A Two-Factor Model to Investigate the Effect of Time and Location to the Total Consumption Poverty Lines (TCPL) in Zimbabwe
American Journal of Theoretical and Applied Statistics
Volume 5, Issue 2, March 2016, Pages: 39-48
Received: Jan. 27, 2016; Accepted: Feb. 8, 2016; Published: Mar. 1, 2016
Views 3423      Downloads 79
Authors
Romeo Mawonike, Department of Mathematics and Computer Science, Great Zimbabwe University, Masvingo, Zimbabwe
Blessing Chigunyeni, Department of Mathematics and Computer Science, Great Zimbabwe University, Masvingo, Zimbabwe
Article Tools
Follow on us
Abstract
Poverty is rampant throughout the entire country of Zimbabwe and is smelt everywhere as its wave penetrates every sector of the economy. Zimbabwe’s poverty is directly linked to its extremely high unemployment rate. Men, women, and youth are all affected by unemployment, including university graduates, as a number of industries and businesses have closed over the years, due to decline in tobacco exports, and the loss of revenue from the mining and farming sectors. Geographical location has a significant role in determining the income one has to spend to earn a living as there is some disparity in total consumption poverty lines with different provinces. Financial assistance or aids also varies in volume with the nature of province. In this paper, we seek to investigate whether Total consumption poverty line in Zimbabwe varies with time (type of month) and or with geographical location (the type of province into which one lives). We further seek to investigate which provinces share the same TCPL and which ones are most affected. We apply an ordinary Two–Factor Factorial Design to conclude our investigation.
Keywords
Experimental Design, Total Consumption Poverty Line, Analysis of Variance, Multiple Comparisons
To cite this article
Romeo Mawonike, Blessing Chigunyeni, A Two-Factor Model to Investigate the Effect of Time and Location to the Total Consumption Poverty Lines (TCPL) in Zimbabwe, American Journal of Theoretical and Applied Statistics. Vol. 5, No. 2, 2016, pp. 39-48. doi: 10.11648/j.ajtas.20160502.11
Copyright
Copyright © 2016 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
References
[1]
Zimbabwe National Statistics Agency (ZIMSTAT), 2013. Poverty and Poverty Datum Line Analysis in Zimbabwe 2011/12. Website: www.zimstat.co.zw.
[2]
World Bank 2001. World Development Report 2000/2001: Attacking Poverty. Oxford University Press, New York, USA.
[3]
Asare, O.M.S., 2011. How poverty is a fortress without drawbridges and why we must build bridges. Masters Dissertation. UMI Dissertation Publishing, ProQuest. USA.
[4]
Namara, R.E., Hanjra, M.A., Castillo, G.E., Ravnborg, H.M., Smith, L., and Koppen, B., 2010. Agricultural water management and poverty linkages. Agricultural Water Management. 97, 520–527.
[5]
Saunyama, T.C. 2014. The Contribution of Informal Sector Trade to Poverty Reduction in Rusape, Zimbabwe. Masters Dissertation. University of Pretoria. South Africa.
[6]
Chambers, R., 1988. Poverty in India: Concepts, Research and Reality. Discussion Paper 241. Institute of Development Studies, University of Sussex, U.K.
[7]
World Bank 2008. Voices of the Poor. Website: http://go.worldbank.org
[8]
Smith, G. 2004. US Aid to Africa. Review of African Political Economy 31, (102), 698–703.
[9]
Siphambe, H.K. 2003. Dimensions and measures to reduce poverty in Botswana. Botswana Journal of African Studies 17, (2).
[10]
Magombeyi, M.S., Taigbenu, A.E. and Barron, J., 2013. Rural poverty and Food insecurity mapping at district level for improved agricultural water management in the Limpopo River Basin. Colombo, Sri Lanka: CGIAR Challenge Programon Water and Food (CPWF). 54pp. (CPWF Research for Development (R4D) Series6).
[11]
Booysen, F., S. Van DerBerg, R., Burger, M., Von Maltitz, and Rand, G., 2005. Using an asset index to assess trends in poverty in seven sub-Saharan African countries. Paper presented at the Conference on Multidimensional Poverty hosted by the International Poverty Center of the United Nations Development Program (UNDP), 29–31 August 2005. Brasilia, Brazil.
[12]
Tarp, F., Simler, K., Matusse, C., Heltberg, R., and Dava, G., 2002. The Robustness of Poverty Profiles Reconsidered. Food Consumption and Nutrition Division of the International Food Policy Research Institute. Discussion Paper No.124.
[13]
Sullivan, C., 2002. Calculating a water poverty index. World Development 30, (7), 1195–1210.
[14]
World Bank 2013. Working for a World Free of Poverty. Website: http://data.worldbank.org/country/
[15]
Beaudoin, S.M., 2007. Poverty in World History. Routledge, New York.
[16]
Thurow, R., and Kilman, S., 2009. Enough. Public Affairs. Philadelphia.
[17]
Nyathi, D. 2012. An Evaluation of Poverty Alleviation Strategies Implemented by Non–Governmental Organizations (NGOs) in Zimbabwe: A Case of Binga Rural District. Masters Dissertation. University of Fort Hare. South Africa.
[18]
Mundau, M. 2013. The Impact of Donor–Funded Community Empowerment Projects on Poverty Alleviation: A Case of Selected Projects in Chiredzi District of Zimbabwe. Masters Dissertation. University of Fort Hare. South Africa.
[19]
Zulu, L. 2013. Female Education Breaks the Cycles of Poverty: A Case study of Chikomba Rural District, Zimbabwe. Masters Dissertation. Nelson Mandela Metropolitan University. South Africa.
[20]
Montgomery, D.C., 2001. Design and Analysis of Experiments, 5th Edition. John Wiley & Sons. New York. USA.
ADDRESS
Science Publishing Group
1 Rockefeller Plaza,
10th and 11th Floors,
New York, NY 10020
U.S.A.
Tel: (001)347-983-5186