| Unit name | Econometrics 1 |
|---|---|
| Unit code | EFIM20011 |
| Credit points | 20 |
| Level of study | I/5 |
| Teaching block(s) |
Teaching Block 1 (weeks 1 - 12) |
| Unit director | Professor. Jolivet |
| Open unit status | Not open |
| Units you must take before you take this one (pre-requisite units) |
EFIM10023 Mathematics for Economics AND OR MATH10013 Probability and Statistics |
| Units you must take alongside this one (co-requisite units) |
None |
| Units you may not take alongside this one |
None |
| School/department | School of Economics |
| Faculty | Faculty of Social Sciences and Law |
Why is this unit important?
Economics, as a social science, relies on analysis of observed data to test and improve theoretical models, with econometrics providing the tool to build causal relationships between economic variables.
A strong understanding of causal analysis is imperative to understand the strategies used within empirical research papers. This unit will help you to understand empirical research, and will help you develop your own toolkit for analysing data using statistical software packages such as Stata.
How does this unit fit into your programme of study?
This unit revises, and builds upon the material seen in your year 1, statistical methods unit, and continues to develop the building blocks underpinning modern econometrics, and acts as a key pre-requisite for both Econometrics 2, and a number of final year units. The use of statistical software packages will also provide key preparation for students who go on to study the Applied Economics Dissertation.
Overview of content
In this unit, you will study tools to conduct a descriptive analysis and describe the statistical relationship between variables in the data. You will also develop a deeper understanding of causal analysis, and then discuss general evaluation problems in experimental and non-experimental settings.
How will students, personally, be different as a result of the unit?
Students will develop an understanding of causal analysis, both focussed towards interpreting published empirical research, and as a core building block towards carrying out their own research, through the dissertation.
Learning Outcomes
Students will be able to:
Teaching will be delivered through a combination of large and small group classes, supported by online resources
Tasks which help you learn and prepare you for summative tasks (formative):
Tasks which count towards your unit mark (summative):
When assessment does not go to plan
If students fail the unit such that credit points cannot be awarded at the first attempt, they will normally be provided reassessment in the failed element(s).
The reassessment tasks will be:
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. EFIM20011).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the University Workload statement relating to this unit for more information.
Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. For appropriate assessments, if you have self-certificated your absence, you will normally be required to complete it the next time it runs (for assessments at the end of TB1 and TB2 this is usually in the next re-assessment period).
The Board of Examiners will take into account any exceptional circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.
