Assignment 3

Overview

For this assignment, we are going to be evaluating Michael Ross’s influential book The Oil Curse. According to Michael Ross, oil undermines democracy in a number of ways. We will map some data in order to evaluate different aspects of his argument.

Submission note: Accept the invitation on Blackboard to submit this assignment via GitHub.

Step 1: Create a data frame with country shapes (25 pts)

Use rnaturalearth to extract and store country shapes as simple features in a data frame. Filter out Antarctica and glimpse() the data to make sure everything looks right.

Step 2: Visualize democracy (25 pts)

a. Download one of the democracy (e.g. electoral democracy, liberal democracy, participatory democracy, deliberative democracy or egalitarian democracy) using the vdemlite package. Then add iso3c codes to it with the countrycode package. See module 1.2 to refresh your memory on how to do this. (Note: you don’t have to add region names for this exercise.) glimpse() the data to make sure everything is there.

b. Using iso_a3_eh codes from rnaturalearth and the iso3c codes you just added to the V-Dem data, join the V-Dem data to the country shapes. glimpse() the data to make sure everything look right.

c. Use ggplot() and geom_sf() to map the data. Use theme_map() from ggthemes and give it a viridis or other color scheme. Give the map appropriate labels.

Step 3: Use a map app to explore the relevance of other indicators (25 pts)

The central argument in Michael Ross’s book is that oil rents undermine democracy because oil provides a non-tax source of revenue to governments. If people don’t have to worry about taxes, then they don’t have to be concerned about what their leaders are doing. He calls this the “fiscal theory of democracy.” Let’s use the map app we built in module 3.1 for exploring World Bank data to evaluate this claim.

a. In your assignment folder, create a subfolder called ‘function’ and use it to store your map function helper script like we did in module 3.1.

b. Now add the source() code chunk that will enable you to call the map function in your Quarto document.

c. Use your function to map taxes as a percent of government revenue. You can use taxes on goods and services (GC.TAX.GSRV.RV.ZS) or taxes on income, profits and capital gains (GC.TAX.YPKG.RV.ZS). Then use it to map oil rengs (NY.GDP.PETR.RT.ZS). Do you see evidence of a relationship between taxes and oil rents?

d. Use the wb_search() function to identify at least one other variable that would be relevant for evaluating Ross’s theory. Use your function to map that variable. Then describe the relationship with oil wealth (if any) and how the map is relevant to Ross’s theory.

Step 4: Make a leaflet map of conflict in an oil rich country (25 pts)

In Chapter 5 of the Oil Curse, Michael Ross argues that oil wealth is destabilizing for developing countries due to the fact that rebels and the government fight over oil. Your task for this question is to explore the relationship between conflict and oil in a leaflet map.

a. Select a country case to work with. This should be a oil-rich country that has recently experienced high levels of internal conflict. Examples include Iraq, Syria, Yemen and Nigeria. Use your AI to identify a country and a period of time to analyze. Say a few words about your country case and the time period you will be looking at.
b. Now, following the step laid out in module 3.2, filter a few months of conflict data from the UCDP GED dataset for your selected country and convert the coordinates simple features using the st_as_sf() function from the sf package.

c. Next, produce a leaflet map that displays markers representing conflict events. Have the markers display the name of the location where the conflict event occurred when the user hovers over them. Have the popup windows display the number of deaths and the date of the event when the user clicks on them. Use “OpenTopoMap” as your basemap.

Extra Credit (3 pts)

See if you can find a list of the ten biggest oil fields and in your country and their geographic coordinates. Put those coordinates to a .csv file. You can try using an AI for this, but you may have to do some “jail breaking” because it could be interpreted as sensitive information. Now see if you can read the data into R and use it to plot the location of the oil fields in a fresh map. What did you find in terms of the relationship between oil and conflict?

Submission

After rendering your document, export your project folder and submit it on Blackboard. You will find the link to the Coding Assignment one submission portal under the Assignments link. There is a screen capture video in the Discord server that will help you understand how to do this.