IB Economics HLTopic 4 — The Global EconomyPaper 1, 2 & 3Evaluation~10 min read
Comparing the Different Approaches
Every development indicator is wrong in some way. The exam question is never “which one is correct” — it is “which one is useful for this purpose, and what does it miss”. This page is about answering that well.
📚 What you need to know
All development indicators have limitations; none captures everything.
Because development is multidimensional, a range of indicators is always better than one.
Composite indicators give broader insight; single indicators give sharper targeting.
Much development data is qualitative or estimated, so it carries bias and error.
Data takes years to gather, so published figures lag reality.
Statistical reporting is subject to political pressure and should be read with care.
The ladder of measurement
Think of the choice as four levels. Each one costs more effort and tells you more, and knowing which level a question is operating at makes the answer much easier to structure.
Notice that level 2 deliberately has no single verdict. Several indicators tell you more but force you to weigh them yourself, which is exactly what an examiner wants to see you doing.
Single versus composite
✓ WHERE SINGLE INDICATORS WIN
Precision. Infant mortality means one thing and cannot be diluted by an unrelated component.
Targeting. A government can act directly on literacy or vaccination rates.
Speed. Some respond within a year or two of a policy change.
Transparency. Nobody has chosen a weighting on your behalf.
✓ WHERE COMPOSITES WIN
Breadth. They reflect the multidimensional nature of development.
Comparability. One score ranks countries without cherry-picking a measure.
Balance. A country cannot look developed on income alone.
Policy focus. A weak component shows a government exactly where to work.
Notice that the two columns are not opposites. Composites are built out of single indicators, so the sensible position is to use a composite for the headline and single indicators to explain it. Say that in an evaluation and you have your judgement ready-made.
The problems all of them share
The trend is often more informative than the number. A rising figure from a low base usually matters more than a flat figure from a high one.
Problem
Why it happens
What it means for your answer
Time lag
Surveys take years to design, run, check and publish
Say the figure describes the past, and read the trend as well as the level
Qualitative judgement
Wellbeing, governance and empowerment cannot be counted directly
Treat those scores as estimates carrying real uncertainty
Political pressure
Governments have strong incentives to report flattering numbers
Be suspicious of very large jumps over very short periods
The informal economy
Unrecorded work is excluded from official output figures
Income indicators understate low-income economies, sometimes badly
Averages
Every headline indicator divides a total by a population
Ask who is getting the gains before drawing a conclusion
Growth and development are related, not identical
Growth usually helps development: higher output means higher incomes and more tax revenue for schools, clinics and infrastructure. But whether it delivers depends on two things.
🧩 What decides whether growth becomes development
How evenly the income is shared. Growth concentrated in a few hands lifts the average and few lives.
What the growth is built on. Growth from one extractive industry can raise GDP while producing pollution and displacement that lower living standards.
Whether the government converts it. Tax revenue only becomes development if it is spent on health, education and infrastructure rather than lost to corruption.
The reverse also happens. Development can run ahead of growth where a country invests heavily in health and schooling from a low income base, which is why HDI rankings and GDP rankings never line up exactly.
Worked examples
WORKED EXAMPLE 1
Two countries have the same HDI. Country R has a much lower IHDI and a much higher GII. Which is more developed, and how confident can you be? [6]
Step 1: what the equal HDI tells you
On average health, schooling and income are similar in both.
Step 2: what the IHDI adds
R’s lower IHDI means a larger share of its human development is lost to inequality, so the typical person in R is worse off than the average suggests.
Step 3: what the GII adds
A higher GII means greater gender inequality, so the gap in R falls disproportionately on women.
Step 4: confidence
Reasonably high, because two independent measures point the same way. But both rely on data that lags by years and on survey estimates.
The other country is more developed; the conclusion is well supported but not certain
WORKED EXAMPLE 2
A country reports that its GDP per capita rose 6% last year. Explain why this may not mean development improved. [4]
Reason 1: distribution
The rise is an average. If it went to the top fifth, most households saw nothing.
Reason 2: the source of the growth
Growth from a single extractive industry can raise output while generating negative externalities that reduce health and living standards.
Reason 3: what was measured
GDP counts output, not health, schooling, safety or environmental quality.
Reason 4: whether it was converted
Higher tax revenue only becomes development if it is actually spent on merit and public goods.
Growth is a necessary condition, not a sufficient onethis four-reason structure works for almost any “growth is not development” question
💡 Exam tip
Give every indicator a strength and a weakness. One-sided criticism reads as a rehearsed line.
Recommend a range of indicators, then say which one you would lead with and why.
Use the data lag point in data-response questions. It is a genuine, specific limitation.
Comment on the trend in a table of figures, not just the latest value.
When a question compares two countries, pick indicators from different families rather than three income measures.
⚠ Common mix-up
More indicators is not automatically better. Poorly chosen ones just add noise.
Composite indicators are not objective. Someone decided the weightings.
A rising indicator is not proof a policy worked. Correlation is not causation.
Do not say all data is unreliable and stop there. Say which specific weakness matters here.
Growth and development are related. Denying any link is as wrong as treating them as identical.
Up next: Poverty Traps — the diagram that explains why low-income countries stay low-income even when everyone is working hard.
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