ECONS529-22B (HAM)

Microeconometrics

15 Points

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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)

: yilan.chen@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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Paper Description

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The course is structured in five parts: 1) a brief review of estimation principles 2) research designs and the analysis of causal effects 3) discrete and limited dependent variable models, 4) econometric issues for panel and survey data 5) microeconometric applications of machine learning

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Paper Structure

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The paper is taught through interactive workshops and laboratories and includes a self-directed component in the form of an applied microeconometric research paper that each student will prepare.
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Learning Outcomes

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Students who successfully complete the paper should be able to:

  • 1. Critically evaluate research designs underlying applied microeconometric analyses
    Linked to the following assessments:
  • 2. Specify and estimate microeconometric models that are valid for particular data and research designs
    Linked to the following assessments:
  • 3. Interpret and critically evaluate the outcomes of empirical analyses derived from econometric software
    Linked to the following assessments:
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Assessment

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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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Assessment Components

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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
22 Aug 2022
5:00 PM
10
  • Online: Submit through Moodle
✔
2. Research Design
12 Sep 2022
5:00 PM
18
  • Email: Convenor
✔
3. Test
18 Oct 2022
2:00 PM
20
  • Online: Submit through Moodle
✔
4. Data Sources and Code Appendix
4 Nov 2022
9:00 PM
22
  • Email: Convenor
✔
5. Research Paper
4 Nov 2022
9:00 PM
30
  • 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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Required and Recommended Readings

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Required Readings

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There is no set text, but several books are recommended (and are held on course reserve in the library)
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Recommended Readings

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Josh Angrist and J-S Pischke. 2015. Mastering 'metrics: The Path from Cause to Effect

Jeffrey M. Wooldridge. 2013. Introductory Econometrics: A Modern Approach

William Greene. 2018. Econometric Analysis (8th Edition)

Scott Cunningham 2021 Causal Inference. available here: https://mixtape.scunning.com/

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Other Resources

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In order for to you appreciate the ongoing development of econometric methods, and the debates over their various uses, it will be important to become familiar with some resources on the web.

Amongst the blogs that are worth sampling are:

Development Impact Blog

http://blogs.worldbank.org/impactevaluations/

Econometrics Beat:

http://davegiles.blogspot.co.nz/

A very useful resource for finding applied papers that use econometric methods is:

Research Papers in Economics

http://repec.org/

Resources on the internet for helping to learn R are available at:

https://www.r-bloggers.com/2015/12/how-to-learn-r-2/

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Online Support

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Lecture notes will be provided in Moodle, ahead of class.
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Workload

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Contact hours are typically four hours per week. An additional 8-10 hours per week should be kept aside for reading and for gaining proficiency in the R software. Towards the end of the semester the balance between class time and self-directed work will shift more to self-directed work, as each student works on their individual research paper.
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Linkages to Other Papers

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Note any linkages to other papers where the linkage is of importance.
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Prerequisite(s)

Prerequisite papers: One of ECON304, ECON404, ECONS303, ECON528, ECONS528, ECON543 or ECONS543 or equivalent

Corequisite(s)

Equivalent(s)

Restriction(s)

Restricted papers: ECON504, ECON529

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