ECO3038 : Microeconometrics
- Offered for Year: 2025/26
- Available to incoming Study Abroad and Exchange students
- Module Leader(s): Dr Tom Lane
- Owning School: Newcastle University Business School
- Teaching Location: Newcastle City Campus
Semesters
Your programme is made up of credits, the total differs on programme to programme.
| Semester 2 Credit Value: | 10 |
| ECTS Credits: | 5.0 |
| European Credit Transfer System | |
Pre-requisite
Modules you must have done previously to study this module
| Code | Title |
|---|---|
| ECO2009 | Econometric Analysis |
Pre Requisite Comment
For Incoming Study Abroad and Exchange students:
For ECO3038 Microeconometrics it is expected that the student has studied the following topics:
1. Ordinary Least Squares (OLS) Model: Background and Estimation
2. Assumption of the OLS model
3. Properties of the OLS model: Unbiasedness and Efficiency
4. Hypothesis Testing
5. Goodness of Fit and Analysis of Variance
6. Functional Forms of Regression Models
7. Multiple Regression Analysis
8. Dummy Variables
9. Model Specification
10. Heteroscedasticity
11. Autocorrelation
12. Introduction to Time Series Analysis
Co-Requisite
Modules you need to take at the same time
Co Requisite Comment
N/A
Aims
The module introduces students to methods in discrete choice modelling theoretically and using empirical examples from Economics to highlight their real world applicability. Students will apply methods using statistical software on both simulated and real data applications. By the conclusion of this module students will be equipped to implement the discussed methods using real data and be able to interpret the estimation results in economically relevant contexts. The module focuses on techniques commonly used with micro data and is distinct from ECO3008. The module is particularly valuable to students who are intending to take a Masters course and for those considering a career as a data or policy analyst.
Outline Of Syllabus
The syllabus will include the following:
- Random Utility Model
- Maximum Likelihood Estimation
- Logit Model and Login Estimation
- Generalized Method of Moments
- Mixed Logit Model
- Random-coefficient models
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Guided Independent Study | Assessment preparation and completion | 20 | 1:00 | 20:00 | N/A |
| Scheduled Learning And Teaching Activities | Lecture | 14 | 1:00 | 14:00 | The lectures will be delivered present in person. |
| Guided Independent Study | Directed research and reading | 20 | 1:00 | 20:00 | N/A |
| Scheduled Learning And Teaching Activities | Small group teaching | 4 | 1:00 | 4:00 | Computational exercises |
| Guided Independent Study | Independent study | 42 | 1:00 | 42:00 | N/A |
| Total | 100:00 |
Teaching Rationale And Relationship
The lectures will introduce students to the theoretical material and show their relevance through applications. Seminars will centre around hands on exercises allowing students to apply the learned concepts to data and to understand their relevance to economic issues and interpretation.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Report | 2 | M | 100 | Students will work on an empirical data project to apply the methods learned in the module. 1800 words |
Assessment Rationale And Relationship
In order to assess the learning and skills outcomes of this module, students will be assessed via an empirical data project (data will be provided to students) to show that they can apply the relevant techniques, show their understanding of the theoretical concepts and appropriately interpret data results. Students will have opportunity to practice these skills in the seminars.
RESIT INFORMATION: If students are eligible to a second attempt resit will be an assignment and the resit calculation will be based 100% on the submission.
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- ECO3038's Timetable