If GDP is the wrong tool for measuring a good life, what is the right one? Over the past few decades economists have built several answers. None of them is perfect, and the interesting part is not memorising the lists but understanding what each one decided to count, and why.
📘 What you need to know
Alternative measures exist because national income statistics cannot capture well-being on their own.
The OECD Better Life Index rates member countries across 11 areas of life.
The Happiness Index surveys people about 10 areas of their own lives, so the data is what people report themselves.
The Happy Planet Index asks how efficiently a country turns environmental resources into long, happy lives.
GDP produces positive data (measurable facts). Happiness surveys produce normative data (judgements and opinions).
The Easterlin Paradox: income and happiness rise together up to a point, after which the link becomes much weaker.
These measures complement GDP rather than replacing it, and each involves judgements you can criticise.
Why build a different measure at all
Once you accept that GDP measures production rather than living, the next question is obvious: what would you measure instead? Every answer to that has to make a choice about what a good life contains. Health? Free time? Trust in government? Clean air?
Those are not economic questions with objective answers, which is exactly why these indices are contested. But building them forces the choices into the open, and that is valuable in itself.
Three indices, three different starting questions. The Better Life Index measures conditions, the Happiness Index measures feelings, and the Happy Planet Index measures efficiency.
The OECD Better Life Index
The OECD built this index across its member countries. It rates each on 11 areas considered essential to well-being, so a country can be strong in some and weak in others rather than being reduced to one number.
Area
What it looks at
Housing
Living conditions and the share of household spending going on housing
Income
Net household income and net household wealth
Jobs
Job security, average earnings and the unemployment rate
Community
The strength of social support networks
Education
Quality of education, attainment and skills
Environment
Environmental health, especially air pollution and water quality
Civic engagement
Voter turnout and involvement in making laws
Health
Life expectancy and self-reported health
Life satisfaction
Overall satisfaction people report with their lives
Safety
How safe people feel walking alone at night, and the murder rate
Work-life balance
Share of employees working very long hours, and time left for leisure
Look at how many of these are exactly the things GDP misses: safety, community, free time, clean air, civic life. That is not an accident. The index was built by working out what GDP leaves out and then measuring it directly.
The Happiness Index
This one takes a different route. Instead of measuring conditions from the outside, it asks people about their own lives across ten areas: psychological well-being, health, time balance, community, social support, education and culture, environment, governance, material well-being, and work.
The strength is obvious. If you want to know whether people’s lives are going well, asking them is a reasonable place to start, and it captures things no official statistic can.
The weakness is equally obvious. Answers depend on mood, on culture, and on what people are comparing themselves against. This is normative data: it reflects opinion. National income statistics are positive data: they can in principle be verified. Both have a place, and knowing the difference is worth a mark.
The Happy Planet Index
The HPI asks a question the other two do not: at what environmental cost was this well-being achieved?
The idea behind the index
well-being × life expectancy, weighed against ecological footprint
It combines three variables: well-being, life expectancy and ecological footprint. Countries that deliver long, satisfying lives while using few resources score highly. Countries that deliver similar lives while consuming enormously score badly.
Why this produces surprising rankings: some very rich countries fall a long way down the HPI, because their high life expectancy and satisfaction come with an ecological footprint several times the sustainable level. Meanwhile some middle income countries score at the top. That is not an error in the index. It is the whole point of it.
The Easterlin Paradox
This is the finding that ties the topic together. Within any country at a point in time, richer people do tend to report being happier. But once a country passes a certain level of income, further growth in average income seems to do much less for average reported happiness.
The usual explanations are worth knowing:
Basic needs get met. The first increases in income buy food, shelter, safety and healthcare. Later increases buy things that matter less.
People adapt. A pay rise feels wonderful and then becomes normal.
Comparison matters more than level. If everyone’s income rises together, nobody feels richer relative to their neighbours.
Careful with this one in an essay. The paradox does not say growth is pointless. It says the relationship between income and happiness is strong at low incomes and weak at high ones, which is an argument about where growth does the most good, not an argument against growth.
WORKED EXAMPLE
Country X ranks 8th on GDP per capita but 60th on the Happy Planet Index. Explain how both can be true. [4]
Step 1: what each index measures
GDP per capita measures output per person. The HPI measures how efficiently a country converts environmental resources into long, satisfying lives.
Step 2: why the rankings divergeA high income country can have a very large ecological footprint, which the HPI penalises heavily and GDP does not count at all.Step 3: the underlying pointhigh output and sustainable well-being are different achievementsBoth rankings are correct, because they are answering different questionsWhenever two indices disagree, start by asking what each one chose to count.
WORKED EXAMPLE
Evaluate the use of happiness surveys as a measure of a country’s progress. [4]
In favour
They capture health, relationships, security and free time, all of which affect living standards and none of which appear in GDP.
In favourAsking people directly avoids assuming that more output automatically means better lives.Againstthe data is normative, so answers shift with mood, culture and expectationsAgainst
Cross-country comparison is difficult, because the same question can mean different things in different cultures.
Best used alongside national income data, not instead of itTwo clear points each way and a judgement. That is the shape examiners reward.
💡 Exam tip
Know one index properly rather than three vaguely. Being able to name several areas of the Better Life Index and say why they matter beats a list of three titles.
Use the words positive and normative. They are the precise way to describe the difference between GDP data and survey data.
State the Easterlin Paradox carefully. Income and happiness are linked up to a point.
Criticise the alternatives too. They involve arbitrary weightings, they are slow to collect, and they are hard to compare across cultures.
Land on “complement, not replace”. It is almost always the right judgement in these essays.
Connect back to sustainability. The HPI links straight to common pool resources and externalities from Topic 2.
⚠️ Common mix-up
Treating these indices as objective truth. Every one of them involved somebody deciding what to count and how heavily to weight it.
Confusing the Better Life Index with the Happiness Index. One measures conditions from outside, the other asks people directly.
Thinking the HPI simply rewards being poor. It rewards delivering long, satisfying lives at a low environmental cost, which is not the same thing.
Saying the Easterlin Paradox proves growth does not matter. It says the relationship weakens at high income levels.
Listing index components without explaining them. The marks are in the explanation, not the list.
Forgetting to keep GDP in the answer. A question about alternative measures still expects you to compare them with national income data.
Up next: Aggregate Demand and Its Components, which starts the model you will use for the rest of macroeconomics.
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