Outline

Overview

From online dating to criminal behaviour, economics is increasingly being used to analyse non-market issues. This unit provides insights on these issues using an economic perspective. An underlying premise of this analysis is that people respond to incentives created by rules and institutions, sometimes in perverse or unintended ways. This unit studies real-world cases, including food and obesity, crime and punishment, sports, discrimination, and the role of government in correcting market failures. The unit also considers the implications for traditional economic analysis if information is imperfect and people are not fully rational.

Unit details and rules

Academic unit	Economics
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Ranae Jabri, ranae.jabri@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2026

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Written exam	Final exam Multiple-choice, short-answer, and extended-response questions	50%	Formal exam period	2 hours	AI prohibited
Outcomes assessed:
Out-of-class quiz	Online Quiz - EFT Early Feedback Task	0%	Week 03 Due date: 13 Mar 2026 at 23:59 Closing date: 14 Mar 2026	Canvas Quiz	AI allowed
Outcomes assessed:
Written test	In-semester test Paper-based test: short-answer and multiple-choice questions	30%	Week 07 Due date: 16 Apr 2026 at 13:30	1 hour	AI prohibited
Outcomes assessed:
Written work	Team agreement Team agreement and project proposal	5%	Week 09 Due date: 01 May 2026 at 23:59	Canvas	AI allowed
Outcomes assessed:
Presentation	Group presentation 10-minute video group presentation	15%	Week 13 Due date: 25 May 2026 at 23:59 Closing date: 26 May 2026	10-minute video	AI allowed
Outcomes assessed:
= group assignment ? = early feedback task ?

Early feedback task

This unit includes an early feedback task, designed to give you feedback prior to the census date for this unit. Details are provided in the Canvas site and your result will be recorded in your Marks page. It is important that you actively engage with this task so that the University can support you to be successful in this unit.

Assessment summary

Group video presentation: Students will be asked to form groups of 4-6 to work together on this assessment. Specific details of the assessment task will be provided later in the semester.
In-semester test: Consists of multiple-choice and short-response questions.
Final exam: Consists of multiple-choice, short-response, and extended-response questions.
Early feedback task: Online multiple-choice quiz given in Week 3 to provide early feedback to students.
Practice Quizzes: Two online multiple-choice quizzes will be given in Weeks 7 and 12 to help students prepare for the exams. These optional quizzes will cover material on the required readings and slides for the previous topics. The quizzes will be posted on Canvas and will remain open until the final exam.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy (Schedule 1).

As a general guide, a High Distinction indicates work of an exceptional standard, a Distinction a very high standard, a Credit a good standard, and a Pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100	To be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at an exceptional standard as defined by grade descriptors or exemplars established by the faculty.
Distinction	75 - 84	To be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at a very high standard as defined by grade descriptors or exemplars established by the faculty.
Credit	65 - 74	To be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at a good standard as defined by grade descriptors or exemplars established by the faculty.
Pass	50 - 64	To be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at an acceptable standard as defined by grade descriptors or exemplars established by the faculty.
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Week 01	Introduction: Thought process of an economist	Lecture (2 hr)
Week 01	Introduction: Thought process of an economist	Tutorial (1 hr)
Week 02	Economics of Sports	Lecture (2 hr)
Week 02	Economics of Sports	Tutorial (1 hr)
Week 03	Economics of Discrimination	Lecture (2 hr)
Week 03	Economics of Discrimination	Tutorial (1 hr)
Week 04	Economics of Food	Lecture (2 hr)
Week 04	Economics of Food	Tutorial (1 hr)
Week 05	Economics of Love	Lecture (2 hr)
Week 05	Economics of Love	Tutorial (1 hr)
Week 06	Economics of Altruism	Lecture (2 hr)
Week 06	Economics of Altruism	Tutorial (1 hr)
Week 07	In-semester test	Lecture (1 hr)
Week 08	Economics of Crime	Lecture (2 hr)
Week 08	Economics of Crime	Tutorial (1 hr)
Week 09	Economics of Environment	Lecture (2 hr)
Week 09	Economics of Environment	Tutorial (1 hr)
Week 10	Economics of Ethics	Lecture (2 hr)
Week 10	Economics of Ethics	Tutorial (1 hr)
Week 11	Economics of Healthcare	Lecture (2 hr)
Week 11	Economics of Healthcare	Tutorial (1 hr)
Week 12	Economics of Gambling	Lecture (2 hr)
Week 12	Economics of Gambling	Tutorial (1 hr)
Week 13	Group presentations	Lecture (2 hr)
Week 13	Group presentations	Tutorial (1 hr)

Attendance and class requirements

Attendance: According to Faculty Board Resolutions, students in the Faculty of Arts and Social Sciences are expected to attend 90% of their classes. If you attend less than 50% of classes, regardless of the reasons, you may be referred to the Examiner’s Board. The Examiner’s Board will decide whether you should pass or fail the unit of study if your attendance falls below this threshold.
Lecture recording: All lectures will be recorded and made available to students on Canvas.
Preparation: Students should commit to spend approximately three hours’ preparation time (reading, studying, assignments, etc.) for every hour of scheduled instruction.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

Refer to the Canvas site and the Reading List for all the required readings in each topic.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. think like an economist
LO2. apply the economic way of thinking to all aspects of the world they live in
LO3. understand the consequences and implications of public policy discussions and debates
LO4. work productively, collaboratively, and openly in diverse groups and across cultural boundaries.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

This unit has been updated since it was last offered in response to staff and student reviews. In particular, students will in their groups complete a team agreement and project proposal assignment to incrementally prepare for the group video assignment.

Disclaimer

Important: the University of Sydney regularly reviews units of study and reserves the right to change the units of study available annually. To stay up to date on available study options, including unit of study details and availability, refer to the relevant handbook.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Early feedback task

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

ECON1006: The Economics of Everything

Semester 1, 2026 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Early feedback task

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links