• Class Number 4418
  • Term Code 3330
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
    • Dr Juergen Meinecke
    • Dr Juergen Meinecke
  • Class Dates
  • Class Start Date 20/02/2023
  • Class End Date 26/05/2023
  • Census Date 31/03/2023
  • Last Date to Enrol 27/02/2023
SELT Survey Results

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

Due to small class size, I aim to hold an in-person exam on campus. We will discuss this during the semester.

If an in-person exam is not possible:

Exams will be held remotely through the Wattle Class Site. Stable and reliable internet connection is necessary and a webcam required for invigilation..

Required Resources

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

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

I have requested these books for 2 hour reserve at Chifley library (ebook versions where possible).

Staff Feedback

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

  • written comments on weekly assignments
  • verbal comments during lectures and tutorials
  • 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


Class Schedule

Week/Session Summary of Activities Assessment
1 Projections weekly assignment
2 Ordinary Least Squares Estimation weekly assignment
3 Ordinary Least Squares Estimation weekly assignment
4 Ordinary Least Squares Estimation weekly assignment
5 Instrumental Variables Estimation weekly assignment
6 Instrumental Variables Estimation weekly assignment
7 Instrumental Variables Estimation weekly assignment
8 Instrumental Variables Estimation weekly assignment
9 Instrumental Variables Estimation weekly assignment, and computational assignment
10 Maximum Likelihood Estimation weekly assignment
11 Limited Dependent Variable Models weekly assignment
12 Extremum Estimators, M-Estimation no new assignment in last week

Tutorial Registration

It is not necessary to enroll for tutorials.

Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Analytical assignments 30 % * * 1,2,3,4,5
Computational assignment 10 % 02/05/2023 19/05/2023 1,2,3,4,5
Final exam 60 % * 29/06/2023 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


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:

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 ‘Wattle’ 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.


Weekly course activities are structured in the following way:

  • workshop, two hours, covering lecture material and analytical exercises
  • computer labs, two hours
  • all activities are offered live on-campus, can be live-streamed on demand

All activities (workshops and labs) are discussion based and will not be recorded, nor will worked solutions be provided. Activities benefit from and depend on your participation and engagement.

Students who, through unavoidable and unplanned occurrences, are unable to attend a tutorial are encouraged to work through the problems and attend a consultation session

for discussion and solutions.

Attendance at ALL activities, while not compulsory, is expected given the demanding nature of the course ( in line with “Code of Practice for Teaching and Learning”, clause 2 paragraph (b)). If you are unable to attend regularly, you should not take this course.


See Assessment Task 3

Assessment Task 1

Value: 30 %
Learning Outcomes: 1,2,3,4,5

Analytical assignments

There will be 11 weekly assignments. Each assignment will be marked out of 5. Only your 8 best assignments will be considered towards your final course mark. (You may choose to submit fewer than 11 problem sets as only the best 8 are considered.) The total mark on your 8 best assignments will be multiplied by 3/4 to yield a maximum mark of 30 to reflect that the assignments count 30% towards your final course mark.

Every Wednesday morning (starting week 1) an assignment will be posted to be solved and handed in by the Tuesday 11am of the following week. The weekly deadlines are sharp. Late assignments will not be accepted under any circumstances. The last assignment will be posted in week 11.

We attempt to return the marked assignment a few days after the due date (ideally in that same week). The assignments will be discussed during tutorial sessions after you have handed in your solutions. For example, you will discuss assignment 1 in the week 2 tutorials and we will return assignment 2 to you in week 2, and so on.

No late assignments under any circumstances!


Level of attainment:ExemplaryCompetentDeveloping


Description of criterion

Clarity, exposition

Clean write up, sensible structure, transparent organization, well presented

1 mark

0.5 mark

0 mark


Analytical derivations are being kept minimal

1 mark

0.5 mark

0 mark


Derivations are mathematically correct

3 marks

2 marks

1 mark

Column total:

5 marks

3 marks

1 mark

Assessment Task 2

Value: 10 %
Due Date: 02/05/2023
Return of Assessment: 19/05/2023
Learning Outcomes: 1,2,3,4,5

Computational assignment

There will be one computational assignment that covers the material covered in the weekly computer labs. The computational assignment will be posted in week 7, is due at 11am on Tuesday of week 9, and will be returned by Friday of week 11.

The assignment will be given to you as a Jupyter notebook. Work on the assignment will require coding in Julia as well as commenting and interpreting your results. Submission will be via Wattle file upload.

Assessment Task 3

Value: 60 %
Return of Assessment: 29/06/2023
Learning Outcomes: 1,2,3,4,5

Final exam

A final exam will be held during the ANU exam period. The exam will cover material presented throughout the entire course. The final exam is compulsory to attend. The format of the final exam will follow the format of the practice exams that are available on the course website. Reading time is 0 minutes, writing time is 120 minutes. Further details will be provided during lecture by week 10. The mark will be returned by 29 June 2023.

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 Wattle 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.

Returning Assignments

Analytical assignments will be returned in the week following the submission due date. For example: Assignment 1 will be returned to you in week 2, assignment 2 in week 3, and so forth.

When you receive a marked assignment 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 assignment). We will not, under any circumstances, remark assignments 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).

Dr Juergen Meinecke

Research Interests

Econometrics, Computational

Dr Juergen Meinecke

By Appointment
By Appointment
Dr Juergen Meinecke

Research Interests

Dr Juergen Meinecke

By Appointment
By Appointment

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