Introductory Econometrics

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.

Learning outcomes

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