A Level H1 Economics Practice Paper 4

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TuitionGoWhere Practice Paper - Economics H1 A-Level

TuitionGoWhere Exam Practice (AI)
Subject: Economics H1
Level: A-Level
Paper: Practice Paper (Version 4 of 5)
Duration: 75 minutes
Total Marks: 60
Name: ___________________________
Class: ___________________________
Date: ___________________________

Instructions:

• This practice paper is based on the A-Level H1 Economics data-response format.
• Answer all questions using the provided extracts, tables, and diagrams.
• Calculators are permitted.
• Write your answers in the spaces provided.

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Case Study: Small State Economic Adjustment (2020–2024)

Extract 1

The country of Littoria is a small open economy. From 2020 to 2021, global travel restrictions caused tourist arrivals to fall from 6.2 million to 1.1 million. The government responded with a wage subsidy scheme for hospitality firms and accelerated digital adoption grants. By 2023, tourist arrivals recovered to 5.8 million, but the composition shifted: eco-tourism and remote-work visitors rose, while mass-package tourism fell.

Extract 2

In 2022, Littoria imposed a minimum price on low-skilled hourly wages at $9.50, up from the market-clearing$8.20. Employers in food services reported reduced hiring of part-time youth workers. A subsidy for apprenticeship training was introduced at the same time.

Table 1: Littoria Selected Indicators

Year	Real GDP Growth (%)	Unemployment (%)	Govt Education Spending per Student (Primary, $)	Govt Education Spending per Student (University, $)
2020	-4.1	6.8	11,200	21,500
2021	1.3	5.1	11,600	22,100
2022	3.4	3.9	12,100	23,400
2023	4.0	3.2	12,500	24,800
2024	3.7	3.0	12,900	25,600

Table 2: Tourism Revenue by Type ($ million)

Year	Mass Package	Eco / Remote
2020	4200	900
2021	800	600
2022	2100	1500
2023	2600	2900
2024	2400	3400

Image pending generation: graph for Q5.

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Section A: Data Interpretation (Questions 1–5) [10 marks]

1. With reference to Table 1, compare the government education spending per student for primary and university education from 2020 to 2024. [2]

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2. Describe the trend in Littoria's unemployment rate from 2020 to 2024. [2]

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3. Using Table 2, compare the tourism revenue from mass package and eco/remote tourism in 2021 and 2024. [2]

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4. With reference to Extract 1, explain one reason why the composition of tourism changed by 2023. [2]

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5. Using the graph in Fig 1, describe the relationship between real GDP growth and unemployment in Littoria. [2]

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Section B: Microeconomic Analysis (Questions 6–12) [20 marks]

6. With reference to Extract 2, explain the likely effect of the minimum wage increase on youth employment using a demand-supply diagram for the low-skilled labour market. [4]

Image pending generation: diagram for Q6.

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7. Explain the likely price elasticity of supply of apprenticeship training places in the short run. [2]

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8. Using Extract 1, explain how the wage subsidy scheme could have reduced unemployment. [3]

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9. With reference to Table 2, calculate the percentage change in total tourism revenue from 2020 to 2024. Show your working. [3]

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10. Explain one possible market failure that the apprenticeship subsidy in Extract 2 could address. [2]

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11. Using a demand-supply diagram, explain how a subsidy on digital adoption grants (Extract 1) affects the market for digital services. [4]

Image pending generation: diagram for Q11.

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12. Discuss whether the minimum wage policy in Extract 2 achieved equity. [2]

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Section C: Macroeconomic & Evaluative Response (Questions 13–20) [30 marks]

13. Using Table 1, compare real GDP growth and unemployment between 2020 and 2023. [2]

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14. With reference to Extract 1 and Table 1, explain how the fall in tourist arrivals in 2020 could have caused the GDP contraction. [3]

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15. Using an AD/AS diagram, explain how the wage subsidy and digital grants could shift aggregate demand. [4]

Image pending generation: diagram for Q15.

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16. Evaluate whether Littoria's standard of living improved from 2020 to 2024 using Table 1 and Extracts. [8]

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17. Explain the opportunity cost of government spending on university education rising from $21,500 to$25,600 per student. [2]

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18. Using a PPC diagram, explain how the recovery in tourism and digital adoption could affect Littoria's production possibility curve by 2024. [3]

Image pending generation: diagram for Q18.

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19. Discuss one unintended consequence of the minimum wage policy in Extract 2. [3]

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20. Evaluate the effectiveness of Littoria's policy response to the 2020 crisis using evidence from all extracts and tables. [5]

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Answer Key: TuitionGoWhere Practice Paper - Economics H1 A-Level (Version 4)

Section A: Data Interpretation (10 marks)

Q1 [2 marks]

• Both primary and university education spending per student increased from 2020 to 2024. [1]
• University spending was consistently higher and grew from $21,500 to$25,600 (+$4,100) while primary grew from$11,200 to $12,900 (+$1,700); university rose by a larger absolute amount. [1]
• Teaching note: Compare both sectors with values and direction. Common mistake: stating only one sector.

Q2 [2 marks]

• Unemployment fell from 6.8% (2020) to 3.0% (2024). [1]
• The decline was steady and accelerating after 2021, reaching 3.0% by 2024. [1]
• Teaching note: Direction + rate. Trap: only say "fell" without values.

Q3 [2 marks]

• In 2021, mass package ($800m) exceeded eco/remote ($600m) by $200m. [1]
• By 2024, eco/remote ($3400m) exceeded mass package ($2400m) by $1000m; composition reversed. [1]

Q4 [2 marks]

• Global travel restrictions in 2020 changed consumer preferences and firm offerings; by 2023 eco-tourism and remote-work visitors rose because firms adapted via digital grants and visitors sought less crowded options. [2] (Any one valid reason from Extract 1)
• Teaching: Link extract evidence to composition shift.

Q5 [2 marks]

• Fig 1 shows an inverse relationship: as Real GDP growth rose (from -4.1% to 4.0%), unemployment fell (6.8% to 3.2%). [1]
• The two lines move in opposite directions across all years. [1]

Section B: Microeconomic Analysis (20 marks)

Q6 [4 marks]

• Diagram: labour demand D, supply S, eq wage $8.20; min wage$9.50 above eq creates excess supply. [2]
• Explanation: At higher wage, quantity supplied of youth labour rises, quantity demanded falls → unemployment among youth. [2]
• Teaching: Use extract: food services reduced hiring youth. Minimum wage > market clearing causes surplus.

Q7 [2 marks]

• PES likely low (<1) in short run because training places require time to set up (trainers, facilities). [2]
• Teaching: PES = responsiveness of Qs to price; time constraint reduces elasticity.

Q8 [3 marks]

• Wage subsidy lowers effective labour cost to firms, so they retain workers instead of laying off. [1]
• This maintains income and consumption, reducing cyclical unemployment from tourism shock. [1]
• Extract 1: hospitality firms received subsidy, aiding recovery. [1]

Q9 [3 marks]

• Total 2020 = 4200 + 900 = 5100. Total 2024 = 2400 + 3400 = 5800. [1]
• % change = (5800 - 5100)/5100 × 100 = 13.73%. [2]
• Working: 700/5100 = 0.1373 → 13.7% (allow 13.7–13.8)

Q10 [2 marks]

• Possible failure: information failure / under-provision of training (youth lack skills). Subsidy corrects by raising supply of trained workers. [2]

Q11 [4 marks]

• Diagram: S shifts right to S1 due to subsidy (lowers cost). [2]
• Price falls, quantity of digital services rises. [2]
• Teaching: subsidy is supply-side, not demand.

Q12 [2 marks]

• Equity improved for low-skilled workers earning $9.50 vs$8.20 (fairer wage). [1]
• But equity worsened for excluded youth unemployed. [1]
• Teaching: trade-off required by syllabus.

Section C: Macroeconomic & Evaluative (30 marks)

Q13 [2 marks]

• GDP growth: -4.1% (2020) to 4.0% (2023) – recovered. [1]
• Unemployment: 6.8% to 3.2% – fell. [1]

Q14 [3 marks]

• Tourism is export-equivalent; arrival fall cuts consumption & I in hospitality. [1]
• X falls → AD shifts left → real GDP contraction (Table 1: -4.1%). [2]

Q15 [4 marks]

• AD/AS diagram: AD shifts right to AD1. [2]
• Wage subsidy raises disposable income → C rises; digital grants raise I → AD↑, real output↑. [2]

Q16 [8 marks]

• Mark descriptors:
  • Use of data: rising education spend, falling unemployment, GDP recovery (2)
  • Material living standard: higher GDP, lower unemployment (2)
  • Non-material: tourism mix, skills (2)
  • Evaluation: ignores inequality, environmental cost of eco-tourism (2)
• Teaching: Must use Table 1 + Extracts, show trade-offs.

Q17 [2 marks]

• Opportunity cost = other goods/services forgone (e.g. primary education or healthcare) when more spent on university. [2]

Q18 [3 marks]

• PPC2020 inside due to unemployment; by 2024 outward shift from tourism recovery + digital adoption raising capacity. [3]
• Diagram must show outward shift.

Q19 [3 marks]

• Unintended: youth unemployment rose (Extract 2). [1]
• Firms substituted to machines/apprentices. [1]
• Net equity effect ambiguous. [1]

Q20 [5 marks]

• Effective: wage subsidy + digital grants aided fast recovery (GDP 4.0%, unemp 3.2%). [2]
• Partial: min wage hurt youth. [1]
• Use evidence from all tables/extracts. [2]
• Teaching: evaluation needs trade-off and data reference.