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ECON2038 Applied Econometrics

Module overview

The module will enable you to apply statistical and econometric techniques to the estimation and testing of economic models and for causal inference. It will thereby provide you with the skills necessary both to undertake your own empirical studies and to evaluate empirical work in the published literature.

Linked modules

Pre-reqs: ECON2043 OR ECON2041

Aims and Objectives

Learning Outcomes

Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

• abstract the essential features of economic systems into a statistical model
• identify violations of the assumptions of classical linear regression and propose adequate solutions.
• analyse and interpret economic data in an informative manner using econometric methods.
• apply statistical techniques to empirical data for statistical inference on the effects of economic policies and testing economic models.

Transferable and Generic Skills

Having successfully completed this module you will be able to:

• use quantitative reasoning and analyse and interpret data, using output from standard statistical software.
• successfully collaborate with others in a team on data analysis problems.
• communicate the results and conclusions of data analyis thorugh an executive summary.

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

• statistical tools for economic analysis that account for violations of classical linear regression assumptions.
• statistical tests for the empirical evaluation of economic policy.

Syllabus

This module extends the discussion of econometrics presented in the first semester of the second year, focusing on issues that arise in applying the classical linear regression model to actual economic data. We examine the problems associated with specifying economic models in forms which are amenable to estimation and testing using available economic data. Consideration is given to the nature of economic data - the methods by which it is collected and compiled and the difficulties these may present for the applied economist interested in the evaluation of economic policies or the testing of theoretical hypotheses. Methods for testing model specification and alternative techniques for handling problems of misspecification are discussed. The module provides practical experience of applying econometric techniques to economic data using standard statistical software.

Learning and Teaching

Teaching and learning methods

Lectures, (computer-based) tutorials.

Resources & Reading list

Textbooks

J. Wooldridge (2015). Introductory Econometrics: A Modern Approach. South-Western Cengage Learning.

R.C. Hill, W.E. Griffiths and G.C. Lim (2018). Principles of Econometrics. John Wiley.

Assessment

Assessment strategy

Two take-home coursework assignments during the semester and a final written exam, supported by continuous formative assessment in form of problem sets. This is the same for internal repeat. Assessment for referral and external repeat is through final written exam only.

Summative

This is how we’ll formally assess what you have learned in this module.

Referral

This is how we’ll assess you if you don’t meet the criteria to pass this module.

Repeat

An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.

Repeat Information

Repeat type: Internal & External