• Class Number 3602
  • Term Code 3030
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
  • COURSE CONVENER
    • Dr Nicholas Biddle
  • LECTURER
    • Maria Jahromi
  • 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

The philosophy of Case Studies is that the best way to learn how to research is to do research. Students conduct, under the supervision of faculty, their own research projects, culminating in the writing of a research paper. Lectures will be given on a selection of topics that can prove useful in research.

Learning Outcomes

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

  1. formulation of research objective
  2. execution of a research agenda to adress the research objective
  3. a demonstration of your competency in the research methods your objective mandates
  4. writing a research paper
  5. presentation of the research project

Research-Led Teaching

This course has a heavy research focus. Students will be required to replicate existing applied econometric research on real data, and extend this research using their own research questions and ideas.

Required Resources

Students will be given a list of required readings in the first lecture of the course. This will include (a) texts that summarise the main techniques used in the course (available online through the ANU Library) (b) between 4-6 compulsory case-studies of applied econometrics that will be used in lectures and (c) between 4-6 case-studies that will form the basis of student assessment

Staff Feedback

Students will be given feedback in the following forms in this course:

  • Worked answers for Quiz 1
  • Verbal feedback on Research presentation
  • Written feedback on Research proposal and report
  • Computer Lab worked examples

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.

Other Information

Course Format

Lecture:  To be confirmed at start of semester

Computer Lab: To be confirmed at start of semester.

Class Schedule

Week/Session Summary of Activities Assessment
1 Introduction to course During this first lecture, we will introduce the content of the course and discuss different types of data that can be used in applied econometrics. We will talk about the concept of an independent and a dependent variable, and different ways to analyse data. We will introduce the potential topics for student assignments, and discuss how to access data No computer Lab
2 Continuous Data I During the lecture, we will introduce the main techniques for analysing individual-level data for continuous dependent variables. This includes a discussion of univariate and bivariate analysis, as well as simple linear regression. Computer Lab: Simple Linear Regression
3 Continuous Data II (pre-recorded lecture) We will continue the discussion of analysis of continuous dependent variables by looking at multiple linear regression (when there is one dependent variable and more than one independent variable). We will discuss the assumptions underlying linear regression, and the different ways in which they can be violated. No Computer Lab - Public Holiday Assessment Task 1 due
4 Categorical Data I During the lecture for this week, we will discuss one of the main extensions to micro-econometrics, the use of non-continuous dependent variables. We will begin by looking at binary dependent variables (yes/no) and how to calculate and interpret odds ratios and marginal effects in Logit/Probit regression. Computer Lab - Multiple linear regression and dummy variables
5 Categorical Data II We will extend our analysis of categorical dependent variables by looking at instances of more than two categories. This includes multinomial Logit/Probit; ordered Logit/Probit; and count data Computer Lab - Logit/Probit and calculation of predicted probabilities
6 Time Series I We will switch the focus of our analysis during this lecture, and look at the analysis of aggregate data, with a particular focus on time series analysis. We will discuss the concepts of (and main techniques for) lags, stationarity, and structural breaks. Computer Lab - Multinomial and Ordered Logit/Probit
7 Time Series II - Intro to panel data We will extend our analysis of 'time', by looking at the main techniques for panel data analysis. That is, when we have more than one observation, for more than one individual. We will begin our discussion of panel data by discussing pooled regression and differencing. Computer Lab - Introduction to time series analysis Assessment Task 2 due
8 No lecture - Public Holiday
9 Time series III - Panel data continued We will extend our analysis of panel data by looking at fixed and random effects regression Computer Lab - Time series models, dynamic causal effects and forecasting
10 Student presentations Assessment Task 3 due
11 Presenting data We will discuss some of the practicalities of summarising data for an academic or policy audience. Computer Lab - Panel data analysis
12 Summary and questions on case study Computer Lab - Assistance with case studies project Assessment Task 4 due

Tutorial Registration

There is one Computer Lab scheduled. Details are on the ANU timetable website: http://timetabling.anu.edu.au/sws2020.


Assessment Summary

Assessment task Value Due Date Learning Outcomes
Online Quiz 1 5 % 13/03/2020 3
Proposal 15 % 24/04/2020 3
Research presentation 10 % 11/05/2020 1, 2
Research report 45 % 29/05/2020 2, 3, 4, 5
Online Quiz 2 25 % 12/06/2020 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. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

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.

Assessment Task 1

Value: 5 %
Due Date: 13/03/2020
Learning Outcomes: 3

Online Quiz 1

Student will undertake a quiz through Wattle based on the content covered in Weeks 1 to 3. Students will have one-week to complete the quiz online before the due date (through Wattle) and will consist of a combination of multiple choice and short answer questions. Students will be required to explain concepts, interpret econometric results, and undertake basic analysis. It is expected that the quiz will have 3 questions.

Assessment Task 2

Value: 15 %
Due Date: 24/04/2020
Learning Outcomes: 3

Proposal

Students will submit a 1000-word research proposal based on their independent research. Students will be able to choose one of eight research reports that they will be required to replicate and make a minor extension to. These will be provided via Wattle on or before Week 1 of class. Students can also request to replicate and extend a paper outside of the eight suggested by the lecturers. This proposal should include a brief summary of the main findings, methods and data of the original paper, as well as the proposed extension. Submission will be via turnitin.

Assessment Task 3

Value: 10 %
Due Date: 11/05/2020
Learning Outcomes: 1, 2

Research presentation

Students will give a five minute presentation on their own independent research. It is highly recommended that students present on the same paper from their Research Proposal. However, students are able to change with permission from the Convenor. if they encounter difficulties. Students will give the presentations during Week 10 during the time allocated to the computer lab and lecture. It is expected that students will participate in and comment on the presentations of other students.


More details will be given in Week 01 and Week 07

Assessment Task 4

Value: 45 %
Due Date: 29/05/2020
Learning Outcomes: 2, 3, 4, 5

Research report

Students will submit a 4,000-5,000 word essay based on their independent research. It is highly recommended that students present on the same paper from their Research Proposal and Presentation. However, students are able to change with permission from the Convenor. More details will be given in Week 01

Assessment Task 5

Value: 25 %
Due Date: 12/06/2020
Learning Outcomes: 4, 5

Online Quiz 2

Student will undertake a quiz through Wattle based on the content covered in the entirety of the course. Students will have two weeks to complete the quiz. The quiz will consist of a combination of multiple choice and short answer questions, as well as a short essay based on an additional set of applied econometric readings (provided at the end of the course through Wattle). Students will be required to explain concepts, interpret econometric results, and undertake basic analysis.

Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. At its heart, academic integrity is about behaving ethically, committing to honest and responsible scholarly practice and upholding these values with respect and fairness.


The ANU commits to assisting all members of our community to 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 be familiar with the academic integrity principle and Academic Misconduct Rule, 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 Academic Misconduct Rule is in place to promote academic integrity and manage academic misconduct. Very minor breaches of the academic integrity principle may result in a reduction of marks of up to 10% of the total marks available for the assessment. The ANU offers a number of online and in person services to assist students with their assignments, examinations, and other learning activities. Visit the Academic Skills website for more information about academic integrity, your responsibilities and for assistance with your assignments, writing skills and study.

Online Submission

You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.

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

Late submission of assessment tasks without an extension are penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of assessment tasks is not accepted after 10 working days after the due date, or on or after the date specified in the course outline for the return of the assessment item. Late submission is not accepted for take-home examinations.

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.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted 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.

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 Nicholas Biddle
6125 1301
nicholas.biddle@anu.edu.au

Research Interests


https://researchers.anu.edu.au/researchers/biddle-ng

Dr Nicholas Biddle

By Appointment
Maria Jahromi
6125 6550
maria.jahromi@anu.edu.au

Research Interests


Maria Jahromi

By Appointment

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