The goal of this module is to provide students with a solid foundation in the statistical and econometric techniques that allow them to conduct independent empirical investigations in economics and finance. The approach centers on the regression methods, including their use in estimating and testing the validity of models in economics and finance. The module serves as a guide for business managers, research economists and practitioners. The aims are that students will: (i) acquire “hands on” training in the use, presentation and interpretation of economic data; (ii) understand aspects of the theories and principles of econometric analysis in economics and finance, (iii) be aware of a range of inferential techniques commonly employed in econometrics, and (iv) understand the limitations of such techniques in different circumstances.
A Demonstrate in-depth knowledge and understanding of OLS assumptions and of their violations
B Critically evaluate and apply a range of mathematical and statistical techniques necessary for understanding and using econometric methodology.
C Formulate, estimate and test a wide range of models in empirical analyses.
D Use the econometric package STATA in real applications.
There will be a two-hour lecture per week that covers some of the most important topics in modern econometrics, for doing and understanding empirical work. Our focus is mainly on the applied aspect of econometrics; that is, the module does not concentrate too much on the formulae behind each technique nor on formal proofs, but on the intuition behind the approaches and their practical relevance. In addition, the students will make use of the computing facilities and software for the analysis of real data and problems in the lab sessions. STATA is used to computing practical in which students will apply the theories learned in lectures. Reference to journal articles will expose students to both applications of, and developments in, techniques in the areas they will be studying.