- Class Number 7745
- Term Code 3160
- Class Info
- Unit Value 6 units
- Mode of Delivery In Person
- AsPr Martine Mariotti
- AsPr Martine Mariotti
- 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
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 that is permitted in an examination room will be updated on course wattle, “Exams related” section
There will not be designated textbooks, but the following books 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 Chiffley 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). 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.
Online lecture delivery, prerecorded lectures. Tutorials will be both online and in person, students may choose which option to attend however we cannot accommodate switching formats during the semester.
|Week/Session||Summary of Activities||Assessment|
|1||Introduction Randomized Experiments||Computer laboratory|
|2||Directed Acyclical Graphical (DAG) Model||Lab and Tutorial 1|
|3||Regression Discontinuity Design||Lab and Tutorial 2|
|4||Regression Discontinuity Design||Lab and Tutorial 3|
|5||Panel Data||Lab and Tutorial 4|
|6||Difference in differences design||Lab and Tutorial 5 Midterm exam Or|
|7||Instrumental Variables||Lab and Tutorial 6 Midterm exam|
|8||Instrumental Variables||Lab and Tutorial 7|
|9||Synthetic Control||Lab and Tutorial 8 - Assignment Due Or|
|10||Matching||Lab and Tutorial 9 - Assignment Due|
|11||Matching||Lab and Tutorial 10|
|12||Randomization Inference and Bootstrapping||Lab and Tutorial 11|
Tutorials will be delivered remotely live via zoom for this semester. Sign up for tutorials will be available on the Wattle course site in o-week where more details can be found.
|Assessment task||Value||Learning Outcomes|
|In tutorial participation||10 %||1,2,3,4,5|
|Midterm Exam||25 %||1,2,3,4,5,6|
|Final Exam||40 %||1,2,3,4,5,6|
* 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 Misconduct Rule before the commencement of their course. Other key policies and guidelines include:
- Student Assessment (Coursework) Policy and Procedure
- Special Assessment Consideration Policy and General Information
- Student Surveys and Evaluations
- Deferred Examinations
- Student Complaint Resolution Policy and Procedure
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 Integrity . 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.
Due to continued travel restrictions this course will be delivered through online platforms. Aspects of the delivery will be asynchronous. However, there will be live lectures/tutorials/workshops also taking place. 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. Details will be announced through Wattle and in class.
Assessment Task 1
Learning Outcomes: 1,2,3,4,5
In tutorial participation
Students will be required to contribute to discussions in the weekly live zoom tutorial. Each student will need to discuss their solutions in the tutorial. Marks will be awarded for contribution to the discussion and not whether the answers are right or wrong. Students will be given a mark based on their 10 best tutorials out of 11. Feedback will be given after tutorial 5.
Assessment Task 2
Learning Outcomes: 1,2,3,4,5,6
There will be a R based assignment due in either week 8 or week 9, depending on the date of the mid-semester exam, this decision will be made by the end of week 2. Students must submit the assignment through turnitin. 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: 1,2,3,4,5,6
This will be held in either week 6 or week 7, this decision will be made by the end of week 2. 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: 1,2,3,4,5,6
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 11.
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.
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.
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.
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 Diversity 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
AsPr Martine Mariotti
AsPr Martine Mariotti