• Class Number 3062
  • Term Code 2930
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
  • COURSE CONVENER
    • AsPr Kailing Shen
  • LECTURER
    • AsPr Kailing Shen
  • Class Dates
  • Class Start Date 25/02/2019
  • Class End Date 31/05/2019
  • Census Date 31/03/2019
  • Last Date to Enrol 04/03/2019
SELT Survey Results

The overall aim of the course is to introduce students to the practical application of micro-econometric methods. Micro-econometrics is concerned mainly with the analysis of crosssectional and short panel data from individuals, households, firms, regions etc. (Macro-econometrics is concerned mainly with analysing economic time series and long panel data from one or more countries.) The course goes beyond the linear regression models used to estimate simple associations between dependent and independent variables. It covers nonlinear models used to analyse for example discrete and censored dependent variables, and it covers estimation of causal effects as opposed to associations. The necessary econometric theory will be covered/reviewed and numerous applications will be discussed. In addition, practical aspects of data analysis will be discussed using the software Stata.

Learning Outcomes

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

  1. Explain the principles and purpose of Monte Carlo simulation methods.
  2. Explain parametric and nonparametric curve fitting methods.
  3. Explain econometric concepts such as causality, endogeneity, confounding factors, selection, and simultaneity.
  4. Explain econometric techniques for estimating causal effects.
  5. Appreciate econometric research and journal articles using the techniques discussed.
  6. Investigate the properties of econometric techniques using Monte Carlo simulation.
  7. Identify issues and problems (such as endogeneity) in empirical applications which may affect the analysis or the interpretation of estimates and tests.
  8. Use Stata to manage and analyse data.
  9. Carry out an empirical analysis of data using the econometric techniques discussed.
  10. 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

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.

Staff Feedback

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

  • written comments
  • verbal comments
  • feedback to the whole class
  • to groups
  • to individuals

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

Other Information

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/

Class Schedule

Week/Session Summary of Activities Assessment
1 Data types by dimensions and sources lab (Introduction to Stata)
2 Empirical micro-economics research: an overview lab (More on Stata), assignment 1 due by Friday 5pm
3 Journal paper discussion I: a classical example of descriptive study lab
4 Identification topic I: choice of control variables (why? Omitted variable bias formula? Potential problems & caveats?) lab, assignment 1 returned by Monday 5pm
5 Journal paper discussion II: a classical example of dif-dif study lab, assignment 2 due by Friday 5pm
6 Identification topic II: dif-dif and fixed effect approach (why? How? Potential problems & caveats?) lab
7 Journal paper discussion III: a classical example of IV study lab, assignment 2 returned by Monday 5pm
8 Identification topic III: instrumental variable approach (why? How? Potential problems & caveats?) lab, assignment 3 due by Friday 5pm
9 Journal paper discussion IV: a classical example of regression discontinuity study lab
10 Identification topic IV: regression discontinuity approach (why? How? Potential problems & caveats?) lab, assignment 3 returned by Monday 5pm
11 A more generalized perspective on IV: the concepts of LATE, ATT lab
12 Propensity matching versus regression lab
13 Examination Period Final Exam

Tutorial Registration

Tutorial signup for this course will be done via the Wattle website. Detailed information about signup times will be provided on Wattle or during your first lecture. When tutorials are available for enrolment, follow these steps:

1.           Log on to Wattle, and go to the course site

2.           Click on the link “Tutorial enrolment”

3.           On the right of the screen, click on the tab “Become Member of…..” for the tutorial class you wish to enter

4.           Confirm your choice

If you need to change your enrolment, you will be able to do so by clicking on the tab “Leave group….” and then re-enrol in another group.  You will not be able to enrol in groups that have reached their maximum number.  Please note that enrolment in ISIS must be finalised for you to have access to Wattle

Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Assignment 1: cross sectional data analysis 15 % 08/03/2019 18/03/2019 1.2.3.4
Assignment 2: panel data analysis 15 % 29/03/2019 23/04/2019 1.2.3.4
Assignment 3: regression specifications and interpretations 15 % 03/05/2019 13/05/2019 1.2.3.4
Final Exam 55 % 06/06/2019 04/07/2019 1.2.3.4

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.

Participation

Active participation and discussion will be expected. The participation will be judged by the quantity and quality of discussion on class.

Details of Assessment Tasks will announced through Wattle and on class.

 

Examination(s)

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

Assessment Task 1

Value: 15 %
Due Date: 08/03/2019
Return of Assessment: 18/03/2019
Learning Outcomes: 1.2.3.4

Assignment 1: cross sectional data analysis

  1. Use Stata to summarize the cross sectional data provided and interpret your numeric answers.
  2. Use Stata to address several open questions regarding individuals' behaviours.

This is an assignment to be done individually. The assignment will be given in week 1. The answers for part 1 is usually one sentence and the answers for part 2 is no more than 2 paragraphs. The assignment will be returned online through wattle. More details will be provided on course wattle later.

Assessment Task 2

Value: 15 %
Due Date: 29/03/2019
Return of Assessment: 23/04/2019
Learning Outcomes: 1.2.3.4

Assignment 2: panel data analysis

  • Use Stata to summarize the panel data provided and interpret your numeric answers.
  • Use Stata to create graphs to describe individuals' behaviour over time.

This is an assignment to be done individually. The assignment will be given in week 3. The answers for part 1 is usually one sentence and the answers for part 2 is no more than 2 paragraphs besides the graphs. The assignment will be returned online through wattle. More details will be provided on course wattle later.

Assessment Task 3

Value: 15 %
Due Date: 03/05/2019
Return of Assessment: 13/05/2019
Learning Outcomes: 1.2.3.4

Assignment 3: regression specifications and interpretations

  • interpret the results and coefficients of several different regression specifications;
  • propose a research question as required

This is an assignment to be done individually. The assignment will be given in week 6. The answers for part 1 is usually one paragraph and the answers for part 2 is no more than 2 paragraphs. The assignment will be returned online through wattle. More details will be provided on course wattle later.

Assessment Task 4

Value: 55 %
Due Date: 06/06/2019
Return of Assessment: 04/07/2019
Learning Outcomes: 1.2.3.4

Final Exam

The final exam will cover all the materials discussed throughout the semester. The exam will be 2 hours with no permitted materials.This is an exam to be done individually. The final exam will have multiple choice questions, true or false questions as well as short problems. We will not need computer lab for the exam. Details will be announced through course Wattle later.

Academic Integrity

Academic integrity is a core part of our culture as a community of scholars. At its heart, academic integrity is about behaving ethically. This means that all members of the community commit to honest and responsible scholarly practice and to upholding these values with respect and fairness. The Australian National University commits to embedding the values of academic integrity in our teaching and learning. We ensure that all members of our community 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 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 University has policies and procedures in place to promote academic integrity and manage academic misconduct. Visit the following Academic honesty & plagiarism website for more information about academic integrity and what the ANU considers academic misconduct. The ANU offers a number of services to assist students with their assignments, examinations, and other learning activities. The Academic Skills and Learning Centre offers a number of workshops and seminars that you may find useful for your studies.

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) as 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

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

Through Turnitin

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.

Resubmission of Assignments

Students wish to resubmit some or all assignments will need to get the permission from the course convenor

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).

AsPr Kailing Shen
6125 3903
kailing.shen@anu.edu.au

Research Interests


Labour economics, public policy, applied econometrics, Chinese economics

AsPr Kailing Shen

Tuesday 15:00 16:00
Tuesday 15:00 16:00
Wednesday 13:00 14:00
Wednesday 13:00 14:00
AsPr Kailing Shen
6125 3903
kailing.shen@anu.edu.au

Research Interests


AsPr Kailing Shen

Tuesday 15:00 16:00
Tuesday 15:00 16:00
Wednesday 13:00 14:00
Wednesday 13:00 14:00

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