For students:

Advanced Econometrics 2 (5 cr)

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Code:
ECOM-R315
Field:
Econometrics
Targets:
Research Master's students PhD students
Organiser:
University of Helsinki - Economics
Instructor:
Mika Meitz
Period:
Period 2
Format:
Lecture
Method:
Remote teaching
Remote:
Zoom link can be found in Moodle
Enrollment:
Sisu How to enroll?

In case of conflicting information consider the Sisu/Courses/Moodle pages the primary source of information.

Content

This course moves beyond the standard linear regression model and conventional least squares estimation. Important econometric estimation principles, such as generalized method of moments and maximum likelihood estimation, are covered and the related statistical inference procedures discussed. Basic concepts of simulation-based methods are also introduced. Specifically, the topics covered in the course include

  • Generalized method of moments estimation (basic concepts, asymptotic estimation theory, statistical inference)
  • Maximum likelihood estimation (basic concepts, asymptotic estimation theory, statistical inference)
  • Simulation methods (Monte Carlo simulations, Bootstrap)

Teaching

  • Completion method: remote teaching (a link to Zoom can be found in the course Moodle area)
  • Schedule: can be found in Course Page and Sisu
  • Study materials: can be found in Moodle
    • For some courses, it is enough to register in Sisu and you can access directly the Moodle area, please note, however, that it may take up to two hours after registration to enter the Moodle area.
    • Log in with your UH username to be able to use all the features of the course workspace
    • More tips for enrolling in Moodle can be found here
  • Self study material to be studied before the course starts

Please register for the course in the UH Sisu with your UH username, further instructions can be found here.

University-specific instructions

Aalto University Students
  • Code: ECON-L4200
  • Target groups: PhD / rMSc
  • Credit points: 5
  • Credit transfer: apply for substitution in Sisu
Hanken Students
  • Code: 26054
  • Target groups: PhD / rMSc
  • Credit points: 5
  • Credit transfer: apply for substitution in Sisu
University of Helsinki Students

  • Code: COM-R315

  • Target groups: PhD / rMSc

  • Credit points: 5

FDPE Students Students
  • Target groups: PhD
  • Credit points: please check your curriculum
  • Credit transfer: please apply for credit transfer according to your home university's procedures

Learning outcomes

After the course, the student should know the properties of the estimators introduced and be able to apply them and the related inferential procedures in empirical work. The course should also give a solid foundation for the study of more specialised microeconometric and time series methods.