ECON 2515 - Intermediate Applied Econometrics II

North Terrace Campus - Summer - 2022

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 but does not include time series econometrics. 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.

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Course Details

Course Code	ECON 2515
Course	Intermediate Applied Econometrics II
Coordinating Unit	Economics
Term	Summer
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 .

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 team

最新糖心Vlog 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.	5

Learning & Teaching Modes

Summer School is intensive over 6 weeks. There are 24 hours of lectures and 11 hours of tutorials.
Students are expected to attend tutorials and they will not be recorded. If any tutorial is missed, students will need to catch up on any missed material.

Workload

No information currently available.

Learning Activities Summary

Topics	Title	Chapters
1	Introduction and review	Chapters 1 and 3
2	The simple regression model	Chapter 4
3	Multiple regression Analysis: estimation	Chapter 5
4	Multiple regression analysis: inference	Chapter 6
5	Model specification	Chapter 7
6	Multiple regression analysis with qualitative information: binary (or dummy) variables	Chapter 8
7	Heteroscedasticity	Chapter 9

The 最新糖心Vlog'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
Mid-term test	Individual	20%	1-5
Final Exam	Individual	50%	1-5
Total:		100%

Assessment Related Requirements

Some assignments and homework require you to use STATA software. The 最新糖心Vlog has recently purchased a site licence for Stata, and Stata 17.0 MP is now available in the Software Centre to download. Any student who needs it has access to it as long as they have a compatible operating system and memory etc.
Students may download it to one personally-owned device. See the ITDS ‘Software for Students’ page: /technology/your-services/software/software-for-students. The info for Stata is down at the bottom of the list.

Stata is also 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 always be available.

Assessment Detail

1. There will be 1 assignment to be submitted in groups throughout the course. No individual work will be accepted for this component. Further details will be posted to MyUni. Modified arrangements due to exceptional circumstances will be considered on a case-by-case basis. The dates and submission guidelines will be announced on MyUni. The assignment is worth 30% of the final grade and is not redeemable.

2. There will be a mid-semester test worth 20% of the final grade. Further details will be announced on MyUni. The test is redeemable if students choose not, or are unable, to do the tests. The weighting of the missed test 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 .

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.

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
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.

Authorised by:	Deputy Vice-Chancellor and Vice-President (Academic)
Maintained by:	Course Outlines Administrator

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