Module Details

SC968-7-SP-CO: Panel Data Methods

Year: 2017/18
Department: Sociology
Essex credit: 20
ECTS credit: 10
Available to Study Abroad / Exchange Students: Yes
Full Year Module Available to Study Abroad / Exchange Students for a Single Term: No
Outside Option: No

Staff
Supervisor: Dr Renee Luthra
Teaching Staff: Dr Renee Luthra
Contact details: Michele Hall, Graduate Administrator, Telephone 01206 873051, Email: socpgadm@essex.ac.uk

Module is taught during the following terms
Autumn Spring Summer

Module Description

Aims of the course
This course gives students a practical grounding in the theory and methods of panel data analysis. It has the following key aims:

* To allow students to interpret and critically assess published studies using panel data
* To provide students with the skills and confidence to manipulate panel datasets on their own in the future
* To give an overview of different approaches to panel data analysis
* To develop practical skills in selecting and conducting different types of panel data analysis
* To provide an opportunity for students to compare results of analysing the same data with different panel methods
* The course includes a review of standard regression methods (OLS, logit and probit) and covers longitudinal data manipulation, transition matrices, continuous and discrete fixed and random effects models, and survival analysis.

Learning and Teaching Methods

LAB SESSIONS

Each lecture is followed by a lab-based session where students will use Stata to implement the methods covered in the lectures. Please note that this is an intensive course, and most students will need to spend several hours in the lab each week, in addition to these scheduled sessions, in order to cover the work.

The data used will be a subset from the British Household Panel Survey (BHPS), and the exercises will involve the sort of analysis that professional social scientists might need to undertake.

Most sessions will build on the work of a previous session; it is therefore important that students keep copies of all their do-files and outputs.

Students should already be familiar with the fundamentals of Stata, including:

* basic data management techniques
* working in interactive and batch mode
* basic analytical techniques such as OLS, logit and probit

If you are unsure about your competence in Stata, please talk to the course tutors well before the start of the course.

LECTURE OUTLINE

Week 16
A review of concepts for regression modeling, or what you should know already

Week 17
Understanding and using panel data: introduction and management

Week 18
Understanding and using panel data: merging files and weights

Week 19
Panel data methods I: transition matrices, lagged and first difference models

Week 20
Panel data methods II: Fixed effects and random effects models

Week 21
Reading week: readin and evaluating published panel data studies

Week 22
Fixed and random effects models - properties, tests and specification issues

Week 23
Panel data methods III: Event history analysis

Week 24
Event history analysis - properties, tests and specification issues

Week 30
Review and sum up

Week 31
In Class Test

Assessment

100 per cent Coursework Mark

Coursework

One piece of directed applied coursework using Stata. In-Class Test: 2:00 hour in-class test in week 2631 Other Assessment Details: In class test: 2.00 hour in class in week 31

Other details

In class test: 2.00 hour in class in week 23

Bibliography

  • Please see module outline on moodle

Further information