ECONS303-19A (HAM)

Applied Quantitative Research Methods

15 Points

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Division of Management
School of Accounting, Finance and Economics

Staff

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Convenor(s)

Selin Guney

Selin Guney
4315
MSB.2.10
To be advised
selin.guney@waikato.ac.nz

Lecturer(s)

John Gibson

John Gibson
4289
MSB.2.15
Thursday 1-2 pm
john.gibson@waikato.ac.nz

Administrator(s)

: denise.martin@waikato.ac.nz

Placement Coordinator(s)

Tutor(s)

Student Representative(s)

Lab Technician(s)

Librarian(s)

: clive.wilkinson@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 six parts: 1) a review of estimation principles, including Least Squares, Maximum Likelihood, and Generalized Method of Moments estimation 2) research designs and the identification of causal effects 3) sample design features, heteroscedasticity and robust inference, 4) failures of exogeneity assumptions: measurement errors, omitted heterogeneity, simultaneous equation bias, 5) limited dependent variable models, sample selection bias, and computationally-intensive techniques (non- and semi-parametrics, quantile regression and bootstrapping), and 6) regression analysis with time-series data.

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Paper Structure

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The paper is taught through lectures and laboratories and includes a self-directed component in the form of an applied econometric research paper that each student will prepare.
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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
    Linked to the following assessments:
  • 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
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  • Interpret the output 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. Diagnostic Quiz
7 Mar 2019
2:00 PM
5
  • Hand-in: In Lecture
2. Midterm Test
11 Apr 2019
2:00 PM
26
  • Hand-in: In Lecture
3. Critical Review
14 May 2019
12:00 PM
12
  • Online: Submit through Moodle
4. Final Test
28 May 2019
8:00 AM
32
  • Hand-in: In Lecture
✔
5. Research Paper
14 Jun 2019
5:00 PM
25
  • Online: Submit through Moodle
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)
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Recommended Readings

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James H. Stock and Mark W. Watson, 2011. Introduction to Econometrics.

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

Marno Verbeek. 2012. Guide to Modern Econometrics

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

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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 (noting also that Stata is a web-aware software that can use the internet to facilitate collaboration and for the dissemination of results and of new estimation routines and other advances in the software).

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 Stata and for finding new estimation routines and other helpful additions to the core software are:

Boston College Statistical Software Components

https://ideas.repec.org/s/boc/bocode.html

UCLA Resources to help you learn and use Stata

http://www.ats.ucla.edu/stat/stata/

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Online Support

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Lecture notes will be provided in MyWeb, 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 Stata 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: ECON204 or ECONS205

Corequisite(s)

Equivalent(s)

Restriction(s)

Restricted papers: ECON304 and ECON404

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