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Instructor-led course

Provided by: Social Sciences Research Methods Programme


This course has 1 scheduled run. To book a place, please choose your preferred date:


Wed 22 Feb 2023


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Time Series Analysis


Description

This module introduces the time series techniques relevant to forecasting in social science research and computer implementation of the methods. Background in basic statistical theory and regression methods is assumed. Topics covered include time series regression, Vector Error Correction and Vector Autoregressive Models, Time-varying Volatility, and ARCH models. The study of applied work is emphasized in this non-specialist module. Topics include:

  • Introduction to Time Series: Time series and cross-sectional data; Components of a time series, Forecasting methods overview; Measuring forecasting accuracy, Choosing a forecasting technique
  • Time Series Regression; Modelling linear and nonlinear trend; Detecting autocorrelation; Modelling seasonal variation by using dummy variables
  • Stationarity; Unit Root test; Cointegration
  • Vector Error Correlation and Vector Autoregressive models; Impulse responses and variance decompositions
  • Time-varying volatility and ARCH models; GARCH models
Target audience
  • University Students from Tier 1 Departments
  • Further details regarding eligibility criteria are available here
Prerequisites
  • A background in basic statistical theory and regression methods
  • A working knowledge of statistical concepts up to the level of Linear Regression
Assessment

There may be an online open-book test at the end of the module; for most students, the test is not compulsory.

Textbook

Hill, Griffiths & Lim (2011). Principles of Econometrics (4th ed). John Wiley & Sons. ISBN-10: 0470626739. ISBN-13: 978-0470626733.

Software

Stata

How to Book

Click the "Booking" panel on the left-hand sidebar (on a phone, this will be via a link called Booking/Availability near the top of the page).

Moodle

Moodle is the 'Virtual Learning Environment' (VLE) that the SSRMP uses to deliver online courses.

SSRMP lecturers use Moodle to make teaching resources available before, during, and/or after classes, and to make announcements and answer questions.

For this reason, it is vital that all SSRMP students enrol onto and explore their course Moodle pages once booking their SSRMP modules via the UTBS, and that they do so before their module begins. Moodle pages for modules should go live around a week before the module commences, but some may be made visible to students, earlier.

For more information, and links to specific Moodle module pages, please visit our website

Duration

8 hours - A morning lecture and an afternoon lab session
This is an intensive, one-day module

Theme
Statistics

Events available