ECON 723 : Econometrics 2

Business and Economics

2020 Semester One (1203) (15 POINTS)

Course Prescription

An overview of time series econometrics, designed to introduce a range of material in stationary and nonstationary time series including: modern model determination methods, unit root and co-integration theory, non-linear time series analysis and continuous time models. Students will be introduced to practical time series forecasting methods.

Course Overview

The course introduces students to advanced techniques in time series and panel data econometrics, including: model selection and identification; stationary and non-stationary time series modelling; unit root and cointegration theory; and structural vector autoregressions and related multivariate models. Classes are delivered in a computer lab so that students can apply content to real world problems as they learn.

Course Requirements

No pre-requisites or restrictions

Capabilities Developed in this Course

Capability 1: Disciplinary Knowledge and Practice
Capability 2: Critical Thinking
Capability 3: Solution Seeking
Capability 4: Communication and Engagement

Learning Outcomes

By the end of this course, students will be able to:
  1. Understand and apply the foundations of econometric theory (Capability 1 and 4.2)
  2. Critically evaluate hypotheses or policies using empirical methods (Capability 2 and 4.2)
  3. Understand and apply strategies to uncover causal relationships in observational data (Capability 3 and 4.2)
  4. Use a computer programming language to manage and analyze data in a team setting (Capability 3 and 4.3)

Assessments

Assessment Type Percentage Classification
Assignments 35% Group & Individual Coursework
Project 65% Individual Coursework
Assessment Type Learning Outcome Addressed
1 2 3 4
Assignments
Project

Workload Expectations

This course is a standard 15 point course and students are expected to spend 10 hours per week involved in each 15 point course that they are enrolled in.

For this course, you can expect 2 hours of lectures, a 2 hour tutorial, 2 hours of reading and thinking about the content and 4 hours of work on assignments or the final project.

Learning Resources

Prescribed Texts:
Hamilton, J.D. (1994), Time Series Analysis, Princeton University Press. 
Baltagi, Badi H. (2013), Econometric Analysis of Panel Data, Wiley.

Digital Resources

Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).

Please remember that the recording of any class on a personal device requires the permission of the instructor.

Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the internet. A student's assessed work may be reviewed against online source material using computerised detection mechanisms.

Inclusive Learning

All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.

Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website at http://disability.auckland.ac.nz

Special Circumstances

If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.

If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page: https://www.auckland.ac.nz/en/students/academic-information/exams-and-final-results/during-exams/aegrotat-and-compassionate-consideration.html.

This should be done as soon as possible and no later than seven days after the affected test or exam date.

Student Feedback

At the end of every semester students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback and respond with summaries and actions.

Your feedback helps teachers to improve the course and its delivery for future students.

Class Representatives in each class can take feedback to the department and faculty staff-student consultative committees.

Student Charter and Responsibilities

The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter (https://www.auckland.ac.nz/en/students/forms-policies-and-guidelines/student-policies-and-guidelines/student-charter.html).

Disclaimer

Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.

In this course you may be asked to submit your coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. The final decision on the completion mode for a test or examination, and remote invigilation arrangements where applicable, will be advised to students at least 10 days prior to the scheduled date of the assessment, or in the case of an examination when the examination timetable is published.

Published on 17/12/2019 11:50 a.m.