Econometrics

Lecturer: Dali Laxton

Dates: 17.02.2023 – 12.05.2023

Lectures, Seminars: Friday 14:00 – 17:50

Office hours: online on Tuesday 18:00-19:00 per request


Course Description

The course is designed to give students experience of using basic econometric methods important in
economics and other business subjects. It provides skills in regression essential for understanding
much of the literature of economics, finance, and empirical studies in other areas of business.


The main textbook:

•       Wooldridge, J.M. Introductory Econometrics – A Modern Approach. 5th ed. Michigan State
University, 2013. ISBN-13: 978-1-111-53104-1.

•       Studenmund, A. H. (2011): Using Econometrics: A Practical Guide. 6th Edition, Pearson
Addison Wesley. ISBN: 978-0-13-136773-9.


Pre-requisites

Basic matrix algebra, elementary probability and mathematical statistics.


Course objectives

The course is designed to give students experience of using econometric methods important in
economics, finance and other business subjects. It provides skills in regression essential for
understanding much of the literature of economics, finance, and empirical studies in other areas of
business.

We begin with the simple regression and multiple regression models. They are treated in depth and
in range of applications. Careful attention is given to the interpretations of regression results
and hypothesis testing. A part of the course introduces various modern tools for analyzing economic
time series regression. Moreover, further topics in regression analysis are presented including
regression with panel data and binary dependent variable.

By the end of the course, students should be able to use regression models in many different
applications and to critically examine reported regression results in empirical research in
economics and other business studies. They will be able to identify and deal with a number of
econometric problems in the analysis of time series and cross-section data and will have experience
of a range of basic econometric methods.

The course is designed to give students an understanding of why econometrics is necessary and to
provide them with a working knowledge of basic econometric tools so that: they can apply these
tools to modelling, estimation, inference, and forecasting in the context of real-world economic
problems; they can evaluate critically the results and conclusions from others who use basic
econometric tools; they have a foundation and understanding for further study of econometrics and
they have an appreciation of the range of more advanced techniques that exist and that may be
covered in later econometric courses


Grading (Tentative)

Quick Quizzes 10%

These quizzes will be held every week. The goal is to ensure that the students prepare for the
classes regularly.  Students, who will write less than 3 quizzes in total, will have to take the
final exam at additional 10% weight and this component of grading will be cancelled. During quiz
students are not allowed to use any textbook, any notes and help from classmates. Final grade will
be decided based on 4 best quiz grades among total submitted quizzes.

Class participation: 10%

The grading will be decided in the end of the course based on the activeness and responsiveness of
the students during the classes. Therefore, attending the seminars is essential. Students who have
near zero participation will have to take final exam at additional 10% weight and this component of
grading will be cancelled.

Class project: 20%

Project serves to encourage students apply the skills and techniques acquired during the
econometrics classes to real data. Thus, prepares them for independent thinking and own research.
Presentations on May 5^th.

Midterm exam: 30 %

The midterm exam will take place during regular class on March 24^th. You are not allowed to use
any textbook, any notes or electronic devices. There will be no make-up for the midterm exam.

Final Exam: 30 %

Final exam will take place on May 12th. You are not allowed to use any textbook, any notes or
electronic devices. There will be two possible make-up exams for the final exam (dates TBA).


Grade distribution:

A: 85 – 100

B: 70 - 84

C: 60 – 69

D: 50 – 59

F: 0 – 49

NOTE: The maximum latter grade in make-up exam is B.

Outline

 (This is a tentative schedule to be updated based on students' progress.)

1.       Introduction to econometrics and working with data

2.       A non-technical introduction to regression

3.       Simple regression model

4.       Multiple regression model

5.       Hypothesis testing – statistical inference

6.       Freeing up the classical assumptions – heteroskedasticity

7.       Instrumental variables method

8.       Qualitative choice and limited dependent variable models

9.       Regression with time series variables

10.   Vector autoregressive models

11.   Models for panel data

12.   Other models, methods and issues