Health care cost is an increasingly important part of the U.S. economy. In this exercise you are to identify variables that are predictors for drug cost, either individually or in combination. Use the data file Health Care Cost Analysis, which contains annual health care costs for the period 1960-2008. As a first step you are to explore the simple relationships between drug cost and individual variables using a combination of simple correlations and graphical scatter plots. You should also examine the changes in drug cost and other variables over time. Medical care costs are, of course, affected by various national policies and changes in health care providers and health insurance practice. Based on these analyses, develop a multiple regression model that predicts drug costs. You will probably find that the model has errors that are serially correlated and this possibility should be tested for by using the Durbin-Watson test.
If serial correlation exists in your initial model then use the difference variables to estimate a model that predicts the change in drug costs as a function of change in the predictor variables. Again, explore the simple relationship between the change in drug cost and the change in the other predictor variables using correlations and scatter plots. Using these results, develop a multiple regression model using the changes in variables to predict the change in drug cost.
Prepare a report that identifies variables that are related to drug cost individually and in combination.
$$
\begin{array}{ll}
\hline \text { C1 } & \text { Year } \\
\text { C2 } & \text { National Health Expenditures } \\
\text { C3 } & \text { Medicare } \\
\text { C4 } & \text { Hospital Care } \\
\text { C5 } & \text { Physician and Clinical Services } \\
\text { C6 } & \text { Prescription Drugs } \\
\text { C7 } & \text { Admin. \& Net Cost of Priv. Hlth } \\
\text { C8 } & \text { Income Low } 5 \text { th } \\
\text { C9 } & \text { Income Median } \\
\text { C10 } & \text { Income High } 5 \text { th } \\
\text { C11 } & \text { Income High } 5 \% \\
\text { C12 } & \text { Population } \\
\text { C13 } & \text { Unemployment } \\
\text { C14 } & \text { Percent } 65 \text { plus } \\
\text { C15 } & \text { Per age }<5 \\
\text { C16 } & \text { Lag Hosp care } \\
\text { C17 } & \text { Difference Hosp Care } \\
\text { C18 } & \text { Difference Physician } \\
\text { C19 } & \text { Difference Drugs } \\
\text { C20 } & \text { Difference Population } \\
\text { C21 } & \text { Difference } \%>65 \\
\text { C22 } & \text { Difference } \%<5 \\
\text { C23 } & \text { Difference Medicare Cost } \\
C 24 & \text { Difference Income }>5 \% \\
C 25 & \text { Difference Income Median } \\
C 26 & \text { Lag Diff } \% \text { Age }>65 \\
\hline
\end{array}
$$