ECON 306 - Homework 4
A solved homework set for ECON 306 covering economic principles.
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ECON 306 - Homework 4
The following two problems will require a lot of calculations in. It will generate many pages of output.
Here is how your should organize it. The first pages should contain your answers to all the questions,
along with showing any key algebraic equations or explanations you need to use along the way.
After that, include a printout of the output from the regressions you executed in support of your answers.
Highlight any numbers in this output that you used in the first section. (You are encouraged to save paper
here, you may print this section with a small font, double-sided and/or with 2-up format.) Last, include a
copy of the DO file that contains the commands you asked STATA to execute. Be sure you organize
these in a way that will be clear to the reader.
The following two problems will require a lot of calculations in. It will generate many pages of output.
Here is how your should organize it. The first pages should contain your answers to all the questions,
along with showing any key algebraic equations or explanations you need to use along the way.
After that, include a printout of the output from the regressions you executed in support of your answers.
Highlight any numbers in this output that you used in the first section. (You are encouraged to save paper
here, you may print this section with a small font, double-sided and/or with 2-up format.) Last, include a
copy of the DO file that contains the commands you asked STATA to execute. Be sure you organize
these in a way that will be clear to the reader.
1) In this exercise we will examine whether a teacherβs physical attractiveness has any impact
on student course evaluations. The dataset to use is called teaching ratings, and a description
of the variables is available as well. You can access these through the course website. Use
an Ξ±=.05 for hypothesis testing.
Weβll first examine whether our control variables seem to have any predictive power for
ratings.
a.) Weβll start with some basic dummy variable regressions to test for differences between
groups:
1) Regress course_eval on minority. Report the coefficients and p-values. Do minority
instructors have significantly different course evaluations compared to non-
minorities?
ππππππ β ππππ = π. ππ β π. ππππ ππππππππ, π β πππππ = π. πππ
So being minority is not significant in evaluation result at 5% significance level.
(Although it is significant and negative at 10% level)
2) Regress course_eval on female. Report the coefficients and p-values. Do females
have significantly different course evaluations from males?
ππππππ β ππππ = π. ππ β π. πππ ππππππ, π β πππππ = π. πππ
Yes, Being female will decrease the evaluation score by 0.168, it is significant at 1% level.
3) Run a final regression to test whether the effect of being a minority changes
depending on whether the person is female. Report the coefficients and p-values. Can
you reject the hypothesis of no effect?
ππππππ β ππππ = π. ππ β π. ππ ππππππ β π. ππππ ππππππππ,
π β πππππ: ππππππ: π. πππ
After controlling for being minority, being female still has a significant negative
impact on evaluation. Yes, you can reject the hypothesis of no effect.
b.) Now regress course_eval on beauty, age, age^2 [youβll need to create this], nnenglish,
female, minority, onecredit. Are any variables not statistically significant? Which? This
is Model 1.
π΄ππ ππ π: ππππππ β ππππ = π·π + π·π ππππππ + π·ππππ + π·ππππππ + π·ππππππππππ +
π·π ππππππ + π·πππππππππ + π·ππππππππ ππ
age and age^2 are not significant. nnenglish and minority are significant at 5% level but
not at 1% level.
Use Model 1 to answer the following:
1) Calculate an F-test for the hypothesis that age and age^2 jointly have no effect on
course_eval. You can execute this test however you prefer.
π(π, πππ) = π. ππ
The answer is not significant, so we can not reject that age and age^2 have no effect on
course-eval.
on student course evaluations. The dataset to use is called teaching ratings, and a description
of the variables is available as well. You can access these through the course website. Use
an Ξ±=.05 for hypothesis testing.
Weβll first examine whether our control variables seem to have any predictive power for
ratings.
a.) Weβll start with some basic dummy variable regressions to test for differences between
groups:
1) Regress course_eval on minority. Report the coefficients and p-values. Do minority
instructors have significantly different course evaluations compared to non-
minorities?
ππππππ β ππππ = π. ππ β π. ππππ ππππππππ, π β πππππ = π. πππ
So being minority is not significant in evaluation result at 5% significance level.
(Although it is significant and negative at 10% level)
2) Regress course_eval on female. Report the coefficients and p-values. Do females
have significantly different course evaluations from males?
ππππππ β ππππ = π. ππ β π. πππ ππππππ, π β πππππ = π. πππ
Yes, Being female will decrease the evaluation score by 0.168, it is significant at 1% level.
3) Run a final regression to test whether the effect of being a minority changes
depending on whether the person is female. Report the coefficients and p-values. Can
you reject the hypothesis of no effect?
ππππππ β ππππ = π. ππ β π. ππ ππππππ β π. ππππ ππππππππ,
π β πππππ: ππππππ: π. πππ
After controlling for being minority, being female still has a significant negative
impact on evaluation. Yes, you can reject the hypothesis of no effect.
b.) Now regress course_eval on beauty, age, age^2 [youβll need to create this], nnenglish,
female, minority, onecredit. Are any variables not statistically significant? Which? This
is Model 1.
π΄ππ ππ π: ππππππ β ππππ = π·π + π·π ππππππ + π·ππππ + π·ππππππ + π·ππππππππππ +
π·π ππππππ + π·πππππππππ + π·ππππππππ ππ
age and age^2 are not significant. nnenglish and minority are significant at 5% level but
not at 1% level.
Use Model 1 to answer the following:
1) Calculate an F-test for the hypothesis that age and age^2 jointly have no effect on
course_eval. You can execute this test however you prefer.
π(π, πππ) = π. ππ
The answer is not significant, so we can not reject that age and age^2 have no effect on
course-eval.
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Document Details
University
University of Waterloo
Subject
Economics