• Class Number 7558
• Term Code 3160
• Class Info
• Unit Value 6 units
• Topic Online
• Mode of Delivery Online
• COURSE CONVENER
• Dr Hoa Nguyen
• LECTURER
• Dr Hoa Nguyen
• Class Dates
• Class Start Date 26/07/2021
• Class End Date 29/10/2021
• Census Date 14/09/2021
• Last Date to Enrol 02/08/2021
• TUTOR
• Dr Hoa Nguyen
SELT Survey Results

Econometric Techniques (IDEC8017)

This course is an introduction for economics graduate students to the techniques of econometrics. The emphasis is on the essential ideas and the applications of econometric methods rather than on technical and theoretical details. However the results are not just presented but instead are derived using a mixture of rigour and intuition so as to leave as few loose ends as possible. We recognise that available economic data are either cross sectional (observations on several economic units - usually countries, firms or households - at a single point in time) or time series (observations one economic unit over time), or panel (observations on several economic units followed through time), and each type of data may need its special set of tools. We start with the linear regression model, which is the simplest model for explaining one variable using several explanatory variables, and then move to an introduction to ‘micro-econometrics', i.e., methods most useful for the analysis of cross sectional data, and an introduction to ‘macro-econometrics', i.e., methods most useful for the analysis of aggregate data over time.

## Learning Outcomes

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

1. interpret regression coefficients in linear and nonlinear regression models
2. assess the fit and statistical significance of econometric relationships
3. construct interval estimates and hypothesis tests of interesting economic hypotheses, including those involving several parameters
4. distinguish different forms of data and the models appropriate for them: cross section and time series
5. critically assess choices of functional form
6. understand the assumptions in the statistical model, the consequences of failure and methods of detection
7. use the statistical package.

## Research-Led Teaching

This course is research-focused in the sense that students are required to apply econometric techniques to real data and answer questions that are policy relevant.

Nil

Nil

Nil

Nil

## Staff Feedback

Students will be given feedback in the following forms in this course:
• 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 Lecture - Week 1-4: Simple and multiple regression analysis Wooldridge, 2011. Chapters 1, 2, 3, 4 Verbeek, 2008. Chapter 2 Angrist and Pischke, 2011. Chapters 2 and 3. All assessments
2 Lecture - Week 4-5: Asymptotic analysis and further issues in multiple regression analysis Wooldridge, 2011. Chapters 5 and 6 Verbeek, 2008. Chapter 2 (Sections 2.5 and 2.6) and chapter 3 (Sections 3.1-3.3) All assessments
3 Lecture - Week 5-6: Heteroskedasticity and autocorrelation Wooldridge, 2011. Chapters 8 and 12 Verbeek, 2008. Chapter 4 All assessments
4 Lecture - Weeks 6, 9, 10: Endogeneity, instrumental variables, GMM Wooldridge, 2011. Chapters 13, 14, 15 and 16 Verbeek, 2008. Chapter 4 Angrist and Pischke, 2011. Chapter 4 All assessments
5 Lecture - Week 10-12: Regression analysis with time series data Wooldridge, 2011. Chapter 18 Verbeek, 2008. Chapter 8 (sections 8.1, 8.3, 8.4) and chapter 9 (sections 9.1, 9.2) All assessments
6 Lecture: Limited dependent variable models (if there is enough time) Wooldridge, 2011. Chapter 17 (Section 17.1) Verbeek, 2008. Chapter 7 (Section 7.1)
7 Examination Period Assessment Task 4

## Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Quiz 1 10 % 28/08/2021 15/09/2021 1, 2, 3,
Quiz 2 10 % 23/10/2021 29/10/2021 1, 2, 3, 4, 5
Weekly group in-class presentation 5 % 04/08/2021 29/10/2021 1, 2, 3, 4, 5
Group Assignment 1 10 % 10/09/2021 24/09/2021 1, 2, 3,
Group Assignment 2 10 % 15/10/2021 29/10/2021 1, 2, 3, 4, 5
Final exam 55 % 31/10/2021 02/12/2021 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

## 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.

Nil

## Examination(s)

One open book exam

Value: 10 %
Due Date: 28/08/2021
Return of Assessment: 15/09/2021
Learning Outcomes: 1, 2, 3,

Quiz 1

Wattle-based quiz 1 cover the learning outcomes: 1, 2, and 3.

Value: 10 %
Due Date: 23/10/2021
Return of Assessment: 29/10/2021
Learning Outcomes: 1, 2, 3, 4, 5

Quiz 2

Wattle-based quiz 1 cover the learning outcomes: 1, 2, 3, 4 and 5.

Value: 5 %
Due Date: 04/08/2021
Return of Assessment: 29/10/2021
Learning Outcomes: 1, 2, 3, 4, 5

Weekly group in-class presentation

This group-based assessment (starts from week 2) covers the learning outcomes: 1, 2, 3, 4 and 5.

It aims to foster collaboration in learning among students and encourage students' in-class participation. This group membership will change every week. Students are assigned randomly into groups, which are randomly chosen to solve problems during weekly tutorials. Students' performance will be marked jointly by the lecturer (50% of the weight) and other non-presenting students (50% of the weight).

Value: 10 %
Due Date: 10/09/2021
Return of Assessment: 24/09/2021
Learning Outcomes: 1, 2, 3,

Group Assignment 1

This group assignment 1 covers the learning outcomes: 1, 2, and 3.

The purpose of assignments are twofold. The first is to train students in how to conduct analysis and present econometric results. Therefore, some of the questions in these assignments will require a computational exercise to obtain results which are then written up into a report. Furthermore, assignments will give students some training in how to become a relatively independent researcher by asking them to perform some analysis not (well) covered in the course. The second is to encourage collaboration and cohort experience among students.

Value: 10 %
Due Date: 15/10/2021
Return of Assessment: 29/10/2021
Learning Outcomes: 1, 2, 3, 4, 5

Group Assignment 2

This group assignment 2 covers the learning outcomes: 1, 2, 3, 4 and 5.

The purpose of assignments are twofold. The first is to train students in how to conduct analysis and present econometric results. Therefore, some of the questions in these assignments will require a computational exercise to obtain results which are then written up into a report. Furthermore, assignments will give students some training in how to become a relatively independent researcher by asking them to perform some analysis not (well) covered in the course. The second is to encourage collaboration and cohort experience among students.

Value: 55 %
Due Date: 31/10/2021
Return of Assessment: 02/12/2021
Learning Outcomes: 1, 2, 3, 4, 5

Final exam

Final Examination covering the whole course will be held during the examination period with the specific date to be confirmed by the ANU examination office.

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

The ANU uses 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. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

## Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

## Late Submission

No late submission is allowed in this course. You may get some assessments redemptive to the final exam if you have legitimate reasons.

## 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

All assessments will be marked and returned to students within two weeks after the due date.

## 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.

Not allowed.

## Privacy Notice

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).

## Convener

 Dr Hoa Nguyen 02 6125 8447 hoa.nguyen@anu.edu.au

### Research Interests

Applied Economics, Microeconometrics, Poverty and Inequality, Food Policy

### Dr Hoa Nguyen

 By Appointment

## Instructor

 Dr Hoa Nguyen 02 6125 8447 hoa.nguyen@anu.edu.au

### Dr Hoa Nguyen

 By Appointment

## Tutor

 Dr Hoa Nguyen 02 61258447 hoa.nguyen@anu.edu.au

### Dr Hoa Nguyen

 By Appointment