The course covers advanced estimation methods in econometrics. Specific topics include: projections and ordinary least squares estimation; endogeneity; instrumental variables and two stage least squares estimation; maximum likelihood estimation of models with limited dependent variables. The course is primarily theoretical and looks at various estimators and their finite sample and asymptotic properties.

 

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

1. define OLS, IV and maximum likelihood estimators mathematically;
2. derive and examine finite sample and asymptotic properties of these estimators analytically;
3. demonstrate an understanding of the strengths and limitations of the different estimators;
4. employ linear algebra in key econometric derivations;
5. apply econometric theory to concrete examples in economics.

Research-Led Teaching

This course teaches the advanced methods at the cutting edge of econometric research.

Examination Material or equipment

No materials permitted for midterm or final exam.

Required Resources

The main textbook for the course is Econometrics by Bruce Hansen (available as a free pdf online, find it!).

Recommended Resources

In addition to the freely available book by Hansen, you may want to consult these awesome books:

• A Primer in Econometric Theory by John Stachurski.
• Econometric Analysis by William H. Greene
• Econometric Analysis of Cross Section and Panel Data by Jeffrey Wooldridge

Staff Feedback

Students will be given feedback in the following forms in this course:

• written comments on weekly problem sets
• verbal comments during lectures and workshops
• verbal comments during consultations

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.

Other Information

Course website

All relevant course material (lecture slides, assignments, etc.) will be available under https://juergenmeinecke.github.io/EMET8014/

Assumed knowledge

This is a PhD level course. I expect you to be familiar and comfortable with the following topics:

• set theory, functions
• sequences, series, limits
• univariate and multivariate calculus (incl derivatives and integrals)
• linear algebra

YOU SHOULD NOT TAKE THIS COURSE IF YOU DO NOT FEEL COMFORTABLE WITH ANY OF THESE TOPICS!

Class Schedule

Week/Session	Summary of Activities	Assessment
1	Projections
2	Ordinary Least Squares Estimation	Problem Set 1 due
3	Ordinary Least Squares Estimation	Problem Set 2 due
4	Ordinary Least Squares Estimation	Problem Set 3 due
5	Instrumental Variables Estimation	Problem Set 4 due
6	Mid-semester examination	Mid-semester examination(no problem set due)
7	Instrumental Variables Estimation	Problem Set 5 dueComputer Assignment 1 due
8	Instrumental Variables Estimation	Problem Set 6 due
9	Instrumental Variables Estimation	Problem Set 7 due
10	Instrumental Variables Estimation	Problem Set 8 due
11	Maximum Likelihood Estimation	Problem Set 9 dueComputer Assignment 2 due
12	Limited Dependent Variable Models	Problem Set 10 due

Tutorial Registration

It is not necessary to enroll for tutorials.

Assessment Summary

Assessment task	Value	Due Date	Return of assessment	Learning Outcomes
Problem Sets	10 %	*	*	1,2,3,4,5
Computer Assignment	20 %	*	*	1,2,3,4,5
Midterm exam	20 %	30/03/2026	24/04/2026	1,2,3,4,5
Final Examination	50 %	04/06/2026	02/07/2026	1,2,3,4,5

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details

Policies

ANU has educational policies, procedures and guidelines , which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Integrity Rule before the commencement of their course. Other key policies and guidelines include:

• Academic Integrity Policy and Procedure
• Student Assessment (Coursework) Policy and Procedure
• Extenuating Circumstances Application
• Student Surveys and Evaluations
• Deferred Examinations
• Student Complaint Resolution Policy and Procedure
• Code of practice for teaching and learning

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the Academic Skills website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Canvas’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.

Participation

Weekly course activities are structured as follows:

• two hours of lectures (recorded on Echo360)
• a workshop focused on the weekly problem sets (discussion-based, not recorded)
• computer labs based on the weekly Jupyter notebooks (discussion-based, not recorded)
• all activities are delivered face to face on campus

Workshops and computer labs are discussion-based and rely on active participation. For this reason, I will not provide worked solutions to the weekly problem sets or the computer lab activities. If, due to unavoidable and unplanned circumstances, you are unable to attend a session, you should still work through the relevant problems and then attend a consultation for discussion and guidance.

Attendance at all activities is not compulsory, but it is expected given the demanding nature of the course (consistent with the Code of Practice for Teaching and Learning, clause 2 paragraph (b)). If you are not able to attend classes regularly, you should carefully consider whether this course is the right fit for you.

Examination(s)

See information above, under assessments.

Assessment Task 1

Problem Sets

Overview

There will be 10 weekly problem sets.

A new problem set will be released every Monday morning (starting in Week 1). You should solve it and submit a handwritten solution via Canvas by 11:00am on the following Monday.

Deadlines are strict. Late submissions will not be accepted under any circumstances.

There will be no problem set in Week 5 (to allow time to study for the Week 6 midterm exam). The final problem set will be posted in Week 11.

Marking

Problem sets will be check-marked only. Marks are based mainly on completeness and overall correctness, not on presentation details or small algebraic slips.

The purpose is to keep you practicing the weekly material and to give you a clear signal about whether you’re broadly on track. If you would like individual feedback, we’re very happy to discuss your work after the weekly workshops or during consultation hours.

Rubric

Each problem set receives one of three marks: 0, 1/2, or 1, according to the rubric below.

1 mark

• Complete and broadly correct.
• You attempted all questions.
• Your working shows a clear method and the solution is overall correct.
• Any mistakes are minor (e.g., small arithmetic/algebra slips) and do not undermine the main reasoning.

1/2 mark

• Substantial attempt, but with errors or gaps.
• You submitted work for the set and made meaningful progress on most questions, but:
• there are noticeable errors in reasoning, definitions, or key steps, and/or
• some parts are incomplete or unclear, and/or
• final answers look doubtful even if the approach is partly right.
• Think of this as: “You engaged seriously, but there are issues to fix.”

0 marks

• Not submitted, or
• Too incomplete to assess (e.g., only a small fraction attempted), or
• Mostly incorrect with little evidence of a viable method.

Best 8 out of 10

Only your best 8 problem sets will count toward your final course mark. This means you may submit fewer than 10 sets without penalty, since only the top 8 are used.

Across your best 8 submissions, the maximum contribution is 10% towards the final course mark. To convert your total (out of 8) into a course percentage, we apply an inflation factor of 1.25.

• Example A: total = 8 marks ? (8 x 1.25 = 10%)
• Example B: total = 6 marks ? (6 x 1.25 = 7.5%)

Marking turnaround and feedback

We aim to return marks within a few days of the due date (ideally in the same week).

Substantive feedback—and an opportunity to ask questions—will be provided in that week’s workshop session. For example: Problem Set 1 is posted Monday of Week 1, due 11:00am Monday of Week 2, and then discussed in the Week 2 workshop (currently scheduled for Wednesdays).

Assessment Task 2

Computer Assignment

Overview

There will be two computational assignments, covering material from the weekly computer labs.

Each assignment will be provided as a Jupyter notebook. You will complete the tasks by writing Julia code, and by commenting on and interpreting your results as you go. You will submit your completed notebook via Canvas file upload.

Timeline

• Both assignments will be available for download at the beginning of the semester.
• Assignment 1: due in Week 7; marks returned by Week 8.
• Assignment 2: due in Week 11; marks returned by Week 12.

Marking

Each assignment is marked out of 10. A detailed breakdown showing how partial marks are awarded will be included in the assignment notebook itself.

Marking turnaround and feedback

We aim to return marks within one week of the deadline.

Substantive feedback—and an opportunity to ask questions—will be provided in the following week’s computer lab session. For example, Assignment 1 is due in Week 7, and will be discussed in the Week 8 computer lab.

Assessment Task 3

Midterm exam

A midterm exam will be held during the lecture in Week 6. It will assess material covered across the course to date, and attendance is compulsory.

The exam has no reading time and 90 minutes writing time.

We aim to return the marks to you in week 7.

Further details will be provided in lectures by Week 5.

Assessment Task 4

Final Examination

A final exam will be held during the ANU exam period. It will cover material from the entire course, and attendance is compulsory.

The exam has no reading time and 120 minutes writing time.

Further details will be provided in lectures by Week 10. A practice exam will also be made available so you can get a realistic sense of the format and level of difficulty.

Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.

The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.

The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.

 

The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.

Online Submission

You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of your assignment for your records.

Submission will be online via Canvas file upload. Details provided during the week 1 and 2 lectures (with timely reminders throughout).

Hardcopy Submission

Not permitted.

Late Submission

No submission of assessment tasks without an extension after the due date will be permitted. If an assessment task is not submitted by the due date, a mark of 0 will be awarded.

Referencing Requirements

The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material. Any use of artificial intelligence must be properly referenced. Failure to properly cite use of Generative AI will be considered a breach of academic integrity.

Returning Assignments

Problem sets will be returned in the week following the submission due date. For example: problem set 1 will be returned to you in week 2, problem set 2 in week 3, and so forth.

When you receive a marked problem set back you should check immediately if you agree with the marking. If not, you must raise your concerns promptly (within one week of receiving the problem set). We will not, under any circumstances, remark problem sets for which you have not raised your concerns within this time frame. Reminders of this policy will be given on several occasions throughout the semester.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Resubmission of Assignments

Not permitted

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.

Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

• ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
• ANU Accessibility for students with a disability or ongoing or chronic illness
• ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
• ANU Academic Skills supports you make your own decisions about how you learn and manage your workload.
• ANU Counselling promotes, supports and enhances mental health and wellbeing within the University student community.
• ANUSA supports and represents all ANU students