Unit information: Quantitative Methods 2 in 2037/38

Please note: Programme and unit information may change as the relevant academic field develops. We may also make changes to the structure of programmes and assessments to improve the student experience, occasionally this includes not running units if they are not viable.

Unit name Quantitative Methods 2
Unit code ECON20013
Credit points 20
Level of study I/5
Teaching block(s) Teaching Block 2 (weeks 13 - 24)
Unit director Dr. Mike Peacey
Open unit status Not open
Units you must take before you take this one (pre-requisite units)

None

Units you must take alongside this one (co-requisite units)

ECON20012 Quantitative Methods 1

Units you may not take alongside this one

None

School/department School of Economics
Faculty Faculty of Arts, Law and Social Sciences

Unit Information

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 economic research and to make informed decisions for policy interventions. This unit will help you develop your own toolkit for analysing data using statistical software packages and to differentiate between mere correlations and causal relationships.

How does this unit fit into your programme of study?

This unit builds on the statistical analysis skills in Quantitative Methods 1 and will equip you with the necessary econometrics skills required for understanding economics research in your final year units, as well as enable you to apply econometrics techniques to new problems and data sets, such as in the final year project.

Your learning on this unit

Overview of content

In this unit, you will build upon the topics covered in Quantitative Methods 1, and will develop your understanding of establishing causal relationships between economic variables.

In the unit, you will see how to apply topics such as

  • Heteroskedasticity and the FGLS estimator
  • Serial Correlation
  • Causality using identification strategies such as Instrumental Variables and Fuzzy RDD
  • Estimation using limited dependent variable through the linear probability model and logit
  • Panel Data

How will students, personally, be different as a result of the unit

You will develop an understanding of models of causal inference, and how they can be used to estimate relationships between economic variables.

Learning Outcomes

By the end of this unit, you will be able to:

  1. Solve algebraic models to obtain properties of statistical estimators
  2. Perform and interpret econometric analysis using a statistical software package
  3. Explain the meaning of econometric results and provide an economic interpretation
  4. Determine whether some statistical relationship can be interpreted as causal
  5. Apply econometric techniques to real-world data to evaluate real-world questions

How you will learn

Students will be taught through a combination of large group lectures and smaller group lab sessions, and students’ independent study.

How you will be assessed

Tasks which help you learn and prepare for summative tasks

You will be given weekly assignments to complete across a range of elements of the unit. You will gain feedback through solutions, and the opportunity to discuss your answers during office hours.

Tasks which count towards your unit mark (summative)

  • Portfolio of tasks, based around data analysis, carried out in small group classes (20%) (Assesses ILOs 2, 3, 4 and 5)
  • Exam (2 hours) (80%) (Assesses all ILOs)

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:

  • Portfolio of tasks, based around data analysis (20%) (Assesses ILOs 2, 3, 4 and 5)
  • Exam (2 hours) (80%) (Assesses all ILOs)

Resources

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. ECON20013).

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 assessment methods listed in this unit specification are designed to enable students to demonstrate the named learning outcomes (LOs). Where a disability prevents a student from undertaking a specific method of assessment, schools will make reasonable adjustments to support a student to demonstrate the LO by an alternative method or with additional resources.

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.