- Class Number 3062
- Term Code 2930
- Class Info
- Unit Value 6 units
- Mode of Delivery In Person
- AsPr Kailing Shen
- 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
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.
Upon successful completion, students will have the knowledge and skills to:
- Explain the principles and purpose of Monte Carlo simulation methods.
- Explain parametric and nonparametric curve fitting methods.
- Explain econometric concepts such as causality, endogeneity, confounding factors, selection, and simultaneity.
- Explain econometric techniques for estimating causal effects.
- Appreciate econometric research and journal articles using the techniques discussed.
- Investigate the properties of econometric techniques using Monte Carlo simulation.
- Identify issues and problems (such as endogeneity) in empirical applications which may affect the analysis or the interpretation of estimates and tests.
- Use Stata to manage and analyse data.
- Carry out an empirical analysis of data using the econometric techniques discussed.
- Interpret the findings in an empirical analysis, and discuss caveats and potential problems.
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.
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
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.
RSE has a Frequently Asked Questions page where you can find relevant policies and information on a broad range of topics
|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 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 task||Value||Due Date||Return of assessment||Learning Outcomes|
|Assignment 1: cross sectional data analysis||15 %||08/03/2019||18/03/2019||18.104.22.168|
|Assignment 2: panel data analysis||15 %||29/03/2019||23/04/2019||22.214.171.124|
|Assignment 3: regression specifications and interpretations||15 %||03/05/2019||13/05/2019||126.96.36.199|
|Final Exam||55 %||06/06/2019||04/07/2019||188.8.131.52|
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:
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.
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.
There will be a formal final exam for this course. Details will be announced through Wattle and on class.
Assessment Task 1
Learning Outcomes: 184.108.40.206
Assignment 1: cross sectional data analysis
- Use Stata to summarize the cross sectional data provided and interpret your numeric answers.
- 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
Learning Outcomes: 220.127.116.11
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
Learning Outcomes: 18.104.22.168
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
Learning Outcomes: 22.214.171.124
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 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.
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.
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.
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.
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. 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
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
Labour economics, public policy, applied econometrics, Chinese economics
AsPr Kailing Shen