Second year module
Lecturer: Joanne S Ercolani
This module reviews basic concepts of probability, statistical theory and methods introduced in year 1 modules. It develops ideas of random variables, sampling, estimation, hypothesis testing and related aspects of inferential methods. Two variable and multiple regression models are developed and estimation procedures considered under the classical assumptions as well as violations of these assumptions. Applications to empirical economics are introduced to link the statistical and econometric methods to a range of problems in economics. Weekly problem classes and computer laboratory sessions support the lectures.
This linked module consists of: further violations of the assumptions of the classical linear regression model, issues of model misspecification, the importance of dynamic models in econometric work, implementation and interpretation of results on a range of applied topics. Weekly problem classes and computer laboratory sessions support the lectures.
On completion of this module the student will:
have an understanding of the nature of statistical inference
be able to apply a range of basic methods of inference to practical problems in econometrics and empirical economics
have developed some practical computing skills; be able to interpret the results of methods applied
have an understanding of basic econometric theory
be able to apply more advanced econometric techniques
have developed practical computing skills
be able to interpret econometric results
3 hr examination 60%
2 x Tests 20% each