Labour Force Case Study

Labour force participation rate (LFPR)
Working age population (WAP) - Number of people Not in the labour force = Labour force (LF)
LF/(WAP)= LFPR 12,900,000 – 100,000 = 12,800,000

(12800000/12900000)*100 = 99.2%

Labour force participation rate = 99.2%

Unemployment rate (UER)
Labour force – (Full time employees + Part time employees) = Number of unemployed people
Number of unemployed people / Labour force = unemployment rate
X = Number of employed people = Full time employees + Part time employees
X = 4,953,000 + (0.18X)
X = 6,040,243

12,800,000 – 6,040,243 = 6,759,757

6,759,757 / 12,800,000 = 52.8%

Unemployment rate = 52.8%

Question 1B (5 marks)

Year 2005 2006
Population 15,000,000 15,000,000
Working age population 12,900,000 12,900,000 …show more content…
More people leads to more labour which then leads to more people to produce goods. More labour supply also affects wages. Since there is more competition to get a job, companies can drive wages down. An increase in labour also increases potential GDP because ‘full employment’ consists of more people.
Free tertiary education
One can assume free tertiary education causes more people to take higher education. More educated people give a smarter work force, and a smarter workforce results in higher labour productivity, since human capital is increased. Higher labour productivity increases real GDP, since 1 hour of labour now produces more goods.
The graphs suggest the ‘Free tertiary education’ strategy will yield best results, this is because of diminishing marginal returns. As graph 2 shows, you only move along the product function (PF) when you increase the labour force, which has been established as the outcome of the ‘lump sum of money’ strategy. On the other hand the ‘free tertiary education’ strategy will make the PF shift upwards, increasing the GDP without being stopped by diminishing