ECON 221 : Introduction to Econometrics

Business and Economics

2020 Semester One (1203) (15 POINTS)

Course Prescription

An introduction to model building and empirical research methods in economics. Emphasises the use and interpretation of single equation regression techniques in formulating and testing microeconomic and macroeconomic hypotheses. Cross-section and time series modelling, as well as qualitative choice models will be covered. There will be examples of the uses of econometrics in a variety of areas through statistical analysis, problem solving and econometric estimation using a statistical computer package.

Course Overview

This course builds on the knowledge of introductory statistics and economics, requiring some knowledge of algebra and calculus (such as logarithmic functions and differentiation).  Ideal preparation is STATS 125 and MATHS 130. BCOM students – we recommend that you substitute STATS 125 for STATS 108 in the core.  For further study in econometrics, students can progress to ECON 321 Econometrics.
This is a recommended course for all students interested in Economics and is a prerequisite for the Honours and Master's programmes in Economics.  It is one of the prerequisites for the Stage III Economics courses ECON 321 Econometrics and is recommended for ECON 302 Economics of Labour Markets.

Course Requirements

Prerequisite: 15 points from ECON 152, MATHS 108, 130, 150, 153, STATS 101, 102, 108, 125, 191

Capabilities Developed in this Course

Capability 1: Disciplinary Knowledge and Practice
Capability 2: Critical Thinking
Capability 3: Solution Seeking
Graduate Profile: Bachelor of Commerce

Learning Outcomes

By the end of this course, students will be able to:
  1. Learn the mathematical and statistical tools required for econometric analysis (Capability 1)
  2. Know the basic principles of econometric modelling and analysis (Capability 2)
  3. Be able to understand the assumptions that underpin the classical regression model (Capability 1)
  4. Know how to apply regression analysis to real-world economic examples and data sets (Capability 3)
  5. Conduct hypothesis testing and prediction (Capability 1)
  6. Be able to recognise and make adjustments for a number of common regression problems. (Capability 2)

Assessments

Assessment Type Percentage Classification
Assignments 30% Individual Coursework
Test 30% Individual Test
Final Exam 40% Individual Examination
Assessment Type Learning Outcome Addressed
1 2 3 4 5 6
Assignments
Test
Final Exam
As a general rule, you will need to score 50% to pass the course.  Plussage does NOT apply.
Students must be able to show an understanding of the course material and extend the mechanics of linear regression analysis.  Emphasis will be placed on the ability to: (1) correctly interpret coefficients in the context of specific regression models, (2) construct appropriate regression specifications that can be used to test economic hypotheses of interest; (3) recognise and understand the consequences when confronted with a variety of common regression problems, and (4) understand appropriate modelling solutions for econometric modelling.

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 3 hours of lectures, a 1 hour tutorial.

For the 12 teaching weeks, this totals to 48 hours. Since the course as a whole represents approximately 150 hours of study, that leaves a total of 102 hours across the entire semester for independent study, e.g. reading, reflection, preparing for assessments/exams, etc.

Learning Resources

Prescribed Text:
  • J.M. Wooldridge, Introductory Econometrics, 5th edition, 2013, South-Western (4th or 6th edition will also work).
This book is closely followed.  You will find it essential for success in the course to regularly follow the textbook readings and applications on the topics covered.  There are helpful questions at the end of each chapter.  The book has a useful appendix on review of probability and statistical distributions.

Main Supplementary Reading:
  • J.H. Stock and M.W. Watson, Introduction to Econometrics, 4th edition, 2020, Pearson Education.
This book could be used instead of Wooldridge textbook.

Additional resources:
The following are other useful introductory econometrics books, and they are available in the General Library.
  • D. Gujarati and D. Porter, Basic Econometrics, 5th edition, McGraw-Hill, 2009.
  •     A.H. Studenmund, Using Econometrics: A Practical Guide, 5th edition, Addison Wesley, 2006.
  •     Damodar Gujarati, Essentials of Econometrics, 3rd edition, McGraw Hill, 2006.


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 20/12/2019 03:04 p.m.