成人大片

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

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

1. explain econometric concepts and results intuitively 

2. proficiently use STATA for econometric and statistical analysis

3. conduct independent data analysis and inquiry using the tools of statistics and econometrics

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

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

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.

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 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.

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
d. Identifying and estimation a structural equation

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 and the tutor. Questions over the telephone are strongly discouraged. Students may utilise the online forum of MyUni.

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.

Students will be assessed based on the following criteria:

Assessment Task	Task Type	Weighting	Learning Outcome
Group Assignments	Group	20%	1,2,3
Individual Assignments	Individual	30%	1
Final Examination	Individual	50%	1

See MyUni for due dates

Group Homework component remains the same. Please consider the use of Zoom or any other preferred software for your online meetings. If you choose to meet face to face, please observe social distancing.

Final Exam: details to be advised at a later date. (Note that this will not be an invigilated exam requiring personal attendance.)

Attendance in class and tutorials is expected.

Some assignments require to use STATA which is installed in the computer labs or may be accessed via ADAPT on your personal devices. Please allow additional time for completing the assignments as the computer labs may not be always available.

1. There will be 3 group assignments in total. 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 2 out of 3 marks will count toward the semester grade for this component. Because not all of these marks count for assessment, no special consideration will be given to students who do not submit the homework (or submit it late) for medical, compassionate or any other reason. 

2. There will be 2 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 1 out of 2 marks will count toward the semester grade for this component. Because not all of these marks count for assessment, no special consideration will be given to students who do not submit the homework (or submit it late) for medical, compassionate or any other reason. 

3. The final test will be in the lab during week 13 or 14. The dates will be announced in advance on myUni. All requirements will be posted on myUni

Homework will be posted almost each week. Missed or late submissions will not be accepted and will be graded 0. 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.

Each assessment addresses University Graduate Attributes of deep discipline knowledge, critical thinking and problem solving skills, career and leadership readiness to achieve the Course Learning Outcomes 1, 2, and 3. In addition, group homework addressess University Graduate Attributes of teamwork and communication skills and self-awareness and emotional intelligence to achieve the Course Learning Outcomes 2 and 3.

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

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.  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.