- Class Number 7450
- Term Code 3260
- Class Info
- Unit Value 6 units
- Mode of Delivery In Person
- AsPr Martine Mariotti
- Class Dates
- Class Start Date 25/07/2022
- Class End Date 28/10/2022
- Census Date 31/08/2022
- Last Date to Enrol 01/08/2022
This course takes the theoretical econometric tools students have learned in other courses and teaches students how to apply those techniques to real world problems and data. The course focuses on the concept of causal inference and the different techniques used to causally identify the effect of treatments on outcomes. Using economic data and modern computer software, students learn how to conduct empirical studies by replicating well known econometric analyses. The techniques covered are: Regression Discontinuity Design, Panel Data Methods, Difference in difference analysis, Instrumental Variables, Synthetic Control, Bootstrapping and Randomisation Inference.
Upon successful completion, students will have the knowledge and skills to:
- explain econometric concepts such as causality, endogeneity, confounding factors, selection, and simultaneity;
- explain econometric techniques for estimating causal effects;
- investigate the properties of econometric techniques using Monte Carlo simulation;
- use statistical software to manage and analyse data;
- carry out an empirical analysis of data using the econometric techniques discussed.
Based on all the econometrics tools previously studied, this course prepares students for applying the most appropriate econometric tools in empirical works, especially using
micro data. By explaining the advantages and potential problems of common identification strategies, students will develop a sense of how to make choices among different
strategies based on available data and economic research questions at hand.
Examination Material or equipment
Details about the material or equipment will be updated on course wattle, “Exams related” section
Students can access R through the university IT commons, in the university computer labs or they can install it on their own devices. R is a free user written program.
There will not be designated textbooks, but the following books at the graduate level might be helpful:
· Handbook of Labor Economics, Vol 3A, Orley C. Ashenfelter and David Card, Chapter 23, Empirical Strategies in Labor Economics, by Joshua D. Angrist and Alan B.
Krueger (http://www.irs.princeton.edu/pubs/pdfs/401.pdf )
· Microeconometrics: Methods and Applications, by Cameron and Trivedi
· Mostly Harmless Econometrics: An Empiricist’s Companion, Joshua D. Angrist and Jörn-Steffen Pischke, Princeton and Oxford: Princeton University Press
· Mastering Metrics, Joshua D. Angrist and Jörn-Steffen Pischke, Princeton and Oxford: Princeton University Press
All these materials are available either online or in the Chifley Library.
Students will be given feedback in the following forms in this course:
- written comments
- verbal comments
- feedback to whole class, groups, individuals, focus group etc
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). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.
RSE has a Frequently Asked Questions page where you can find relevant policies and information on a broad range of topics https://www.rse.anu.edu.au/students/students/frequently-asked-questions/
|Week/Session||Summary of Activities||Assessment|
|1||Introduction Randomized Experiments||Optional tutorial on how to use R|
|2||Directed Acyclical Graphical (DAG) Model||Tutorial 1|
|3||Regression Discontinuity Design||Tutorial 2|
|4||Regression Discontinuity Design||Tutorial 3|
|5||Panel Data||Tutorial 4|
|6||Difference in differences design||Tutorial 5 - Midterm Or|
|7||Instrumental Variables||Tutorial 6 - Midterm|
|8||Instrumental Variables||Tutorial 7|
|9||Synthetic Control||Tutorial 8 - Assignment Due Or|
|10||Randomization Inference and Bootstrapping||Tutorial 9 - Assignment Due|
Tutorials will be in person on campus. Students who cannot be on campus can join the tutorial via zoom. ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage. https://www.anu.edu.au/students/program-administration/timetabling].
|Assessment task||Value||Learning Outcomes|
|Tutorial participation||10 %||184.108.40.206,5|
|Mid-semester exam||25 %||220.127.116.11,5,6|
|Final Exam||40 %||18.104.22.168,5,6|
* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details
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 Integrity Rule before the commencement of their course. Other key policies and guidelines include:
- Academic Integrity Policy and Procedure
- Student Assessment (Coursework) Policy and Procedure
- Special Assessment Consideration Guideline and General Information
- Student Surveys and Evaluations
- Deferred Examinations
- Student Complaint Resolution Policy and Procedure
- Code of practice for teaching and learning
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 Academic Skills 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.
Lectures will be face to face, those face to face deliveries will be recorded for students who cannot attend lectures. Details on the delivery of this course and expectations of student participation are outlined in further detail on the Wattle course site. In addition, tutorials are a discussion-based class. Providing worked solutions would not effectively compensate for missing a tutorial. Students who, through unavoidable and unplanned occurrences, are unable to attend a tutorial class one week are encouraged to work through the problems and attend a consultation session for discussion and solutions.
There will be a formal final exam for this course delivered on-line. Details will be announced through Wattle.
Assessment Task 1
Learning Outcomes: 22.214.171.124,5
Students will be marked on tutorial participation, students are expected to provide verbal answers to tutorial questions, this will count 10% of the final mark. In order for this activity to be valuable students are encouraged to attempt each week’s tutorial prior to meeting in the computer laboratory/online. Students will be marked on the accuracy of answers but will also be rewarded for attempting to answer the question regardless of accuracy. 50 % of each week’s participation mark will go towards attempting to answer, 50 % will go towards accuracy. I will take each person’s ten best tutorial marks for the final mark. Marks will be uploaded each week to Wattle's Gradebook.
Assessment Task 2
Learning Outcomes: 126.96.36.199,5,6
There will be a R based assignment due in either week 9 or week 10, depending on the date of the mid-semester exam, a decision will be made at the end of week 2. Students must submit the assignment through turnitin or in the Wattle assignment app. The assignment will be posted on Wattle at least 2 weeks before the due date. Assignments will be returned no later than 3 weeks after submission.
Assessment Task 3
Learning Outcomes: 188.8.131.52,5,6
This will be held in either week 6 or week 7, a decision will be made by the university timetabling division. It will cover all the material we have covered in class and tutorials by that date. The exam is 120 minutes long. There may be a computer programming component depending on the size of the class. The exam questions will be in pdf form, answers should be submitted as RMarkdown document converted to pdf (this will be taught in the course). Details will be posted on Wattle and announced in class by week 4. Exams will be returned no later than 3 weeks after the exam.
Assessment Task 4
Learning Outcomes: 184.108.40.206,5,6
An online final examination will be held according to the published university schedule posted at http://timetable.anu.edu.au/. It is the student’s responsibility to be informed about changes to the examination timetable. The examination material of the final examination will be everything covered in the lectures, including material already covered in the mid-semester examination.
The exam will be approximately 2.5 hours long.
Questions will either be in the form of a Wattle quiz or downloadable pdf document. Your answers will either be done on Wattle or uploaded in Wattle as a pdf. Which of the two will be determined once the course commences. More details will be announced in class during week 10.
Academic integrity is a core part of the ANU culture as a community of scholars. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.
The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.
The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.
The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.
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.
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 not permitted. If submission of assessment tasks without an extension after the due date is not permitted, a mark of 0 will be awarded.
The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material.
Through Turnitin or on the Wattle assignment app.
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.
Resubmission of Assignments
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).
- ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
- ANU Access and inclusion for students with a disability or ongoing or chronic illness
- ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
- ANU Academic Skills and Learning Centre supports you make your own decisions about how you learn and manage your workload.
- ANU Counselling Centre promotes, supports and enhances mental health and wellbeing within the University student community.
- ANUSA supports and represents undergraduate and ANU College students
- PARSA supports and represents postgraduate and research students
Economic History, Development Economics
AsPr Martine Mariotti