Who are and where are the Rwanda’s poorest? A Small Area Estimation Method
Main Article Content
Abstract
As Rwanda is achieving its vision of moving from a low to a middle–income country during the period 2000–2020, its capability of ending poverty along the Sustainable Development Goals’ era (2015–2030) mostly depends on how well the increasing prosperity will be shared among Rwandans along the way up to the 2030 horizon. Knowing those who have not yet benefited enough from the ongoing progress should help Rwanda’s policy makers and other development agencies to serve that purpose. With this perspective, this work has the two major objectives of estimating poverty by sector and studying the relationship between poverty and related variables in Rwanda. We tackle the first objective with the Small Area Estimation method (SAE) and covers the second with the Poisson regression. We find that (1) most of the very poor are located within rural areas, (2) live in larger households and, (3) have female household heads.
Downloads
Article Details
The authors acknowledge that the Revista de Fomento Social assumes as its own the intellectual property rights over their work and grant the journal the permissions of distribution and public communication of the same established in the Berlin, Bethesda and Budapest declarations; for this reason they accept that the work presented be distributed in open access, protecting the copyright under a "Creative Commons Attribution-NonCommercial-NoDerivativeWorks 4.0 (CC BY-NC-ND) license.
You may copy, use, disseminate, transmit and publicly display provided that:
Cite the authorship of the work, the publication in Revista de Fomento Social, issue, year and the pages where you found the information.
No commercial benefit may be obtained.
No derivative works may be made for commercial purposes that are not authorized by the journal.
Authors are encouraged to disseminate the article electronically (Revista de Fomento Social, number, year, pagination, ISSN, DOI, etc.), in order to favor its circulation and diffusion, increase its citation and reach among the academic community.
The information of the journal will be provided to Dulcinea
References
CHANDRA, H., ADITYA K., SUD U. C. (2018): “Localised estimates and spatial mapping of poverty incidence in the state of Bihar in India–An application of small area estimation techniques”, Plos ONE, 13(6): e0198502.https//doi.org/10.1371/journal.pone.0198502.
COULOMBE, H., WODON, Q. (2007): Combining census and household survey data for better targeting: The West and Central Africa Poverty Mapping Initiative, Findings Africa Region No. 280, The World Bank, Washington, D.C.
FOSU, K. A. (2015): “Growth inequality and poverty in Sub-Saharan Africa”, Oxford Development Studies, 43(1), pp. 44-59.
GHANA STATISTICAL SERVICE (2015): Ghana poverty mapping report, Publication & Sales unit.
JIANG, J., NGUYEN, T., RAO, J. S. (2011): “Best predictive small area estimation”, Journal of the American Statistical Association, 106, pp. 732-745.
MINISTRY OF FINANCE AND ECONOMIC PLANNING (2019): Revised Version of Vision 2020, http://www.minecofin.gov.rw/index.php?id=148&L=132, consulted last time on the 2nd November 2019.
MONGONGO, P. D. (2016): “On the measurement and use of equality weighted growth”, Iberoamerican Journal of Development Studies, 5(2), pp. 126-139.
NATIONAL INSTITUTE OF STATISTICS OF RWANDA (NISR): Poverty Mapping Report, 2013/14; May 2017.
OVERSEAS DEVELOPMENT INSTITUTE (2015): Combining finances and policies to implement a transformative post-2015 development agenda, European Report on Development 2015, European Commission’s online publication, http://ecdpm.org/wp-content/uploads/2015-European-Report-on-Development-English.pdf (accessed for the last time on September 14, 2018).
PFEFFERMANN, D., (2002): “Small area estimation: new developments and directions”, International Statistical Review, 70(1), pp. 125–144.
PINKOVSKIY, M., SALA–I–MARTIN, X. (2014): “Africa is on time”, Journal of Economic Growth, 19(3), pp. 311–338.
SACHS, J. (2015): The age of sustainable development, Columbia university press, New York.
STATISTICS SOUTH AFRICA (2018): Poverty Mapping in South Africa, Stats SA Library Cataloguing–in–Publication (CIP) Data.
TEZANOS, S., QUIÑONES, A., GUIJARRO, M. (2013): “Inequality, aid and growth: Macroeconomic impact of aid grants and loans in Latin America and the Caribbean”, Journal of Applied Economics, 16(1), pp. 153–177.
UGANDA BUREAU OF STATISTICS (2018): Poverty Maps of Uganda, Technical report.
UNITED NATIONS (2015): Transforming our world: the 2030 Agenda for Sustainable Development, A/RES/70/1
WORLD BANK (2018): World Development Indicators, www.worldbank.org, consulted last time on the 25th October 2018.
— (2019): Poverty Mapping in Georgia, ECA Poverty and Equity Global Practice, World Bank.
