This module presents a systematic and operational approach to the econometric modelling of economic time series, which gives an understanding of the techniques in practical, appropriate, analytical and rigorous manner. Econometric analysis is a core skill in modern economics.
The module links theory to empirical studies of the macroeconomy and includes the following topics:
Univariate Time Series Analysis
• Concepts of stochastic processes;
• Types of linear processes: Autoregressions and moving averages
• Nonstationary linear processes
• Predicting stochastic processes
• Estimation of linear time series models
Dynamic Econometric Models
• Nonsense Regressions;
• The autoregressive distributed lag model;
• Cointegration and equilibrium correction.
Multiple Time Series Models
• Vector autoregressive processes;
• Structural analysis: Causality and impulse-response analysis.
These topics are illustrated with a range of theoretical and applied exercises, which will be discussed in seminars and computer classes. As such, the module emphasises the development of practical skills in the use of software for empirical research, and introduces students to the research methods used by macroeconomists in academia, government departments, think tanks and financial institutions. It also helps students to prepare for the quantitative requirements of a master programme in economics.
This module appears in the following module collections.
Total contact hours: 39 hours
Private study hours: 111
Total study hours: 150
This module is compulsory for Single Honours Economics with Econometrics and Financial Economics with Econometrics.
This module is an elective for all other Single and Joint Honours degree programmes in Economics.
This module is available to well-qualified students from other Faculties.
Method of assessment
40% coursework as follows:
Applied Computer Exercise (10%)
Empirical Project (30%)
Examination, 2 hours (60%)
Time series econometrics is an expansive area of econometric theory and application. Most modern introductory texts provide an introduction to the issues discussed in the module:
Green, W.H. (2003). Econometric Analysis. 5th edition, Englewood Cliffs, NJ: Prentice
Gujarati D N (2002). Basic Econometrics. 4th edition, New York: McGraw-Hill.
Johnston, J. and J. DiNardo (1997). Econometric Methods. 4th edition, New York: McGraw.
Wooldridge J.M. (2016). Introductory Econometrics. 6th edition, Cengage.
See the library reading list for this module (Canterbury)
On completion of the module, you will be able to:
* understand and abstract the time-series properties of economic data.
* synthesise and critically compare different econometric analyses of an economic issue.
* demonstrate analytical skills that can be used to formulate and consider a range of econometric problems and issues.
* practice the use of econometric concepts especially in relation to time series analyses.
* demonstrate critical understanding of statistical, graphical and numerical data analyses.
* collate, examine and interpret time-series data in the context of economic theory and policy.
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Credit level 6. Higher level module usually taken in Stage 3 of an undergraduate degree.
- ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
- The named convenor is the convenor for the current academic session.
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