最新糖心Vlog

ECON 2504 - Intermediate Econometrics II

North Terrace Campus - Summer - 2014

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.

  • General Course Information
    Course Details
    Course Code ECON 2504
    Course Intermediate Econometrics II
    Coordinating Unit Economics
    Term Summer
    Level Undergraduate
    Location/s North Terrace Campus
    Units 3
    Contact Up to 4 hours per week. Intensive in Summer Semester.
    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
    Assessment Typically, tutorial participation &/or exercises, assignments, tests & final exam
    Course Staff

    Course Coordinator: Patricia Sourdin

    Semester 1
    Course Coordinator: Dr Nicholas Sim
    Office hours: will be held by the lecturer on Monday 4-5pm or by appointment only
    Office location: Nexus 10, Level 4, Room 4.46
    Telephone: 8313 4927

    Semester 2
    Course Coordinator: Dr Patricia Sourdin
    Email: patricia.sourdin@adelaide.edu.au
    Office hours: TBA
    Office location: Nexus 10, Level 4, Room 4.06
    Telephone: 8313 1175
    Course Timetable

    The full timetable of all activities for this course can be accessed from .

  • Learning Outcomes
    Course Learning Outcomes
    The 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
    最新糖心Vlog Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    最新糖心Vlog Graduate Attribute Course Learning Outcome(s)
    Knowledge and understanding of the content and techniques of a chosen discipline at advanced levels that are internationally recognised. 1,2
    The ability to locate, analyse, evaluate and synthesise information from a wide variety of sources in a planned and timely manner. 1,2
    An ability to apply effective, creative and innovative solutions, both independently and cooperatively, to current and future problems. 1,2
    A proficiency in the appropriate use of contemporary technologies. 2,3
  • Learning Resources
    Required Resources

    TEXT BOOK(S)
    The required textbook is Principles of Econometrics, 4th Edition, Wiley by R. Carter Hill, William E. Griffits and Guay C. Lim.

    Recommended Resources

    The recommended book to accompany the required text is Using Stata for Principles of Econometrics, 4th Edition, by Adkins and Hill.

    Online Learning

    provides lecture notes and other course materials. Please check this page frequently for important announcements and corrections.

  • Learning & Teaching Activities
    Learning & Teaching Modes

    Classes will meet three times a week: twice for a 2-hour lecture on Thursday, 11AM – 1PM and 2 - 4PM, at Napier, G03, Lecture Theatre, and once for a 2-hour tutorial on Friday, 10AM - 12 noon or 1pm - 3pm at Nexus10, 220, Comp Suite 1.
    The lecturer will hold office hours on Wednesday, 9.30-10.30AM and by appointment.
    Please adhere to the designated office hours.

    Workload

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    Weekly assignments are issued each week. The assignments are not graded, but as class participation, students may (mostly likely will) be asked to present their solutions during tutorial discussion.  

    Learning Activities Summary

    The course is held from 3 March to 10 June 2014. There are two one-hour lectures per week and one two-hour tutorial per week. The full timetable of all activities for this course can be accessed from the Course Planner at

    The required textbook is Principles of Econometrics, 4th Edition, Wiley by Hill, Griffiths and Lim (HGL). Another useful book, but not required for the course, is Using Stata for Principles of Econometrics by Adkins and Hill.

    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 Requirements

    Homework 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  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.

  • Assessment

    The 最新糖心Vlog's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary

    Students will be assessed based on the following criteria:

    Class Participation (during tutorials): 10%
    Mid-term test: 30%
    Final examination 60%

    Unless informed otherwise, the mid-term test will be scheduled on Thursday 24 January 2013, during the 2-4PM lecture.

    Assessment Related Requirements
    Attendance in class and tutorials is required.
    Assessment Detail

    The assignments will be posted one week prior to the due date. Each week, I will ask a different group of students (based on last names in alphabetical order) to prepare the assignment questions. While the assignment is not graded, students may (and will mostly likely) be asked to share their solutions with the class. This will count as class participation, which constitutes 10 percent of the overall assessment. Note that supplementary test or examination will not be given to replace the missed ones. Unless there are valid reasons and proper documentation, a missed test or examination will be graded 0.

    Submission
    Submission of the assignments is not required.
    Course Grading

    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 .

  • Student Feedback

    The 最新糖心Vlog 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 最新糖心Vlog 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.

  • Student Support
  • Policies & Guidelines
  • Fraud Awareness

    Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student鈥檚 disciplinary procedures.

The 最新糖心Vlog of Adelaide is committed to regular reviews of the courses and programs it offers to students. The 最新糖心Vlog of Adelaide therefore reserves the right to discontinue or vary programs and courses without notice. Please read the important information contained in the disclaimer.