Time Series Econometrics - EC820

Location Term Level Credits (ECTS) Current Convenor 2019-20
Canterbury
(version 4)
Spring
View Timetable
7 15 (7.5) PROF H Krolzig

Pre-requisites

EC821 Econometric Methods

Restrictions

None

2019-20

Overview

The module offers a research-oriented introduction to contemporary time series econometrics by linking econometric theory to empirical studies of the macro-economy and financial markets. It introduces models and methods used in central banks and research institutions for policy analysis and forecasting. It integrates empirical illustrations through the use of computer-based exercises with macroeconomic and financial data using appropriate software. We start with providing comprehensive treatment of univariate time series analysis and deal in details with the modelling and forecasting of stationary and non-stationary stochastic processes. We then look into models of time-varying volatility. Finally, we generalise the learned techniques to multiple time series and study co-integration.

Details

This module appears in:


Contact hours

36 hours of academic teaching in the form of lectures and seminars

Method of assessment

30% Project (2000 words)
10% In-Course Test (60 minutes)
60% Examination (2 hours)

Indicative reading

• Hamilton, James. Time Series Analysis. Princeton University Press, 2014
• Enders, Walter. Applied Econometric Times Series. 4th Edition. Wiley, 2014
• Lütkepohl, Helmut. New Introduction to Multiple Time Series Analysis. Springer, 2006
• Franses, Philip, van Dijk, Dick and Anne Opschoor. Time Series Models for Business and Economic Forecasting. 2nd Edition. Cambridge University Press, 2016

See the library reading list for this module (Canterbury)

Learning outcomes

On successfully completing the module students will be able to:

• demonstrate a comprehensive understanding of econometric techniques used with time series data
• demonstrate critical assessment in reading and interpretation of empirical macroeconomic research
• be practised in own modelling of economic series using advanced econometric theory
• demonstrate the ability to undertake complex empirical research using statistical software for time series analysis
• utilise modern computing resources to access and acquire time series data from relevant sources
• demonstrate enhanced problem-solving skills with complex quantitative models
• present convincing and rigorous economic arguments orally as well as in written form

University of Kent makes every effort to ensure that module information is accurate for the relevant academic session and to provide educational services as described. However, courses, services and other matters may be subject to change. Please read our full disclaimer.