Course description

Econometrics with Programming

Introduction

The aim of the course is to equip the students with an understanding of econometric techniques at a level expected among master students in economics, finance and related disciplines. Programming will be introduced and used as a natural part of data analysis, and simulation will be used to assess the finite sample behavior of large sample techniques, and to assess robustness properties of statistical methods. Both theoretical and practical exercises will be given.

Course content

  1. Review of probability and basic statistics.
  2. Multiple linear regression.
  3. Time series models.

Learning outcome knowledge

After taking this course, students should have a solid knowledge of the general linear regression model, its most common extensions – including time series analysis – and estimation theory under econometric assumptions, as well as gaining practical experience in applying these models using modern software.

Students should also be able to independently write Matlab programmes related for data analysis, perform simulation experiments, and develop their critical reasoning for econometric investigations.

Exam organisation

  • Written assignment: 40%
  • Written exam: 60%