Edexcel IAL Economics: Measuring development and constraints on growth (YEC11)

This guide covers specification section 4.3.6, items 1(a) to 1(c) and the first five bullets of item 2(a), of the Pearson Edexcel International Advanced Subsidiary/Advanced Level in Economics specification (YEC11), Issue 2, June 2018. In the specification, Units 1 and 2 make up the International AS and Units 3 and 4 add the International A2 content. This topic sits in Unit 4 (Developments in the global economy), which only the full International A Level candidates take.

Every country and figure below is invented. Demographic, debt, credit, infrastructure, skills and non-economic constraints, and the strategies for development, sit on other pages. Use the revision notes and the practice questions with this guide. The course hub, the printable checklist and the free diagnostics show where you stand. For GDP, GNI and PPP, see the economic growth guide.

What the specification asks for

Item	What you must be able to do
1(a)	Name the three HDI components and say how each is measured
1(b)	Judge the HDI for comparing countries and years
1(c)	Use six other indicators of development
2(a)	Explain commodity price volatility, primary product dependency (Prebisch-Singer), the savings gap (Harrod-Domar), the foreign currency gap and capital flight

1(a) The Human Development Index

Growth is a rise in real output. Development is wider: people live longer, learn more and can afford more. The HDI combines three components into one number between 0 and 1.

Component	Usual measure
Health	Life expectancy at birth
Education	Mean years of schooling of adults, and expected years of schooling for children
Income	Gross national income per head, adjusted for purchasing power

Each component is turned into an index using a minimum and a maximum: index = (actual - minimum) / (maximum - minimum). Income is entered as a natural logarithm, so each extra unit of income counts for less as income rises. The education index averages the two schooling indices. The HDI is the geometric mean of the three indices. The limits below are illustrative and not necessarily those in use today. Life expectancy runs from 20 to 85 years. Expected schooling runs from 0 to 18 years and mean schooling from 0 to 15. Income runs from 100 to 75,000 cu (currency units, PPP).

Worked example 1. In Alder, life expectancy is 74.0 years, expected schooling 13.2, mean schooling 8.4 and income 12,000 cu.

Health    = (74 - 20)/65                   = 0.8308
Education = (13.2/18 + 8.4/15)/2
          = (0.7333 + 0.5600)/2            = 0.6467
Income    = ln(12,000/100) / ln(75,000/100)
          = 4.7875 / 6.6201                = 0.7232
HDI       = (0.8308 x 0.6467 x 0.7232)^(1/3) = 0.7297 -> 0.730

The arithmetic mean would be 0.7335. The geometric mean is lower because it penalises an uneven profile.

Worked example 2 (over time). Ten years later Alder has life expectancy 77.0, expected schooling 14.4, mean schooling 9.6 and income 15,000 cu. Health is 0.8769, education 0.7200 and income 0.7569, so the HDI is 0.7818 (0.782). It rose by 0.052. If only income had risen to 15,000, the HDI would be 0.7409, a rise of just 0.011, so most of the gain came from health and education.

1(b) Advantages and limitations of the HDI

Advantages

• It looks beyond income, so a country cannot score well on money alone.
• It is one number, so ranking and tracking over time are simple.
• The logarithm reflects diminishing returns to income: a rise from 2,000 to 3,000 cu lifts the income index by 0.061, but 40,000 to 41,000 cu lifts it by only 0.004.
• The geometric mean means a very low score on one component cannot be fully offset by a high score on another.

Limitations

• It is an average. Alder’s HDI says nothing about how income, schooling or health are shared.
• It leaves out the environment, political freedom, security, gender gaps and unpaid work.
• Equal weights are a judgement. Many would weight health more than schooling.
• Two different profiles can give similar scores. Beta (life expectancy 80, expected schooling 6, mean schooling 3, income 60,000) scores 0.620. Corra (66, 16, 11, 3,000) scores 0.666. Beta is richer but ranks lower.
• Data are estimates, and limits can change, so compare like with like.

Evaluation. The HDI beats real GDP per head for a broad view of living standards, but it is not a full measure of wellbeing. A strong answer states what the HDI adds, what it omits, and then judges which matters more for the comparison in the question.

1(c) Other measures of development

Indicator	What it shows	Caution
Share of adult male labour in agriculture	Structure of the economy. A high share suggests low-productivity work	Ignores women’s work, and large mechanised farming can give high output with few workers
Access to clean water	Public health and infrastructure	Access is not the same as quality or reliability
Energy consumption per capita	Industrial activity and living standards	Rich countries may use energy wastefully, and fuel type matters
Internet access per thousand	Information, skills and market access	Speed and cost vary, and access is not use
Mobile phones per thousand	Communication and mobile banking	Can exceed 1,000 because people hold several subscriptions
Doctors per thousand	Health capacity	Rural and urban distribution, and nurses and clinics, are missed

Worked example 3. Country P and Country Q (invented):

Indicator	P	Q
Adult male labour in agriculture	58%	9%
Clean water access	61%	99%
Energy per head (kg oil equivalent)	450	3,900
Internet users per thousand	85	880
Doctors per thousand	0.2	3.4

Q has 38 percentage points more clean water access, 8.7 times the energy per head, 10.4 times the internet access and 17 times the doctors per thousand. Share and number differ: if P’s adult male labour force grows from 4.0 million to 4.6 million while the agricultural share falls from 58% to 44%, farm workers fall from 2.32 million to 2.02 million, a drop of 12.8%, not 14%. The share fell by 14 percentage points. Say which you mean.

2(a) Economic constraints on growth and development

Commodity price volatility

Primary commodity demand and supply are price inelastic in the short run. Supply cannot respond quickly, because crops take a season to grow, and buyers cannot easily switch. Small shifts in supply cause large price swings.

Worked example 4 (Ravia). A crop price index over six years is 100, 128, 91, 74, 112 and 96. Year-on-year changes are +28.0%, -28.9%, -18.7%, +51.4% and -14.3%. Suppose demand has an elasticity of -0.5, a poor harvest cuts supply by 10% and a good one raises it by 10%. Price moves by roughly 10 / 0.5 = 20%, so price index 1.2 times quantity 0.9 gives revenue of 1.08, up 8%, while 0.8 times 1.1 gives 0.88, down 12%. Farmers gain from shortages and lose from bumper years, so planning is hard.

For Ravia as a whole, crop exports are 4.5 bn cu of GDP 20 bn cu. A 19% price fall with unchanged volume cuts export earnings by 0.855 bn cu, or 4.3% of GDP. Effects include lower farm incomes, falling tax revenue, a weaker balance of payments and risky investment. Diversification reduces exposure.

Primary product dependency and the Prebisch-Singer hypothesis

The hypothesis claims that, over the long run, the prices of primary exports fall relative to the prices of manufactured imports, so developing countries that depend on primary products see their terms of trade worsen. The terms of trade index is 100 times the export price index divided by the import price index.

Worked example 5. Over 20 years Ravia’s export price index rises from 100 to 112 and its import price index from 100 to 160. Terms of trade = 112 / 160 x 100 = 70, a 30% deterioration. A machine that cost 10 tonnes of crop (1,000 / 100) now costs 1,600 / 112 = 14.3 tonnes, 43% more.

Reasons given: low income elasticity of demand for primary products (Engel’s law: as incomes rise, a smaller share of extra income is spent on food). If world income rises 3% a year and income elasticity is 0.4 for primary goods and 1.6 for manufactures, demand grows by 1.2% and 4.8% respectively, and over 20 years demand for manufactures reaches 2.55 times its starting level against 1.27 times for primary goods. Synthetic substitutes add to this.

Evaluation. Evidence is mixed. Some primary products, such as oil or metals, have seen long booms. Manufactures prices can also fall, and the result depends on the start and end dates chosen. Dependency also exposes countries to volatility and gives little scope for productivity growth, so diversification matters either way.

The savings gap (Harrod-Domar)

The model says growth rate g = s / k, where s is the savings ratio and k the capital-output ratio. Higher saving raises investment and growth, while a lower k means capital is used more efficiently.

Worked example 6 (Selvia). GDP is 50 bn cu, s is 8% and k is 3.5. Growth is 8 / 3.5 = 2.3%. To reach 6% growth, s needed = 0.06 x 3.5 = 21%, so investment must be 10.5 bn cu while domestic saving is 4.0 bn cu. The savings gap is 6.5 bn cu, 13 percentage points of GDP. If improved infrastructure lowers k to 2.8, s needed is 16.8% and the gap falls to 8.8 percentage points (4.4 bn cu). At 6% growth with population growth of 2.5%, real GDP per head grows by about 3.4%.

Limitations: k is assumed constant, saving may not become investment if banks are weak, technology and human capital are ignored, and foreign finance may add to debt.

The foreign currency gap

Many capital goods and fuels must be imported, so a country may have enough local savings but lack foreign currency.

Worked example 7. Selvia’s 10.5 bn cu investment needs imported capital goods of 40%, or 4.2 bn cu. Fuel and intermediate imports are 3.0 bn cu and other imports 3.3 bn cu, so imports total 10.5 bn cu. Export earnings are 7.0 bn cu and remittances 1.2 bn cu, total 8.2 bn cu. The foreign currency gap is 10.5 - 8.2 = 2.3 bn cu. A foreign inflow of 6.5 bn cu closes the larger savings gap and more than covers the 2.3 bn cu currency gap, leaving 4.2 bn cu to spare. The larger gap sets the binding constraint.

Capital flight

Capital flight is a large, rapid outflow of money by residents, often from fear of instability, inflation, devaluation, weak property rights or high taxes.

Worked example 8. Suppose Selvia’s residents send 1.8 bn cu abroad, 45% of domestic saving and 3.6% of GDP. Saving left for investment is 2.2 bn cu, so the savings gap widens to 8.3 bn cu. Demand for foreign currency rises, so the foreign currency gap widens to 4.1 bn cu and the currency tends to depreciate. The tax base falls and growth under g = s / k falls to 1.3%. The cause also matters: flight is a symptom of weak confidence, so capital controls treat the outflow but not the reason. Controls can also deter genuine inflows.

Common errors

• Describing the HDI as a measure of income or listing components without saying how they are measured.
• Mixing percentage and percentage-point changes.
• Writing the terms of trade the wrong way up.
• Treating Harrod-Domar as a forecast rather than a model with fixed k.
• Saying capital flight only involves the rich without tracing its effect on investment and the exchange rate.

Official syllabus

Pearson Edexcel International Advanced Subsidiary/Advanced Level in Economics specification (YEC11), Issue 2, June 2018, Pearson Education Limited, Unit 4, section 4.3.6.