What is development? The naïve answer — 'higher GDP per capita' — is wrong in a way that has shaped the last fifty years of economic thinking. Amartya Sen's 1999 Development as Freedom is the canonical re-framing: development is the expansion of substantive human capabilities, not just income. This module is the philosophical foundation of the course; everything that follows builds on what you decide development is FOR.
Growth ≠ development
An economy can grow without developing. Real per-capita GDP can rise while life expectancy falls, while inequality explodes, while political freedom contracts. Equatorial Guinea's per-capita GDP rose by a factor of 17× between 1995 and 2015 on the back of oil discoveries, while child malnutrition, infant mortality, and political freedoms barely moved or worsened. Growth happened; development didn't.
Conversely, development can occur without proportional growth. Kerala (the Indian state) achieved 1980s life-expectancy at first-world levels despite modest per-capita income — through public investment in primary health and female literacy. Sri Lanka, Costa Rica, and Bangladesh have similar stories of development outpacing income.
The Capability Approach (Sen, Nussbaum)
Sen's reframing: development is the expansion of substantive freedoms — the real opportunities people have to be and do what they have reason to value. Capabilities are the real freedoms; functionings are what people actually do with those freedoms (eat well, be educated, work productively, participate in public life). Income is one means to capability, but not the end.
Why the capability framing matters operationally
If development is income, the policy goal is 'grow GDP faster.' If development is capability expansion, the policy goal is 'remove the constraints on what citizens can do' — which can include income but also health, education, security, voice, environmental quality. The capability frame changes which interventions count as developmental. Martha Nussbaum (2011) operationalised the approach by proposing ten central capabilities: life; bodily health; bodily integrity; senses, imagination, thought; emotions; practical reason; affiliation; other species; play; political and material control over one's environment. Each is a dimension a society can fail or succeed at.
The Human Development Index (HDI)
Mahbub ul Haq, with Sen's input, designed the HDI as a compromise: simple enough to be a single number, broader than GDP. Published annually by UNDP since 1990.
HDI construction
HDI is the geometric mean of three sub-indices: • Health — life expectancy at birth (normalised on a 0-1 scale; min 20 years, max 85 years) • Education — average of expected years of schooling and mean years of schooling (each normalised) • Income — log of GNI per capita PPP (normalised) HDI = (Health × Education × Income)^(1/3) The geometric mean (not arithmetic) means a country that does well on two but poorly on the third is penalised more than under an arithmetic mean. You can't compensate poor health with high income. Kenya HDI 2023: 0.601 (Medium Human Development category, ranked 152 of 193) Equatorial Guinea HDI 2023: 0.650 (Medium HD, ranked 145 of 193) Mauritius HDI 2023: 0.802 (High HD, ranked 72 of 193) Norway HDI 2023: 0.966 (Very High HD, ranked 2 of 193)
The Multidimensional Poverty Index (MPI)
Alkire-Foster (2011) framework. Poverty is measured across 10 indicators in 3 dimensions:
- Health (2 indicators) — nutrition; child mortality in the household
- Education (2 indicators) — years of schooling of any adult; school attendance for school-age children
- Living standards (6 indicators) — cooking fuel; sanitation; drinking water; electricity; housing; assets
A household is 'MPI-poor' if it is deprived in at least 33% of the weighted indicators. MPI = headcount × intensity (the average % of indicators in which the poor are deprived). This decomposability — by dimension, region, ethnic group — makes MPI especially useful for targeting policy.
Kenya MPI 2023 (UNDP): 38.7% of population multi-dimensionally poor; intensity 44.6%. The disaggregation shows rural-urban gaps (rural MPI 56% vs urban 12%), county-level gaps (Turkana 80%+ vs Nairobi 4%), and dimensional patterns (the binding constraint varies — cooking fuel and sanitation dominate in most counties; education in some northern counties).
What GDP misses
GDP is a measure of market production, period. It misses:
- Distribution — same GDP, very different welfare implications between an egalitarian and a highly-unequal society
- Environment — natural capital depletion is not deducted. Cutting down a forest adds to GDP (timber sales); the lost ecosystem services are uncounted
- Unpaid work — household production, subsistence agriculture, caregiving. In African economies where 40-60% of the workforce is in subsistence/informal work, this omission is substantial
- Resilience and shock-coping — a country that grows 5% one year and shrinks 8% the next has the same average growth as one that grew 1% and 1%, but the first is much worse for welfare
- Distributional dynamics across generations — GDP says nothing about whether growth depends on resource depletion that will leave future generations worse off
The Stiglitz-Sen-Fitoussi report (2009) and 'Beyond GDP'
Commissioned by French President Sarkozy in 2008, the Stiglitz-Sen-Fitoussi Commission report on the measurement of economic performance and social progress is the most influential recent statement on why GDP is inadequate as a national-progress measure and what to use instead. Twelve recommendations covering household consumption measurement, distribution, sustainability, quality of life. The OECD Better Life Index is a downstream operationalisation. Worth reading in full.
Inequality measures
If distribution matters, so does measuring it. Three common measures:
- Gini coefficient — 0 (perfect equality) to 1 (one person has all income). Kenya Gini 2024 ≈ 0.39 (improved from ~0.50 in the 1990s but still high); South Africa Gini ≈ 0.63 (one of the world's most unequal); Norway Gini ≈ 0.27. Easy to compute but compresses the entire distribution into one number
- Palma ratio — share of income held by the top 10% divided by share held by the bottom 40%. More sensitive to extreme inequality than Gini. Kenya Palma 2024 ≈ 1.7 (the top 10% earn 1.7× what the bottom 40% earn combined)
- Income share of the top 1%, top 0.1% — what Piketty (2014) popularised. Captures the explosion of top incomes that Gini and Palma may smooth over. Africa-wide data is sparse but improving (Chancel-Piketty-Saez-Zucman World Inequality Database)
Exercise
Country A and Country B both have GDP per capita of $4,500, life expectancy of 65, and adult literacy of 80%. But Country A has a Gini coefficient of 0.30 and infant mortality of 18 per 1,000 live births; Country B has a Gini of 0.55 and infant mortality of 45 per 1,000. (1) Compute the HDI for both countries (assume identical for the three HDI dimensions). (2) Despite identical HDI, why is Country A considered more developed? (3) Apply the capability approach: what specific capability difference does the infant-mortality gap reveal? (4) Recommend the indicator set you'd use in addition to HDI to track development in either country.