Applied Econometrics for Time-Series Data Analysis
- Module Code:
- Module Not Running 2019/2020
- Year of study:
- Final Year
- Taught in:
- Term 1
This course builds technically on the second-year course Econometrics (15 340 0103), the prerequisite for this course. It also builds conceptually on the core course: Macroeconomic Analysis. The course is designed to provide students with a "hands-on" environment. It aims at helping students deepen and broaden their knowledge and understanding of econometric techniques needed for empirical analyses of time-seires data for macro and also financial modelling research. In addition, the course also aims to develop students' abilities in critical evaluation of what is taught in econometrics textbooks.
Objectives and learning outcomes of the module
LO1. By the end of the course the students will have developed the necessary skills needed for empirical research using econometric techniques in addressing modelling issues using time-series data; Through their computer based assignments they will also be trained in conducting research using primary data; The students will also deepen their other transferable skills such as, written communication, teamwork, numeracy; computer literacy, problem solving, and analytical skills.
two-hour lecture and a one-hour workshop each week.
Scope and syllabus
Main econometric techniques: Regression analyses, residual diagnostic tests, multicollinearity and omitted variable bias (confounding), dynamic model specification, model selection, forecasting and cross validation; main economic modelling topics: Capital asset pricing model (CAPM), costs and production function, demand elasticity estimation, modelling the Phillips curve.
Method of assessment
3,000 word essay (100% of the total mark for the module) due Term 2.
Standard textbooks of econometrics, macroeconomics and finance:
E.R. Berndt, The Practice of Econometrics, Addison-Wesley. 1990
Peter Kennedy, A guide to Econometrics, 6E, 2008