- Class Number 2753
- 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
This course provides an introduction to econometric methods and their applications. The main workhorse of applied econometrics is the linear regression model and the course will develop its theory and look at a wide range of applications. The course emphasizes intuitive and conceptual understanding as well as hands on econometric analysis using modern computer software on data sets from economics and business. Students learn how to conduct empirical studies, as well as how to analyze and interpret results from other empirical works. We cover a broad range of topics, including: brief review of basic statistics; ordinary least squares estimation and its properties; choice of functional form; departures from standard OLS assumptions; time series analysis.
This is a hand-on course with a focus on applications in economics as well as business. A standard statistical software will be used during computer sessions, no special programming skills are required.
Upon successful completion, students will have the knowledge and skills to:
- define the ordinary least squares (OLS) estimator in the linear regression model;
- derive and examine statistical properties of the OLS estimator;
- employ the central limit theorem to approximate the statistical distribution of the OLS estimator;
- demonstrate an understanding of the strengths and limitations of the OLS estimator;
- summarise and analyse actual economic data with use of a specialised econometric software;
- contextualise and critically evaluate the results of empirical an
This course teaches state-of-the-art methods and practices in econometrics. We will use applications and data sets from recently published papers in top academic journals.
Examination Material or equipment
Exams will be held remotely through the Wattle Class Site. Stable and reliable internet connection is necessary and a webcam required for invigilation.
The textbook for the course is Introduction to Econometrics (fourth edition, 2019) by Stock and Watson. The lecture is based on this textbook. The textbook can be purchased from the on campus bookshop, or a small number of copies are available in the ANU library (Chifley library holds copies on reserve and e-reserve).
We will work through applied econometric exercises using a statistical software package. No preliminary knowledge of statistical computing is required, we will learn all required skills in a "learning by doing manner" during the computer tutorials. The recommended software is available in the ANU computer labs. More information will be provided in week 1 of the semester.
Staff FeedbackStudents will be given feedback in the following forms in this course:
- Written comments
- Verbal comments
- Feedback to the whole class, to groups, to individuals, focus groups
Student FeedbackANU 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). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.
Material for the course is available on the Wattle Class Site and also on the following course website:
|Week/Session||Summary of Activities||Assessment|
|1||Introduction, Review of Statistics|
|2||Review of Statistics|
|3||Principles of Econometric Modelling||Online quiz 1|
|4||Simple Linear Regression Model|
|5||Simple Linear Regression Model||Online quiz 2|
|6||Simple Linear Regression Model||Assignment 1|
|7||Multiple Linear Regression Model|
|8||Multiple Linear Regression Model|
|9||Extensions of the Regression Model||Online quiz 3|
|10||Time Series Regression Models|
|11||Time Series Regression Models||Assignment 2|
|12||Time Series Regression Models||Online quiz 4|
Interactive computer labs will be held weekly (starting from week 2). Labs will be available both on campus and via Zoom (only for students who are not able to attend in-person). ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage. https://www.anu.edu.au/students/program-administration/timetabling].
|Assessment task||Value||Learning Outcomes|
|Online quizzes||20 %||1,2,3,4,5,6|
|Computer lab participation||10 %||1,2,3,4,5,6|
|Final Exam||50 %||1,2,3,4,5,6|
* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details
PoliciesANU 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 Misconduct Rule before the commencement of their course. Other key policies and guidelines include:
Assessment RequirementsThe 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 ANU Online website Students may choose not to submit assessment items through Turnitin. In this instance you will be required to submit, alongside the assessment item itself, hard copies of all references included in the assessment item.
Moderation of AssessmentMarks 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:.
- Lecture material is available in form of pdf slides and pre-recorded screencasts;
- Workshops (two hours) offered live on campus in a large group and simultaneously live-streamed for remote access (please see timetable for details);
- Computer labs (one hour) offered live on campus in small groups, and alternatively live-streamed (via Zoom or MS Teams) for students who study remotely.
The workshops and computer labs are discussion based and will not be recorded, nor will worked solutions be provided. Workshops and labs benefit considerably from your participation and engagement. Students who, through unavoidable and unplanned occurrences, are unable to attend a workshop or lab are encouraged to work through the problems and attend a consultation session for discussion and solutions.
Attendance at live activities, while not compulsory, is expected in line with “Code of Practice for Teaching and Learning”, clause 2 paragraph (b).
See Assessment Task 4
Assessment Task 1
Learning Outcomes: 1,2,3,4,5,6
There will be two compulsory take home assignments. Each assignment counts 10% towards your total course mark.
While the assignments focus on applied econometric work using statistical/econometric software, they also test your understanding of intuitive concepts and theory from the lecture and the problem solving tutorial.
- Assignment 1 is due in week 6 on 29 March 2023 at 11:00am (sharp!) and will be returned in week 7 of the semester.
- Assignment 2 is due in week 11 on 17 May 2023 at 11:00am (sharp!) and will be returned in week 12 of the semester.
Assignments must be submitted via file upload on Wattle by the due date. Further details about assignment submission will be given during lectures. Assignments will be made available on the course website at the beginning of the semester (week 1).
These assignments should be your own work. You may discuss assignments with classmates, but you should do all your own computing and writing of the assignments. It is an offense against the University's regulations to copy from other students assignments.
- If you miss an assignment without an approved reason a mark of zero will be given.
- If you miss an assignment with an approved reason (for example, due to documented sickness) the final exam will be scaled up commensurately. (That is, the final exam will effectively make up for the missed assignment.)
Assessment Task 2
Learning Outcomes: 1,2,3,4,5,6
There will be 4 compulsory online quizzes throughout the semester. Each quiz counts 5% towards your total course mark.
Each quiz tests all the material covered in the lectures, computer tutorials, and problem solving tutorials.
- Quiz 1 takes place Wed/Thu in week 3 - covering material from weeks 1 and 2
- Quiz 2 takes place Wed/Thu in week 5 - covering material from weeks 3 and 4
- Quiz 3 takes place Wed/Thu in week 9 - covering material from weeks 5, 6, 7, and 8
- Quiz 4 takes place Wed/Thu in week 12 - covering material from weeks 9, 10, and 11
- The quizzes are offered through the Wattle Class Site. The format of the quizzes is mostly multiple choice and true/false type questions.
- Each quiz will be available from 9:00am on the Wednesday of the corresponding week until 3:00pm on the Thursday of the corresponding week. During this 30 hour time window you can attempt the quiz once, and you have 60 minutes to complete it. Marks will be available upon closure of the quiz at 3:00pm on the Thursday of the week.
More information will be offered during weeks 1 and 2 of the semester (with timely reminders throughout the semester).
- If you miss a quiz without an approved reason a mark of zero will be given.
- If you miss a quiz with an approved reason (for example, due to documented sickness) the final exam will be scaled up commensurately. (That is, the final exam will effectively make up for the missed quiz.)
Assessment Task 3
Learning Outcomes: 1,2,3,4,5,6
Computer lab participation
Your participation is an essential part in the overall learning experience (both for you as well as your classmates!) in the course. I will evaluate you on your participation during the weekly computer labs. By participation I specifically mean:
- answering questions;
- asking relevant and helpful questions.
Feel free to participate in and contribute to these sessions!
Do not be afraid to give "wrong" answers; as long as you are constructively engaged, there is no such thing as a wrong answer. After every tutorial your tutor will take note of students who participated in class and at the end of the semester I will aggregate these numbers to an overall participation mark. Please see the marking rubric below for further guidance. I will post progress marks on Wattle at the end of week 6 to offer you early feedback on your participation.
Do not confuse participation with attendance! In order to participate, you do need to attend. But in addition you also need to contribute to the tutorial discussion. (Attendance is necessary but not sufficient for participation.)
|Level of attainment:||Exemplary||Competent||Developing|
Description of criteria
Provided constructive comments
Constructive comments focus on significant issues that bear on the topic in question.They include elaboration on a topic, explaining its assumptions, using helpful examples or analogies.
Asked relevant and constructive questions
Relevant and constructive questions focus on significant issues that bear on the topic in question.
Articulated ideas clearly
Use of clear, simple sentences to explain one’s ideas.
Presented well structured arguments
Comments are coherent and set out in a systematic manner such that people can follow what you are saying.
Demonstrated consideration and respect of others
If there are differences of opinion, they are explored in a considerate and respectful way.
Assessment Task 4
Learning Outcomes: 1,2,3,4,5,6
A final exam will be held during the ANU exam period and will be delivered online through the Wattle Class Site. The exam will cover material presented throughout the entire course (including lectures, problem solving tutorials, and computer tutorials). 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.
Academic IntegrityAcademic integrity is a core part of our culture as a community of scholars. At its heart, academic integrity is about behaving ethically. This means that all members of the community commit to honest and responsible scholarly practice and to upholding these values with respect and fairness. The Australian National University commits to embedding the values of academic integrity in our teaching and learning. We ensure that all members of our community understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. The ANU expects staff and students to uphold high standards of academic integrity and act ethically and honestly, to ensure the quality and value of the qualification that you will graduate with. The University has policies and procedures in place to promote academic integrity and manage academic misconduct. Visit the following Academic honesty & plagiarism website for more information about academic integrity and what the ANU considers academic misconduct. The ANU offers a number of services to assist students with their assignments, examinations, and other learning activities. The Academic Skills and Learning Centre offers a number of workshops and seminars that you may find useful for your studies.
Assignment submission is via the Wattle file upload facility. Details will be provided during the lecture by week 6. We will NOT be using Turnitin.
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.
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 RequirementsAccepted academic practice for referencing sources that you use in presentations can be found via the links on the Wattle site, under the file named “ANU and College Policies, Program Information, Student Support Services and Assessment”. Alternatively, you can seek help through the Students Learning Development website.
Assignments will be returned in the week following the submission due date.
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 any 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 PenaltiesExtensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure The Course Convener may grant extensions 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
Distribution of grades policyAcademic 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 studentsThe 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 Diversity and inclusion 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 and Learning Centre supports you make your own decisions about how you learn and manage your workload.
- ANU Counselling Centre promotes, supports and enhances mental health and wellbeing within the University student community.
- ANUSA supports and represents undergraduate and ANU College students
- PARSA supports and represents postgraduate and research students
Dr Juergen Meinecke