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Unit outline_

ECON7030: Economics Research Project

Semester 2, 2024 [Normal day] - Camperdown/Darlington, Sydney

This unit represents a culminating academic experience for students in the Master of Economics by bringing together their knowledge in economic theory and methodology to analyse an economic problem. The unit involves writing a 6,000-word report. The emphasis is on students acquiring skills in identifying an economic problem, undertaking the required analysis using appropriate tools, and disseminating the results.

Unit details and rules

Academic unit Economics
Credit points 6
Prerequisites
? 
24 credit points from Economics elective units of study
Corequisites
? 
None
Prohibitions
? 
ECON7010 or ECON7020
Assumed knowledge
? 

None

Available to study abroad and exchange students

No

Teaching staff

Coordinator Chandana Maitra, chandana.maitra@sydney.edu.au
The census date for this unit availability is 2 September 2024
Type Description Weight Due Length
Attendance Seminar attendance & write-up on research insights
Attend a School seminar in one of the 13 weeks; submit discussion post
3% Ongoing 1.5 hr attendance; 200 words write-up
Outcomes assessed: LO1 LO6 LO5 LO4 LO3 LO2
Small test Article review
Review a scholarly article (in class), applying the learning from Lec 1-4
7% Week 05
Due date: 27 Aug 2024 at 18:00

Closing date: 27 Aug 2024
600 words
Outcomes assessed: LO1 LO6 LO5 LO4 LO3 LO2
Assignment Literature review & research proposal
Review literature & write a research proposal (topic prescribed by UC)
20% Week 06
Due date: 07 Sep 2024 at 23:59

Closing date: 07 Sep 2024
1000 words
Outcomes assessed: LO6 LO1 LO2 LO3 LO4 LO5
Assignment Data extraction and descriptive research
Extract data from the recommended sources and conduct descriptive analysis
20% Week 08
Due date: 21 Sep 2024 at 23:59

Closing date: 21 Sep 2024
1000 words
Outcomes assessed: LO6 LO1 LO2 LO3 LO4 LO5
Presentation In-class presentation
In-class presentation of final research report
10% Week 11
Due date: 15 Oct 2024 at 18:00

Closing date: 15 Oct 2024
5 minutes/700 words (slides)
Outcomes assessed: LO1 LO6 LO5 LO4 LO3 LO2
Assignment Final research report
Complete report: RQ, literature, model, results, discussion, conclusion
40% Week 13
Due date: 02 Nov 2024 at 23:59

Closing date: 02 Nov 2024
2500 words
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6

Assessment summary

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

Outstanding

Distinction

75 - 84

Superior 

Credit

65 - 74

Sound

Pass

50 - 64

Satisfactory

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.

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 Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

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 2023 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 2023. 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

WK Topic Learning activity Learning outcomes
Week 01 Introduction to the Unit. Let's talk about research & replication. Lecture (3 hr) LO1 LO2 LO3 LO4 LO5
Week 02 Recap: Statistical analysis using real-world data: Part 1 Lecture (3 hr) LO1 LO2 LO3 LO4 LO5
Week 03 Recap: Statistical analysis using real-world data: Part 2 Lecture (3 hr) LO1 LO2 LO3 LO4 LO5
Week 04 Recap: Statistical analysis using real-world data: Part 3 Lecture (3 hr) LO1 LO2 LO3 LO4 LO5
Week 05 In-class assignment + getting started with data analysis Lecture (3 hr) LO1 LO2 LO3 LO4 LO5
Week 06 Download and clean the data (handle missing observations, detect and smooth noise, identify and address inconsistencies). Workshop (3 hr) LO3 LO4
Week 07 Review distribution of key variables, take decisions on data transformation, and generate summary statistics. Workshop (3 hr) LO1 LO3 LO4
Week 08 Visualize the data. Find the story in your data. Create relevant tables & figures. Interpret the results. Workshop (3 hr) LO3 LO4 LO5
Week 09 Start building your empirical model. Workshop (3 hr) LO3 LO4 LO5
Week 10 Continue with statistical estimation. Get preliminary results from your proposed model, identify where you might have gone wrong and reflect on how you should revise your model. Workshop (3 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 11 Present your research in class and get feedback from your peers and instructors before you submit the final research report in Week 13. Presentation (3 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 12 Conduct robustness checks for statistical models. Finalize your results. Accurately interpret findings. What do your results tell us about the economic issue(s) that you have chosen to study? Workshop (3 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 13 Integrate the pieces into the final report. Polish up the codes and prepare links to your data sets - to be used by your assessors to replicate your results. Time to think about policy implications & limitations of your research, and to offer directions for future research. Workshop (3 hr) LO1 LO2 LO3 LO4 LO5 LO6

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: Most lectures (in recording-equipped venues) will be recorded and may be made available to students on the LMS. However, you should not rely on lecture recording to substitute your classroom learning experience.

  • Preparation: Students should commit to spend approximately three hours’ preparation time (reading, studying, homework, essays, 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

All readings for this unit will be available on Canvas.

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.

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

  • LO1. Identify a well-defined research question and, where appropriate, formulate testable hypotheses.
  • LO2. Synthesise the relevant literature and identify an area of potential contribution.
  • LO3. Apply economic analysis to address a specific research question.
  • LO4. Use appropriate empirical or theoretical tools to provide insight into the economic issue(s) under study and discuss the advantages of the chosen approach relative to other methods.
  • LO5. Communicate the result of the economic analysis to both specialist and non-specialist audiences in both written and verbal form.
  • LO6. Develop ability to self-reflect. Identify areas of strength and weakness in your skill set and knowledge.

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
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

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

Updated schedule and assessments based on student feedback to include additional scaffolding that break down the summative assessment into more manageable sub-tasks.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

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