non-monetary indicators

Economic Development: Non‑Monetary Indicators (Cambridge IGCSE / A‑Level)

1. Why non‑monetary indicators matter

• GDP and GNI measure the *value* of economic activity but give no information about how that activity affects people’s lives.
• Non‑monetary indicators capture the dimensions that the Cambridge syllabus expects students to evaluate when discussing “progress and development”: health, education, gender equality, poverty, basic services and environmental sustainability.
• They allow students to meet the three assessment objectives (AO):
  • AO1 – Knowledge: define each indicator and explain what it measures.
  • AO2 – Application & Analysis: use data to compare countries, calculate rates of change and link the indicator to economic theory (efficiency, equity, externalities, etc.).
  • AO3 – Evaluation: assess the strengths and weaknesses of the indicator and discuss policy implications.

2. Syllabus mapping – where non‑monetary indicators fit

2.1 AS‑Level (Micro‑ and macro‑foundations)

AS Topic	Exact sub‑topic(s)	How a non‑monetary indicator can be used
AS 1.1‑1.6 – Basic economic ideas (scarcity, factors of production, PPC)	PPC & “well‑being” – limits of monetary measures	Show a *social* PPC that adds a health axis (e.g., life expectancy) alongside output.
AS 2.1‑2.5 – Demand & supply, elasticities, welfare	Consumer & producer surplus; income‑elasticity of demand	Use the *elasticity of demand for education* to explain why a 1 % rise in income raises school enrolment more in low‑income countries; treat life‑expectancy gains as a “social surplus”.
AS 3.1‑3.3 – Government intervention & redistribution	Market failure, public goods, equity	Illustrate a negative externality with carbon emissions per capita; evaluate a public‑health programme using the infant mortality rate (IMR).
AS 4.1‑4.6 – National income, AD/AS, growth, unemployment, inflation	Growth vs. development debate; aggregate demand shifts	Compare a country’s GDP growth rate with its HDI trend to discuss “qualitative” growth.
AS 5.1‑5.4 – Fiscal, monetary and supply‑side policy	Fiscal multiplier, government spending on health/education	Show how a 5 % rise in public‑health expenditure (fiscal policy) correlates with a 2 % fall in IMR.
AS 6.1‑6.5 – International trade, exchange rates, balance of payments	Trade‑off between growth and environment; terms of trade	Use carbon emissions per capita to illustrate the environmental cost of export‑led growth.

2.2 A‑Level (Advanced topics)

A‑Level Topic	Exact sub‑topic(s)	Indicator(s) that add analytical depth
7 – Advanced microeconomics (market structures, externalities)	Negative externalities, positive externalities, welfare loss	Carbon emissions per capita (negative); mean years of schooling (positive).
8 – Labour market & income distribution	Labour‑force participation, gender wage gap	Gender Inequality Index (GII) – female labour‑force participation; GDI – gender gap in HDI.
9 – Macroeconomic policy (multiplier, Phillips curve)	Phillips curve – trade‑off between inflation and unemployment	Use infant mortality or life expectancy as a “social cost” indicator to discuss how a policy that reduces unemployment may affect health outcomes.
10 – Government macro‑policy & international issues	Evaluation of development strategies, aid effectiveness	HDI, MPI and GII together provide a multi‑dimensional assessment of a country’s development plan.
11 – Globalisation, sustainability and development	Environmental sustainability, resource depletion, global inequality	Ecological footprint and carbon emissions per capita to discuss the sustainability of trade‑driven growth.

3. Key concepts linked to non‑monetary indicators

• Efficiency vs. equity: Compare GDP per capita (efficiency) with GII (equity). A high GDP with a high GII shows efficient production but unequal outcomes.
• Externalities: Carbon emissions per capita illustrate a negative production externality; mean years of schooling illustrate a positive externality (higher productivity for the whole economy).
• Opportunity cost: Allocating resources to improve life expectancy may reduce short‑run output but increase long‑run labour productivity.
• Marginal analysis: Estimate the marginal benefit of an additional year of schooling on life expectancy using regression data (e.g., 0.4 % increase in life expectancy per extra year).
• Time horizon: Short‑run shocks (e.g., a pandemic) cause a sudden dip in life expectancy, whereas long‑run trends are reflected in HDI growth.

4. Core non‑monetary indicators

4.1 Human Development Index (HDI)

The HDI combines three dimension indices – health, education and income – into a single figure ranging from 0 to 1.

Formula (unit‑free)

\[ \text{HDI}= \frac{1}{3}\Big(I_{\text{health}}+I_{\text{education}}+I_{\text{income}}\Big) \]

• Health index (years) \[ I_{\text{health}}=\frac{\text{Life expectancy at birth (years)}-20}{85-20} \] Assumption: minimum 20 years, maximum 85 years (UNDP bounds).
• Education index – geometric mean of two sub‑indices: \[ I_{\text{education}}=\sqrt{\frac{\text{Mean years of schooling}}{15}\times\frac{\text{Expected years of schooling}}{18}} \] Assumption: 0–15 years for mean schooling, 0–18 years for expected schooling.
• Income index – uses natural logarithms to reflect diminishing marginal utility of income: \[ I_{\text{income}}=\frac{\ln(\text{GNI per capita (USD, PPP)})-\ln(100)}{\ln(75\,000)-\ln(100)} \] Assumption: lower bound USD 100, upper bound USD 75 000 (2011 PPP).

Interpretation: A higher HDI indicates better overall human development, but a single number can mask internal inequalities – a key point for AO3 evaluation.

4.2 Gender Development Index (GDI)

• Compares the HDI of women with that of men.
• Formula: \(\displaystyle \text{GDI}= \frac{\text{HDI}_{\text{women}}}{\text{HDI}_{\text{men}}}\).
• Value < 1 → women are disadvantaged; value = 1 → gender parity.

4.3 Gender Inequality Index (GII)

• Captures gender gaps in three dimensions:
  1. Reproductive health – maternal mortality ratio (MMR) and adolescent birth rate.
  2. Empowerment – proportion of parliamentary seats held by women and proportion of women with at least secondary education.
  3. Labour market – female labour‑force participation rate.
• Values range from 0 (no inequality) to 1 (maximum inequality).

4.4 Health‑related indicators

• Life expectancy at birth (years) – average years a newborn is expected to live.
• Infant mortality rate (IMR) (deaths per 1 000 live births) – deaths of infants under one year.
• Maternal mortality ratio (MMR) (deaths per 100 000 live births) – deaths of women during pregnancy or within 42 days of termination.

4.5 Education‑related indicators

• Literacy rate (% of population aged 15 + who can read and write a simple statement).
• Net enrolment ratio (NER) – percentage of the official school‑age population enrolled at each level (primary, secondary, tertiary).
• Mean years of schooling (years) – average number of years of education received by adults aged 25 +.
• Expected years of schooling (years) – number of years a child of school‑entry age can expect to receive.

4.6 Poverty and living standards

• Poverty headcount ratio (relative) – % of population living below 60 % of median national income.
• Multidimensional Poverty Index (MPI) – combines deprivations in health, education and living standards; expressed as a % of people who are multidimensionally poor.

4.7 Basic services

• Access to clean water – % of population using an improved water source (as defined by WHO/UNICEF).
• Access to improved sanitation – % of population using facilities that hygienically separate waste from human contact.

4.8 Environmental sustainability

• Carbon emissions per capita (tonnes CO₂ per person per year).
• Ecological footprint (global hectares per person) – land and water area required to sustain consumption patterns.

5. Comparative table of selected non‑monetary indicators

Indicator	Dimension(s) measured	Typical data source	Key limitation(s)	Syllabus relevance
Human Development Index (HDI)	Health, Education, Income	UNDP Human Development Report	Aggregates diverse dimensions; masks intra‑national inequality; depends on quality of underlying data.	Growth vs. development (AS 4.3, A‑Level 11.3)
Gender Development Index (GDI)	Gender gaps in HDI components	UNDP Human Development Report	Uses same data as HDI; does not capture unpaid care work or cultural barriers.	Equity & redistribution (AS 3.2, A‑Level 10.2)
Gender Inequality Index (GII)	Reproductive health, empowerment, labour market	UNDP Human Development Report	Complex calculation; limited comparability across very different societies.	Policy evaluation (A‑Level 11.4)
Life expectancy at birth	Overall health conditions	World Bank, WHO	Sensitive to short‑term shocks (e.g., pandemics); does not reflect quality of life.	Externalities & welfare (AS 2.5, A‑Level 9.3)
Infant mortality rate (IMR)	Child health & health‑system effectiveness	UNICEF, WHO	Under‑reporting in low‑capacity systems; revisions can alter trends.	Health‑policy analysis (AS 3.3, A‑Level 10.1)
Literacy rate	Basic education attainment	UNESCO Institute for Statistics	Definition of “literacy” varies; informal learning not captured.	Human capital & productivity (AS 2.3, A‑Level 7.4)
Net enrolment ratio (NER)	Access to education	UNESCO, World Bank	Does not show quality of education or dropout rates.	Education as growth driver (AS 4.4, A‑Level 7.2)
Poverty headcount ratio (relative)	Income distribution & social welfare	World Bank	Arbitrary poverty line; ignores depth and severity of poverty.	Equity & redistribution (AS 3.2, A‑Level 10.2)
Access to clean water & sanitation	Basic services & public health	WHO/UNICEF Joint Monitoring Programme	Ignores water quality, reliability, seasonal variation.	Externalities & government intervention (AS 3.1, A‑Level 9.2)
Carbon emissions per capita	Environmental sustainability	International Energy Agency, World Bank	Does not capture distribution of emissions within a country; excludes other pollutants.	Sustainable development & externalities (A‑Level 9.4, 11.6)
Ecological footprint	Resource use & sustainability	Global Footprint Network	Based on average consumption; ignores trade‑off between domestic and imported footprints.	Globalisation & sustainability (A‑Level 11.6)

6. Using non‑monetary indicators in policy analysis (AO2 & AO3)

1. Set a clear development objective. Example: “Reduce the infant mortality rate (IMR) to below 20 deaths per 1 000 live births by 2030.”
2. Select the most appropriate indicator(s). For the example, use IMR and, as a supporting measure, access to clean water.
3. Collect and organise data. Gather a time‑series (e.g., 2000‑2020) for the target country and at least two comparable peers.
4. Analyse trends.
   • Calculate the average annual percentage change: \(\displaystyle \%Δ = \frac{(V_{t}-V_{t-1})}{V_{t-1}}\times100\).
   • Identify structural breaks – e.g., a sharp decline after the introduction of a national immunisation programme in 2012.
5. Link changes to specific policies. Show, for instance, that a 5 % increase in public‑health spending coincided with a 2 % fall in IMR, using a simple regression or correlation analysis.
6. Evaluate the analysis.
   • Data reliability – coverage, under‑reporting, revisions.
   • Unintended consequences – e.g., rapid urbanisation increasing pressure on health facilities.
   • Indicator sufficiency – IMR alone does not reveal maternal health; suggest adding MMR and water‑access data for a fuller picture.

7. Sample assessment tasks (AO1‑AO3)

AO1 – Knowledge

• Define the Human Development Index and list its three component indices, stating the minimum and maximum values used in each sub‑index.
• Explain the difference between the Gender Development Index (GDI) and the Gender Inequality Index (GII), giving one advantage of each.

AO2 – Application & Analysis

• Using the data below, calculate the HDI for Country X (life expectancy = 72 years, mean years of schooling = 9, expected years of schooling = 14, GNI per capita = US$12 000). Show every step, including the use of the logarithmic income index.
• Analyse the trend in carbon emissions per capita for Country Y from 2000‑2020. Comment on how the trend relates to the country’s export‑led growth strategy.

AO3 – Evaluation

• Assess the strengths and weaknesses of using the HDI as the sole measure of a country’s development. In your answer, discuss data quality, the masking of inequality and the relevance to policy‑making.
• Evaluate the effectiveness of a government’s free‑primary‑school policy by comparing changes in net enrolment ratio, mean years of schooling and literacy rate over a ten‑year period. Consider possible unintended effects.