ECON 7204 - Econometrics IV
North Terrace Campus - Semester 1 - 2024
General Course Information
Course Code ECON 7204 Course Econometrics IV Coordinating Unit Economics Term Semester 1 Level Postgraduate Coursework Location/s North Terrace Campus Units 3 Contact Up to 4 hours per week Available for Study Abroad and Exchange Y Incompatible ECON 4014 Assumed Knowledge ECON 7243 Course Description The objective of this course is to study more advanced topics in econometrics. Students are expected to have knowledge in statistics and multiple regression models at the level of Econometrics III/PG or equivalent. Topics typically include linear regression models, instrument variables (IV) estimation, generalized method of moment (GMM), maximum likelihood estimation (MLE), limited dependent variable (LDV) models, treatment effect and sample selection corrections, panel data methods, Monte Carlo simulations and bootstrap methods. The emphasis is on understanding the models and the related theories. Through the course, we will apply the theories developed to real-world data and interpret the estimation results in many different respects.
Course Coordinator: Professor Firmin Doko TchatokaOffice location: Nexus 10, Level 4, Room 4.47
Telephone: 8313 1174
The full timetable of all activities for this course can be accessed from Course Planner.
The detailed list of topics will be given in the first class and posted on MyUni.
Course Learning OutcomesOn successful completion of this course, students will be able to:
- Use various advanced econometric models, estimation methods and related econometric theories.
- Apply the above theories to empirical data or be able to develop new econometric theory.
- Use statistical packages like STATA, MATLAB, R or Python to estimate econometric models using real world data.
University Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
University Graduate Attribute Course Learning Outcome(s)
Attribute 1: Deep discipline knowledge and intellectual breadth
Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.
Attribute 2: Creative and critical thinking, and problem solving
Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.
Attribute 3: Teamwork and communication skills
Graduates convey ideas and information effectively to a range of audiences for a variety of purposes and contribute in a positive and collaborative manner to achieving common goals.
Attribute 4: Professionalism and leadership readiness
Graduates engage in professional behaviour and have the potential to be entrepreneurial and take leadership roles in their chosen occupations or careers and communities.
Attribute 5: Intercultural and ethical competency
Graduates are responsible and effective global citizens whose personal values and practices are consistent with their roles as responsible members of society.
Required ResourcesLecture notes will be posted on MyUni before each lecture.
Marno Verbeeck A Guide to Modern Econometrics 4th Edition, A John Willey & Sons, Ltd, 2012
Matlab Available on the computers in Honours student room, PhD student room,
and the computer lab (10 Pulteney 217 Computer Suite 2 and Computer
2 Stata Available on the computers in Honours student room, PhD student room,
and the computer lab (10 Pulteney 217 Computer Suite 2 and Computer Suite 3)
NB: Students are encouraged to use software other than the ones listed here. However, they must ensure that the software is appropriate for their project. Students who use computers connected to the University network can request ITS to install Matlab on their machines.
A.C. Cameron and P.K. Travedi Microeconometrics: Methods and Applications Cambridge University Press, 2005 J.M. Wooldridge Econometric Analysis of Cross Section and Panel Data MIT Press, 2002 F. Hayashi Econometrics Princeton University Press, 2000 P. A. Ruud An Introduction to Classical Econometric Theory Oxford, 2000. J. Hamilton Time Series Analysis Princeton University Press, 1994
NB: Lecture notes will be put on the course webpage before each lecture. Students need to print out lecture notes and bring them to class.
1 Check your student email often as course-related announcements are communicated via email 2 MyUni All the materials such as lecture notes, problem sets and their answer keys, Matlab manual, etc. will be posted on the MyUni course webpage, www.myuni.adelaide.edu.au
Learning & Teaching Activities
Learning & Teaching Modes
2 Reading textbooks 3 Just in time teaching (JiTT) assessment 4 Problem solving and computer exercises 5 Empirical Project
NB: It is important for students to be able to apply what they learn in class to real world data by using computer programs
such as Matlab, Gauss, C++, R and Stata.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.Any student in this course is expected to attend all lectures, workshops and labs throughout the semester.
JiTT 3 hours/week Additional readings and empirical project 2 hours/week Problem solving and computer exercises 2 hours/week
NB: The above guide is for private study, that is, study outside of your regular classes.
Learning Activities Summary
Teaching & Learning Activities Related Learning Outcomes Lectures 1 Readings 1 Problem solving and computer exercises 2,3
TENTATIVE LECTURE SCHEDULE (subject to changes)
WEEK CHAPTERS TOPICS 1 Review of the classical multivariate linear model: estimation, inference, and violation of basic assumptions 2 Instrumental variables methods and GMM 3 Nonlinear least squares (NLS) and Maximum likelihood (ML) estimations 4 Models With Limited Dependent Variables 5 Models Based on Panel data 6 Sample Selection and Treatment Effects
The University's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Assessment SummaryThe final mark for this course will be determined by:
Assessment Task Task Type Due Weighting Learning Outcome Just in Time Teaching (JiTT) Readings Refer to MyUni 10% 1 Homework and Computer Exercises Problem solving and computing Refer to MyUni 30% 1,3 Empirical project Formative, reading and computing Refer to MyUni 20% 2,3 Final Exam Formative, problem solving and computer exercises Refer to MyUni 40% 1,2
Assessment Detail1. Just in Time Teaching (JiTT)
In the unit I plan to use the Just in Time Teaching (JITT) technique. You will be required to read some material before the relevant workshop and lecture. I will post the questions on MyUni. There will be three questions that will be covered in the following week’s lecture, workshops and labs. You will submit your answers by Saturday 5pm. It is important to bear in mind that while you will not be assessed on the content of your answers I will nevertheless use the JiTT assessments to form a question in the midterm and final exams. I will also form view of the effort you are putting into being prepared for the following week’s class—I read your submissions before the Monday class. The mark here is an incentive to encourage you to participate rather than an assessment of the content.
2. Homework and Computer Exercises
Problem sets and computer exercises will be given to you fortnightly. Details (including submission dates) will be provided on MyUni and discussed with students in lectures. Late submission will be accepted only if accompanied by appropriate documentation, for example, a medical certificate. Each student must write and turn in her/his own homework to me right before lecture begins in class on the due date. Students must write their name and student ID number on the cover sheet.
3. Empirical Project
Students must complete an applied econometric study of an economic or financial relationship and answer a research question that they pose. The maximum length of the final version of the project is 15 pages + references + appendix. Students must replicate one of the following paper:
1. Fama, E. and French, K., 2004. Common Risk Factors in the Returns on Stocks and Bonds. Journal of Financial Economics, (33) 3-56.
2. I. Mourife and A. Siow, 2000. The Cobb Douglas Marriage Matching Function: Marriage matching with peer effects, 2021. Journal of Labor Economics.
3. Daron Acemoglu, Simon Johnson, James A. Robinson, 2001. The Colonial Origins of Comparative Development: An Empirical Investigation. American Economic Review, 91(5) 1369-1401.
4. Graddy, K., 1995. Testing for Imperfect Competition at the Fulton Fish Market. The RAND Journal of Economics, (26) 75-92.
5. Narayan, P., Narayan, S., and Prasard, A., 2008. Understanding the Oil Price-exchange Rate Nexus for the Fiji Islands. Energy Economics (30) 2686-2696.
6. Nunn, Nathan, and Leonard Wantchekon, 2011. The Slave Trade and the Origins of Mistrust in Africa. American Economic Review, 101(7) 3221–3252.
7. Esther Duflo, Pascaline Dupas and Michael Kremer, 2015. Education, HIV and Early Fertility: Experimental Evidence from Kenya.
American Economic Review, 105(9), pp. 2257-97.
8. Susan Athey, Jonathan Levin and Enrique Seira, 2011. Comparing Open and Sealed Bid Auctions: Theory and Evidence from Timber Auctions. Quarterly Journal of Economics, vol. 126(1), 207-257.
The project is divided in three parts: A, B, and C.
Project Part A (due date: Week four of March): Must contain the abstract and data description
1. Clearly state the question that you will be investigating. Do not repeat the abstract from the source paper.
2. Provide the source of the data or the name of the database that you are planning to use.
3. Speculate what type of results you would expect to get in answer to your stated question.
Expected length: 1 page
4. Type of data (e.g. panel, time series, cross sectional, pooled cross sectional, etc.).
6. Dimensions of your data.
7. List variables that you will be using for your project.
8. Provide 5-point summary for all variables used in your analysis.
9. Graph your data and interpret the results (stationarity, seasonality, trends, structural breaks…).
Expected length: 3-4 pages
Project Part B (due date: Week four of April): Residual Analysis
In this part of the assessment you have to specify and test the data selected for your project with your chosen models. Justify the models’ selection through residual analysis and additional tests (you will have to determine which tests will be applicable for your chosen data type and chosen models).
Expected length: 2-3 pages
Project Part C (due date: week two of June): Final Empirical Project
The term paper is your opportunity to construct a model and analyze it using econometric methods. A good paper will have the following format structure:
1. Introduction (modified and improved Project Part A)
a. Why do we care?
b. What else is known about this problem?
c. What are the limitations of previous studies?
a. Data collection
b. Sources and Descriptive statistics (modified and improved Project Part A)
3. The model
a. Estimation and Testing
b. Residual analysis (modified and improved Project Part B)
a. What are the main findings?
b. Do you find the empirical results convincing?
c. Interpret your findings and stress their significance
a. Summary of main contributions
b. How do you think the study could be improved?
6. Reference List
Each term paper will have an assignment submission cover page. Projects should be up to 15 pages of text (with all references cited in the appropriate text), bibliography, tables and figures, and any appendix material. You must include all relevant computer printouts including one that clearly lists your data in a compact. Your grade will depend on your mastery of the relevant econometric theory and the organization of your paper.
4. Final Exam
2 hours multi-part problem solving questions: will cover all the lectures, JiTT, Homework and Computer Exercises, and labs. Written sample answers will not be provided. Help with questions that you have made a genuine attempt to answer may be provided by your lecturer/tutor either individually or in a group.
SubmissionRefer to ASSESSMENT DETAIL. After being marked, generally, the assessment will be returned to students in class about a week after
Grades for your performance in this course will be awarded in accordance with the following scheme:
M10 (Coursework Mark Scheme) Grade Mark Description FNS Fail No Submission F 1-49 Fail P 50-64 Pass C 65-74 Credit D 75-84 Distinction HD 85-100 High Distinction CN Continuing NFE No Formal Examination RP Result Pending
Further details of the grades/results can be obtained from Examinations.
Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.
Final results for this course will be made available through Access Adelaide.
If a student receives 45-49 for their final mark for the course they will automatically be granted an additional assessment. This will most likely be in the form of a new exam (Additional Assessment) and will have the same weight as the original exam unless an alternative requirement (for example a hurdle requirement) is stated in this semester’s Course Outline. If, after replacing the original exam mark with the new exam mark, it is calculated that the student has passed the course, they will receive 50 Pass as their final result for the course (no higher) but if the calculation totals less than 50, their grade will be Fail and the higher of the original mark or the mark following the Additional Assessment will be recorded as the final result.
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