ECON 3502 - Econometrics III

North Terrace Campus - Semester 2 - 2025

The course reviews the multiple linear regression and introduces advanced topics in econometrics such as pooling cross sections across time, advanced panel data, instrumental variables, limited dependent variable models and sample selection correction, and advanced time series topics. The focus is on understanding the methods involved, using statistical software (STATA or R or Matlab) to provide the results and then interpreting and commenting on these results. Particular attention is paid to the econometric theory, to the application of econometrics to real-world problems, and to the interpretation of the estimation results.

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Course Details

Course Code	ECON 3502
Course	Econometrics III
Coordinating Unit	Economics
Term	Semester 2
Level	Undergraduate
Location/s	North Terrace Campus
Units	3
Contact	Up to 4 hours per week
Available for Study Abroad and Exchange	Y
Prerequisites	ECON 2517
Restrictions	Available only to B.Economics (Advanced) students
Assessment	Typically group and individual assignments and final exam

Course Staff

Course Coordinator: Dr Emiliano A. Carlevaro

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. demonstrate an in-depth knowledge of regression analysis

2. explain advanced econometric concepts including panel data methods, IV regressions, limited dependent variable models and advanced topics in times series

3. proficiently use statistical software (usually STATA, Matlab, or R) for econometric and statistical analysis

4. conduct independent data analysis and inquiry using advanced econometric methods

5. interpret results and shortcomings of the analysis.

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.	1,2,4,5
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.	3,4,5
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.	3,4,5
Attribute 8: Self-awareness and emotional intelligence Graduates are self-aware and reflective; they are flexible and resilient and have the capacity to accept and give constructive feedback; they act with integrity and take responsibility for their actions.	4,5

Learning & Teaching Modes

2 hours of weekly lectures and 2 hours of weekly lab workshops

Workload

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

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 two hours of workshops each week, which means that students should undertakeat least 8 hours of self-study each week of the teaching term.

Learning Activities Summary

Tentative schedule (subject to change)

Week/s	Modules
1	Module 1 – Review of Multiple Linear Regression 1.1 Definition of the multiple linear regression model 1.2 Classical assumptions 1.3 Matrix notations and derivations of the ordinary least squares (OLS) estimates 1.4 Finite Samples Properties of OLS: Unbiasedness, Gauss-Markov Theorem (Section E.2, Wooldridge textbook) 1.5 Asymptotic Analysis: Consistency and Asymptotic Normality (Section E.4, Wooldridge textbook)
2-3	Module 2 – Pooling Cross Sections across Time: Simple Panel Data Methods (Chapter 13, Wooldridge textbook) 2.1 Pooling independent cross sections across time 2.2 Policy analysis with pooled cross sections 2.3 Two-period panel data analysis 2.4 Policy analysis with two-period panel data 2.5 Differencing with more than two time periods
4-5	Module 3 – Advanced Panel Data Methods (Chapter 14, Wooldridge textbook) 3.1 Fixed effects estimation 3.2 Random effects models 3.3 The correlated random effects approach
6-8	Module 4 – Instrumental Variables Estimation and Two Stage Least Squares (Chapter 15, Wooldridge textbook) 4.1 Motivation: omitted variables in a simple regression model 4.2 IV estimation of multiple regression model 4.3 Two stage least squares 4.4 IV solutions to errors-in-variables problems 4.5 Testing for endogeneity and test overidentifying restrictions
9-10	Module 5 – Limited Dependent Variable Models (Chapter 17, Wooldridge textbook) 5.1 Logit and Probit models for binary response 5.2 Tobit model for corner solution responses 5.3 Censored and truncated regression models 5.4 Sample selection corrections
11-12	Module 6 – Advanced Time Series Topics (Chapter 18, Wooldridge textbook) 6.1 Infinite distributed lag models 6.2 Testing for unit roots 6.3 Spurious regression 6.4 Forecasting

Specific Course Requirements

Homework completion will require access to STATA. STATA may be accessed via IT software webpage or in the computer lab in Nexus 10. Please refer to http://www.adelaide.edu.au/its/student_support/labs/ for further details.

For course related questions, students are encouraged to utilise the discussion board or the designated office hours of the lecturer.

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	Word Count/ Time	Due	Learning Outcome
Projects	Group, Summative	30%	Varying	Around weeks 8 and 12	1-5
Active participation	Individual, Summative	10%	Varying	During workshops	1-5
Quizzes	Individual, Summative	10%	Varying	Every 2 weeks	1-5
Final Exam	Individual, Summative	50%	3 hours	End of semester	1-5

There are NO hurdle requirements.

Assessment Related Requirements

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

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

Assessment Detail

Projects
There are 2 projects which are in groups. These projects involve carrying out econometric analysis and writing a report.

Active participation
Participation during workshop sessions will be graded.

Quizzes
There will be 5 quizzes ocurring around every 2 weeks. Only the best 3 will be counted. Hence, no late submissions are accepted.

Final exam
3-hour multi-part problem solving questions: will cover all the course content and requires the use of statistical sofware. It is a submitted through MyUni. The student will have access to a computer.

Submission

1) Submission of group projects is online through MyUni. Students should retain any assignment or files submitted. Failure to submit an assignment on time will lead to a zero mark.

2) Submission of quizzes is online through MyUni. Only best 3 are counted. Failure to submit on time will lead to a zero mark.

3) Active participation marks require the physical presence of the student on the teaching room.

4) Extensions and alternative assessment conditions: It is your responsibility to contact the lecturer in the first 2 weeks of the semester to discuss extension or alternative assessment options. This applies to ALL students, included but not limited to those registered with the disability centre or the elite athletes program. Exceptional circumstances will be evaluated by your lecturer on a
case-by-case basis and should be discussed whenever possible at least 3 business days hours before the due date of each assessment.

5) It is intended that all assessment will be returned within two weeks.

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
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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