Course overview
- Study period
- Semester 2, 2024 (22/07/2024 - 18/11/2024)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Economics School
The purpose of the course is to offer advanced students in Economics, Commerce and Business an understanding of the econometric tools that apply to microeconomic data. The approach is from an applied perspective. Lectures will introduce specific cross-sectional and panel models and the techniques required to estimate/predict with the model. The course will make use of the econometric package, Stata, for purposes of analysing of the data. Core content includes the analysis of individual-level data on the economic behaviour of individuals or firms using regression methods for cross section and panel data. Skills and Perspective provided by applications in the area of labour economics, consumer choice, health and education.
Assumed Background: Students are expected to have an intermediate knowledge (second year undergraduate at least) of economic theory and econometrics or statistics and mathematics (see prerequisites).
The course covers concepts and methods that are widely employed in contemporary applied microeconomics. It will be centred around the estimation of causal or treatment effects using regression-based analysis. Empirical examples will be drawn from recent research in labour, development, education, and health.
Course requirements
Assumed background
Students are expected to have an intermediate knowledge (second year undergraduate at least) of economic theory and econometrics or statistics and mathematics (see prerequisites).
Prerequisites
You'll need to complete the following courses before enrolling in this one:
ECON2300 + (ECON2010 or ECON2011)
Incompatible
You can't enrol in this course if you've already completed the following:
ECON3300
Course contact
School enquiries
All enquiries regarding student and academic administration (i.e. non-course content information, e.g., class allocation, timetables, extension to assessment due date, etc.) should be directed to enquiries@economics.uq.edu.au.
Enquiries relating specifically to course content should be directed to the Course Coordinator/Lecturer.
Course staff
Lecturer
Tutor
Timetable
The timetable for this course is available on the UQ Public Timetable.
Additional timetable information
Tutorials commence in week 1. Students are required to log their preferences for a tutorial group through My Timetable and attend their allocated timeslot. It is essential that you attend the tutorial class you have signed to, as classes are held in computer labs where numbers are strictly limited in each group. If your tutorial is scheduled on a public holiday, you may attend another tutorial in that week.
Students should refer to the timetable prior to the commencement of classes to ensure that they have the most up-to-date information, as from time to time late room changes may occur.
Public Holidays: Wed 14 August (Royal Queensland Show), Mon 7 October (King's Birthday).
In-Semester Break: 23 - 29 September. Semester 2 classes recommence Mon 30 September.
Aims and outcomes
This course aims to (i) provide students with an advanced understanding of microeconometric models and estimation methods; (ii) enable students to program and analyse econometric models using the software Stata; and (iii) allow students to read and understand advanced econometric work in academic journals.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Connect foundational economic knowledge acquired in microeconomics and econometrics to real-world issues.
LO2.
Explain the difference between causality and correlations, and choose the appropriate econometric method in different contexts.
LO3.
Apply econometric methods to real-world data using appropriate statistical software, report and critically interpret empirical results.
LO4.
Summarize empirical academic papers published in economic journals and develop your own research ideas.
Assessment
Assessment summary
Category | Assessment task | Weight | Due date |
---|---|---|---|
Quiz | 2 online quizzes | 30% (15% each) |
30/08/2024 2:00 pm 20/09/2024 2:00 pm
- The first quiz will be open (online) in week 6 from 14:00 on the Thursday to 14:00 on the Friday. - The second quiz will be open (online) in week 9 from 14:00 on the Thursday to 14:00 on the Friday. |
Paper/ Report/ Annotation | Article review and research idea | 35% |
4/10/2024 2:00 pm |
Computer Code, Tutorial/ Problem Set | Problem set in Stata | 35% |
25/10/2024 2:00 pm |
Assessment details
2 online quizzes
- Mode
- Written
- Category
- Quiz
- Weight
- 30% (15% each)
- Due date
30/08/2024 2:00 pm
20/09/2024 2:00 pm
- The first quiz will be open (online) in week 6 from 14:00 on the Thursday to 14:00 on the Friday.
- The second quiz will be open (online) in week 9 from 14:00 on the Thursday to 14:00 on the Friday.
- Learning outcomes
- L01, L02, L03
Task description
The 60-minute, online, open-book quizzes will contain MCQs and scenarios (sequential series of MCQs). Incorrect answers will not be subject to penalties.
The first will focus on all the material taught up to lecture 4 and tutorial 6. The second will focus on all the material taught up to lecture 7 and tutorial 9.
This assessment task evaluates students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Quizzes will be submitted via BB.
Deferral or extension
You may be able to apply for an extension.
The online quizzes have a maximum extension of 3 days (excluding weekend days) to ensure timely feedback to other students.
Requests for the granting of extensions must be submitted through my.UQ: Applying for an extension - my.UQ - University of Queensland with supporting documentation before the submission due date and time. If an extension is approved, the new agreed date for submission will be noted on the application and the student notified through their student email. Extensions cannot exceed the number of days you suffered from a medical condition, as stated on the medical certificate.
Late submission
Where an extension has not been previously approved, the below penalties apply to late or non-submission of a quiz:
- Less than 5 minutes late: 5%
- From 5 minutes to less than 15 minutes late: 20%
- More than 15 minutes late: 100%
If students experience interruptions to their quiz and need to apply for an extension, they must collect and provide suitable evidence that the late submission was beyond their control. Such evidence may include: screenshots, photos, or emails from AskUs.
Article review and research idea
- Mode
- Written
- Category
- Paper/ Report/ Annotation
- Weight
- 35%
- Due date
4/10/2024 2:00 pm
- Learning outcomes
- L01, L02, L03, L04
Task description
- We expect students to produce a 2-page summary of an academic paper. Students will select a paper that fits with their research interests among a list of very well-established/published papers. The summary should follow a standard structure outlining the research question; the data; the empirical strategy...
- The 1-page research proposal should follow the same structure and present a research idea that you would like to implement in the future (i.e based on a research question that you find exciting). It should clearly explain the potential issues with estimating the parameter of interest and the econometric method proposed to overcome these difficulties (in words and using regression notations). You have to use a method that was covered in this course. Students should describe potential datasets but are not expected to produce the empirical analysis.
- Further instructions will be provided at least one week before the deadline.
- Please do not email the lecturer with questions about this assessment because all students should have the same information regarding the assessment.
- Please do not email the lecturer asking questions about a research idea, because it has to be your idea!
- You will need to demonstrate that: you understand the difference between correlations and causality when summarising an academic paper and when proposing your own research ideas. Particular attention will be given to the accurate description of econometric methods and results.
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI tools.
Submission guidelines
The assignment must be submitted via BB by the due date and time.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.
Limitations to the duration of the extension apply to ensure all grades can be finalised.
Requests for the granting of extensions must be submitted through my.UQ: Applying for an extension - my.UQ - University of Queensland with supporting documentation before the submission due date and time. If an extension is approved, the new agreed date for submission will be noted on the application and the student notified through their student email. Extensions cannot exceed the number of days you suffered from a medical condition, as stated on the medical certificate.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Penalties will be applied unless an extension has been granted.
Problem set in Stata
- Mode
- Written
- Category
- Computer Code, Tutorial/ Problem Set
- Weight
- 35%
- Due date
25/10/2024 2:00 pm
- Learning outcomes
- L01, L02, L03
Task description
- The problem set consists of questions that require short answers and some calculations in STATA.
- Further details about the problem set will be provided in class and posted to our course BB site.
- The problem set will be given at least a week in advance of the due date.
- Please do not email the lecturer asking questions about the problem set because all students should have the same information regarding these problem sets.
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI tools.
Submission guidelines
Submit via Blackboard by the due date and time.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 14 days. Extensions are given in multiples of 24 hours.
Limitations to the duration of the extension apply to ensure all grades can be finalised.
Requests for the granting of extensions must be submitted through my.UQ: Applying for an extension - my.UQ - University of Queensland with supporting documentation before the submission due date and time. If an extension is approved, the new agreed date for submission will be noted on the application and the student notified through their student email. Extensions cannot exceed the number of days you suffered from a medical condition, as stated on the medical certificate.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Penalties will be applied unless an extension has been granted.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
Grade | Cut off Percent | Description |
---|---|---|
1 (Low Fail) | 0% - 29% |
Absence of evidence of achievement of course learning outcomes. |
2 (Fail) | 30% - 46% |
Minimal evidence of achievement of course learning outcomes. |
3 (Marginal Fail) | 47% - 49% |
Demonstrated evidence of developing achievement of course learning outcomes |
4 (Pass) | 50% - 64% |
Demonstrated evidence of functional achievement of course learning outcomes. |
5 (Credit) | 65% - 74% |
Demonstrated evidence of proficient achievement of course learning outcomes. |
6 (Distinction) | 75% - 84% |
Demonstrated evidence of advanced achievement of course learning outcomes. |
7 (High Distinction) | 85% - 100% |
Demonstrated evidence of exceptional achievement of course learning outcomes. |
Additional course grading information
A student’s final overall end of semester percentage mark will be rounded to determine their final grade. For example, 64.5% rounds to 65%, while 64.4% rounds to 64%.
Supplementary assessment
Supplementary assessment is available for this course.
Additional assessment information
Plagiarism
The School of Economics is committed to reducing the incidence of plagiarism. Further information on plagiarism and how to avoid an allegation of plagiarism is available in this course profile under Policies & Guidelines. Please refer to the Academic Integrity Module (AIM). It is strongly recommended that you complete the AIMᅠif you have not already done so.
Referencing and Citing
APA is the required referencing style in this course.
Assignments must be substantially your own work. If you wish to report another author’s point of view you should do so in your own words, and properly cite the reference in accordance with the school style. Direct quotations should be used sparingly, form a small part of your work, and must be placed in quotation marks and duly referenced.
Any material taken from texts and other references, including electronic resources, CD‐ROMS, and the Internet, must be acknowledged using the accepted School style.
Students are encouraged to discuss issues that arise in this course together. However, the written work you submit must be entirely your own. Similarly, you must not help another student to cheat by lending assignments (present or past).
For more information on referencing styles, visit the library.
If you do not reference the materials used in your assignment correctly, you could be found guilty of academic misconduct.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Find the required and recommended resources for this course on the UQ Library website.
Own copy required
You'll need to have your own copy of the following reading resources. We've indicated below if you need a personal copy of the reading materials or your own item.
Item | Description |
---|---|
Book |
Introductory econometrics: a modern approach
by Wooldridge; Jeffrey M. - 2020 Edition: 7th Publisher: Cengage ISBN: 9781337558860; 9781337671330; 9789355731074 |
Book |
Mostly harmless econometrics: an empiricist's companion
by Angrist; Joshua David; Pischke; Jörn-Steffen - 2009 Publisher: Princeton University Press ISBN: 9781400829828; 9781282608092; 9780691120348; 9780691120355 |
Additional learning resources information
Learning resources (Angrist Pischke (2009) and Wooldridge (2020)) are available free of charge from the library at: ECON3360 St Lucia | University of Queensland (talis.com).
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
Learning period | Activity type | Topic |
---|---|---|
Week 1 (22 Jul - 28 Jul) |
Lecture |
Lecture 1: Review linear regressions Readings/Ref: Angrist Pischke, 2009 (chapter 3); Wooldridge, 2020 (chapters 1-4) Learning outcomes: L01, L02 |
Tutorial |
Tutorial 1: Introduction to STATA Learning outcomes: L02, L03 |
|
Week 2 (29 Jul - 04 Aug) |
Lecture |
Lecture 2: Randomised controlled trials (RCT) Readings/Ref: Angrist Pischke, 2009 (chapter 2); Wooldridge, 2020 (sections 3.2-3.4; 6.2; 8.1-8.2) Learning outcomes: L01, L02, L03, L04 |
Tutorial |
Tutorial 2: Stata application of linear models First class in Stata. Running regressions and interpreting outputs from Stata. Learning outcomes: L02, L03 |
|
Week 3 (05 Aug - 11 Aug) |
Lecture |
Lecture 3: Instrumental variables Readings/Ref: Angrist Pischke, 2009 (chapter 4); Wooldridge, 2020 (chapter 15) Learning outcomes: L01, L02, L03, L04 |
Tutorial |
Tutorial 3: Stata applications of RCTs Learning outcomes: L02, L03 |
|
Week 4 (12 Aug - 18 Aug) |
Lecture |
Lecture 4: Simultaneous equations model Readings/Ref: Wooldridge, 2020 (chapter 16) Learning outcomes: L01, L02, L03, L04 |
Tutorial |
Tutorial 4: Stata applications of IV Please note that Wed 14 August is a public holiday, there will be no tutorial on this day. If you attend tutorial on this day, please attend another session for this week only. Learning outcomes: L02, L03 |
|
Week 5 (19 Aug - 25 Aug) |
Lecture |
Lecture 5: Regression discontinuity design (RD) Readings/Ref: Angrist Pischke, 2009 (chapter 6) Learning outcomes: L01, L02, L03, L04 |
Tutorial |
Tutorial 5: Stata applications of IV Learning outcomes: L02, L03 |
|
Week 6 (26 Aug - 01 Sep) |
Lecture |
Lecture 6: Difference-in-differences Readings/Ref: Angrist Pischke, 2009 (chapter 5); Wooldridge, 2020 (chapter 13) Learning outcomes: L01, L02, L03, L04 |
Tutorial |
Tutorial 6: Stata applications of simultaneous equations model Learning outcomes: L02, L03 |
|
Week 7 (02 Sep - 08 Sep) |
Lecture |
Lecture 7: Advanced panel data methods Readings/Ref: Angrist Pischke, 2009 (chapter 5); Wooldridge, 2020 (chapter 14) Learning outcomes: L01, L02, L03, L04 |
Tutorial |
Tutorial 7: Stata applications of sharp RD Learning outcomes: L02, L03 |
|
Week 8 (09 Sep - 15 Sep) |
Lecture |
Lecture 8: Research paper Readings/Ref: Angrist Pischke, 2009 (chapter 1); Wooldridge, 2020 (chapter 19) Learning outcomes: L02, L04 |
Tutorial |
Tutorial 8: Stata applications of fuzzy RD Learning outcomes: L02, L03 |
|
Week 9 (16 Sep - 22 Sep) |
Lecture |
Lecture 9: Limited dependent variable models Readings/Ref: Wooldridge, 2020 (chapter 7 & 17) Learning outcomes: L01, L02, L03, L04 |
Tutorial |
Tutorial 9: Stata applications of difference-in-differences Learning outcomes: L02, L03 |
|
Mid Sem break (23 Sep - 29 Sep) |
No student involvement (Breaks, information) |
Mid-Semester break No lecture or tutorials during the break. |
Week 10 (30 Sep - 06 Oct) |
Lecture |
Lecture 10: Interactive Q&A This will be an opportunity for students to ask questions about assessment 2 (article review and research idea) Learning outcomes: L01, L02, L04 |
Tutorial |
Tutorial 10: Stata applications of panel data methods Learning outcomes: L02, L03 |
|
Week 11 (07 Oct - 13 Oct) |
Lecture |
Lecture 11: Propensity score matching (PSM) Learning outcomes: L01, L02, L03, L04 |
Tutorial |
Tutorial 11: Stata applications of LDV models Learning outcomes: L02, L03 |
|
Week 12 (14 Oct - 20 Oct) |
Lecture |
Lecture 12: Quantile regression Readings/Ref: Angrist Pischke, 2009 (chapter 7) Learning outcomes: L01, L02, L03, L04 |
Tutorial |
Tutorial 12: Stata applications of PSM Learning outcomes: L02, L03 |
|
Week 13 (21 Oct - 27 Oct) |
Lecture |
Lecture 13: Revision lecture Learning outcomes: L01, L02, L03, L04 |
Tutorial |
Tutorial 13: Stata applications of QR Learning outcomes: L02, L03 |
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments - Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.