EC303-Applied Econometrics

Module Provider: School of Politics, Economics and International Relations
Number of credits: 20 [10 ECTS credits]
Level:6
Terms in which taught: Autumn term module
Pre-requisites: EC204 Introductory Econometrics or EC204NU Introductory Econometrics
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2021/2

Module Convenor: Prof Simonetta Longhi
Email: s.longhi@reading.ac.uk

Type of module:

Summary module description:

This module is one of two applied econometric modules which provide further development of econometric methods introduced in Parts 1 and 2; EC303 focuses on micro-econometrics.Ìý EC303 provides a solid grounding in recent developments in applied micro-econometrics, enables students to understand what is the most appropriate econometric method for a given set of data and problem faced, and gain practical experience (with computer classes) in analysing a wide range of economic questions.Ìý This module provides a flexible route to assessment, with students having an element of choice between coursework only or a combination of exam and coursework for their assessment.

Aims:
The aim of this module is to provide a solid grounding in recent developments in applied econometrics. It will enable students to understand what is the most appropriate econometric method for a given set of data and problem faced, and gain practical experience (with computer classes) in analysing a wide range of economic questions.

Assessable learning outcomes:

At the end of the module students should be able to:

• understand the need for, and the nature of, advanced econometric methods;


• implement advanced econometric methods using common computer software packages;


• read academic papers in economics and understand the suitability of the methods employed.

Additional outcomes:

Students will be able to understand and comment on the quality of econometric output, both that created by themselves, and that created by others.Ìý

Outline content:

Topics may include: panel data methods, limited dependent variable models, selection models, instrumental variables, and other micro-econometric techniques.

Brief description of teaching and learning methods:
Formal lectures and computer classes; supported independent study.