OxfordAQA International AS and A-level Economics: Rational and behavioural choice (9640)

This guide covers sections 3.3.1.1 and 3.3.1.2 of the OxfordAQA International AS and A-level Economics specification (9640, version 1.2). Section 3.3 is extra International A2 content, beyond the International AS. It teaches the individual as a rational decision maker, then the behavioural challenge to that picture. The objectives and growth of firms are separate statements and are not covered here. All the countries, firms and figures are made up for illustration.

Use it with the revision notes and the practice questions. Other links: course hub, checklist, diagnostics and the guide to demand and elasticity.

Outcomes covered

Section	Outcome
3.3.1.1	Utility theory: total and marginal utility, diminishing marginal utility, utility maximisation
3.3.1.1	Why information matters for decisions; the significance of asymmetric information; imperfect information as a barrier to rational choice and a source of market failure
3.3.1.2	Bounded rationality and bounded self-control
3.3.1.2	Biases: computational problems, inertia, rules of thumb, anchoring, social norms
3.3.1.2	Altruism and perceptions of fairness
3.3.1.2	How firms and governments may act on behavioural evidence, including nudges

The specification says diminishing marginal utility supports a downward-sloping demand curve. It does not expect the principle of equi-marginal utility, so that is left out.

The rational decision maker

Traditional theory assumes an individual who weighs the options, uses the information available and picks the one giving most satisfaction. Satisfaction is called utility. Such a person aims at utility maximisation.

Total and marginal utility

• Total utility (TU): total satisfaction from consuming a quantity of a good in a period.
• Marginal utility (MU): the satisfaction gained from consuming one additional unit; arithmetically, the change in TU.

The hypothesis of diminishing marginal utility holds that the more of a good you consume in a period, the smaller the satisfaction each additional unit brings compared with the last. It is a hypothesis about typical behaviour, not a law.

Worked example. Country A is invented. A resident rates her weekly swimming visits in utils (an invented unit).

Visits	TU	MU	MU in currency units
1	40	40	20
2	70	30	15
3	90	20	10
4	100	10	5
5	100	0	0
6	90	-10	-5

MU is each TU minus the one before: 70 - 40 = 30, 90 - 70 = 20, and so on. Each MU is smaller than the last, which fits the hypothesis. TU rises while MU is positive, peaks where MU is zero, and falls when MU is negative. A sketch in words: the MU curve slopes down from 40 and crosses the horizontal axis at 5 visits. The TU curve rises at a slowing rate, flattens at 100 and turns down.

If visits were free, a utility maximiser would go four or five times, since TU is highest (100) at both. She would never choose six.

Utility maximisation and demand

Suppose she values one util at 0.5 currency units. The last column is then the most she will pay for each extra visit. She buys a visit only if what it is worth to her is at least the price.

Price per visit	Visits bought	Reason
16	1	Second visit worth 15, below 16
12	2	Third visit worth 10, below 12
8	3	Fourth visit worth 5, below 8
4	4	Fourth worth 5, at least 4; fifth worth 0

As the price falls from 16 to 4, visits rise from 1 to 4. Because each extra unit is worth less, she takes more only at a lower price. That is the link between diminishing marginal utility and a downward-sloping demand curve. Note that this explains the slope of one person’s demand for one good. You are not required to compare several goods.

Information and decision making

Rational choice needs good information about price, quality, risks and alternatives. If information is missing, wrong or hard to compare, agents cannot choose as theory assumes.

Worked example (imperfect information). In Country A two energy tariffs are offered. X charges a fixed 20 a year plus 0.12 per unit. Y charges 90 plus 0.08 per unit. A household uses 1,500 units.

• X: 20 + 0.12 × 1,500 = 200.
• Y: 90 + 0.08 × 1,500 = 210.

A buyer who compares only the unit price picks Y, as 0.08 is below 0.12, and pays 10 more. The break-even use is where 20 + 0.12q = 90 + 0.08q, so 0.04q = 70 and q = 1,750 units. Below 1,750 units X is cheaper. At 2,000 units X costs 260 and Y 250, so the better choice reverses. Rational choice therefore needs the whole picture and the sum.

Asymmetric information

Asymmetric information exists when the buyer and the seller are not equally well informed, because one side knows more. A seller knows more about a product’s quality, or a buyer of insurance knows more about their own risk.

Worked example. An insurer in Country B sells cover to 1,000 people. Half are low-risk, with an expected claim of 100 a year each. Half are high-risk, with an expected claim of 500. The insurer cannot tell them apart.

1. Average expected claim: (100 + 500) ÷ 2 = 300, so it charges 300.
2. Revenue 1,000 × 300 = 300,000; claims 500 × 100 + 500 × 500 = 300,000. It breaks even.
3. Suppose low-risk people value cover at no more than 150. Charged 300, they leave.
4. Now 500 high-risk people pay 150,000 but claim 250,000, a loss of 100,000.
5. The premium must rise towards 500 to break even.

Low-risk people who would gladly buy cover at a fair price, and an insurer willing to sell it, never trade. That is market failure: the market does not allocate resources efficiently because one side lacks information. Remedies include screening, compulsory cover and public provision.

Behavioural influences

Behavioural economists question the assumption that individuals are rational and aim to maximise utility. They study how people actually decide.

Bounded rationality and bounded self-control

Bounded rationality: decision makers face limits on information, time and processing ability, so they use simpler methods and often settle for an acceptable choice rather than the best.

Bounded self-control: people know what is best for them but fail to act on it, because they give too much weight to the present.

Worked example. A member pays 36 a month for a gym and plans 12 visits, a cost of 3 a visit. She goes 3 times, so each visit costs 36 ÷ 3 = 12. Pay-per-visit at 7 would have cost 3 × 7 = 21, so she lost 15 by failing to follow her plan.

Biases in decision making

• Computational problems: the sum is too hard, so people use a rough guess. A loan of 5,000 charges 1% a month, compounding, repaid after 12 months. Many people assume 12%, giving 5,600. The true amount is 5,000 × 1.01¹² = 5,634.13, which is 34.13 more, because 1.01¹² - 1 is 12.68%.
• Inertia: sticking with the current option because changing takes effort. A saver leaves 3,000 in an account paying 0.5% (15 a year) when another pays 3.0% (90). Inertia costs her 75 a year.
• Rules of thumb: simple shortcuts that save effort but misfire. “Never pay over 10 for lunch” rejects a meal worth 14 to you at 10.50.
• Anchoring: judging by an initial reference number. A sofa is shown as “was 900, now 540”, which looks 40% cheaper (540 ÷ 900 = 0.6). If similar sofas sell for 500, the “bargain” is 8% dearer: (540 - 500) ÷ 500.
• Social norms: unwritten rules about how people behave, followed because others do. A hotel card says most guests reuse towels. Reuse rises from 38% to 47% of 400 stays, from 152 to 188, which is 36 more.

Altruism and fairness

People often give without personal gain, and they care about fairness. Altruism means their utility depends on others’ wellbeing, so a purely self-interested model misses behaviour such as charity. Perceptions of fairness shape reactions to prices and wages.

Worked example. A shop sells 500 umbrellas a day at 10. In a storm, 800 customers would buy at 10 and it has stock for 800, so it raises the price to 18 and still sells all 800. Revenue is 800 × 18 = 14,400 against 8,000 at the old price, a gain of 6,400. Customers see this as unfair and 25% of regulars stop buying, so afterwards sales fall to 375 a day (revenue 3,750 against 5,000). If this lasts 6 days, the loss is 6 × 1,250 = 7,500, more than the gain. Fairness can make the profit-maximising move a poor one.

Firms, governments and nudges

Firms use behavioural evidence. They set anchors with high “was” prices, make renewal automatic knowing inertia keeps customers, and frame choices to suit.

Governments may use nudges: ways of steering choices without banning options or greatly changing prices. Examples are default enrolment, social-norm messages and clearer information.

Worked example. A firm has 800 staff. With opt-in, 35% join a savings plan: 280. With opt-out, 80% stay in: 640. That is 360 more members. At 60 a month each, extra saving is 360 × 60 × 12 = 259,200 a year. Inertia explains why the default matters.

Another case: a council writes to 20,000 households with a norm message. On-time payment rises from 78% to 83%, from 15,600 to 16,600. Letters cost 0.5 each, 10,000 in all, so 10 per extra payer.

Evaluating nudges. For: cheap, keep choice, work where information fails. Against: effects may fade, vary between people and be hard to measure; some argue they are manipulative; for large externalities a tax or regulation may fit better, since a nudge could be too weak. Judge by the size of the problem and the evidence of effect.

Common errors

• Defining marginal utility as total utility divided by units.
• Saying a rational person never errs; the model assumes it as a simplification.
• Mixing up bounded rationality (a limit on deciding well) and bounded self-control (not following the plan).
• Naming a bias without tying it to the case.
• Calling a nudge a ban or a tax.
• Treating asymmetric information as simply “missing” information: one side knows more.

Official syllabus

Source: the OxfordAQA International AS and A-level Economics (9640) specification, version 1.2, Oxford International AQA Examinations. Sections 3.3.1.1 and 3.3.1.2.