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1) In a short paragraph describe and explain what the Herfindahl index is. You can use the reference provided in the class exercise or any other citation.

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2) Compare the following information between hospitals located in high, moderate, and low concentration health insurance markets?

a) What are the main significant differences between hospitals in the different insurance markets? (use the ANOVA test)

b) What is the impact of being in a high-concentration health insurance market on hospital revenues and costs?

c) Does being in a high concentration market have a positive impact on net hospital benefits?

d) What about the number of Medicare and Medicaid discharges? Are hospitals in high concentration insurance markets more likely to accept Medicare and Medicaid patients?

e) What is the impact of other variables?

(Note: to answer the last question, please compute Medicare-discharge ratios and Medicaid-discharge ratios first and then run two t-Tests (high concentration vs. moderate concentration, and high vs. low concentration market). Please support your findings with an illustrative graph.

Question #4 (Credits 20)

Regression Models

Analyze the data by running a regression model with “Net Hospital Benefits” as the dependent variable and present your results using the Table 4 template below.

```Table 4 – Regression Model 1
```
 Coefficient ST. ERR T Stats P-values Lower 95% Upper 95% Intercept/Constant Total Hospital beds Teaching Hospital Dummy Count (N) = R Square =

a) Describe and discuss your findings.

b) Do the number of hospital beds or whether a hospital is a teaching hospital or not have a positive or negative impact on hospital net-benefit. (Hospital Performance)? In answering this question, consider statistical significance.

Regression Model 2:

Analyze the data by running a linear regression model and present your results using the Table 5 template below.

```
```
```Table 5 – Regression Model 2
```
 Coefficient ST. ERR T Stat P-values Lower 95% Upper 95% Intercept/Constant Total Hospital beds Non-Teaching Hospital Dummy Count (N) = R Square =

a) Describe and discuss your findings.

b) Do the number of hospital beds or whether a hospital is a non-teaching hospital or not have a positive or negative impact on hospital net-benefits. (hospital performance)? In answering this question, consider statistical significance.

c) Use the results from your Regression model 1 and regression model 2 to comment on any differences or similarities in impact of teaching hospital status or non-teaching hospital status on hospital net-benefits. (hospital performance)?

Regression Model 3:

Analyze the data by running a linear regression model and present your results using the Table 6 template below.

```
```
```Table 6 – Regression Model 3
```
 Coefficient ST. ERR T Stat P-values Lower 95% Upper 95% Intercept/Constant Total Hospital beds Teaching Hosp. Dummy Medicare discharge ratio Medicaid discharge ratio Count (N) = R Square =

a) Describe and discuss your findings.

b) Do the number of Medicare or Medicaid patients in a teaching hospital have a positive or negative impact on hospital net-benefits. (hospital performance)? In answering this question, consider statistical significance.

Regression Model 4:

Analyze the data by running a linear regression model and present your results using the Table 7 template below.

```
```
```Table 7 – Regression Model 4
```
 Coefficient ST. ERR T Stat P-values Lower 95% Upper 95% Intercept/Constant Total Hospital beds Non-Teaching Hosp. Dummy Medicare discharge ratio Medicaid discharge ratio Count (N) = R Square =

a) Describe and discuss your findings.

b) Do the number of Medicare or Medicaid patients in a non-teaching hospital have a positive or negative impact on hospital net-benefit. (hospital performance)? In answering this question, consider statistical significance.

c) Based on your findings please recommend three policies to improve hospital performance. Please make sure to use the final model for your recommendation

Question #5 (Credits 20)

Logistic Regression Models

Analyze the data by running a linear regression model and present your results using the Table 8 template below.

Use “being a member of a hospital network” (system_member) as the dependent variable. and the independent variables presented in Table 8 template below

Table 8 – Logistic Model 1

 Coefficient ST. ERR P-Value Exp (coeff) Exp (z SE) Exp (Std. Coeff.) Intercept/Constant Total Hospital costs Count (N) = R Square =
```
```

a) Describe and discuss your findings.

Logistic Model 2:

Analyze the data by running a linear regression model and present your results using the Table 9 template below.

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