BW #20: World inflation (solution)

For the first time in decades, people are talking about inflation. This week, we compare different inflation measures across time and various countries.

This week, we’re looking at the World Bank’s database of inflation information, comparing inflation levels in different countries and as measured in different ways. As I wrote yesterday, inflation is something that we have to measure, and there are different perspectives on how and what we measure. Should we include food prices? And if so, which food? Which brands? In which locations? It quickly gets very complicated.

I should add that Planet Money’s “Indicator” podcast followed a government economist who was checking and comparing prices. Have a listen here: https://www.npr.org/2021/12/29/1068853249/how-do-you-measure-inflation-indicator-favorite

From what I understand, the World Bank’s inflation database collects data from various countries, on the assumption that we can trust those countries’ measurements. (Whether we can is another question entirely!) The Excel document contains a number of different inflation measurements, among them:

• Headline consumer price index

• Food price index

• Energy price index

• Official core consumer price index, the main measure of inflation in most countries

• Producer price index

Each of these is measured on a monthly, quarterly, and annual basis. We will look at only a few of these, and only on an annual basis. (There are some other sheets as well in this document, but we’ll ignore those.)

Data and questions

The World Bank recently released their latest report on inflation rates, as described here:

https://www.worldbank.org/en/research/brief/inflation-database

We’ll be working with this database, which is distributed as an Excel file. You can download it from here:

https://thedocs.worldbank.org/en/doc/1ad246272dbbc437c74323719506aa0c-0350012021/original/Inflation-data.xlsx

The Excel file contains a number of sheets. The first is a general introduction to the document, and the second outlines what the rest of the sheets contain. We’ll be loading a number of these into Pandas as part of our analysis.

There were nine questions this week. Here they are, along with my detailed solutions and explanations: