• Class Number 2341
  • Term Code 3030
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
  • COURSE CONVENER
    • Dr Juergen Meinecke
  • LECTURER
    • Dr Juergen Meinecke
  • Class Dates
  • Class Start Date 24/02/2020
  • Class End Date 05/06/2020
  • Census Date 08/05/2020
  • Last Date to Enrol 02/03/2020
SELT Survey Results

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.

Learning Outcomes

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

  1. define the ordinary least squares (OLS) estimator in the linear regression model;
  2. derive and examine statistical properties of the OLS estimator;
  3. employ the central limit theorem to approximate the statistical distribution of the OLS estimator;
  4. demonstrate an understanding of strengths and limitations of the OLS estimator;
  5. summarise and analyse actual economic data with use of a specialised econometric software;
  6. contextualise and critically evaluate the results of empirical analysis.

Research-Led Teaching

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

None

Required Resources

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 (I have requested to put a few copies on 2 hour loan at Chiefly).

The econometric software for this course is “Stata” Here’s a quick wiki summary of what Stata is: http : //en.wikipedia.org/wiki/Stata. From my own experience, Stata is an exhaustive, well- documented, powerful and user-friendly statistical software. We will get to know Stata during the tutorial in a “learning-by-doing manner” Stata is available in the ANU computer labs. You do not need to purchase your own Stata license.

Staff Feedback

Students 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 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). 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.

Class Schedule

Week/Session Summary of Activities Assessment
1 Introduction, Review of Statistics
2 Review of Statistics
3 Principles of Econometric Modelling
4 Simple Linear Regression Model
5 Simple Linear Regression Model
6 Simple Linear Regression Model Assignment 1
7 Multiple Linear Regression Model
8 Multiple Linear Regression Model
9 Extensions of the Regression Model
10 Time Series Regression Models
11 Time Series Regression Models Assignment 2
12 Time Series Regression Models

Tutorial Registration

Instructions on how to enrol in a tutorial will be available on the Wattle site.

Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Assignment 1 10 % 31/03/2020 23/04/2020 1,2,3,4,5,6
Assignment 2 10 % 19/05/2020 28/05/2020 1,2,3,4,5,6
Tutorial Participations 10 % 29/05/2020 29/05/2020 1,2,3,4,5,6
Final Exam 70 % 04/06/2020 20/06/2020 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

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 Misconduct 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 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 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

See Assessment Task 3

Examination(s)

See Assessment Task 4

Assessment Task 1

Value: 10 %
Due Date: 31/03/2020
Return of Assessment: 23/04/2020
Learning Outcomes: 1,2,3,4,5,6

Assignment 1

Working through exercises is an effective method of learning econometrics, as it is with most mathematical subjects. That means that the assignments are more than simply part of the assessment for the course. Students will be required to submit two written assignments during the semester. The assignments will require computer work as well as analytical work.


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 offence against the University's regulations to copy from other students assignments.


Assignments must be submitted 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).

Assessment Task 2

Value: 10 %
Due Date: 19/05/2020
Return of Assessment: 28/05/2020
Learning Outcomes: 1,2,3,4,5,6

Assignment 2

Working through exercises is an effective method of learning econometrics, as it is with most mathematical subjects. That means that the assignments are more than simply part of the assessment for the course. Students will be required to submit two written assignments during the semester. The assignments will require computer work as well as analytical work.


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.


Assignments must be submitted 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).

Assessment Task 3

Value: 10 %
Due Date: 29/05/2020
Return of Assessment: 29/05/2020
Learning Outcomes: 1,2,3,4,5,6

Tutorial Participations

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 computer tutorial sessions. By participation I specifically mean:

answering questions

asking relevant and helpful questions


Feel free to participate 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 beginning 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.)

Rubric

Level of attainment:ExemplaryCompetentDeveloping

3 points

2 points

1 point

Criteria

Description of criterion

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

Value: 70 %
Due Date: 04/06/2020
Return of Assessment: 20/06/2020
Learning Outcomes: 1,2,3,4,5,6

Final Exam

There will be one final exam. The format of the final exam will follow the format of the practice exams that are available on the course website. Reading time is 15 minutes, writing time is 120 minutes.

Academic Integrity

Academic 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.

Online Submission

Given that numerical nature of the course, no online submissions are permitted.

Hardcopy Submission

Both Assignments must be submitted in hard copy by dropping them into a specially labeled assignment box at the Research School of Economics. (Contact the Student Administrator for details.) The front page of the submitted assignments must show your name, student number and the course name (EMET2007/4007/6007). Assignments missing any of this information will receive a mark of zero. If you put your assignment into the wrong assignment box then you will receive a mark of zero.

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

Accepted 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.

Returning Assignments

Assignments will be returned during tutorials.


When you receive a marked assignment back you should check immediately if you agree with the marking. If not, you must raise your concerns directly (by the end of the tutorial) with your tutor. The tutor will then keep your assignment for reconsideration. Important: Once you leave the tutorial with your assignment you forgo your opportunity for remarking. We will not, under any circumstances, remark any assignments for which you have not raised your concerns in the tutorial session during which the assignment was returned to you.

Extensions and Penalties

Extensions 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

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
56184
juergen.meinecke@anu.edu.au

Research Interests


Econometrics, Computational

Dr Juergen Meinecke

Monday 08:00 09:00
Dr Juergen Meinecke
juergen.meinecke@anu.edu.au

Research Interests


Dr Juergen Meinecke

Monday 08:00 09:00

Responsible Officer: Registrar, Student Administration / Page Contact: Website Administrator / Frequently Asked Questions