ECONOMICS-12 · Research · ENGLISH · PLANNED
State the question and assumptions, draw the model, analyse evidence and test competing explanations.
Study time is an initial activity estimate, excluding extra reading, revision and extended laboratory or project work. Videos and question bodies have not been produced by adding this outline.
Complete these courses or demonstrate equivalent knowledge. These are recommended prerequisites, not enforced enrolment locks.
YouTube playlist: ARK Economics | Graduate Economic Theory and Research Studio
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Sign in to save this learning pathPractical outcome: Reconstruct a small theoretical argument and identify its assumptions.
Explain convex analysis using a visual and one worked real-world example. Context: Reconstruct a small theoretical argument and identify its assumptions. End with a prediction or check-for-understanding.
Explain dynamic programming using a visual and one worked real-world example. Context: Reconstruct a small theoretical argument and identify its assumptions. End with a prediction or check-for-understanding.
Explain mechanism design using a visual and one worked real-world example. Context: Reconstruct a small theoretical argument and identify its assumptions. End with a prediction or check-for-understanding.
Explain information economics using a visual and one worked real-world example. Context: Reconstruct a small theoretical argument and identify its assumptions. End with a prediction or check-for-understanding.
Use the first concepts from this section. Reconstruct a small theoretical argument and identify its assumptions. Produce a labelled diagram, trace or calculation; explain each step and check one changed input.
3–6 questions on the preceding first-half concepts only: recall, visual interpretation, application and one plausible misconception. Explain each answer after submission.
Explain search and matching using a visual and one worked real-world example. Context: Reconstruct a small theoretical argument and identify its assumptions. End with a prediction or check-for-understanding.
Explain heterogeneous agents using a visual and one worked real-world example. Context: Reconstruct a small theoretical argument and identify its assumptions. End with a prediction or check-for-understanding.
Explain dynamic stochastic models using a visual and one worked real-world example. Context: Reconstruct a small theoretical argument and identify its assumptions. End with a prediction or check-for-understanding.
Explain equilibrium existence pathways using a visual and one worked real-world example. Context: Reconstruct a small theoretical argument and identify its assumptions. End with a prediction or check-for-understanding.
Reconstruct a small theoretical argument and identify its assumptions. Work without the example, compare two cases, record assumptions and limitations, then self-review correctness, reasoning and clarity.
6–12 questions covering Convex analysis, Dynamic programming, Mechanism design and the remaining section concepts, with cumulative retrieval from earlier sections. Include a new transfer problem; 70% unlocks progression.
Practical outcome: Critique an empirical paper using an original reproducibility checklist.
Explain maximum likelihood using a visual and one worked real-world example. Context: Critique an empirical paper using an original reproducibility checklist. End with a prediction or check-for-understanding.
Explain generalised method of moments using a visual and one worked real-world example. Context: Critique an empirical paper using an original reproducibility checklist. End with a prediction or check-for-understanding.
Explain bayesian inference using a visual and one worked real-world example. Context: Critique an empirical paper using an original reproducibility checklist. End with a prediction or check-for-understanding.
Explain structural estimation using a visual and one worked real-world example. Context: Critique an empirical paper using an original reproducibility checklist. End with a prediction or check-for-understanding.
Use the first concepts from this section. Critique an empirical paper using an original reproducibility checklist. Produce a labelled diagram, trace or calculation; explain each step and check one changed input.
3–6 questions on the preceding first-half concepts only: recall, visual interpretation, application and one plausible misconception. Explain each answer after submission.
Explain treatment-effect heterogeneity using a visual and one worked real-world example. Context: Critique an empirical paper using an original reproducibility checklist. End with a prediction or check-for-understanding.
Explain spatial dependence using a visual and one worked real-world example. Context: Critique an empirical paper using an original reproducibility checklist. End with a prediction or check-for-understanding.
Explain machine learning for economics using a visual and one worked real-world example. Context: Critique an empirical paper using an original reproducibility checklist. End with a prediction or check-for-understanding.
Explain replication standards using a visual and one worked real-world example. Context: Critique an empirical paper using an original reproducibility checklist. End with a prediction or check-for-understanding.
Critique an empirical paper using an original reproducibility checklist. Work without the example, compare two cases, record assumptions and limitations, then self-review correctness, reasoning and clarity.
6–12 questions covering Maximum likelihood, Generalised method of moments, Bayesian inference and the remaining section concepts, with cumulative retrieval from earlier sections. Include a new transfer problem; 70% unlocks progression.
Practical outcome: Write an original economic research proposal using synthetic or openly licensed data.
Explain literature mapping using a visual and one worked real-world example. Context: Write an original economic research proposal using synthetic or openly licensed data. End with a prediction or check-for-understanding.
Explain research questions using a visual and one worked real-world example. Context: Write an original economic research proposal using synthetic or openly licensed data. End with a prediction or check-for-understanding.
Explain identification strategy using a visual and one worked real-world example. Context: Write an original economic research proposal using synthetic or openly licensed data. End with a prediction or check-for-understanding.
Explain data documentation using a visual and one worked real-world example. Context: Write an original economic research proposal using synthetic or openly licensed data. End with a prediction or check-for-understanding.
Use the first concepts from this section. Write an original economic research proposal using synthetic or openly licensed data. Produce a labelled diagram, trace or calculation; explain each step and check one changed input.
3–6 questions on the preceding first-half concepts only: recall, visual interpretation, application and one plausible misconception. Explain each answer after submission.
Explain robustness planning using a visual and one worked real-world example. Context: Write an original economic research proposal using synthetic or openly licensed data. End with a prediction or check-for-understanding.
Explain distributional interpretation using a visual and one worked real-world example. Context: Write an original economic research proposal using synthetic or openly licensed data. End with a prediction or check-for-understanding.
Explain policy communication using a visual and one worked real-world example. Context: Write an original economic research proposal using synthetic or openly licensed data. End with a prediction or check-for-understanding.
Explain research defence using a visual and one worked real-world example. Context: Write an original economic research proposal using synthetic or openly licensed data. End with a prediction or check-for-understanding.
Write an original economic research proposal using synthetic or openly licensed data. Work without the example, compare two cases, record assumptions and limitations, then self-review correctness, reasoning and clarity.
6–12 questions covering Literature mapping, Research questions, Identification strategy and the remaining section concepts, with cumulative retrieval from earlier sections. Include a new transfer problem; 70% unlocks progression.
Combine all three sections: Write an original economic research proposal using synthetic or openly licensed data. Submit an original worked artifact, evidence or tests, assumptions and a reflection. Rubric: correctness, method, practical usefulness, reproducibility and communication. Self-reviewed, not certified.
6–12 balanced questions sampling every section of Graduate Economic Theory and Research Studio, including interpretation, calculation or reasoning, a misconception and a new application. Passing is 70%; review errors before retrying.
Economic diagrams, synthetic datasets, calculations and evidence-based policy memos. Guided work leads to an independent attempt, with a diagram, explanation, trace, calculation or tested artifact. Question bodies are generated when opened in your private learning path. Programming submissions are stored as text; the platform does not execute submitted code.
Use original or appropriately licensed datasets. Practical science activities use models or supplied data unless a qualified supervisor has reviewed a physical experiment.
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