Econometrics (ECON0108)

Key information

Faculty: Faculty of Social and Historical Sciences
Teaching department: Economics
Credit value: 15

Restrictions: N/A
Timetable

Alternative credit options

This module is offered in several versions which have different credit weightings (e.g. either 15 or 30 credits). Please see the links below for the alternative versions. To choose the right one for your programme of study, check your programme handbook or with your department.

Econometrics (ECON0064)

Description

Summary: This part of the course discusses estimation and inference in econometric models. The 铿乶al couple of lectures will introduce basic elements of time series analysis.

Prerequisites: The course assumes knowledge of Econometrics at the MSc level. The following concepts are taken for granted: random variables, distribution functions (marginal, joint, conditional), transformations of random variables, independence, expectations, conditional expectations, moments, covariance and correlation, (multivariate) normal distribution. To review these topics, see the 铿乺st few chapters of Casella and Berger (2001). Importantly, I will also assume knowledge of most of the 铿乺st chapter of the recommended textbook (chapters 1.1鈥�1.6 of Hayashi (2000)), which includes: the classical linear regression model, OLS estimation, 铿乶ite-sample properties of OLS, hypothesis testing under normality, GLS estimation. Part of this material will be covered by problem sets, but it is a good idea to read up on it beforehand.

Module deliveries for 2024/25 academic year

Intended teaching term: Terms 1 and 2 听听听 Postgraduate (FHEQ Level 7)

Teaching and assessment

Mode of study: In person
Methods of assessment: 100% Exam
Mark scheme: Numeric Marks

Other information

Number of students on module in previous year: 34
Module leader: Professor Andrew Chesher

Last updated

This module description was last updated on 8th April 2024.

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