• Class Number 7707
• Term Code 2960
• Class Info
• Unit Value 6 units
• Mode of Delivery In Person
• COURSE CONVENER
• Dr Hoa Nguyen
• LECTURER
• Dr Hoa Nguyen
• Class Dates
• Class Start Date 22/07/2019
• Class End Date 25/10/2019
• Census Date 31/08/2019
• Last Date to Enrol 29/07/2019
• TUTOR
• Dr Nguyen Hieu
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:

On completion of the course you should be able to understand most of the econometric results that are presented in the applied economics literature and make critical assessments of those results. You should also be able to produce good estimates in fairly simple situations and provide coherent interpretation of those results, including any caveats on their use. Particular skills include:

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

## Examination Material or equipment

Calculator (non programmable)

Unannotated paper-based dictionary

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. Assessment Task 1
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)
3 Lecture - Week 5-6: Heteroskedasticity and autocorrelation Wooldridge, 2011. Chapters 8 and 12 Verbeek, 2008. Chapter 4
4 Lecture - Weeks 6, 9, 10: Endogeneity, instrumental variables, GMM, and Fixed/Random Effects Models Wooldridge, 2011. Chapters 13, 14, 15 and 16 Verbeek, 2008. Chapter 4 Angrist and Pischke, 2011. Chapter 4 Trevor Breusch, Michael B. Ward, Hoa Thi Minh Nguyen and Tom Kompas, 2011. “On the Fixed-Effects Vector Decomposition”, Political Analysis, 19: 123-134. Assessment Task 1 Assessment Task 2
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) Assessment Task 1
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 Examnation Period Assessment Task 3

## Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Assignments 15 % 14/08/2019 09/09/2019 1, 2, 3, 4, 5, 6, 7
Mid-semester examination 25 % 26/08/2019 28/11/2019 1, 2, 3, 4, 5, 6, 7
Final examination 60 % 31/10/2019 28/11/2019 1, 2, 3, 4, 5, 6, 7

* 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)

Two exams in the standard closed-book format

Value: 15 %
Due Date: 14/08/2019
Return of Assessment: 09/09/2019
Learning Outcomes: 1, 2, 3, 4, 5, 6, 7

Assignments

Three assignments, 5% each.

Due: August 14, Septermber 20 and October 9

Value: 25 %
Due Date: 26/08/2019
Return of Assessment: 28/11/2019
Learning Outcomes: 1, 2, 3, 4, 5, 6, 7

Mid-semester examination

90-minute length in standard closed-book format, likely in week 6.

Value: 60 %
Due Date: 31/10/2019
Return of Assessment: 28/11/2019
Learning Outcomes: 1, 2, 3, 4, 5, 6, 7

Final examination

Three hour length in the standard closed-book format.

## 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 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 within two weeks after the due date. Results of mid-semester exam will be published within 20 days after the exam date. Students can see their marked exam scripts by making an appointment with the Crawford School's Student Services.

## 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

## Instructor

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

## Tutor

 Dr Nguyen Hieu 61252188 nguyen.hieu@anu.edu.au