Measuring development

Development Economics, lecture 2

Prof. Dr. Claudius Gräbner-Radkowitsch

Department of Pluralist Economics, Europa-Universität Flensburg

25 September 2026

Where we are

01

Last week: debated on what development is

  • Modernisation — stages, catch-up possible → measure the level and its change

  • Marxism — accumulation, exploitation → measure surplus distribution

  • Dependency — core and periphery → measure the position

Today: every practical operationalisation takes a side in this debate.

There is no “right indicator”

  • Where theory enters the measurement

  • What each indicator family shows — and hides

  • How to choose the one for your task – and defend it

  • How to get the data yourself

Second half: choose your countries, questions and indicators yourself!

Measurement is a choice

02

“First observe, then interpret” does not work

  • The tidy view on empirics: theory enters only after the data

  • The promise: disagreement is about interpretation

  • The universal remedy: go back to the data

But collecting data already presupposes theory.

All observation is theory-laden

  • Claim original due to Norwood Russell Hanson (1958)

  • To say “Country A is more developed than B” you need a number

  • To get a number you need an indicator

  • To choose an indicator you must already have decided what development is

The data cannot settle which conception is right — you need one before you can produce the data.

This is not the claim that data are bad

Theory-ladenness ≠ relativism

Not claimed

  • That all indicators are equally good

  • That measurement is pointless

  • That numbers can be ignored when inconvenient

Claimed

  • There is no neutral vantage point

  • So the choice is a claim to be argued

Theory enters at four points

1 — Concept

“Development”? “Wellbeing”? “Sustainability”?

2 — Conception

Output? Capabilities? Structural change?

3 — Indicator

Which proxy for which dimension?

4 — Aggregation

How are components rescaled, weighted, combined?

The HDI makes all four choices — and many users hide three

  • Conception: capabilities — but only three dimensions

  • The three: a long and healthy life · knowledge · a decent standard of living — proxied by life expectancy, schooling and GNI per capita

  • Why three? Data exist for nearly every country — unlike freedom or environment

  • Aggregation: geometric mean since 2010 — income cannot buy off dying young

A data constraint became a definition — pragmatism is fine, hiding it is not.

Same twelve countries, four conceptions

  • Does the choice actually change anything? This can be checked!
Conception Indicator
Development as material output GDP per capita (PPP)
Development as a long and healthy life Life expectancy at birth
Development as equity Gini coefficient
Development as ecological sustainability CO₂ emissions per capita

The ranking depends on the conception

Own calculation. World Bank WDI, averages 2015–2023.

Output and sustainability point in opposite directions

Rank correlations: 1 = identical ordering.

Output Health Equity Sustainability
Output 1.00 0.74 0.08 -0.82
Health 0.74 1.00 0.38 -0.63
Equity 0.08 0.38 1.00 -0.05
Sustainability -0.82 -0.63 -0.05 1.00
  • Output ≈ health — but Costa Rica outlives the US on a third of the income

  • Output and equity are essentially unrelated

  • Output vs. sustainability strongly negative — Ethiopia last on income, lowest emissions; Qatar the reverse

Under sustainability, the ranking nearly inverts.

The numbers are theory-laden too

  • India’s World Bank Gini is about 25 — lower than Norway’s

  • India: consumption survey. Norway: income data

  • The rich save \(\rightarrow\) consumption always looks more equal

Same column, same dataset, not comparable.

What is on the shelf

03

Five families, five different questions

Family Answers the question Watch out for
GDP / GNI per capita How much is produced / earned? Not a welfare measure
HDI, GDI, GII How long, healthy, educated? Arbitrary equal weights
Gini, top shares, Palma How is it distributed? Income vs. consumption vs. wealth
Poverty lines, MPI How many are deprived? The line is a value judgement
Economic complexity What can this economy make? Exported goods only

Your research question picks the family — never the other way round.

GDP and GNI come apart exactly where it matters

GDP: where production happens. GNI: who receives the income.

  • Ireland, Luxembourg — profits booked in, then repatriated (Ireland publishes a corrected GNI*)

  • Qatar — income flows out to migrant workers

  • Philippines — remittances flow in; GNI > GDP

Interchangeable for most countries – but not all. Always check!

An average cannot see a distribution

Economy A

10 people × 100 EUR

GDP = 1,000 EUR

Economy B

1 person × 991 EUR, 9 × 1 EUR

GDP = 1,000 EUR

GDP cannot tell them apart — it was never built to.

GDP per capita is a plutocratic average

  • Plutocratic mean: total income / heads — the usual GDP per capita

  • Democratic mean: one person, one vote — tracks the typical household

  • Germany 1991–2021: +0.7 % p.a. plutocratic, +0.25 % democratic, -0.2 % for the bottom quarter

“The economy grew” can be true while most people got poorer.

Schulte, J. (2023)

The data are free, and you can get them today

Three sources cover almost everything.

World Bank

data.worldbank.org — GDP, GNI, Gini, poverty, health, education. The workhorse.

UNDP

hdr.undp.org/data-center — HDI, GDI, GII, MPI and their components.

Our World in Data

ourworldindata.org — tidied, documented, every chart as CSV.

In R

WDI queries the World Bank directly → Gräbner-Radkowitsch (2026a)

Your turn

04

Comparing development levels yourself

  1. Groups of three — pick 3 countries

  2. Collect 4 indicators, from ≥ 2 sources

  3. Rank the countries under each

  4. Did the order change? Which choice changed it most?

Instructions, data sources and the three traps: course website → session 2 — nobody has to copy this down.

How to actually do it

No R needed — but it offers a faster route.

Browser — everyone

  1. Search the indicator on data.worldbank.org

  2. Pick your countries, choose a year

  3. Read off the chart, or download the CSV

  4. Visualise with the tool of your choice

R — optional

library(WDI)
WDI(country = c("BR","VN","ET"),
    indicator = c(
      GDPpc = "NY.GDP.PCAP.PP.CD"),
    start = 2020, end = 2023)

Codes are on each indicator’s World Bank page.

Three traps that await

  • Missing year. Surveys are not annual — state the year, or average

  • Not countries. “Sub-Saharan Africa”, “Low income” — drop them unless you mean them

  • The same indicator, two definitions. PPP or market rates? Income or consumption? Pre- or post-tax?

Write each decision down — that belongs in your methods section.

What we learned

05

What to take away

  • No neutral measurement — concept, conception, indicator, aggregation

  • The choice is a claim — put it in the argument accordingly

  • Conceptions rank differently — output vs. sustainability almost inversely

  • Check robustness — if it flips, that is a finding

Before next week

Next: where the HDI’s three dimensions came from — and what was left out.

References

Gräbner-Radkowitsch, C. (2026a) “Accessing Development Data in R” C. Gräbner-Radkowitsch (ed.), Method and Inquiry, available at https://euf-methodology-hub.netlify.app/resources/accessing-development-data-in-r.
Gräbner-Radkowitsch, C. (2026b) “Human Development and Social Indicators” C. Gräbner-Radkowitsch (ed.), Method and Inquiry, available at https://euf-methodology-hub.netlify.app/resources/human-development-and-social-indicators.
Gräbner-Radkowitsch, C. (2026c) “Income, Output, and Complexity Indicators” C. Gräbner-Radkowitsch (ed.), Method and Inquiry, available at https://euf-methodology-hub.netlify.app/resources/income-output-and-complexity-indicators.
Gräbner-Radkowitsch, C. (2026d) “Measuring Inequality and Poverty” C. Gräbner-Radkowitsch (ed.), Method and Inquiry, available at https://euf-methodology-hub.netlify.app/resources/measuring-inequality-and-poverty.
Hanson, N. R. (1958) Patterns of Discovery: An Inquiry into the Conceptual Foundations of Science, Cambridge: Cambridge University Press.
Schulte, J. (2023) Das Bruttoinlandsprodukt: Ein Spiegelbild der Reichen, available at https://www.ifsoblog.de/das-bruttoinlandsprodukt-ein-spiegelbild-der-reichen (accessed September 2026).
Sen, A. (1990) “Development as Capability Expansion,” in K. Griffin and J. Knight (eds.). Human development and the international development strategy for the 1990s. Basingstoke, Hampshire: Macmillan [u.a.], pp. 41–58.