Schedule: 14.04.2020 - 28.05.2020
Teacher in charge (valid 01.08.2018-31.07.2020):
Contact information for the course (applies in this implementation):
Since this is an online course, students are encouraged to post questions to the discussion Forum of this website. General questions about the course should be sent by email to Professor Kuosmanen. Questions concerning the R and GAMS tutorials should be addressed to the
teaching assistant Sheng Dai.
Teaching Period (valid 01.08.2018-31.07.2020):
Not lectured in 2018-2019
V Spring (2019-2020) Otaniemi campus
Learning Outcomes (valid 01.08.2018-31.07.2020):
Developing thorough understanding of the modern methodology of frontier estimation and efficiency analysis, and ability to apply the state-of-the-art estimation techniques to empirical data.
Content (valid 01.08.2018-31.07.2020):
Topics covered in the course will include basic concepts related to the measurement of efficiency and productivity (criteria, objectives, dominance, efficiency, productivity, etc.). Classic data envelopment analysis (DEA) and stochastic frontier analysis (SFA) techniques will be discussed during the course, together with the modern nonparametric regression techniques. Topics of the course also include the estimation of contextual variables that affect efficiency.
Assessment Methods and Criteria (valid 01.08.2018-31.07.2020):
100 % term paper
Elaboration of the evaluation criteria and methods, and acquainting students with the evaluation (applies in this implementation):
Assessment is mainly based on a student project. The
purpose of the student project is to gain some hands on experience of applying
approaches and methods learned during the course to an empirical case of your
choice. The student project can be done alone, or in groups of 2-3 students. Choose
a topic or empirical issue that is interesting for you. A topic that falls
within the scope of your M.Sc. thesis or Ph.D. project is presumably
interesting, and has an added advantage that you are likely to produce material
that can be later useful for your thesis work. Other courses and journal
articles also provide sources of potential topics.
projects will be presented in one of the two workshops in 26 and 28 May.
Further instructions will be provided in due course on the course website.
student project is described in more detail in a written report referred to as
the term paper. The paper should be
written in English, in a good academic style, following the standard style of any
research paper or working paper. The table of contents or the lists of figures
or tables are not required. It is important to explain the methods and
interpret the results, and pay careful attention to the presentation of
results. It is recommended to use figures and tables, but keep in mind that too
much information kills the information.
grading, the main emphasis is in the clear description and motivation of the
methods used, and their appropriateness for the tasks at hand. The novelty of
the topic, approach, or data can be a (big) plus, but they are relatively less
important for a term paper. For example, a decent term paper might be just a
direct replication of a previously reported empirical study with a new set of
data and/or methods.
Workload (valid 01.08.2018-31.07.2020):
Lectures 30 h
Independent work 130 h
Total 160 h (6 ECTS)
Study Material (valid 01.08.2018-31.07.2020):
Lecture notes and additional material are provided on the course website.
The following textbooks may be used as supplementary study material:
Coelli, T., D. Prasada Rao, G.E. Battese. (1998) An introduction to efficiency and productivity analysis. ISBN 0792380606
Details on the course materials (applies in this implementation):
There will be video lectures on 8 themes.
Additional reading related to each theme will be posted on the section "For Aalto Users".
Course Homepage (valid 01.08.2018-31.07.2020):
Prerequisites (valid 01.08.2018-31.07.2020):
Recommended 30C00200 Econometrics.
Grading Scale (valid 01.08.2018-31.07.2020):
Registration for Courses (valid 01.08.2018-31.07.2020):
Details on the schedule (applies in this implementation):
Video lectures and software tutorials will be uploaded on the course website as soon as those are ready.
Online assignments (questions) will be due according to the previously announced schedule of lectures.
The webinar presentations of the student projects will take place in 26th and 28th of May (at 9-12).
The final report of the student project is due in 15th of June.