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Model 3 includes the variable Female and an interaction of Female

Question:

Please show work how to find value of dddddd for question 4, and the answer for question 5 (THIS IS STATA OUTPUTS)

Question 4

Suppose we have a dataset on high school students. Amongst the variables in this dataset are measures of cumulative grade point average (“cumgpa”), a dummy variable for gender (female=1 if the student is female, 0 otherwise), and a dummy variable for race (white=1 if the student is white, 0 otherwise).

We execute a few basic regressions for the dependent variable cumgpa and produce the following output in STATA:

.//Model 1 (coefficients only)

. regress cumgpa white if female==0

——————————————————————————

     cumgpa |     Coef.  Std. Err.     t   P>|t|    [95% Conf. Interval]

————-+—————————————————————-

      white |  .1451916  .0595108    2.44  0.015    .0282578   .2621254

      _cons |   2.20037  .0504937   43.58  0.000    2.101154   2.299586

——————————————————————————

. //Model 2 (coefficients only)

. regress cumgpa white if female==1

——————————————————————————

     cumgpa |     Coef.  Std. Err.     t   P>|t|    [95% Conf. Interval]

————-+—————————————————————-

      white |  .4369624  .1205286    3.63  0.000    .1988222   .6751027

      _cons |  2.378077  .1098111   21.66  0.000    2.161112   2.595042

——————————————————————————

. //Model 3 (coefficients only)

. gen fem_white=female*white

. regress cumgpa female white fem_white

——————————————————————————

     cumgpa |     Coef.  Std. Err.     t   P>|t|    [95% Conf. Interval]

————-+—————————————————————-

     female |  bbbbbbbb  .1243030   

      white |  aaaaaaaa  .0588727   

  fem_white |  cccccccc  .1381102  

      _cons |  dddddddd  .0499523  

——————————————————————————

Model 3 includes the variable Female and an interaction of Female and White (Fem_White). Some of the STATA output has been concealed. These values can be deduced from Models 1,2.

What is the value of the term dddddddd?

Question 5

Suppose we have a dataset on high school students. Amongst the variables in this dataset are measures of cumulative grade point average (“cumgpa”), a dummy variable for gender (female=1 if the student is female, 0 otherwise), and a dummy variable for race (white=1 if the student is white, 0 otherwise).

We execute a few basic regressions for the dependent variable cumgpa and produce the following output in STATA:

.//Model 1 (coefficients only)

. regress cumgpa white if female==0 

——————————————————————————

     cumgpa |     Coef.  Std. Err.     t   P>|t|    [95% Conf. Interval]

————-+—————————————————————-

      white |  .1451916  .0595108    2.44  0.015    .0282578   .2621254

      _cons |   2.20037  .0504937   43.58  0.000    2.101154   2.299586

—————————————————————————— 

. //Model 2 (coefficients only)

. regress cumgpa white if female==1

——————————————————————————

     cumgpa |     Coef.  Std. Err.     t   P>|t|    [95% Conf. Interval]

————-+—————————————————————-

      white |  .4369624  .1205286    3.63  0.000    .1988222   .6751027

      _cons |  2.378077  .1098111   21.66  0.000    2.161112   2.595042

—————————————————————————— 

. //Model 3 (coefficients only)

. gen fem_white=female*white

. regress cumgpa female white fem_white

——————————————————————————

     cumgpa |     Coef.  Std. Err.     t   P>|t|    [95% Conf. Interval]

————-+—————————————————————-

     female |  bbbbbbbb  .1243030   

      white |  aaaaaaaa  .0588727   

  fem_white |  cccccccc  .1381102  

      _cons |  dddddddd  .0499523  

——————————————————————————

Model 3 includes the variable Female and an interaction of Female and White (Fem_White). Some of the STATA output has been concealed. These values can be deduced from Models 1,2.

Suppose the result for ccccccc is .30 (it isn’t). Given everything else on the printout is correct, what is the p-value for a hypothesis test that the coefficient on Fem_White=0? (Hint: there are enough observations for you to use the z-distribution in place of the t.)

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