• Class Number 7449
• Term Code 3260
• Class Info
• Unit Value 6 units
• Mode of Delivery In Person
• COURSE CONVENER
• AsPr Martine Mariotti
• LECTURER
• 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
SELT Survey Results

Applied micro-econometrics (EMET8001)

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. Students will be required to present an econometric paper by summarising the hypothesis and results of the paper, placing it in the literature and critiquing the implementation of the paper.

## Learning Outcomes

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

1. explain econometric concepts such as causality, endogeneity, confounding factors, selection, and simultaneity;
2. explain econometric techniques for estimating causal effects;
3. investigate the properties of econometric techniques using Monte Carlo simulation;
4. use statistical software to manage and analyse data;
5. carry out an empirical analysis of data using the econometric techniques discussed;
6. interpret the findings in an empirical analysis, and discuss caveats and potential problems.

## Research-Led Teaching

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

## Required Resources

We will be using a computer program called R. R is on ANU computers and can also be installed on students' devices. I will provide instructions for installing R in class.

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 Chiffley Library.

## Staff Feedback

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

• feedback to whole class, groups, individuals, focus group etc

## 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

Students are to participate in either an online tutorial or an in class tutorial. We cannot accommodate changes to this participation during the semester.

## Class Schedule

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 Randomization Inference and Bootstrapping Lab and Tutorial 9 - Assignment Due
11 Matching Lab and Tutorial 10
12 Matching Lab and Tutorial 11

## Tutorial Registration

Tutorials will be in person on campus. If there are students who cannot be in Canberra we will organise a live online arrangement. 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 Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Group or Individual Presentation 10 % * * 1,2,3,4,5
Assignment 25 % * * 1,2,3,4,5,6
Midterm Exam 25 % * * 1,2,3,4,5,6
Final Exam 40 % * * 1,2,3,4,5,6
Tutorial 1 0 % 05/08/2022 12/08/2022

* 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 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.

## Participation

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.

## Examination(s)

There will be a formal final exam for this course. Details will be announced through Wattle and in class.

Value: 10 %
Learning Outcomes: 1,2,3,4,5

Group or Individual Presentation

Students will be split into groups and each group given a research paper to summarize and present in the tutorial session. The presentation will count 10 % to the final mark. Groups and presentation dates will be organised at the start of the semester, papers will be given out 2 weeks prior to the presentation due date. Presentations to start in week 3. Presentations will be recorded. Presentations may be individual rather than group depending on enrolments.

Value: 25 %
Learning Outcomes: 1,2,3,4,5,6

Assignment

There will be a R based assignment due in either week 8 or week 9, 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. 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.

Value: 25 %
Learning Outcomes: 1,2,3,4,5,6

Midterm Exam

This will be held in either week 6 or week 7, a decision will be made by the university exam 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.

Value: 40 %
Learning Outcomes: 1,2,3,4,5,6

Final Exam

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.

Value: 0 %
Due Date: 05/08/2022
Return of Assessment: 12/08/2022
Learning Outcomes:

Tutorial 1

Students are required to hand in the answers to tutorial 1 done in RMarkdown so I can assess whether they have mastered the installation of the software as well as installed their libraries and have a general working knowledge of R.

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.

## 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 not permitted. If submission of assessment tasks without an extension after the due date is not permitted, 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.

In tutorial

## 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.

none

## 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.
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.

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

 AsPr Martine Mariotti martine.mariotti@anu.edu.au

### Research Interests

Economic History, Development Economics

### AsPr Martine Mariotti

 Tuesday 14:00 15:00 Tuesday 14:00 15:00

## Instructor

 AsPr Martine Mariotti martine.mariotti@anu.edu.au

### AsPr Martine Mariotti

 Tuesday 14:00 15:00 Tuesday 14:00 15:00