# Open education

In 2020 and 2021, I have recorded some of my lectures. Here I provide these videos together with the slides and lecture notes.

Econometrics (B.Sc.)

This is a standard econometrics course at the bachelor level. It is based on Wooldridge's book *Introductory Econometrics: A Modern Approach.*

Introduction

Simple regression model

Multiple regression

Inference

Asymptotics

Heteroskedasticity

Regression analysis with time series data

Time series: serial correlation and heteroskedasticity

Instrumental variables estimation

Data Science Research Methods (B.Sc.)

This set of lectures is offered to bachelor students in the Data Science program. It covers very standard material on causal inference based on Angrist and Pischke's book* Mostly Harmless Econometrics.*

Econometrics for data scientists

Causality and selection

Selection on observables and matching

Differences-in-differences estimation

Regression discontinuity design

Econometrics (Ph.D.)

This is part of an econometrics course in the first year of our Ph.D. program. Here I cover binary, ordered, and multinomial choice; as well as censoring and truncation.

Introduction

Preliminaries

Binary choice

Binary choice, more general

Ordered choice

Multinomial choice

Multinomial choice, more general

Censoring and truncation

Empirical Industrial Organization (Ph.D.)

This is part of our field course in empirical IO. The videos cover dynamic discrete choice and dynamic games.

Search models

Dynamic demand

Two step estimation of dynamic games