsidize health insurances and costs to those groups.
A survey by Gallup in 2010 revealed that persons the highest uninsured rates is among persons earning less than 24,000 dollars per year. Similarly, that group also benefited the least from employer-paid insurance. It is plausible because most of them have a low bargaining power or are employed on a casual basis. The survey further revealed that the proportion of persons who had insurance in the group was predominantly government insurance schemes. Similarly, a study by Bernard, Banthin, & Encinosa (2009) revealed that the unisured are unuinsured by circumstances and not by choice. Most of them cannot afford health insurance. The median income of persons with private insurance was 2.9 times higher than that of persons who were insured. Besides, the median wealth of persons with private insurance was 23.2 times that of persons without insurance cover.
This paper seeks to assess the validity of this claim. It evaluates whether the uninsured rate is influenced by the median income level. It models uninsured rate as a function of the median income level.
Data
Data on insured rate for each of the 52 states was collected from Kaiser Family Foundation. The data reveals the average uninsured rate of the USA is 10 percent in 2014. Data on the median income for the 52 states in 2014 was collected from the US Census website. The data was transformed by computing the log of the median income.
Scatter Plot
The scatter plot shows a negative relationship between the log of median wage and uninsured rate. The uninsured rate seems to decline as the log of median wage increases.
Descriptive Statistics
Descriptive statistics was computed using Ms Excel. The output is as follows:
The mean of the log of median wage is 4.736 with a standard deviation of 0.0733.
The mean of the uninsured rate is 9.72% with a standard deviation of 3.05%.
Regression Equation
The uninsured rate was modelled as a function of the log of median income. Therefore, the uninsured rate is the dependent variable and the log of median wage is independent variable. An OLS regression assumes a linear relationship between the variables. The regression equation was computed using Ms Excel. The excel output is as follows:
The regression equation will be:
Uninsured Rate = 0.962 – 0.1826*Log of Median Wage
Linear Regression Line on Scatter Plot
The trend line shows a negative correlation between the log of median income and uninsured rate. An increase in the log of median income results in a decline in the uninsured rate. It confirms the reason that the government uses to justify its involvement in the health industry. It is also in line with logical intuition. Human beings will first satisfy basic needs such as clothing, shelter and food. Health insurance comes after satisfying those needs because the benefits are not immediate, they are only realized when one fall sick. If a household does not have enough income to even satisfy the basic needs, then it will most likely not undertake a health insurance scheme.
Correlation
The correlation co-efficient is -.043737. The negative correlation shows an inverse relationship between the two variables.
References
Bernard, D., Banthin, J., & Encinosa, W. (2009). Wealth, Income, And The Affordability Of Health Insurance. Health Affairs, 887-896.
Gallup. (2010, February 20). Health Insurance Coverage Varies Widely by Age and Income. Retrieved from http://www.gallup.com: http://www.gallup.com/poll/126143/health-insurance-coverage-varies-widely-age-income.aspx
Kaiser Family Foundation. (2014). Health Insurance Coverage of the Total Population. Retrieved March 23, 2016, from http://kff.org: http://kff.org/other/state-indicator/total-population/
Koch, G. (2008). Basic Allied Health Statistics and Analysis. London: Cengage Learning.
Woodbury, G. (2002). An Introduction to Statistics (illustrated ed.). London: Cengage Learning.
