ECM651-Economic Data Analysis

Module Provider: School of Politics, Economics and International Relations
Number of credits: 20 [10 ECTS credits]
Level:7
Terms in which taught: Autumn term module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2023/4

Module Convenor: Dr Andy Chung
Email: chunkit.chung@reading.ac.uk

Type of module:

Summary module description:

This module provides an introduction to core topics and methods in the analysis of economic data, while also enabling students to develop their data handling skills using the statistical package Stata and to critically evaluate empirical research papers in economics.

Aims:

The aim of this module is to provide students with an understanding of the main methods of economic data analysis and their applications. The module will introduce students to some of the basic methods used in empirical research in economics and will enable students to gain an understanding and practical experience to apply these methods.

Assessable learning outcomes:

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

1. explain core concepts and methods in econometrics;


2. explain the conditions under which the methods are valid and their limitations.


3. apply the various techniques taught using secondary data and the statistical package Stata, and interpret the results;


4. interpret and critically evaluate the economic data analysis methods used in empirical papers.

Additional outcomes:

The ability to evaluate empirical research and data analysis skills acquired in this module will assist students in carrying out their dissertation or applied economics project, as well as applied coursework in other modules.

Outline content:

Topics to be covered include: different types of economic data; linear regression; estimation; hypothesis testing; tests of model validity; time series methods; cross section and panel data.

Global context:

Examples of the contexts and problems where the methods introduced by this module can be applied will reflect the University’s commitment to global engagement and multi-cultural awareness.

Brief description of teaching and learning methods:

This is a methods based module delivered through a combination of lectures and PC classes. Lectures will introduce the core concepts and methods, which students will have the opportunity to apply through a series of seminars and PC classes, during which there will be group discussion and collaborative work to solve problems. The emphasis is on the interpretation of statistical evidence and the practical application of techniques.

Contact hours:

Ìý	Autumn	Spring	Summer
Lectures	20		2
Practicals classes and workshops	8
Guided independent study:	Ìý	Ìý	Ìý
Ìý Ìý Wider reading (independent)	8
Ìý Ìý Wider reading (directed)	24
Ìý Ìý Exam revision/preparation			40
Ìý Ìý Advance preparation for classes	40
Ìý Ìý Preparation for tutorials	8
Ìý Ìý Preparation of practical report	25
Ìý Ìý Completion of formative assessment tasks	5
Ìý Ìý Reflection	15		5
Ìý	Ìý	Ìý	Ìý
Total hours by term	153	0	47
Ìý	Ìý	Ìý	Ìý
Total hours for module	200

Summative Assessment Methods:

Method	Percentage
Written exam	60
Project output other than dissertation	40

Summative assessment- Examinations:

One 3-hour unseen written examination, focusing on testing students’ abilities to apply their understanding of economic data analysis. Postgraduate examinations are held in the Summer term.

Summative assessment- Coursework and in-class tests:

One Stata-based research project due at the beginning of the spring term. Datasets will be provided, and students will use one of these to apply what they have learned to answer a research question.

Formative assessment methods:

There will be problem sets and computer exercises for each topic, which will be discussed in the weekly seminars/PC classes. Students are expected to attempt these prior to class and will have an opportunity to receive formative feedback during the classes.

Penalties for late submission:

The below information applies to students on taught programmes except those on Postgraduate Flexible programmes. Penalties for late submission, and the associated procedures, which apply to Postgraduate Flexible programmes are specified in the policy 'Penalties for late submission for Postgraduate Flexible programmes', which can be found here: /cqsd/-/media/project/functions/cqsd/documents/cqsd-old-site-documents/penaltiesforlatesubmissionpgflexible.pdf
The Support Centres will apply the following penalties for work submitted late:

• where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of five working days;
• where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

The University policy statement on penalties for late submission can be found at: /cqsd/-/media/project/functions/cqsd/documents/cqsd-old-site-documents/penaltiesforlatesubmission.pdf
You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Assessment requirements for a pass:

A minimum mark of 50%.

Reassessment arrangements:

Re-assessment for all modules takes place in August/September of the same year.

Re-assessment for this module will be by examination only.

Additional Costs (specified where applicable):

1) Required text books:Ìý

2) Specialist equipment or materials:Ìý

3) Specialist clothing, footwear or headgear:Ìý

4) Printing and binding:Ìý

5) Computers and devices with a particular specification:Ìý

6) Travel, accommodation and subsistence:Ìý

Last updated: 18 September 2023