🗓️ Session 2: Measuring Development
Abstract
While the first session focused on the theory of development, this session focuses on its practice—or, more precisely, its measurement. We will discuss how the theoretical construct of “development” can be operationalized and measured. This includes a debate about the theory-ladenness of observations, i.e., the fact that every observation and every measurement is dependent on certain theories and theoretical commitments. Therefore, the topics of this session and the first session are inextricably linked: discussing the definition of development and its measurement must always go hand in hand.
🖥️ Lecture Slides
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Open the slides, click the ☰ button in the top right corner, and choose Tools → PDF Export Mode. Then print the page (Cmd/Ctrl + P) and save it as a PDF.
📚 Mandatory Reading
The whole learning track Measuring Development on Method and Inquiry (Gräbner-Radkowitsch 2026d) belongs to this session. Its resources are the reference you will keep coming back to for the coursework, so it is worth reading them in the order given there.
In advance, at minimum:
- The Theory-Ladenness of Observation (Gräbner-Radkowitsch 2026f) — the conceptual argument the lecture builds on
After the lecture at the latest — the individual indicator families:
- Income, Output, and Complexity Indicators (Gräbner-Radkowitsch 2026c)
- Measuring Inequality and Poverty (Gräbner-Radkowitsch 2026e)
- Human Development and Social Indicators (Gräbner-Radkowitsch 2026b)
Reading these before the lecture is useful as well; what you should not do is leave them until the coursework is due.
Only if you want to work in R:
- Accessing Development Data in R (Gräbner-Radkowitsch 2026a) — how to pull the same data straight from the World Bank instead of clicking through the website
🏆 Further readings
- Chapter 2 in Todaro and Smith (2020)
🎯 In-class task: comparing development levels yourself
We spend the second half of the session on this, working in groups of three. It is the same demonstration you saw for twelve countries in the lecture—only this time with your countries, your indicators and your ranking.
- Pick three countries whose comparison you find interesting.
- Collect four indicators for them, from at least two different sources.
- Rank your three countries separately under each indicator.
- Ask yourselves: did the order change? And which of your choices changed it most?
Where to get the data
All the data are free, and three sources cover almost everything:
| Source | What you find there |
|---|---|
| World Bank Open Data | GDP, GNI, Gini, poverty, health, education—the workhorse |
| UNDP Human Development Data Center | HDI, GDI, GII, MPI and their components |
| Our World in Data | Tidied and documented series; every chart also downloadable as a CSV |
No R is required. Searching for the indicator on the World Bank site, selecting your countries and a year, and then reading the values off the chart (or downloading the CSV) is entirely sufficient.
If you do want to use R, the WDI package queries the World Bank directly:
library(WDI)
WDI(country = c("BR", "VN", "ET"),
indicator = c(GDPpc = "NY.GDP.PCAP.PP.CD"),
start = 2020, end = 2023)The indicator codes are given on each indicator’s page on the World Bank site; Accessing Development Data in R (Gräbner-Radkowitsch 2026a) walks through the whole procedure.
⚠️ Three traps that await
- The missing year. Surveys are not run annually, so not every country has a value for every year. State the year you use, or average over a few.
- Not countries. “Sub-Saharan Africa”, “Low income”, “World” and similar aggregates sit in the same column as countries. Drop them—unless you really mean them.
- The same indicator, two definitions. PPP or market exchange rates? Income or consumption? Pre- or post-tax? Two sources can disagree about a number that carries the same name.
Write every one of these decisions down: this is exactly what belongs in the methods section of a paper.
✍️ Coursework (optional)
- Complete the exercise and write one page documenting : your countries, your indicators and their sources, the resulting rankings, and which choice changed the ranking most; also mention the key challenges you have faced.
- If you have questions or problems, please post them in the Moodle forum; I can pick them up later and give you advice on how to address them in the future