Economics resources for high school students, teachers, and everyone else
Teaching Resources
QCAA Economics Unit 3: International Economics
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Unit 3 Topic 2 : A taxonomy for economic data analysis
THE THREE LEVELS OF ECONOMIC DATA
BACKGROUND:
A critical issue that I see students face in developing their IA2 research reports is how to create links in data to demonstrate how changes in one sector of the economy (or dataset) can be evidenced in another sector (or dataset).
So my question then became: how can I create a sequence of targets to help students to analyse data and economic information at a deeper and more perceptive level?
Subsequently, I have been using a three level taxonomy with students.
The intention is to create an understanding of how to connect information from the granular to the big picture - the idea being that they can create a path of analysis from the micro to the macro. In terms of the marking guide, it will likely help shift students' work closer towards that 'perceptive' end of the ISMG.
Importantly, it has also created a meta-language in economics data analysis - for reflection on the quality and quantity of the research information that the student has collected, to identify information gaps, and to give some targets for the structure of the analysis presented in the report.
This explainer is also published on the student resources page. Below is the explainer for students. I would encourage you to give it a try with your classes!
A big challenge in writing an economics research report is figuring out how to connect the data to demonstrate elements such as cause and effect relationships - how do we create a path of analysis from the microeconomic issues through to macroeconomic outcomes? So let's have a look at how we can create a three level system to deepen our analysis.
LEVEL 1 DATA
Data relating to a stakeholder or individual sector of the economy
(eg.firms and industry sectors, consumers or government)
Examples:
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data on industry trade with foreign customers
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foreign investment activity into an industry sector (eg. mining investment)
LEVEL 2 DATA
Data relating to an overall (aggregate) aspect of trade or investment
Examples:
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total export or import trade values or volumes
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total foreign investment
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Balance of Trade
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Currency valuations
LEVEL 3 DATA
The macroeconomic indicators:
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Gross Domestic Product
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Inflation
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Employment
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Balance of Payments
Applying the three levels of economic data :: Australia / China trade example
In 2021, China enacted a range of trade protection on imports from Australia. Most of these barriers were removed in 2023.
The three level model helps us to analyse and evaluate outcomes during this period of export trade constraints.
LEVEL 1
Australia coal exports to China
LEVEL 2
Australia-China bilateral
balance of trade
LEVEL 3
Australia Current Account
Creating connections between data and economic information presents a significantly more complete picture:
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At level 1, the negative effect of China trade protection on Australia's coal exports is clearly evident.
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This then flows through to level 2, where a downturn in bilateral trade balance is evident in 2022.
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At level 3, the effect is also evident in Net Goods and Services (top line) and Current Account Balance (red line).
I think you'll agree that this method provides some significant insight into the issue, and yields a deeper analysis than just focussing on a dataset in isolation.
Some final ideas:
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Remember: Correlation doesn't always equal causation, so make sure you do further research to determine cause-and-effect.
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The Analysis criteria in the marking guide requires "discerning meaning drawn from patterns and trends ..." as well as "... explanation of economic relationships ...". I reckon that this three level model will give you some targets to achieve "discernment".