Why describing figures is not enough and how examiners expect you to think with them
Data appears in almost every VCE Economics exam. Tables, charts and extracts are not there to test whether students can read numbers. They are there to test whether students can reason economically using evidence.
Year after year, examiner reports make the same point. Many students correctly identify trends but still lose marks because they stop too early. They describe what the data shows, but they do not explain what it means for economic conditions, objectives or policy effectiveness.
In VCE Economics, data is not an add-on. It is part of the argument.
What the Study Design actually expects when data is provided
The Study Design is explicit that students must be able to interpret data related to economic indicators and use that data to analyse and evaluate economic conditions and policy outcomes.
This means students are expected to go beyond observation. They must connect figures to concepts such as aggregate demand, inflationary pressure, unemployment types or living standards.
Simply stating that inflation increased or unemployment fell is not interpretation. It is identification. Marks are awarded when students explain why that change matters.
The most common mistake students make with data
The most common error is treating data as something to summarise rather than something to use.
Students often write sentences like “the data shows that inflation increased from X to Y” and then move on. While accurate, this tells the examiner nothing about economic implications.
A stronger response would explain what that increase suggests about demand pressures, cost conditions or the need for policy intervention.
The difference is not the data itself. It is what the student does with it.
Selecting data matters more than covering all of it
Another issue highlighted in examiner reports is that students try to mention every figure in the stimulus.
This often weakens responses. It leads to rushed writing and shallow explanation.
High-scoring responses are selective. They choose the most relevant figures and use them to support a specific claim. They do not describe the entire table or graph.
In Economics, relevance beats coverage.
Linking data to economic objectives
One of the clearest ways to strengthen data use is to link figures directly to economic objectives.
For example, inflation data should be linked to the objective of low and stable inflation. Unemployment figures should be linked to full employment. Growth data should be linked to strong and sustainable economic growth.
When students make these links explicit, they show the examiner that they understand what the data is for.
Using data to justify policy discussion
Data is especially important in policy questions.
If a question asks students to evaluate the effectiveness of monetary or fiscal policy, the data usually signals the economic problem the policy is addressing. Ignoring that signal almost always caps marks.
Strong responses use data to justify why a policy is appropriate, or to question its effectiveness. For example, persistent inflation may support contractionary policy, while weak growth figures may complicate that decision.
Data should drive the evaluation, not sit beside it.
Explaining direction and magnitude
Examiners consistently reward students who explain both the direction and significance of change.
It is not enough to say something increased or decreased. Students should explain whether the change is substantial, gradual, persistent or volatile, and why that matters economically.
A small rise in inflation may require a different response to a sharp and sustained increase. Data allows students to show this nuance.
Integrating data into sentences, not bolting it on
Another common weakness is adding data at the end of a paragraph without integrating it into the reasoning.
High-scoring responses weave data into their explanation. The figure supports the claim being made in the sentence, rather than appearing as an afterthought.
This makes the response feel controlled and purposeful.
What strong data use looks like in practice
Across exam reports, strong data use follows the same pattern.
Students identify a relevant trend, explain what it shows about economic conditions, and link it to an objective or policy outcome. The data becomes evidence, not description.
This is what separates mid-range responses from high-range ones.
What this means for Economics preparation
Students should practise using data actively, not passively.
Preparation should involve asking questions such as: What does this figure tell me about the economy. Why does this matter. How does it support or challenge a policy decision.
Learning to think this way makes data questions far more predictable.
Working with ATAR STAR
ATAR STAR Economics tutoring places strong emphasis on data interpretation because it is one of the most consistent sources of lost marks.
We teach students how to read stimulus material strategically, select relevant figures, and integrate data into economic reasoning in line with the Study Design.
When students learn to use data properly, their answers become sharper, more persuasive and far more exam-ready.
If you want your Economics responses to show thinking rather than just observation, ATAR STAR provides preparation grounded in how data is actually assessed.