BW #57: International arms trade

When we think of international trade, certain goods typically come to mind, such as oil, cars, clothing, and electronics. While they're unavailable on our supermarket shelves, weapons and military equipment also constitute many billions of dollars in international trade.

Last year, the Stockholm International Peace Research Institute (SIPRI, https://www.sipri.org) estimated that in 2022, worldwide military spending came out to $2,240 billion. Yes, much of that is spent domestically, and includes such expenses as soldiers' salaries. A hefty part of that budget is spent on international procurement — directly from other governments, or from manufacturers allowed to sell arms to foreign governments. Purchases range from guns and bullets to missiles and missile-defense systems to tanks, airplanes, submarines, and ships.

SIPRI released the latest edition of its arms transfers database earlier this week, with data through the end of 2023. I thought that it would be interesting to find out who is selling, who is buying, and what changes we have seen over the last number of years.

Data and seven questions

As I wrote above, this week's data comes from SIPRI's arms transfer database, at

https://armstransfers.sipri.org/ArmsTransfer/

This site allows you to explore the data inside of your browser. However, we'll download the database into a CSV file, thus allowing us to load and work with it in Pandas. Go to

https://armstransfers.sipri.org/ArmsTransfer/TransferRegister

This is the page that lets us explore and download data for each arms transfer that SIPRI tracks, including the exporter, the recipient, the type of weapon, the year in which it was ordered, and so forth. On that page, ask for information from 2000 through 2023. The sorting doesn't matter, but we do want deliveries broken down by year (so click on that checkbox).

Once you've indicated that, click on the red "Download as CSV" button. This will take a little while to run, but within a minute or so, you'll get a file called "trade-register.csv" downloaded to your computer. That'll be our data set for this week's exercises.

A data dictionary describing the methodology used to compiled the database is at

https://www.sipri.org/databases/armstransfers

The most important thing to understand about this database is that it records arms sales using TIV, "trend-indicator value," a SIPRI-specific amount. You can compare TIV across years, countries, and products, but you can't directly convert it to dollars or any other currency.

This week, I have seven tasks and questions for you. The learning goals this week involve grouping, plotting, pivot tables, and handling non-standard character encodings. I’ll be back tomorrow with my detailed explanation, including my Jupyter notebook.

• Create a data frame from the "trade-register.csv" file, keeping the column headers.
• Which five countries exported the greatest total TIV in 2023? (Use the "TIV delivery values" column.)