ECON 2515 - Intermediate Applied Econometrics II
North Terrace Campus - Semester 2 - 2022
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General Course Information
Course Details
Course Code ECON 2515 Course Intermediate Applied Econometrics II Coordinating Unit Economics Term Semester 2 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 ECON 1011 or equivalent Incompatible ECON 2504 Assumed Knowledge ECON 1005 and ECON 1012 Restrictions Not suitable for BEc(Adv) students Assessment Typically assignments, mid-term test and final exam Course Staff
Course Coordinator: Patricia Sourdin
Course Timetable
The full timetable of all activities for this course can be accessed from .
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Learning Outcomes
Course Learning Outcomes
On successful completion of this course, students will be able to:
1. Have an in-depth knowledge of Economic data structure and use adequate visual tools to present data
2. Estimate simple and multiple linear regressions with quantitative data
3. Test and correct for heteroscedasticity
4. Estimate linear regressions with qualitative data
5. Interpret outcomes of the regressions
6. Discuss and communicate methodology and results in a teamUniversity 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) Attribute 1: Deep discipline knowledge and intellectual breadth
Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.
1-5 Attribute 2: Creative and critical thinking, and problem solving
Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.
3,5 Attribute 3: Teamwork and communication skills
Graduates convey ideas and information effectively to a range of audiences for a variety of purposes and contribute in a positive and collaborative manner to achieving common goals.
6 Attribute 4: Professionalism and leadership readiness
Graduates engage in professional behaviour and have the potential to be entrepreneurial and take leadership roles in their chosen occupations or careers and communities.
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Learning Resources
Required Resources
The required textbook for this course is Introductory Econometrics by Jeffrey M. Wooldridge, Mokhtarul Wadud, Jenny Lye, 2nd editionOnline Learning
MyUni Course WebPage provides lecture notes, computer lecture notes, homework questions and solutions. Please check this page frequently for important announcements and corrections. -
Learning & Teaching Activities
Learning & Teaching Modes
Two hours of weekly face to face lectures (may be split into smaller units) and weekly face-to-face one hour tutorials starting in week 2.
Students who are studying offshore are able to participate in all learning activities through online learning. Please consider the use of Zoom or any other preferred communication software for your group assignment meetings.
Workload
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
The University expects full-time students (i.e. those taking 12 units per semester) to devote a total of 48 hours per week to their studies. This translates to 12 hours per week for a semester course.
Learning Activities Summary
Weeks Modules 1-2 Module 1 - Nature of Econometrics and Economic Data
1.1- What is econometrics?
1.2- Steps in empirical economic analysis
1.3- The structure of economic data
1.4- Graphing data
1.5- Causality and the notion of Ceteris Paribus in econometric analysis3-4 Module 2- The Simple Linear Regression Model
2.1- Definition of the simple linear regression model
2.2- Deriving the ordinary least square estimates
2.3- Examples of simple regression obtained using real data
2.4- Properties of OLS
2.5- Unit of measurement and functional form
2.6- Unbiasedness, consistency and variances of the OLS estimates5-6 Module 3- Mulitple Linear Regression Model: Estimation
3.1- Motivation
3.2- Mechanism and interpretation of ordinary least square equation (OLS)
3.3- Properties of OLS estimators7 Mid-term test 8-9 Module 4- Multiple Linear Regression Model: Inference
4.1- Sample distribution of the OLS estimators
4.2- Testing hypotheses about a single population parameter: The t-test
4.3- Confidence intervals
4.4- Testing hypotheses about a single linear combination of the parameter
4.5- Testing multiple linear restrictions: The F-test
4.6- Confidence intervals for predictions
4.7- Reporting regression results10 Module 5- Heteroscedasticity
5.1- Definition of heteroscedasticity
5.2- Testing for heteroscedasticity
5.3- Correcting heteroscedasticity11-12 Module 6-Multiple regression analysis with qualitative information: binary (or dummy) variables
6.1- Describing qualitative information
6.2- A single dummy independent variable
6.3- Using dummy variables for multiple categories
6.4- Interactions involving dummy variables
6.5- A binary dependent variable: The linear probability model (LPM)
8-9101-12Specific Course Requirements
Assignment completion will require access to computer software STATA.
The University has made Stata 17 software available for students to download to a personal Mac/PC. Please follow the instructions at the
link Stata software
Alternatively, you may use the computer labs on campus. Please refer to this for further details.
For course related questions, students are encouraged to use the online forum of MyUni, email the lecturer, or ask questions in lectures or tutorials. -
Assessment
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 Summary
Assessment Task Task type Weighting Learning Outcome Assignments Group 30% 1-6 2 Mid-Term tests Individual 20% 1-5 Final Exam Individual 50% 1-5 Total: 100% Assessment Related Requirements
Some assignments require you to use STATA which is installed in the computer labs or may be accessed remotely via ADAPT on your personal devices, or installed on your own computers.Assessment Detail
1. There will be 3 assignments to be submitted in groups throughout the course. No individual work will be accepted for this component. The best 2 out of 3 marks will count toward the semester grade for this component. Further details will be posted to MyUni.
The dates and submission guidelines will be announced on MyUni. The projects are worth 30% of the final grade.
2. There will be two mid-semester tests worth 10% each (total 20% of the final grade). Further details will be announced on MyUni.
The test is redeemable if students are unable to do the tests. The weighting of the missed tests will be added to the weighting of the final exam.Submission
Submission of the assignments is required as per instructions on MyUni.
Legible hand-writing and the quality of English expression are considered to be integral parts of the assessment process, and may affect marks. Marks cannot be awarded for answers that cannot be read or understood.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 .
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Student Feedback
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.
The revisions to this course, based on student feedback, include a clearer structure of topics, clearer due dates, and making the midterm redeemable. -
Student Support
- Academic Integrity for Students
- Academic Support with Maths
- Academic Support with writing and study skills
- Careers Services
- Library Services for Students
- LinkedIn Learning
- Student Life Counselling Support - Personal counselling for issues affecting study
- Students with a Disability - Alternative academic arrangements
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Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
- Academic Credit Arrangements Policy
- Academic Integrity Policy
- Academic Progress by Coursework Students Policy
- Assessment for Coursework Programs Policy
- Copyright Compliance Policy
- Coursework Academic Programs Policy
- Intellectual Property Policy
- IT Acceptable Use and Security Policy
- Modified Arrangements for Coursework Assessment Policy
- Reasonable Adjustments to Learning, Teaching & Assessment for Students with a Disability Policy
- Student Experience of Learning and Teaching Policy
- Student Grievance Resolution Process
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