Perspectives on economic behaviour
  • Assignment 1
    • Data analysis
    • Discussion
    • Rubric
  • Assignment 2
    • Data analysis
    • Report writing
    • Rubric
  • General
    • Referencing
    • CSV files
    • Feedback
Assignment 2

Rubric

What to look out for
Rubric
Published

27 November 2025

An assessment rubric provides a framework for thinking about whether an assignment is on the right track with respect to key criteria. As for assignment 1, the rubric presented in table 1 contains three levels: unsatisfactory, satisfactory and outstanding.

More information on how to interpret and apply the rubric will be provided in class on 27 November 2025.

Table 1: Assignment 2 rubric
Criteria Unsatisfactory Satisfactory Outstanding
1. Data Analysis and Modelling Data are incomplete, incorrect, or not used appropriately; demand curve not attempted or misinterpreted. Correctly estimates a demand curve with basic interpretation of the results (eg. elasticity) Analysis is thorough, accurate, and demonstrates clear understanding of modelling choices and their implications.
2. Interpretation of Market Concepts Demonstrates limited or incorrect understanding of demand, market-clearing price, or economic rents. Accurately explains and applies key concepts (demand, equilibrium, rents) to the data. Shows deep conceptual insight, connecting theory to data effectively and discussing implications clearly.
3. Evaluation of Allocation Methods Fails to address allocation methods or discusses them superficially without clear reasoning. Compares allocation methods (first-come-first-served, lottery, market-clearing) for fairness and efficiency. Provides a nuanced evaluation of the stated — and other — allocation methods, showing critical reflection on fairness, efficiency, and policy relevance.
4. Policy Recommendation and Reflection No clear recommendation or rationale; ignores the data and/or findings. Provides a reasoned recommendation for ticketing policy consistent with analysis. Recommendation is well-argued, creative, and integrates quantitative results with thoughtful reasoning.
5. Structure, Clarity, and Referencing1 Poorly structured, unclear writing; references missing or incorrect; use of AI not disclosed. Clear, logical structure; correct referencing; AI use disclosed if relevant. Exceptionally clear and well-organised writing; references integrated smoothly; strong academic tone.

See also

The price of a ticket

Data analysis

Report writing

Tips and tricks for drafting

No matching items

Footnotes

  1. As assignment 2 is based on fictional data, and draws only on theory/concepts from the course, references are not necessarily expected in this case. However, to the extent you draw on ideas from sources beyond what is presented in the course (for example, on alternative allocation strategies), it would be appropriate to cite these.↩︎

NF SDU

Nick Ford
University of Southern Denmark
Department of Economics

© 2025 Nick Ford. All rights reserved.