Instructions
Please complete these tasks within one hour of receipt of our email.
Ideal answers should include reproducible script that goes from the data import to the final output, or as many steps as possible so that someone else may recreate your answers. You are encouraged to include comments to your code if submitting work in R or Stata.
We strongly encourage you to use .Rmd or quarto if
you are comfortable with these tools and in any case to include your
answers to all questions in a single document (this can be
.html, .pdf, .doc, .R, .do, .xlsx, etc).
You have been given 2 datasets.
Dataset A (“A_CSES.csv”) is a short version of the Comparative Study of Electoral Systems (CSES) survey wave 2. Each observation in this dataset refers to an individual in a certain year in a specific country.
Dataset B (“B_QoG.xlsx”) is a short version of the Quality of Government (QoG) data. Each observation in this dataset refers to a certain year in a specific country.
Dataset A includes the following variables:
| Variable name | Variable label |
|---|---|
| B1004 | Country-year code |
| B1006_NAM | Country name |
| B1008 | Year |
| B2001 | Age (number of years) |
| B2002 | Gender (1=male; 2=female) |
| B2005 | Union membership (1=is a member; 2=is not a member) |
| B2020 | Income in household (1=low, 5=high) |
| B3014 | It matters who people vote for (1 = it doesn’t matter; 5 = it matters a lot) |
Dataset B includes the following variables:
| Variable name | Variable label |
|---|---|
| cname | Country name |
| year | Year of measurement |
| gle_cgdpc | GDP per capita (in current prices) |
| p_polity2 | Polity score (measure of democracy) |
| undp_hdi | UNDP’s Human Development Index |
Read in both datasets into R using the needed functions for their format. Note that dataset A is a .csv (Comma-Separated Value) file, while dataset B is an .xlsx (Excel) file.
Compare the list of unique countries that are present in datasets A and B. There are 5 countries that are named differently between these 2 datasets. Find these countries and then rename those in dataset B so that they match the names used in dataset A.
Merge dataset B into dataset A using country and
year to match observations. The dataset resulting from the merging
procedure can be called merged_df. Please perform the
merging so that the resulting dataset, has the same number of rows as
dataset A.
From this point onward, please continue your work only with the
merged dataset merged_df. (We also provide this dataset here in case you have not merged properly)
For each country-year pair in the merged dataset, please compute the percentage of respondents who report being members of a union, as well as the GDP per capita recorded in that country-year.
Store this resulting country-year data as a data frame in a new R
object called summary_df.
Display the first rows of summary_df as a table.
The next questions use summary_df. If you did not create
summary_df successfully you can access it here.
Please produce a scatterplot of the relationship between union membership and GDP per capita. Plot union membership on the X-axis, and GDP per capita on the Y-axis.
Run an OLS regression of union membership on year. Display your output.
Please read this text and suggest improvements.
“One really has to say that in the last twelve month’s (See Masters 2022) there have been no
less protests about the conflict then any time before, this has lead some to wonder what affect that might have on future stability (see eg Masterson 2022 and Peters 2021, 2022.)”