Lauren Coughlin

November 5, 2003

ECO-043

The Uninsured Population

 

Introduction

In recent years the United States has witnessed a significant increase in the percentage of the population that is without health insurance.  The Census Bureau estimates that in 2002 nearly 44 million Americans were uninsured (15.5 percent of the population).  As this group continues to grow in size, the pressure to reform the system intensifies.  I predict that each of the following will have an effect on the percentage of uninsured for each state: the unemployment rate, per capita income, population, political party of the governor, and percent of nonwhites all for the year 2000.  What is causing millions of Americans to be uninsured, and why are some states doing better at lowering this level?  In this study I find that the unemployment rate, per capita income, and state population all have a significant impact on the uninsured population. 

 

Model

The percentage of the population that is uninsured is directly related to the unemployment rate, per capita income, population, political party of the governor, and percentage of nonwhites.  This translates into the economic model:

 

Percent Uninsured = b 0 + b 1*Unemployment Rate + b2*Population + b3*Minority + b4*Per Capita Income + b5*Democrat + e.

 

There is a strong economic relationship between the percent uninsured (the dependent variable) and two specific independent variables – unemployment rate and per capita income.  [See graphs below]

            

Figure 1                                                          Figure 2

 

The unemployment rate and percent uninsured produce a positive relationship, and per capita income and percent uninsured produce a negative relationship (both as expected).

 

Data

To estimate this suggested relationship, I used data obtained from the “2001 County and City Data Book” and “The 2000 Census.”  My dependent variable is the percent of Americans uninsured in 2000 (UNINS).  This is measured as a percent for each of the 50 states (numbered in alphabetical order 1-50).  Figure 3 below shows the histogram of the rates for all 50 states.

 

The five independent variables included in the regression were state unemployment rate (UNEMPRATE), state population (POPULATION), percent of nonwhites (MINORITY), income per capita (INCOMEPC), and political party affiliation of the governor (DEMOCRAT).

 

Figure 3

 

Results

The estimated regression for the percentage of the population without insurance was best represented in linear form. The final equation is as follows:

 

Percent Uninsured = b 0 + b 1*UNEMPLOYMENT RATE + b2*POPULATION + b4*PER CAPITA INCOME + e.

 

This regression produces the following results:

 

Variable

Coefficient

Std. Error

t-Statistic

Prob. 

UNEMPRATE

2.042990

0.502487

4.065760

0.0002

POPULATION

1.11E-07

7.52E-08

1.475513

0.1472

DEMOCRAT

-1.678600

0.958033

-1.752132

0.0867

C

5.151214

1.986943

2.592532

0.0129

R-squared

0.323356

    Mean dependent var

13.07083

Adjusted R-squared

0.277221

    S.D. dependent var

3.789569

S.E. of regression

3.221755

    Akaike info criterion

5.257385

Sum squared resid

456.7071

    Schwarz criterion

5.413319

Log likelihood

-122.1772

    F-statistic

7.008933

Durbin-Watson stat

2.032506

    Prob(F-statistic)

0.000592

 

On average, states with higher unemployment rates have a greater percentage of uninsured individuals.  A 1 percent increase in the unemployment rate generates a 1.88 percent increase in the state’s uninsured population.  Insurance status is also closely associated with level of income.  A $5,000 increase in per capita income will lower the uninsured rate by –1.52 percent.  States with high per capita incomes have individuals who have more wealth and are thus better able to purchase health insurance.  Connecticut has the highest per capita income at $40,702, and also one of the lowest unemployment rates at 8.2 percent.

 

Conclusion

My final regression supports the hypothesis stated.  The percentage of the population that is uninsured can best be reduced by a decrease in the unemployment rate, and an increase in per capita income.  States should therefore work to lower the unemployment rate, which will in turn raise per capita income, and have an even stronger effect on the level of insurance held by individuals.  To my surprise, DEMOCRAT was found to be insignificant.  Because democrats are known for being more liberal, I would have predicted that a state with a democratic governor would be more likely to establish programs to provide insurance for the uninsured.