ECON 2504 - Intermediate Econometrics II
North Terrace Campus - Semester 1 - 2016
General Course Information
Course Code ECON 2504 Course Intermediate Econometrics II Coordinating Unit School of Economics Term Semester 1 Level Undergraduate Location/s North Terrace Campus Units 3 Contact Up to 3 hours per week. Intensive in Summer Semester. Available for Study Abroad and Exchange Y Prerequisites ECON 1008 or STATS 1000 or equivalent Incompatible ECON 2006 & STATS 2002, STATS 2003 & MATHS 2103 Assumed Knowledge ECON 1004, ECON 1000, Maths as taught in ECON 1005 Course Description This course provides an introduction to the econometric techniques used to analyse data sets in economics, business and finance. It builds on basic statistics, inference and regression as covered in introductory statistics courses. The focus is on understanding the methods involved, using statistical software to provide the results and then interpreting and commenting on these results. The course reviews basic statistics, regression and inference, and then introduces multiple regression analysis, which remains the most commonly used statistical technique in econometrics. The remainder of the course considers various practical aspects of linear regression models and may include dummy variables, different functional forms and the consequences of violation of the classical regression assumptions.
Course Coordinator: Dr Nadya BaryshnikovaSummer School
Course Coordinator: Dr Patricia Sourdin
Office hours: TBA
Office location: TBA
Course Coordinator: Dr Nadya Baryshnikova
Office hours: TBA
Office location: Nexus 10, Level 4, Room 4.04
Telephone: 8313 4821
Dr Nicholas Sim
Office location: Nexus 10, Level 4, Room 4.46
Telephone: 8313 4927
Office hours: TBA
The full timetable of all activities for this course can be accessed from Course Planner.
Course Learning OutcomesThe course aims to achieve the following outcomes. It will provide students:
1. with knowledge on the fundamentals of econometrics and its application
2. with knowledge and proficiency on the use of statistical packages for econometric and statistical analysis
3. with the ability to conduct independent data analysis and inquiry using the tools of statistics and econometrics
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) Deep discipline knowledge
- informed and infused by cutting edge research, scaffolded throughout their program of studies
- acquired from personal interaction with research active educators, from year 1
- accredited or validated against national or international standards (for relevant programs)
1,2 Critical thinking and problem solving
- steeped in research methods and rigor
- based on empirical evidence and the scientific approach to knowledge development
- demonstrated through appropriate and relevant assessment
1,2,3 Teamwork and communication skills
- developed from, with, and via the SGDE
- honed through assessment and practice throughout the program of studies
- encouraged and valued in all aspects of learning
2,3 Career and leadership readiness
- technology savvy
- professional and, where relevant, fully accredited
- forward thinking and well informed
- tested and validated by work based experiences
2,3 Self-awareness and emotional intelligence
- a capacity for self-reflection and a willingness to engage in self-appraisal
- open to objective and constructive feedback from supervisors and peers
- able to negotiate difficult social situations, defuse conflict and engage positively in purposeful debate
The required textbook is Principles of Econometrics, 4th Edition, Wiley by R. Carter Hill, William E. Griffiths and Guay C. Lim.
The recommended book to accompany the required text is Using Stata for Principles of Econometrics, 4th Edition, by Adkins and Hill.
MyUni Course WebPage provides lecture notes and other course materials. Please check this page frequently for important announcements and corrections.
Learning & Teaching Activities
Learning & Teaching ModesClasses will meet three times a week: twice for a 1-hour lecture and once for a 1-hour tutorial depending on the time slot students sign up for. Office hours with the lecturer and tutors will be announced in due course. Please adhere strictly to the designated office hours.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.The standard undergraduate workload for a full-time student is 48 hours per week which equates to 12 hours per 3 unit course. This course has three hours of lectures and tutorials each week, which means that students should undertake nine hours of self-study each week of the teaching term.
Homework assignments are issued each week. Students are expected to work in groups on these assignments. In addition to the weekly group questions there will be three assignments to be submitted individually for a grade. All students may be asked to present their solutions during each tutorial session.
Learning Activities Summary
The tentative outline of the course (subject to change) is:
1. Introduction to Econometrics (HGL chapter 1)
2. Introduction to Basic Statistics and Probability (Probability Primer)
3. The Simple Linear Regression Model (Chapter 2)
4. Interval Estimation and Hypothesis Testing (Chapter 3)
5. Prediction, Goodness of Fit and Modeling Issues (Chapter 4)
6. The Multiple Linear Regression Model (Chapter 5)
7. Further Inference in the Multiple Regression Model (Chapter 6)
8. Using Indicator Variables (Chapter 7)
9. Heteoskedasticity (Chapter 8)
Specific Course RequirementsHomework completion may require access to STATA. If you do not have STATA at home, you may use the computer labs on campus. Please refer to http://www.adelaide.edu.au/its/student_support/labs/ for further details.
For course related questions, students are encouraged to utilise the designated office hours of the lecturer. Questions over the telephone are strongly discouraged.
Small Group Discovery ExperienceThere will be a Small Group Discovery Experience during two of the tutorials (most likely in Week 5 and Week 10). All students are expected to attend and participate.
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 SummaryStudents will be assessed based on the following:
Tutorial assignments (in groups) 20%
Individual homework assignments 30%
Small Group Discovery 5%
Final examination 45%
Assessment Related Requirements
Assessment Detail1. Tutorial homework will be posted each week. The students will be asked to form groups at the beginning of the course and do the exercises in these groups. No individual work will be accepted for this component. The group homework will be collected in tutorials. The tutor will mark one question of his/her choice. At the end of the course, best 7 out of 10 marks will count toward the semester grade for this component.
2. There will be 3 homework assignments to be submitted individually throughout the course. The dates and submission guidelines will be announced on MyUni. At the end of the course, best 2 out of 3 marks will count toward the semester grade for this component.
3.Small Group Discovery: There will be two Small Group Discovery sessions during tutorials (most likely in weeks 5 and 10). Please check the dates on MyUni. Activity will be assessed at the end of the session. Missed sessions will count as 0. If you cannot attend your Small Group Discovery session at that time, please come to any other tutorial during that week. If you are late by more than 10 minutes, you will be marked as absent (you may be able to make up that session by attending another session during that week, if it is still available).
Unless there are valid reasons and documentation, missed homework, tests or examinations will be graded 0. Please refer to the Modified Arrangements for Coursework Assessment Policy http://www.adelaide.edu.au/policies/3303 (and the Schedule to the Policy)
for further details about eligibility and application forms. Missed or late submissions of any assignments will not be accepted and will be graded 0.
SubmissionSubmission of the assignments is required as per instructions on MyUni.
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.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.
The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.
SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.
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