ECONS543-23B (HAM)

Applied Econometrics

15 Points

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The University of Waikato
Academic Divisions
Division of Management
School of Accounting, Finance and Economics

Staff

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Convenor(s)

Michael Ryan

Michael Ryan
See Moodle
michael.ryan@waikato.ac.nz

Lecturer(s)

Administrator(s)

: denise.martin@waikato.ac.nz

Placement/WIL Coordinator(s)

Tutor(s)

Student Representative(s)

Lab Technician(s)

Librarian(s)

: em.pooley@waikato.ac.nz

You can contact staff by:

  • Calling +64 7 838 4466 select option 1, then enter the extension.
  • Extensions starting with 4, 5, 9 or 3 can also be direct dialled:
    • For extensions starting with 4: dial +64 7 838 extension.
    • For extensions starting with 5: dial +64 7 858 extension.
    • For extensions starting with 9: dial +64 7 837 extension.
    • For extensions starting with 3: dial +64 7 2620 + the last 3 digits of the extension e.g. 3123 = +64 7 262 0123.
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What this paper is about

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This is a graduate level applied econometrics paper. The objective of the course is for the student to learn how to conduct quality applied econometric analyses. Students are expected to have a background in use of multivariate regression analysis and statistical inference. The topics covered include methods of selected methods in causal analysis, limited dependent variable models, time series analysis and forecasting, and applications of machine learning methods in Economics and Finance. The paper requires using the statistical software R.
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How this paper will be taught

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This paper will be taught 100% online. Lecture material will be pre-recorded and provided to students each week. We will have a one hour Zoom call each week at 2pm on Tuesdays; this will start in the first week. This Zoom call serves two purposes. The first is for you to ask questions on the lecture materials. The second is for you to work through some exercises in R so you understand how the techniques introduced in lectures can be applied practically.

PLEASE NOTE (as at 3 July 2023), THERE ARE ADDITIONAL LECTURES AND WORKSHOP TIMES APPEARING IN THE COURSE OUTLINE. THESE ARE IN THE PROCESS OF BEING REMOVED. The 2-3pm Tuesday time slot is the only scheduled class.

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Required Readings

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There is no set text, but several books are recommended. These are:

General

Kennedy, P. (2008). A guide to econometrics (6th ed.). Blackwell Pub.

Wooldridge, J. M. (2020). Introductory econometrics : a modern approach (Seventh edition.). Cengage

Cunningham, S. (2021). Causal inference: The mixtape. Yale University Press (see https://mixtape.scunning.com/)

Hansen, B. (2022). Econometrics. Princeton University Press.

Event studies:

Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (2012). The Econometrics of Financial Markets. Princeton University Press. https://doi.org/10.1515/9781400830213

Time series analysis

Enders, W. (2015). Applied econometric time series. Wiley.

On machine learning, the following articles serve as accessible introductions:

Varian, H. R. (2014). Big data: New tricks for econometrics. Journal of Economic Perspectives, 28(2), 3-28.

Mullainathan, S., & Spiess, J. (2017). Machine learning: an applied econometric approach. Journal of Economic Perspectives, 31(2), 87-106.

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You will need to have

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You will need to have access to R. We will talk about this in the first Zoom meeting we have.
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Learning Outcomes

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Students who successfully complete the course should be able to:

  • Define and explain commonly employed econometric terms and methods
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  • Specify and estimate econometric models from economic data in their cross-section, panel and time series forms
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  • Critically appraise the research design of applied econometric studies
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  • Interpret threats to the validity of reported econometric results and identify estimation strategies to ameliorate threats
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  • Interpret the output from econometric software and its implications for management and policy analysts
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  • Use a statistical program (Stata or R) to estimate econometric models, test hypotheses, and undertake empirical exercises
    Linked to the following assessments:
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Assessments

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How you will be assessed

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The course is 100% internally assessed. An individual research paper is due during the examination period. The assessment gives students a chance to demonstrate their competence in applied econometrics.
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The internal assessment/exam ratio (as stated in the University Calendar) is 100:0. There is no final exam. The final exam makes up 0% of the overall mark.

The internal assessment/exam ratio (as stated in the University Calendar) is 100:0 or 0:0, whichever is more favourable for the student. The final exam makes up either 0% or 0% of the overall mark.

Component DescriptionDue Date TimePercentage of overall markSubmission MethodCompulsory
1. Critical Review
14 Aug 2023
5:00 PM
15
  • Online: Submit through Moodle
2. Research Design
5 Sep 2023
5:00 PM
10
  • In Class: In Tutorial
3. Test
10 Oct 2023
2:00 PM
32
  • Online: Submit through Moodle
4. Research Paper
27 Oct 2023
9:00 PM
33
  • Email: Convenor
5. Data Sources and Code Appendix
27 Oct 2023
9:00 PM
10
  • Email: Convenor
Assessment Total:     100    
Failing to complete a compulsory assessment component of a paper will result in an IC grade
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