Syllabus

Title
0686 Advanced Subject in Economics - Spatial Economics
Instructors
Tamas Krisztin, M.Sc.Ph.D., Philipp Piribauer, Ph.D., Dr. Mathias Moser, Franziska Disslbacher, PhD, MSc, BSc
Type
PI
Weekly hours
4
Language of instruction
Englisch
Registration
09/18/18 to 09/23/18
Registration via LPIS
Notes to the course
Dates
Day Date Time Room
Friday 10/12/18 04:00 PM - 07:00 PM D4.0.144
Tuesday 10/16/18 04:00 PM - 07:00 PM TC.5.02
Friday 10/19/18 04:00 PM - 07:00 PM D4.0.144
Tuesday 10/23/18 04:00 PM - 07:00 PM TC.5.02
Tuesday 11/06/18 04:00 PM - 07:00 PM TC.3.10
Friday 11/09/18 04:00 PM - 07:00 PM D4.0.144
Tuesday 11/13/18 05:00 PM - 08:00 PM D4.0.039
Friday 11/16/18 04:00 PM - 07:00 PM D4.0.144
Thursday 11/22/18 02:00 PM - 05:00 PM LC.-1.038
Friday 11/23/18 04:00 PM - 07:00 PM D4.0.144
Thursday 11/29/18 02:00 PM - 05:00 PM D4.0.144
Friday 11/30/18 04:00 PM - 07:00 PM D4.0.144
Thursday 12/06/18 03:00 PM - 06:00 PM TC.2.03
Thursday 12/13/18 03:00 PM - 06:00 PM D4.0.127
Thursday 12/20/18 02:00 PM - 05:00 PM D4.0.144
Thursday 01/10/19 03:00 PM - 06:00 PM D4.0.144
Thursday 01/17/19 03:00 PM - 06:00 PM D4.0.144
Thursday 01/24/19 03:00 PM - 06:00 PM D4.0.019
Contents

Typically, the sessions will be devoted to lectures that explain the essential materials. Separate tutorial sessions aim at exposing the students to the practical implementation of various techniques in spatial data anlysis and spatial econometrics. Considerable attention will be paid to gaining hands-on experience in the application of spatial extensions of econometric models and techniques in empirical practice. An important aspect of the course is an empirical exercise that students carry out, using their own data (for example, for a master thesis project) or one of the data sets provided. Course material: There is no traditional course text. But the lecture slides and a limited number of readings are provided on the learn@wu platform. Class attendance: required. Classroom citizenship: a respectful interaction among all course participants is expected.

Learning outcomes
The main objective of the course is to expose students to the state of art in spatial economics with emphasis on regional economic growth, spatial econometric methods and empirics. Upon completing the course, students should be able to understand the importance of location and spatial dependence in regional development processes, and to apply spatial econometric methods and techniques in empirical practice.
Attendance requirements

A unit may be missed, but prior notification by e-mail to the course leader is required.
 

 

Teaching/learning method(s)
There will be lectures in which the focal point is on the teacher’s explanation of the essential material. Active participation of the students is, however, expected in all lectures. Class discussions and making small exercises to better comprehend the material will be part of the lectures. Spatial econometrics software and data will be made available for computer lab exercises.
Assessment
Mode of assessment: Active participation and exercises (20%); class project (30%) and final exam (50%). Grades: 87.5-100% (very good: 1), 75.0-87.5% (good: 2), 62.5-75.0% (satisfactory: 3), 50-62.5% (sufficient: 4), 0-50% (fail: 5).
Prerequisites for participation and waiting lists

Recommended previous knowledge and skills
There are no formal prerequisites, but a good knowledge in econometric methods, or a prior undergraduate course in basic spatial statistics or spatial econometrics are highly recommended.
Last edited: 2018-06-21



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