Modelling and the economic method

Explain what an economic model is and why simplifying reality is not a flaw but a necessity. Compare it to a tube map: how is it similar to and how does it differ from the real city?

A café wants a simple model to predict how many coffees it will sell depending on the price it sets. State which two variables the model would include, which things it would leave out (weather, exams, roadworks on the street) and why leaving them out does not make the model useless.

A model of the sandwich market assumes that all buyers know the prices of all cafeterias and that all sandwiches are identical.

1. a) Why are these assumptions not met in reality?
2. b) Why can the model still be useful despite this?

In the model "the higher the ticket price, the fewer bus passengers", indicate which variable the model tries to explain and which is taken as a starting given. Propose two external factors that the model leaves out and that could alter the result.

We want to model why some newsagents sell more than others. Design the model: choose three variables you would include, two reasonable simplifying assumptions, and explain how you would check whether the model works.

Design a model to predict how many daily users your town's new bike hire scheme will have.

1. a) Choose three variables you would include and justify each one.
2. b) Formulate two simplifying assumptions.
3. c) Explain what data you would collect during the first few months to check whether the model works and what you would do if it fails.

"All models are wrong, but some are useful." Discuss this statement applied to a specific economic model (for example, supply and demand): in what sense is it "wrong", what useful predictions it allows, and when it would stop being useful.

What does the Latin phrase "ceteris paribus" mean and why do economists use it? Give an example applied to the relationship between cinema ticket prices and the number of viewers.

Explain what an economic variable is and give three examples (price, quantity sold, household income). Then, in the statement "if it gets hotter, more ice creams are sold", indicate which variable is to be explained and which is used to explain it.

What is an assumption within a model? Point out two hidden assumptions in this statement: "if the bus fare falls, more students will use it" (think about journey time, distances, or the price of the alternatives).

A school model states: "the more weekly hours of study, the better the average grade".

1. a) Which is the explained variable and which is the explanatory one?
2. b) Name two factors that the model leaves out and that can alter the result.
3. c) How would you test the model against data from your own class?

A cinema raises its ticket price by $15\ \%$ and yet is fuller than ever because it has released the film of the year. Using the phrase "ceteris paribus", explain why this case does not refute the model that a higher price means fewer sales. Which variable that the model assumed to be fixed has moved?

The figure shows the steps of the scientific method applied to economics, with one step covered by a question mark. State which step is missing and explain what is done in each of the others.

What is a prediction in economics and how do you check whether it was accurate? Give an example of a prediction about the market in your town (rental prices, shop openings) and explain what data you would look at a year later.

In a classroom, an auction is simulated: the teacher "sells" ten cinema tickets and the students bid using points redeemable for supplies.

1. a) What does this consist of as an economic experiment?
2. b) State one advantage and one limitation of learning economics through classroom experiments instead of observing the real world.

A stationery shop records the price of its notebooks and the units sold for four weeks in a row: at $\text{€}\ 3$ it sells $90$; at $\text{€}\ 4$, $75$; at $\text{€}\ 5$, $62$; at $\text{€}\ 6$, $50$.

1. a) What pattern do the data suggest?
2. b) Formulate a model hypothesis and a testable prediction for a price of $\text{€}\ 7$, stating what assumption you are making.

Meteorologists predict rain fairly accurately; economists fail much more often when predicting crises. Compare both models and explain two reasons why predicting the economy is harder than predicting the weather (think about how people change their behaviour when they learn the prediction).

One county raises the minimum wage in its public sector and the neighbouring one does not. Researchers compare the evolution of employment in both before and after.

1. a) What does this testing strategy called a "natural experiment" consist of?
2. b) What assumption must hold for the comparison to be valid? Reason out what could spoil it.

A consultancy predicts using a model that raising train tickets by $10\ \%$ will reduce passengers by $5\ \%$. The following year, the price rises by $10\ \%$ and passenger numbers fall by $12\ \%$.

1. a) Give two possible explanations for the failure of the prediction.
2. b) Does the failure mean that the model was useless? Reason your answer.

To test whether a new rent subsidy of $\text{€}\ 250$ per month for young people makes housing more affordable for them or ends up driving up rents, a government proposes: "Let us implement it across the entire country for one year and observe whether average rent prices go up or down." Several economists point out that such a test would not allow valid scientific conclusions to be drawn.

1. a) Justify why the government's proposal fails from the point of view of the scientific method: why does a simple "before and after" price comparison fail to isolate the effect of the subsidy (breakdown of the ceteris paribus condition)?
2. b) Faced with the impossibility of experimenting in a closed laboratory, design a strategy based on a "natural experiment" (for example, comparing bordering geographic areas or groups with and without the subsidy) that makes it possible to empirically test the impact of the policy.

A model predicts that cutting VAT for the hospitality sector will create $10,000$ jobs; a year later, employment in the sector has barely changed.

1. a) Give three possible explanations for the failure (assumptions, external factors, measurement).
2. b) Explain how you would improve the model for the next prediction.
3. c) Was the model a scientific failure or part of the process of learning? Reason your answer.

The minimum wage rises and youth unemployment does not change. One economist concludes: "raising the minimum wage does not destroy jobs"; another replies: "without the rise, unemployment would have fallen".

1. a) Explain how the same piece of data admits two interpretations.
2. b) What additional data would you need to decide which is more plausible? Relate it to the idea of "what would have happened" (the counterfactual scenario).

In summer, ice cream sales rise and so do drownings at beaches, but nobody says that ice creams cause drownings. Use this example to explain the difference between correlation and causality, and why confusing them leads to bad decisions.

During an economic recession, a pundit states: "Any sensible family knows that if their income falls, they must tighten their belt and cut their spending as much as possible to get through the rough patch. Therefore, the best policy for the country to overcome the crisis is for all families, businesses, and public administrations to simultaneously reduce their spending by $15\,\%$."

1. a) Relying on the circular flow of income model, refute the pundit's argument: predict what will happen to firms' revenues and employment if all agents attempt to cut their spending at the same time.
2. b) Explain the methodological error the pundit makes by directly extrapolating an individual behavioral pattern (microeconomics) to the whole country (macroeconomics), and propose another economic situation (other than saving or spending) where this same fallacy of composition occurs.

Topic challenge. How does scarcity affect a household's budget? Build your own economic model by applying the scientific method using real data from the CSO.

1. Data collection: Go to the CSO website (cso.ie) and write down the year-on-year rate of change of the CPI for the latest month (for example, $3.2$ %) for three groups: food (primary necessity goods), transport, and leisure (secondary needs).

2. Economic modelling: Propose a hypothesis about how a household reacts to these rising prices. Applying the ceteris paribus condition, build a simplified model: allocate a monthly budget limit of $1500$ € across the three categories and recalculate spending by applying the observed rates of change.

3. Analysis and representation: Design a comparison table and a simple graph showing the budget trade-off. Identify and quantify the opportunity cost of keeping food consumption intact.

4. Reasoned proposal: Write a brief report (one page) presenting your tested hypothesis, evaluating the validity of your model, and justifying which categories you would cut back on to solve the problem of scarcity.

Assessment criteria:

• Thoroughness in obtaining data from the CSO and correctly classifying needs and goods.

• Proper application of the scientific method, model assumptions (ceteris paribus), and calculation of opportunity cost.

• Clear argumentation in the final report and consistency in the graphical representation of decisions.