Office location: Nexus 10, Level 4, Room 4.47
Telephone: 8313 1174

The detailed list of topics will be given in the first class and posted on MyUni.

On successful completion of this course, students will be able to:

1. Use various advanced econometric models, estimation methods and related econometric theories.
2. Apply the above theories to empirical data or be able to develop new econometric theory.
3. Use statistical packages like STATA or MATLAB to estimate econometric models using real world data.

Lecture notes will be posted on MyUni before each lecture.

Required Textbook

Marno Verbeeck		A Guide to Modern Econometrics		4th Edition, A John Willey & Sons, Ltd, 2012

Computer Software

1		Matlab		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)
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

1	E-mail	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

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		Lecture notes
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.

Any student  in this course is expected to attend all lectures, workshops and labs throughout the semester.

Lecture notes		2 hours/week
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.

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

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The 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	15%	1,3
Midterm Exam	Formative, problem solving and computer exercises	Refer to MyUni	15%	1,2
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

Due to the current COVID-19 situation modified arrangements have been made to assessments to facilitate remote learning and teaching. Assessment details provided here reflect recent updates.

To support the changes to teaching, the following revisions to assessment have been made:

Readings: 10%
Problem sets and computer exercise: 30%
Empirical project: 20%
Final exam: 40%.

N/A

1.  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. Midterm Exam (Not available  this year!)

1 h 30 min test containing short answer questions. The date will be posted on MyUni and discussed with students in lectures. There will be no supplementary exam for the midterm exam. If you miss this exam and you provide a medical certificate or compassionate reasons, your final exam will account for 55% (instead of 40%) of your total mark. Please note that, following University policy, dictionaries are not allowed in School of Economics exams. Students may NOT take any type of CALCULATOR to the exam.

4. 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. Clarida, R., Gali, J., and Gertler, M., 2000. Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory. Quaterly Journal of Economics, Feb, 147-180.

3.  Hamermesh, D. and Biddle, J., 1994. Beauty and the labour Market. American Economic Review, (84) 1174-1194.

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. Fair, R., 1978. A Theory of Extramarital Affairs. Journal of Political Economy (86) 45-61.


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

Abstract:

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

Data Description:

4. Type of data (e.g. panel, time series, cross sectional, pooled cross sectional, etc.).

5. Frequency.

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?

    2. Data

        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)

   4. Results

       a. What are the main findings? 

       b. Do you find the empirical results convincing? 

       c. Interpret your findings and stress their significance

   5. Conclusion   

       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.


5. 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.

Refer to ASSESSMENT DETAIL. After being marked, generally, the assessment will be returned to students in class about a week after
submission.

Additional Assessment
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.