📊 Theory and Practice of Econometrics II (IIB Paper 10)

Table of Contents

Paper Content

This paper introduces students to a number of intermediary econometric techniques in time series and microeconometrics. With this course, students will gain a deep understanding of the theory and application of those techniques to economic problems.

What you will learn

  • Time series (Michaelmas term)
    • Univariate time series
    • ARDL models
    • Systems of equations
    • VAR models
  • Microeconometrics (Lent term)
    • Programme evaluation and treatment effects
    • Static and dynamic panel data models
    • Random utility model
    • Binary and multinomial choice models
    • Willingness to pay
    • Ordered response models
    • Machine Learning and Decision Trees


The lecturers distribute four problem sets corresponding to their respective material covered in the lectures. You submit solutions to these problem sets, to which your supervisors provide feedback. The supervisions are organised centrally through the Faculty. Typically, each supervision will be for one hour with at most six students. You will engage with the material actively in the supervision.


STATA can be used to apply most of the econometric techniques taught in this course. EViews contains some useful software targeted towards time series. In R or Python, the students can find packages that implement machine learning methods with decision trees, e.g. the grf package. As the course is evaluated via an exam only (no project), students are not required to learn coding in R or Python.



  • Written paper (usually two hours)


Are there prerequisites?

Yes. This paper contains intermediary econometric methods and builds on the introduction to econometrics in second year (IIA) paper 3.

How many lectures and supervisions are there?

16 lectures are held each in week 1-8 of Michaelmas and Lent term. Both the time series and microeconometrics part come with four supervisions, which are held approximately biweekly in Michaelmas and Lent term.