Syllabus

Titel
1031 Population, Human Capital and Policy II
LV-Leiter/innen
Endale Birhanu Kebede, Ph.D.
Kontakt
  • LV-Typ
    PI
  • Semesterstunden
    4
  • Unterrichtssprache
    Englisch
Anmeldung
16.09.2019 bis 01.10.2019
Anmeldung über LPIS
Hinweise zur LV
Planpunkt(e) Master
Termine
Wochentag Datum Uhrzeit Raum
Mittwoch 02.10.2019 09:00 - 12:00 TC.3.02
Mittwoch 09.10.2019 09:00 - 12:00 D2.0.025 Workstation-Raum
Mittwoch 16.10.2019 09:00 - 12:00 D2.0.031 Workstation-Raum
Mittwoch 23.10.2019 09:00 - 12:00 D2.0.025 Workstation-Raum
Mittwoch 30.10.2019 09:00 - 12:00 D2.0.025 Workstation-Raum
Mittwoch 06.11.2019 09:00 - 12:00 D2.0.025 Workstation-Raum
Mittwoch 13.11.2019 09:00 - 12:00 D2.0.025 Workstation-Raum
Mittwoch 20.11.2019 09:00 - 12:00 D2.0.025 Workstation-Raum
Mittwoch 27.11.2019 09:00 - 12:00 D2.0.025 Workstation-Raum
Mittwoch 04.12.2019 09:00 - 12:00 D2.0.025 Workstation-Raum
Mittwoch 11.12.2019 09:00 - 12:00 D2.0.025 Workstation-Raum
Mittwoch 18.12.2019 09:00 - 12:00 D2.0.025 Workstation-Raum
Mittwoch 08.01.2020 09:00 - 12:00 D2.0.025 Workstation-Raum
Mittwoch 15.01.2020 09:00 - 12:00 D2.0.025 Workstation-Raum
Mittwoch 22.01.2020 09:00 - 12:00 D2.0.025 Workstation-Raum

Inhalte der LV

In this hands-on programming course, participants will learn how to use basic and advanced spreadsheet techniques (in Excel and VBA) to present and analyze demographic data.

More specifically, students will embark on a journey to understand the evolution of population and human capital (with a specific focus on educational attainment) in a country of their choosing. We will then define future scenarios and project population and human capital into the future, first along the basic dimensions of age and sex, later by level of educational attainment. Once the model is ready, we will explore the policy implications of different assumptions.

Lernergebnisse (Learning Outcomes)

After completion of this course, students will be able to

- apply different demographic techniques using Excel and Visual Basic

- calculate and interpret life tables

- perform demographic projections applying cohort-component methodology

- learn how to work with and transform large demographic data sets

Regelung zur Anwesenheit

atleast 12 out of 15 units

*Because of a very interactive nature of the teaching method, i advise  all participants in the course attend all sessions.

Lehr-/Lerndesign

This is an intensive hands-on computer lab course. The screen of the instructor is projected to be seen by all participants.

There will be a frequent back and forth between the instructor explaining a new concept or method followed by the students implementing this method on their computers. Students will be provided with input data, but will also have to search for their own data on the internet and download it for their calculations. In addition to the regular active participation in class and in group discussions, students will have to deliver reports in which they demonstrate how they could apply the new methods to new data.

Because of this style of intensive interactive teaching it is essential that all participants in the course attend all sessions.

Leistung(en) für eine Beurteilung

Demographic country profile (30%); to be presented in class and submitted as a written report

2. Population projections (50%)

   a. by age and sex (20%); using the WIC data for the country chosen, to be submitted in Excel-format, including a running VBA-macro (not a written report)

   b. by age, sex, and,  if possible, by education  and labor force participation (30%); to be presented in class and submitted as a final report before the end of the semester

3. Classroom participation and quiz(20%)

Teilnahmevoraussetzung(en) und Vergabe von Wartelistenplätzen

Particiaption in Course I - Population, Human Capital and Policy

 

Prerequisites for Incoming Exchange Students nominated by WU partner universities:
Minimum requirements to attend this course:
• Economics (accumulated minimum of 16 ECTS credits) OR
• Social sciences (accumulated minimum of 16 ECTS credits) OR
• Mathematics / statistics / quantitative methods (accumulated minimum of 16 ECTS credits)
Proficiency in English is required. If you do not meet this requirement, we reserve the right to withdraw students from the course.

Zuletzt bearbeitet: 01.07.2019



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