Outline

Overview

This unit of study builds on knowledge acquired in previous studies in order to apply economic principles to real-world problems. Lectures cover the nature of economic research, theoretical concepts, and methods of applied economic analysis. Students will develop skills to interpret and communicate economic analysis to an interdisciplinary audience.

Unit details and rules

Academic unit	Economics
Credit points	6
Prerequisites ?	12 credit points at 2000 level from one of the following subject areas: Econometrics or Economic Policy Analysis or Economics or Environmental, Agricultural and Resource Economics or Financial Economics
Corequisites ?	None
Prohibitions ?	ECOS3991 or ECOS3992 or ECOS3993 or ECOS3997
Assumed knowledge ?	None
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Stefanie Schurer, stefanie.schurer@sydney.edu.au

Assessment

The census date for this unit availability is 31 August 2026

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Research analysis	Final Report Write a final report that will be submitted online.	60%	Week 11 Due date: 23 Oct 2026 at 23:59 Closing date: 06 Nov 2026	3,000 words	AI allowed
Outcomes assessed:
Written work	Media Report Educate a non-specialist audience with a accessible analysis and language. Guidance: Write as if submitted to The Conversation. Submitted online.	40%	Week 13 Due date: 06 Nov 2026 at 23:59 Closing date: 20 Nov 2026	1,500 words	AI allowed
Outcomes assessed:

Assessment summary

Detailed information for each assessment can be found on Canvas.

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.

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.

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 a good 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.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

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.

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	Rich by Design: Using Economics and Evidence to Build a Flourishing Life: Content	Lecture (2 hr)
Week 02	Rich by Design: Using Economics and Evidence to Build a Flourishing Life: Content	Lecture (2 hr)
Week 02	Tutorial 1	Tutorial (1 hr)
Week 03	Rich by Design: Using Economics and Evidence to Build a Flourishing Life: Content	Lecture (2 hr)
Week 03	Tutorial 2	Tutorial (1 hr)
Week 04	Rich by Design: Using Economics and Evidence to Build a Flourishing Life: Content	Lecture (2 hr)
Week 04	Tutorial 3	Tutorial (1 hr)
Week 05	Rich by Design: Using Economics and Evidence to Build a Flourishing Life: Content	Lecture (2 hr)
Week 05	Tutorial 4	Tutorial (1 hr)
Week 06	Rich by Design: Using Economics and Evidence to Build a Flourishing Life: Content	Lecture (2 hr)
Week 06	Tutorial 5	Tutorial (1 hr)
Week 07	Rich by Design: Using Economics and Evidence to Build a Flourishing Life: Content	Lecture (2 hr)
Week 07	Tutorial 6	Tutorial (1 hr)
Week 08	Rich by Design: Using Economics and Evidence to Build a Flourishing Life: Content	Lecture (2 hr)
Week 08	Tutorial 7	Tutorial (1 hr)
Week 09	Rich by Design: Using Economics and Evidence to Build a Flourishing Life: Content	Lecture (2 hr)
Week 09	Tutorial 8	Tutorial (1 hr)
Week 10	Rich by Design: Using Economics and Evidence to Build a Flourishing Life: Content	Lecture (2 hr)
Week 10	Tutorial 9	Tutorial (1 hr)
Week 11	Rich by Design: Using Economics and Evidence to Build a Flourishing Life: Review	Lecture (2 hr)
Week 11	Tutorial 10	Tutorial (1 hr)
Week 12	Tutorial 11	Tutorial (1 hr)

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

Vaillant, G. E. (2012). Triumphs of Experience: The Men of the Harvard Study of Adult Development. Harvard University Press.
Kahneman, D., & Deaton, A. (2010). High Income Improves Evaluation of Life but Not Emotional Well-Being. Proceedings of the National Academy of Sciences, 107(38), 16489–16493.
Diener, E., & Seligman, M. E. P. (2002). Very Happy People. Psychological Science, 13(1), 81–84.
Browning, Martin, and Thomas F. Crossley. 2001. "The Life-Cycle Model of Consumption and Saving." Journal of Economic Perspectives 15 (3): 3–22.
Ben-Porath, Yoram (1967). The Production of Human Capital and the Life Cycle of Earnings, The Journal of Political Economy, Vol. 75, No. 4, Part 1 (Aug., 1967), pp. 352-365.
O'Donoghue, T., & Rabin, M. (1999). Doing It Now or Later. American Economic Review, 89(1), 103–124.
Grossman, M. (2000). The Human Capital Model. In A. J. Culyer & J. P. Newhouse (Eds.), Handbook of Health Economics (Vol. 1A, pp. 347–408). Elsevier.
Becker, G. S., & Lewis, H. G. (1973). On the Interaction between the Quantity and Quality of Children. Journal of Political Economy, 81(2), S279–S288.
Heckman, J. J. (2006). Skill Formation and the Economics of Investing in Disadvantaged Children. Science, 312(5782), 1900–1902.
Waite, L. J. (1995). Does Marriage Matter? Demography, 32(4), 483–507.

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. Explain how investment and compounding operate across multiple domains of life.
LO2. Apply lifecycle economic models to personal decision-making in health, relationships, skills and financial assets.
LO3. Analyse the effects of discounting, myopia, time inconsistency, and peer pressures.
LO4. Evaluate trade-offs between present and future consumption and individual and collective gains.
LO5. Design commitment mechanisms that improve long-term outcomes.
LO6. Construct a personal "rich and fulfilled life" investment strategy grounded in economic principles.
LO7. Read and critically interpret data, statistics, and empirical evidence relevant to personal economic decisions.

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 is a newly designed course and I will be teaching this unit for the very first time. Its contents are as follows: Title: Rich by Design: Using Economics and Evidence to Build a Flourishing Life Description: This unit applies economic principles of investment, intertemporal choice, and human capital development to everyday life. Students learn how economic reasoning can be used to make wise decisions about health, education, finances, relationships, and personal development. A recurring emphasis on data literacy — reading graphs, interpreting statistics, and evaluating empirical claims — equips students to assess evidence about their own lives rather than rely on intuition alone. Using lifecycle models and evidence from neoclassical and behavioural economics, students develop and practice a framework for evaluating investments that create long-term wellbeing and flourishing.

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

Assessment summary

Assessment summary

Use of generative artificial intelligence (AI)

Academic integrity

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

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

ECOS3994: Interdisciplinary Impact in Economics D

Semester 2, 2026 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment summary

Use of generative artificial intelligence (AI)

Academic integrity

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

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