Instructions
- Homework assignment is here with all questions commented out.
- Complete all of the coding tasks in the
.qmd file
- Upload your individual exercise to your
GitHub repo by Wed 11:59pm.
- Remember to clean your github repo and sort hw submissions by weeks. Each week should have one folder.
# Use the world data set to analyze the determinants of female
# representation (women09)
# 1. Estimate a constant-only model
# 2. Estimate a model that uses per capita GDP (gdp_10_thou) as
# the main independent variable.
# 3. Create a graph that shows the estimated effect of per capita
# GDP on female representation using the effect function.
# 4. Estimate a model that uses a dummy variable that measures
# electoral system (pr_sys) as the main independent variable.
# 5. Create a graph that shows the estimated effect of electoral
# system on female representation using the effect function.
# 6. Estimate a model that includes per capita GDP AND electoral
# system dummy at the same time.
# 7. Comparing the four models you have estimated so far, which
# one fit the data best?
# 8. Create a graph that shows the effect of per capita GDP
# on Y for countries that adopt proportional representation system.
# Hint 1: use the given.values option.
# Hint 2: to refer to the pr_sys variable in the given.values option,
# you need to call it "pr_sysYes", not "pr_sys".
# Hint 3: pr_sysYes is either 1 (Yes) or 0 (No)
# 9. Try creating the same graph by providing "gdp_10_thou:pr_sys" as the term.
# 10. Estimate a regression model of female representation that uses
# region as the main independent variable.
# 11. Create an effect plot that shows the relationship between region and
# female representation.
# 12. Estimate a regression model of female representation on per cpaita
# GDP that controls for region. Based on the results, can we say
# per capita GDP is an important determinant of female representation?
# Why or why not?
# 13. Estimate a regression model of female representation on frac_eth3, a
# three-category ordinal variable that measures levels of ethnic fractionalization.
# In doing so, adopt the dummy variable approach
# (i.e., treat this variable as a nominal variable).
# 14. Based on the results, do you think ethnic fractionalization levels
# have a positive/negative impact on female representation?
# You may answer this either by looking at the regression table you
# created above or by creating an effect plot.
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# Note that statistical significance can be VERY MISLEADING here.
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