Econ 3050 Course Outline

Course Title: Undergraduate Econometrics 2Course Code: Econ 3050Level: 3Semester: 2Credits: 3Pre-requisites: Econ 3049

Course DescriptionThis course covers advanced time series topics such as vector autoregressions, ARIMA modelling and cointegration. In addition to this the course will provide an introduction to panel data methods. Students are expected to have proper knowledge of what was taught in Econ 3049. Please revise accordingly if you do not. You are also expected to use your knowledge of Econometric Views in this course. If you do not have prior knowledge of this programme, I advise that you gain experience with it by reading the help files and actually doing some work with it on your own. Some knowledge of matrix algebra is expected and you will be referred accordingly during the class to material that will assist you in that area.

PurposeThis course is important to the students in the BSc. Economics programme because it shows students how the different aspects of economics may be combined to produce a scientific approach that can be used to find solutions to economic problems. Both students who intend to pursue graduate studies and those who wish to enter the workforce will benefit from this course. Graduate work in the area of economics usually calls for some prior econometric knowledge. Doing this course will give you the added advantage. In the workplace employers often ask for econometric training. This will be an asset to your future employer.

Instructor InformationName: Varuna L. RamlalOffice address and phone: TBAEmail address: varuna.ramlal@gmail.com; varuna.ramlal@sta.uwi.eduOffice hours: Wednesday 2-3pm (appointments also permitted)Preferred method of contact: Email

Letter to the Student Dear Student,I am very pleased that you have chosen to pursue Undergraduate Econometrics 2. This course will be challenging but rewarding. I am very enthusiastic about it and I assure you that I will do my best to ensure that you enjoy learning and practicing econometrics as much as I do. I do have certain expectations of you and I will outline them as follows: attend ALL your lectures AND tutorials (there are regulations about this, see the Additional Information section); make a habit of reading before class even if you think you will not understand because when I explain in class you will remember what you read or where you had problems understanding things; practice questions from the START; coordinate your groups early and finally, do not hesitate to come to office hours or make an appointment if you think you need further assistance with the course material.Let us all enjoy the semester and work hard!

Regards,Varuna L. Ramlal.

1

Content

Week Topic Readings (see Resources section for books)

Objectives

1 Maximum Likelihood Estimation (MLE)

Chapter 9 WT - Understand what maximum likelihood estimation means and why it is necessary- Recall properties of MLE- Understand proofs

2 Wald, Likelihood Ratio and Lagrange Multiplier tests

Chapter 10 WT - Be able to explain each test- Understand how they differ and how they are similar- Know the test statistics- Be able to interpret output

3 Specification and other tests of Model Authenticity

Chapter 11 WT - Understand each test- Ensure that you understand the output- Be able to carry out and interpret the results of each test

4 Stationarity and Unit Roots Chapter 12 WT - Define unit roots- Be able to use the ACF and PACF- Use and interpret other formal unit root tests

5, 6 Introduction to ARIMA modelling Chapter 13 WT - Identify AR(p), MA(q) and ARMA(p,q) processes- Determine if a model is ARIMA- Use the Box-Jenkins iterative process- Detect seasonality- Interpret output

7, 8 Vector Autoregression modelling with some applications

Chapter 14 WT - Understand what a VAR is- Interpret a VAR using the Impulse Response and Variance Decomposition- Causality using a VAR

9, 10 Cointegration Chapter 15 WT - Understand cointegration theory- Engle Granger as a foundation- Johansen procedure for application

11, 12 Introduction to Panel Data Chapters 13, 14 Wooldridge

- Pooling cross sections- Two-period panel analysis- Applications- Fixed effects vs Random effects

13 Revision

Goals/Aims– Students should understand the difference between classical and modern econometric techniques– Student should be able to apply the techniques taught in this course

2

Assignment – You will be required to do an INDIVIDUAL project using the same data from part 1 (ECON3049). It does not matter if several people use the same data set. This is in fact expected since the first course required a group project.– Use the techniques taught in this course to analyse the dataset and comment on the suitability of modern econometric techniques for that dataset versus the method of analysis you used. – Conduct some of the tests outlined in the course.– Due date: April 4th 2012. – Course weighting – 25% (Penalty for late submission – 5% for every day that you are late)– Submission rules: both a soft and hard copy should be submitted. Email the soft copy to me at varuna.ramlal@gmail.com or varuna.ramlal@sta.uwi.edu

Course Assessment1. Project (details listed above)2. Final examination (2 hours) – there will be NO choice in the final examination. Course weighting – 75%

Teaching Strategies1. Lectures2. Tutorials3. In-class discussions4. Projects

ResourcesTextbooks:1. Watson, Patrick K. and Sonja S. Teelucksingh. 2002. A Practical Introduction to Econometric Methods: Classical and Modern. University of the West Indies Press. (WT)2. Wooldridge, Jeffrey M. 2009. Introductory Econometrics: A Modern Approach. 4 th edition. SouthWestern.Other:3. Myelearning site – course code ECON3050

How to Study for this course – Read the chapters before class– Attend lectures AND tutorials (see regulation about this in the following section)– Do questions and past papers – Use additional resources to help you understand the course material

Additional Information

- University Policy concerning attendance: In general students must maintain a 75% attendance at lectures AND tutorials. The regulation is as follows: Examination Regulations for First Degrees, Associate Degrees, Diplomas and Certificates including GPA Regulations;General Examination Regulation:

19. Any candidate who has been absent from the University for a prolonged period during the teaching of a particular course for any reason other than illness or whose attendance at prescribed lectures, classes, practical classes, tutorials, or clinical instructions has been unsatisfactory or who has failed to submit essays or other exercises set by his/her teachers, may be debarred by the

3

relevant Academic Board, on the recommendation of the relevant Faculty Board, from taking anyUniversity examinations. The procedures to be used shall be prescribed in Faculty Regulations.

- University Policy concerning cheating: Cheating

97. (i) Cheating shall constitute a major offence under these regulations. (ii) Cheating is any attempt to benefit one's self or another by deceit or fraud. (iii) Plagiarism is a form of cheating (iv) Plagiarism is the unauthorized and/ or unacknowledged use of another person's intellectual effort and creations howsoever recorded, including whether formally published or in manuscript or in typescript or other printed or electronically presented form and includes taking passages, ideas or structures from another work or author without proper and unequivocal attribution of such source(s), using the conventions for attributions or citing used in this University.

103. (i) If any candidate is suspected of cheating, or attempting to cheat, the circumstances shall be reported in writing to the Campus Registrar. The Campus Registrar shall refer the matter to the Chairman of the Campus Committee on Examinations. If the Chairman so decides, the Committee shall invite the candidate for an interview and shall conduct an investigation. If the candidate is found guilty of cheating or attempting to cheat, the Committee shall disqualify the candidate from the examination in the course concerned, and may also disqualify him/her from all examinations taken in that examination session; and may also disqualify him/her from all further examinations of the University, for any period of time, and may impose a fine not exceeding Bds$300.00 or J$5000.00or TT$900.00 or US$150.00 (according to campus). If the candidate fails to attend and does not offer a satisfactory excuse prior to the hearing, the Committee may hear the case in the candidate's absence.

Grading System– The University now uses the GPA method which allows the students GPA scores as follows:

GRADE MARK GPA

A+ 86 and over 4.3

A 70-85 4.0

A- 67-69 3.7

B+ 63-66 3.3

B 60-62 3.0

B- 57-59 2.7

C+ 53-56 2.3

C 50-52 2.0

C- 47-49 1.7

D+ 43-46 1.3

D 40-42 1.0

F Less than 40 0.0

4