Module ECON41615: ECONOMETRICS II

Department: Business School (Economics and Finance)

ECON41615: ECONOMETRICS II

Prerequisites

• None

Corequisites

• Econometrics I (ECON41515)

Excluded Combination of Modules

• None

Aims

• to build upon the knowledge gained in Econometrics I and provide students with the specific advanced technical skills (both theoretical and practical) necessary to understand the methods employed by financial econometricians;
• to provide students with the tools required to model stationary and non-stationary time series data and obtain forecasts from financial econometric models.

Content

• limited dependent variables: probit and logit model; maximum likelihood.
• asymptotic theory and random regressors: consistency and asymptotic normality; asymptotic properties of OLS and maximum likelihood estimators; endogeneity, instrumental variable, two stage least squares.
• generalized method of moments (GMM)
• error-correction models and cointegration: stationary vs non-stationary time series; unit root tests; spurious regression and the concept of cointegration; EC models; testing for cointegration.
• cointegration in multivariate systems: The Johansen approach; formulation of the dynamic model; deterministic components in the multivariate model.
• forecasting: an introduction to forecasting, forecasting with univariate time series, forecasting volatility, methods for forecast evaluation.
• volatility models: formulating and estimating the ARCH model; the GARCH model and extensions; stochastic volatility models.

Learning Outcomes

• have advanced knowledge of the principles and methods of modern financial econometrics and time series forecasting;
• have extended and deepened their understanding of Econometrics gained in Econometrics I, and improved their critical judgement and discrimination in the choice of techniques applicable to complex situations;
• have extended their understanding of the application of econometric methods and interpretation of the results at an advanced level;
• have extended their understanding of the use of econometric tools to conduce advanced empirical investigations into complex specialised issues.

• have further practised problem solving skills in econometrics at an advanced level and the use of econometric software.

• Written Communication;
• Planning, Organising and Time Management;
• Problem Solving and Analysis;
• Using Initiative;
• Numeracy;
• Computer Literacy.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

• A combination of lectures, seminars and guided reading will contribute to achieving the aims and learning outcomes of this module. The summative written project and examination will test students' knowledge and critical understanding of the material covered in the module, their analytical and problem-solving skills.

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

Work prepared by students for seminars; answers to questions either discussed during a seminar, or posted on DUO; feedback on discussions with teaching staff during consultation hours, or via e-mail.

■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University