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Basic Information
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Location: Helsinki
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Time: Academic year 2010-2011
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Application form
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Deadline for applications:
August 27, 2010
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Please note that the applicants will be informed of their acceptance
after the deadline at the latest
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The course is divided in two parts. In total the
course includes 48 hours of lectures and 24 hours of exercises, two
midterm exams and/or a retake exam
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FDPE recommends that the course is acknowledged
by the student's own university/department with 8 ECTS credit points
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Teaching Staff
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Instructors: Part I Professor
Markku Lanne (University
of Helsinki) and Part II Professor
Pekka Ilmakunnas
(Aalto University School of Economics)
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Teaching assistant:
Part I & II
Matthijs Lof (University of Helsinki)
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Course Requirements and Exams
To pass the course the student must:
- take two midterm exams: the first midterm exam is arranged in the autumn
term and the second midterm exam is arranged in the spring term;
AND/OR
- take a retake exam in the spring term (part I and II must be examined
together);
AND
- get 40 % of the combined maximum points of the two midterm exams or the
retake exam (at the minimum)
AND
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write a term paper (consisting of an independent empirical study) which
will be part of the final grade.
- The final grade consists of two midterm exams or a retake exam (70% of
the final grade) and the term paper (30% of the final grade).
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To take the exams the student must:
- solve at least 50% of the given problems (separately for part I and part
II) "showing good effort" so that the principles of solutions are correct.
- This is a prerequisite for taking both the midterm exams and the retake
exam.
Please note that the students' home departments are responsible for
registering the grades according to their own requirements. FDPE gives the
students, on request, a certificate of the courses passed within the programme.
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Topics
Topics covered in the course include:
- maximum likelihood estimation
- GLS estimation
- instrumental variables
- dynamic models
- simultaneous equations
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How to Prepare Yourself for the
Course
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Matrix notation is used throughout
the course, and you are also expected have basic knowledge of probability
theory and statistical inference. To prepare for the course, review these
topics in advance. A collection of results of matrix algebra and probability
can for example be found in Appendices A and B of Hansen’s econometrics
textbook manuscript (http://www.ssc.wisc.edu/~bhansen/econometrics/Econometrics.pdf).
The course involves a number of empirical exercises and a term paper that
require knowledge of a statistical software package. Therefore, you should
be able to use at least one such package in advance. Canned packages such as
Stata, Limdep or Eviews should be sufficient, but it is advisable to learn a
matrix programming language such as Gauss, Matlab, R or Mata (Stata’s matrix
programming language).
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Instructions on how to prepare yourself for the 1st year FDPE core
courses
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