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ECOM-R314 Advanced Econometrics 1, 5 cr 
Code ECOM-R314  Validity 01.01.2017 -
Name Advanced Econometrics 1  Abbreviation Adv Econom 1 
Scope5 cr   
TypeAdvanced studies
TypeCourse   
  GradingGeneral scale 
  no
    Can be taken more than onceno
Unit Master's Programme in Economics 

Teachers
Name
Mika Meitz 

Description
Target group 

Master’s Programme in Economics (Research track). Open also to doctoral students in economics.

 
Timing 

Annually in the first period

 
Learning outcomes 

After the course, the student should

  • Know the main properties and limitations of the linear regression model 
  • Be familiar with the basics of asymptotic analysis 
  • Be able to employ the linear regression model and related inferential methods in empirical research
 
Completion methods 

The course consists of lectures (24 hours) and exercise sessions (8 hours), where solutions to the homework assignments are discussed. The lectures and exercise sessions are not mandatory. The course is completed by (i) a written final exam and (ii) homework assignments. The homework assignments consist of both analytical and empirical exercises.

 
Prerequisites 

Basic studies in mathematics and statistics, and familiarity with the linear regression model to the extent covered in a Bachelor-level introductory econometrics course.

 
Recommended optional studies 

Knowledge of R (or some other matrix programming language) is useful.

 
Contents 

This course introduces the basic methods used in the linear regression analysis of economic variables. The classical finite sample theory and asymptotic analysis of the linear regression model as well as the necessary methodological tools required for these topics are covered. Specifically, the topics covered in the course include

  • Classical finite sample theory in the linear regression model 
  • The basics of asymptotic theory 
  • Asymptotic theory in the linear regression model 
  • Autocorrelation, heteroskedasticity and dynamic regressors 
  • Specification tests 
  • Omitted variables, instrumental variables and the two-stage least squares estimator (2SLS)
 
Study materials and literature 

Lecture slides and other material assigned by the lecturer

 
Activities and teaching methods in support of learning 

All material related to the course is delivered through the Moodle area of the course, which also contains a discussion forum where students can discuss issues related to the course with each other and the teacher.

 
Assessment practices and criteria 

The grade on a scale from 0 (fail) to 5 is based on the points earned in the final exam. At least 40% of the homework assignments must be completed to take the exam.

 


Current and future instruction
Functions Name Type cr Teacher Schedule
registration period has ended Advanced Econometrics 1  Lecture Course  Mika Meitz 
05.09.19 -10.10.19 thu 14.15-15.45
06.09.19 -20.09.19 fri 12.15-13.45
19.09.19thu 10.15-11.45
27.09.19fri 12.15-13.45
03.10.19 -17.10.19 thu 10.15-11.45
04.10.19 -18.10.19 fri 12.15-13.45
25.10.19fri 10.15-11.45
13.12.19fri 10.00-12.00

Future examinations
No examinations in WebOodi