Exercise #4.  

The variables described below occur in both the WorkWomen.csv and WorkMen.csv data sets, which are based on Chakraborty, Holter, and Stepanchuk (2012). Answer the following questions about the relationship between hours worked and divorce rates:

A. For each of the data sets (WorkWomen.csv and WorkMen.csv), create a scatterplot of hours worked on the Y-Axis and divorce rates on the X-Axis (3 points).

B. For each data set, estimate a fitted OLS regression in which hours worked is regressed (is dependent) on divorce rates. Write the estimated regression equation and include the coefficients in both fitted equations. Discuss all of the coefficients between the two data sets and compared any differences between them (3 points).

C. Calculate the fitted value (Y-hat) and residual for men in Germany (in R, you can look at the row for Germany with WorkMen[6,]). Make sure you show how you arrived at your calculations (3 points).

D. Calculate the fitted value (Y-hat) and residual for women in Spain (in R, you can look at the row for Germany with WorkWomen[14,]). Make sure you show how you arrived at your calculations. (3 points).

Exercise #5.  

Answer the following questions about hours worked and tax rates: 

A. For each data set (WorkWomen.csv and WorkMen.csv), create a scatterplot of hours worked on the Y-axis and tax rates on the X-axis (3 points).

B. For each data set, estimate an OLS regression in which hours worked is regressed (is dependent) on tax rates. Write the estimated regression equation and include the coefficients in both fitted equations. Discuss all of the coefficients between the two data sets and compared any differences between them (3 points).

C. Calculate the fitted value (Y-hat) and residual for men in the United States (in R, you can look at the row for United States with WorkMen[18,]). Make sure you show how you arrived at your calculations (3 points).

D. Calculate the fitted value (Y-hat) and residual for women in Italy (in R, you can look at the row for Germany with WorkWomen[9,]). Make sure you show how you arrived at your calculations (3 points).

Codebook for Exercises 4 and 5 (Table 3.6):

Variables for Divorce Rate and Hours Worked

Variable Name: Description

ID: Unique number for each country

country: Name of the country

hours: Average yearly labor (in hours) for gender specified in data set

divorcerate: Divorce rate per thousand

taxrate: Average effective tax rate