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EC976: Econometrics

  • Gianna Boero

    Module Leader
15 CATS - Department of Economics

Principal Aims

EC976-15 Econometrics for MSc Finance Economics

Principal Learning Outcomes

Subject knowledge and understanding By the end of the module the students will have a deeper and broader knowledge of material needed for empirical quantitative analysis The teaching and learning methods that enable students to achieve this learning outcome are: Series of lectures and tutorials The summative assessment methods that measure the achievement of this learning outcome are: Examination and written assignment.

Cognitive Skills Develop critical insight to appraise econometric results obtained by other researchers. Develop that habit of thought, knowledge and understanding to be able to carry out good quality applied econometric research with confidence and authority. The teaching and learning methods that enable students to achieve this learning outcome are: Class discussions, lectures, topic specific readings. Tutorial discussions and readings of journal articles. Data collection and replication of results. The summative assessment methods that measure the achievement of this learning outcome are: Examination and written assignment.

Key skills Developed key skills through class discussions, weekly exercises and tutorials. Have a deeper and broader knowledge and understanding of material needed for empirical quantitative analysis. The teaching and learning methods that enable students to achieve this learning outcome are: Series of lectures and tutorials.Series of lectures and tutorials The summative assessment methods that measure the achievement of this learning outcome are: Examination and written assignment.

Syllabus

Estimation of unknown parameters in linear models – OLS. Introduction to inference - testing hypotheses about the model parameters. Cross-section data - heteroscedasticity, parameter constancy. Endogeneity and instrumental variables estimation. Limited dependent variable models. Time series models: ARMA. Trends and Cointegration analysis. Vector Autoregression Models. Introduction to ARCH-GARCH models

Context

Assessment

Assessment Method
Coursework (30%) + 2 hour exam (January) (70%)
Coursework Details
Assessment 1 (30%), 2 hour exam (January) (70%)
Exam Timing
N/A

Reading Lists