OPHI, in collaboration with the Statistical, Economic and Social Research and Training Centre for Islamic Countries (SESRIC) and the Islamic Solidarity Fund for Development (ISFD), is inviting applications for a training course in Multidimensional Poverty Measurement that will be hosted in Dakar, Senegal.
The course will be taught in English, but will have simultaneous translation into French and Arabic.
The course will take place from 30 November-6 December, 2015. The purpose of this intensive training is to provide a thorough conceptual and technical introduction to some techniques of measuring multidimensional poverty with a strong emphasis on the Alkire Foster method. The empirical motivation for measuring multidimensional poverty will be presented as well as the conceptual motivation, drawing on Amartya Sen’s capability approach.
Applicants are warmly invited to apply by completing the application form which is available by clicking HERE. The closing date for applications is 25 September 2015, and participants will be informed of selection from 30 September.
**N.B. please forward all relevant attachments to firstname.lastname@example.org
More details on the course and a draft agenda are available here. Any further enquiries can be directed to Julia Zulver (email@example.com).
The training courses is addressed to those who are working on, or actively interested in gaining skills in, multidimensional poverty measurement, particularly, professionals, government officials, academics, and post-graduate students. Other applicants having a demonstrated research interest in empirical analysis in these topics will be considered on the basis of their experience and space availability.
- A demonstrable knowledge of STATA is an absolute pre-requisite for attending the course. Every attendant to the training course will need to have STATA 10 or higher installed in his/her laptop. The software is not provided by the organizers
- Where possible, participants should have a strong knowledge in quantitative methods (e.g. econometrics, statistics, etc), and a strong interest in poverty measurement and analysis.