Thinking like an economist

Positive and normative statements

A positive statement is about what is, was or will be. It can be tested against evidence, so it can be shown to be true or false. A normative statement is about what ought to be. It contains a value judgement, so evidence alone cannot settle it.

A positive statement does not have to be correct. "Unemployment fell to 20% last year" is positive, because we can check it, and it is almost certainly false. What matters is that it can be tested.

Policy debates mix the two. Positive economics tells us what a policy is likely to do. Normative economics decides whether the result is worth having.

Models, assumptions and ceteris paribus

The real economy has millions of people making decisions at once. To make sense of it, economists build models: simplified versions of reality that keep the important relationships and ignore the rest. A map works the same way. A map of the Dublin Luas that showed every house would be useless.

Models rest on assumptions. The most famous is ceteris paribus, Latin for "all other things being equal". To study how a change in price affects the quantity demanded of a cinema ticket, we assume income, tastes and the price of other goods stay the same. Otherwise we could not tell which change caused the effect.

Models have limits. If the assumptions are unrealistic, the predictions may fail. A good economist asks: which assumptions does this model make, and are they reasonable here?

Learning from economic history

Economic history gives economists their evidence. Three episodes matter for the Leaving Certificate: the Great Depression, the Irish crisis of the 1950s, and the Great Recession with the Irish banking crisis.

The Great Depression of the 1930s

It began with the Wall Street Crash of 1929 and spread worldwide. Its main features were:

• A huge fall in output and in incomes.

• Mass unemployment, in some countries a quarter or more of the workforce.

• Falling prices (deflation) and falling demand.

• Bank failures and a collapse in lending.

• A fall in world trade as countries raised tariffs to protect their own industries.

Governments at first tried to balance their budgets, which deepened the fall in demand. This led economists, notably John Maynard Keynes, to argue that governments should spend more to support demand in a slump.

The Irish crisis of the 1950s

In the 1950s Ireland followed a policy of protectionism: high tariffs on imports to protect Irish industry, with the aim of self-sufficiency. The small home market could not support efficient industries, and exports were weak.

Effects:

• Very low growth, while other European economies boomed.

• High unemployment and heavy emigration, with many people leaving for Britain.

• A falling population and low living standards.

The policy change came in the late 1950s. The programme Economic Development (1958), linked with T. K. Whitaker, moved Ireland towards free trade and export-led growth, encouraged foreign direct investment and reduced reliance on tariffs. Growth rose in the 1960s.

The Great Recession and the Irish banking crisis (2008-2010)

Ireland had a property boom in the Celtic Tiger years. Banks lent heavily, house prices rose far above sustainable levels, and the economy depended on construction and tax revenue from property. When the global financial crisis arrived in 2008, the bubble burst. Banks faced huge losses, the Government guaranteed bank liabilities, public finances worsened, unemployment rose sharply, and many people emigrated again.

The responses included bank recapitalisation, spending cuts and tax rises (austerity), and financial support from the EU and IMF. Lessons learned include tougher financial regulation by the Central Bank of Ireland, higher capital requirements for banks, and more caution about relying on property-related taxes.

Working with data

Economists test their ideas with data. Three simple measures summarise a set of numbers.

• Mean: add all the values and divide by how many there are.

• Median: the middle value when the data are in order (for an even number of values, the average of the two middle ones).

• Range: the largest value minus the smallest.

Percentage points and percentage change

These are easy to confuse, and examiners test it.

• Percentage point change is the plain difference between two rates.

• Percentage change compares the change with the starting value: $\dfrac{\text{new} - \text{old}}{\text{old}} \times 100$.

Designing a survey

A good survey needs:

• Sample selection: a sample that represents the whole group. A random sample, such as every fifth name on the school roll, is better than asking only your friends. A bigger sample reduces chance error.

• Clear questions: short, neutral and answerable, for example "How many hours do you work each week?" rather than "Don't you think working ruins your results?"

• Presentation: tables, bar charts or scatter plots, with averages calculated for each group.

• Sources of bias: a non-random sample, leading questions, students giving untruthful answers, and non-response (those who do not answer may differ from those who do).

Correlation and causation

Two things can move together without one causing the other. When they move together, we say they are correlated. Causation means a change in one thing actually produces a change in the other.

Suppose counties that spend more on youth training have lower youth unemployment. This is a correlation. It does not prove the training caused the fall. Other explanations are possible:

• A third factor: richer counties with more employers may both fund more training and have more jobs.

• Reverse causation: counties with high unemployment might be given extra funding, which would create the opposite pattern.

• Coincidence: a small sample can produce a pattern by chance.

To strengthen the conclusion, economists could compare the same counties before and after training expanded, and use more years of data and more counties. The ideal is a controlled experiment: randomly give some young people training and others none, then compare. But there are limits. It is unethical to deny people a beneficial programme just for research, and it is hard and costly to follow young people for years. Economists therefore often rely on natural experiments, such as a programme introduced in some counties before others, and on statistical controls.

This is also why economics is harder to treat as a laboratory science. Economists cannot easily run controlled experiments on whole economies, people respond to being studied, and value judgements influence which questions are asked. That is the heart of the debate about whether economics is a science.

Vuelve al principio: "Unemployment in Ireland fell last year" is a positive statement, because the CSO figures can check it. "Rents in Dublin are too high" is normative, because "too high" is a value judgement that data cannot settle on its own.

Summary