Econometrics 2: Topics in Time Series - ECON5430

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Module delivery information

Location Term Level1 Credits (ECTS)2 Current Convenor3 2022 to 2023
Canterbury
Spring Term 6 15 (7.5) Hans-Martin Krolzig checkmark-circle

Overview

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 gives an introduction to univariate time series analysis, dynamic econometric modelling and multiple time series, linking theory to empirical studies of the macroeconomy.

All 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 you to the research methods used by macroeconomists in academia, government departments, think tanks and financial institutions. It also helps you to prepare for the quantitative requirements of a master programme in economics.

Details

Contact hours

Total contact hours: 30 hours
Private study hours: 120
Total study hours: 150

Availability

This module is compulsory for Single Honours Economics with Econometrics and Financial Economics with Econometrics.
This module is optional for all other Single and Joint Honours degree programmes in Economics.
This module is available to well-qualified students from other divisions.

Method of assessment

Main assessment methods
*Temporary Assessment Method for 2022/23*

Applied Computer Exercise (10%)
Group Project (10 pages) 20%
Examination, 2 hours (70%)

Reassessment Instrument: 100% exam

Indicative reading

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

* Johnston, J. and J. DiNardo (1997). Econometric Methods. 4th edition, New York: McGraw.

* Wooldridge J.M. (2016). Introductory Econometrics. 6th edition, Cengage.

Advanced textbooks on time-series econometrics include:

* Enders, W. (2014), Applied Economics Time Series. 4th edition. New York: Wiley.

* Franses, P.H., vanDijk, D., and A. Opschoor (2014), Time Series Models for Business and Economic Forecasting. 2nd edition. Cambridge: Cambridge University Press.

* Hamilton, J.D. (1994). Time Series Analysis. Princeton: Princeton University Press.

* Hendry, D.F. (1995). Dynamic Econometrics. Oxford: Oxford University Press.

* L├╝tkepohl H. (2006). Introduction to Multiple Time Series Analysis. New York: Springer.

Additional readings will be given for the selected topics in the module outline.

See the library reading list for this module (Canterbury)

Learning outcomes

On successfully completing the module students will be able to:

8.1. Understand and abstract the time-series properties of economic data

8.2. Synthesise and critically compare different econometric analyses of an economic issue

8.3. Demonstrate analytical skills that can be used to formulate and consider a range of econometric problems and issues

8.4. Practise the use of econometric concepts especially in relation to time series analysis.

8.5. Demonstrate critical understanding of statistical, graphical and numerical data analyses

8.6. Collate, examine and interpret time-series data in the context of economic theory and policy

Notes

  1. Credit level 6. Higher level module usually taken in Stage 3 of an undergraduate degree.
  2. ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
  3. The named convenor is the convenor for the current academic session.
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