23572 Applied Microeconometrics
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Credit points: 6 cp
Subject level:
Undergraduate
Result type: Grade and marksRequisite(s): 23571 Introductory Econometrics OR 25571 Introductory Econometrics
These requisites may not apply to students in certain courses.
There are course requisites for this subject. See access conditions.
Anti-requisite(s): 25572 Applied Microeconometrics
Description
Applied Microeconometrics equips students with a general knowledge of model building, which stands them in good stead for basic empirical work in business environments. It provides students with the analytic tools required for further study in cross sectional econometrics. The approach to modelling, and the reasoning about multi-variable empirical relationships, strengthens students' analytic skills.
Subject learning objectives (SLOs)
| 1. | interpret micro-econometric analysis correctly |
|---|---|
| 2. | estimate and evaluate panel data models |
| 3. | understand other micro-econometric models such as binary dependent variable models and instrumental variable estimation |
Course intended learning outcomes (CILOs)
This subject also contributes specifically to the following program learning objectives:
- Locate relevant data and apply appropriate econometric techniques to quantify the size of economic relationships in specified markets and economies (2.2)
Contribution to the development of graduate attributes
This subject offers an understanding of the econometric tools that apply to microeconomic data, from an applied perspective. It will introduce specific cross-sectional and panel models and the techniques required to estimate and predict with the model. The subject will make use of an advanced econometrics package for the purpose of analysing data.
This subject contributes to the development of the following graduate attributes:
- Critical thinking, creativity and analytical skills
- Communication and interpersonal skills
This subject also contributes specifically to develop the following Program Learning Objectives:
- 3.1: Produce high quality written texts that clearly articulate the application and justification of economic concepts and frameworks to particular problems to propose insightful solutions
- 3.3: Undertake a team based project to solve a complex economic problem
Teaching and learning strategies
This subject offers an understanding of the econometric tools that apply to microeconomic data, from an applied perspective. It will introduce specific cross-sectional and panel models, theoretical backgrounds necessary to interpret micro-econometric analysis, and techniques required to estimate and predict with the model. The subject will make use of an advanced econometrics package for the purpose of analysing data.
This subject will be delivered through a combination of lectures and active learning experiences where ongoing feedback is provided in weekly tutorials. It is therefore imperative that students prepare for and attend all campus based learning activities.
Subject delivery is based on a problem-based strategy this is designed to develop students’ understanding of and ability to apply theory that is covered in the lectures. Collaborative activities focus on problem sets that will enable students to assess their understanding of the theoretical side of the econometric methods covered in the lecture. Students are also challenged to develop their skill in using the Stata software in order to complete these problem sets.
Reading assignments will provide students with opportunities to learn how econometric methods covered in the lecture are actually used in real academic papers and learn how we evaluate research papers critically.
In addition to feedback provided in each interactive session, further feedback for the problem sets and reading assignments will be given during tutorials.
Students are expected to visit the UTS Online web site of the subject, which provides all the relevant information and materials, including lecture notes, problem sets, and papers for reading assignments.
Throughout the semester, students are expected to work on their end-of-term research project, which will provide the most effective way for students to master the theories and methods taught in the class by learning-by-doing rather than simply solving ready-made problem sets. For this reason, students will work on their original research topic. Full range of assistance will be given. By the end of the first half of the subject (before StuVac week), students submit research proposal, for which the lecturer will provide detailed and practical feedback. In the second half of the subject, students will present their progress, which provide them opportunities to get feedback from the lecturer and to learn from their classmates.
Content (topics)
- Pooling cross sections across time: simple panel data methods
- Difference-in-difference estimator
- Advanced panel data methods
- Instrumental variable estimation and two stage least squares
- Binary dependent variable models
- Using statistical package
- Empirical projects
Assessment
Assessment task 1: Assignment (Individual)
| Objective(s): | This addresses subject learning objective(s): 1, 2 and 3 |
|---|---|
| Weight: | 20% |
Assessment task 2: In-Class Assessment (Individual)
| Objective(s): | This addresses subject learning objective(s): 1, 2 and 3 |
|---|---|
| Weight: | 40% |
Assessment task 3: Research Project (Individual)
| Objective(s): | This addresses subject learning objective(s): 1, 2 and 3 This addresses program learning objectives(s): 2.2 |
|---|---|
| Weight: | 40% |
| Length: | A maximum of 15 pages of 1.5 spaced text will be read. There is no limit on references, figures, and tables which should appear at the end of the paper. |
Minimum requirements
Students must achieve at least 50% of the subject’s total marks.
Recommended texts
Stock, James & Watson, Mark (2019) Introduction to Econometrics, 4th ed., Global Edition, Pearson ($60 for
E-book)
Wooldridge, J.M. (2019) Introductory Econometrics: A Modern Approach, 7th Edition, Cengage
Angrist, J & Pischke, J (2014) Mastering 'Metrics: The Path from Cause to Effect, Princeton
Other resources
The Business School's "Guide to Writing Assignments": http://www.uts.edu.au/current-students/business/study-and-assessment-resources/developing-your-academic-writing