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This course teaches advanced skills in practical econometrics. Our coverage will include the following topics: OLS, FGLS, robust standard errors, panel data, Stata programming, writing .do files, Monte Carlo experiments, bootstrapping, model selection, and exercises in data cleaning. While the course will present some theory, the emphasis in this class is on doing. A distinctive characteristic of the class is that we will illustrate key concepts using computer simulations so that students can "see" the practical consequences of the issues they are studying.
In this course you will learn: - How to use Stata - How to estimate linear relationships using OLS and FGLS estimators - How to interpret regression output - How to test linear hypotheses about regression coefficients, and know how to interpret those tests - The consequences of “nonspherical errors” (heteroskedasticity, serial correlation, and cross-sectional correlation) and estimation procedures for dealing with these problems - The problems caused by endogeneity and some methodologies for dealing with this problem - Some of the opportunities and challenges offered by panel data - A wide variety of panel data estimators including fixed effects, random effects, and multi-level models - Bootstrapping of standard errors - Data cleaning - Dasics of computer programming
(1) ECON213 or STAT202; and (2) MATH102 or MATH199
Students must attend one activity from each section.
Peng Sun
The ‘45% rule’ does not apply to this course. That is, student does not need to reach 45% weighted average across invigilated assessments. Please refer to https://learn.canterbury.ac.nz/course/view.php?id=7744 for further information. Assessment In Te Reo Māori In recognising that Te Reo Māori is an official language of New Zealand, the University provides for students who may wish to use the Te Reo Māori in their assessment. If you intend to submit your work in Te Reo Māori you are required to do the following: Read the Assessment in Te Reo Māori Policy and ensure that you meet the conditions set out in the policy. This includes, but is not limited to, informing the Course Coordinator 1) no later than 10 working days after the commencement of the course that you wish to use Te Reo Māori and 2) at least 15 working days before each assessment due date that you wish to use Te Reo Māori. Assessment: Term Test Term Test. A two-hour test is scheduled for Tuesday, May 5th, 7:00-9:00 pm in Rehua 008(TBD). It is computer-based and will test you over the first seven weeks of course material. It is open book, open notes, open internet, open AI, and you may access all your files electronically. Assessment: Group Project For the group project, Students will be allocated to groups and will present their analysis in PowerPoint presentations to the class. Further details will be given later. Grading: Grading will range from 0-4 and be based on the following criteria: (i) effectiveness of PowerPoint slides (style), (ii) effectiveness of personal presentation, (iii) quality of data analysis, (iv) ability to answer questions, and (v) sharing of presentation tasks across team members (to encourage equal participation across members). Assessment: Final Exam The final exam is comprehensive and is again computer-based, open book, open notes, open internet, NO AI, and you may access all your files electronically. The time and date of this exam will be set by the Registry once enrolments close. Use of AI on all Course Assessments Yes! Students are encouraged to use AI (e.g., ChatGPT/Copilot) in all aspects of the course except exams, from learning the material to helping during assignments, and group projects, including PowerPoint presentations. Here some ways that you can use AI to learn econometrics. Answering questions: AI can answer questions about econometrics concepts, theories, and methods. Just type your question into the AI chat and it will provide an answer. Still uncertain? You can ask follow-up questions or ask it to elaborate the parts of the answer you didn’t understand. Testing your knowledge: AI can give you questions to test your knowledge about a subject. For example, you can ask AI to give you five questions to test your knowledge of instrumental variables. You can then type your answers into AI and ask it to grade your answers. Providing instruction and examples: AI can give step-by-step instructions on how to apply econometrics methods. It can also give examples of applications to help you better understand concepts and how to do things. Giving your feedback on your work: You can ask AI to review and critique things that you write. You can paste your regression output into AI and ask it to interpret it. Writing and explaining code: You can cut and paste assignment questions into AI and ask it to write the programming code necessary to answer the question. Alternatively, you can paste code into AI and ask it to explain what the code is doing. Explore! Experiment! Have fun with it! But be careful! AI makes mistakes. It is an aid, not a substitute, for your learning.
Jeffrey Wooldridge; Introductory Econometrics: A Modern Approach ; 7th; Cengage Learning, 2020.
Domestic fee $1,003.00
International fee $4,538.00
* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.
For further information see Department of Economics and Finance .