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Course Outlines

ECON 7001 - Econometrics PG

North Terrace Campus - Semester 1 - 2015

The course focuses on the estimation, inference and identification of linear models. We will discuss the issues and challenges of linear regression models, how to interpret the results of these models, and apply econometrics can be applied to study real-world problems. The topics to be covered in the course include estimation issues such as model misspecification, measurement errors endogenous regressors, as well as instrumental variable regressions, panel data approaches, and econometric analysis using matrices. STATA, a standard software for econometric and statistical analysis, will be used throughout the course. Practical applications of the course will be discussed during the fortnightly seminar.

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  • General Course Information
    Course Details
    Course Code ECON 7001
    Course Econometrics PG
    Coordinating Unit Economics
    Term Semester 1
    Level Postgraduate Coursework
    Location/s North Terrace Campus
    Units 3
    Contact Up to 3 hours per week
    Available for Study Abroad and Exchange Y
    Prerequisites ECON 7051 or equivalent
    Restrictions Available to MFin&BusEc, GradCertEc, GradCertIntEc, GradDipIntEc, GradDipAppEc, MAppEc(Int), MAppEc, MAppEc(PubPolicy) & MEc(Course) students only
    Assessment Typically tutorial participation, regular quizzes, and a project
    Course Staff

    Course Coordinator: Dr Nadya Baryshnikova

    Dr Nadya Baryshnikova
    Email: nadya.baryshnikova@adelaide.edu.au
    Office location: Nexus 10, Level 4, Room 4.04
    Telephone: 8313 4821
    Office hours: To be advised


    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
    The required textbook is J.M. Wooldridge, Introductory Econometrics, 5th Edition, South-Western 2012
    Online Learning

    MyUni Course WebPage provides lecture notes, computer lecture notes, homework questions, solutions and practice exams. Please check this page frequently for important announcements and corrections.

  • Learning & Teaching Activities
    Learning & Teaching Modes

    Classes will meet twice per week, for a 2-hour lecture and a 1- hour tutorial.  Students are expected to be present for all lectures and actively participate in all tutorial activities. The lecturer will hold office hours except for breaks and holidays, with additional hours held by the tutor.

    Workload

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

    The standard postgraduate workload for a full-time student is 48 hours per week which equates to 12 hours per 3 unit course. This course has two hours of lectures and one hour of tutorials each week, which means that students should undertake nine hours of self-study each week of the teaching term.

    Weekly homework assignments are issued each week. The lecturer will choose two of the weekly homework to be submitted and graded. 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. Review of Mathematical Tools, Probability Distributions and Statistical Inference (Wooldridge: Appendices A-C)
    a. Basic mathematical tools
    b. Probability distribution
    c. Point and interval estimation
    d. Large sample properties of estimators
    e. Hypothesis testing and confidence intervals

    2. Linear Regression Analysis (Wooldridge: Chapters 1-3)
    a. Economic Data
    b. Simple linear regression and ordinary least squares (OLS) estimation
    c. Multiple linear regression
    d. The properties, expected value and the variance of the OLS estimator

    3. Issues in Multiple Regression Analysis (Wooldridge: Chapters 4-6)
    a. Inference and hypothesis testing
    b. Large sample properties of the OLS estimator
    c. Other functional form
    d. Goodness of fit

    4. Heteroskedasticity (Wooldridge: Chapter 8)
    a. Heteroskedasticity-robust inference
    b. Testing for heteroskedasticity
    c. Weighted least squares estimation

    5. Specification and Data Issues (Wooldridge: Chapter 9)
    a. Functional form misspecification
    b. Proxy variables
    c. Measurement errors

    Subject to time availability, one or more of the following topics will be covered:

    6. Panel Data (Wooldridge: Chapters 13-14)
    a. Fixed effects estimation
    b. Random effects estimation

    7. Limited Dependent Variable Models and Sample Selection Corrections (Wooldridge: Chapter 7)
    a. Logit and probit models
    b. Tobit models
    c. Poisson regression model
    d. Models with censored and truncated data
    e. Sample selection

    8. Instrumental Variables Estimation and Simultaneous Equations Model (Wooldridge: Chapters 15-16)
    a. Instrumental variables
    b. Two-state least squares estimation
    c. Simultaneity bias in OLS
    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.

    Students may discuss homework assignments among themselves. Homework assignments may be submitted individually or as a group of two students belonging to the same tutorial session. If an assignment is turned in as a group, students in the same group will receive the same score.

    For course related questions, students are encouraged to utilise the designated office hours of the lecturer and the tutor. Questions over the telephone are strongly discouraged. Students may utilise the online forum of MyUni.

  • 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:

    Homework assignments     40%
    Final test                           60%

    Unless instructed otherwise, students are permitted to bring in an A4 size cheat sheet with both sides written for the final test.

    Assessment Related Requirements
    1 - Attendance in class and tutorials is required.
    2 - To gain a pass, a mark of at least 45% must be obtained on the final test as well as a total of at least 50% overall.
    Assessment Detail

    Homework will be posted each week. The lecturer will choose two of the weekly homework assignments to be submitted and graded. For homework to be turned in, missed or late submissions will not be accepted and will be graded 0. 

    The final test will be in the lab during week 13 or 14. The dates will be announced in advance on myUni.
    Supplementary test or examination will not be given to replace the missed ones.

    Unless there are valid reasons and documentations, missed test or examination will be graded 0. Please refer to the Modified Arrangements for Coursework Assessment Policy  (and the Schedule to the Policy) for further details about eligibility and application forms.

    Submission
    Submission of the assignments is required as per instructions on MyUni.
    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 .

    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.
  • 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

    This section contains links to relevant assessment-related policies and guidelines - all university policies.

  • 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.
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